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Up to 10% of children and young people have a specific phobia that can significantly affect their mental health, development and daily functioning. Cognitive-behavioural therapy-based interventions remain the dominant treatment, but limitations to their provision warrant investigation into low-intensity alternatives. One-session treatment is one such alternative that shares cognitive-behavioural therapy principles but has a shorter treatment period.This research investigated the non-inferiority of one-session treatment to cognitive-behavioural therapy for treating specific phobias in children and young people. The acceptability and cost-effectiveness of one-session treatment were examined.A pragmatic, multicentre, non-inferiority randomised controlled trial, with embedded economic and qualitative evaluations.There were 26 sites, including 12 NHS trusts.Participants were aged 7-16 years and had a specific phobia defined in accordance with established international clinical criteria.Participants were randomised 1 : 1 to receive one-session treatment or usual-care cognitive-behavioural therapy, and were stratified according to age and phobia severity. Outcome assessors remained blind to treatment allocation.The primary outcome measure was the Behavioural Avoidance Task at 6 months' follow-up. Secondary outcomes included the Anxiety Disorder Interview Schedule, Child Anxiety Impact Scale, Revised Children's Anxiety and Depression Scale, a goal-based outcome measure, Child Health Utility 9D, EuroQol-5 Dimensions Youth version and resource usage. Treatment fidelity was assessed using the Cognitive Behaviour Therapy Scale for Children and Young People and the One-Session Treatment Rating Scale.A total of 274 participants were recruited, with 268 participants randomised to one-session treatment (in/i = 134) or cognitive-behavioural therapy (in/i = 134). A total of 197 participants contributed some data, with 149 participants in the intention-to-treat analysis and 113 in the per-protocol analysis. Mean Behavioural Avoidance Task scores at 6 months were similar across treatment groups when both intention-to-treat and per-protocol analyses were applied [cognitive-behavioural therapy: 7.1 (intention to treat), 7.4 (per protocol); one-session treatment: 7.4 (intention to treat), 7.6 (per protocol); on the standardised scale adjusted mean difference for cognitive-behavioural therapy compared with one-session treatment -0.123, 95% confidence interval -0.449 to 0.202 (intention to treat), mean difference -0.204, 95% confidence interval -0.579 to 0.171 (per protocol)]. These findings were wholly below the standardised non-inferiority limit of 0.4, which suggests that one-session treatment is non-inferior to cognitive-behavioural therapy. No between-group differences in secondary outcome measures were found. The health economics evaluation suggested that, compared with cognitive-behavioural therapy, one-session treatment marginally decreased the mean service use costs and maintained similar mean quality-adjusted life-year improvement. Nested qualitative evaluation found one-session treatment to be considered acceptable by those who received it, their parents/guardians and clinicians. No adverse events occurred as a result of phobia treatment.The COVID-19 pandemic meant that 48 children and young people could not complete the primary outcome measure. Service waiting times resulted in some participants not starting therapy before follow-up.One-session treatment for specific phobia in UK-based child mental health treatment centres is as clinically effective as multisession cognitive-behavioural therapy and highly likely to be cost-saving. Future work could involve improving the implementation of one-session treatment through training and commissioning of improved care pathways.This trial is registered as ISRCTN19883421.This project was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme and will be published in full iniHealth Technology Assessment/i; Vol. 26, No. 42. See the NIHR Journals Library website for further project information.A phobia is an intense, ongoing fear of an everyday object or situation. The phobia causes distress and the person with the phobia avoids that object or situation. Many children and young people have phobias that affect their daily lives. Cognitive–behavioural therapy helps by changing what people do or think when they have a phobia and is the most common treatment approach. However, cognitive–behavioural therapy is expensive, takes time and is not always easy to get. Different treatments are needed to help children and young people with specific phobias. One such therapy is one-session treatment, which works in similar ways to cognitive–behavioural therapy but takes place over one main 3-hour session. Our study, called ASPECT (Alleviating Specific Phobias Experienced by Children Trial), compared these two treatments to examine whether or not one-session treatment is as effective as cognitive–behavioural therapy. Overall, 274 children and young people aged 7–16 years from 26 sites nationally helped with our research, of whom 268 received either cognitive–behavioural therapy or one-session treatment. The results at 6 months found that one-session treatment and cognitive–behavioural therapy worked as well as each other for treating phobias in children and young people. We also found evidence that one-session treatment is cheaper than cognitive–behavioural therapy. We spoke with children and young people, their parents/guardians and the therapists of the single-session treatment, and we found one-session treatment to be acceptable for their needs. Future research could explore how to make one-session treatment more easily available for children and young people with specific phobias because it can save time and money, and works just as well as cognitive–behavioural therapy.

Background Mental disorders have become a public health crisis. Early prevention is key. Parenting programmes are effective for children aged ≥ 3 years; however, there is a lack of evidence of their effectiveness for children aged ≤ 2 years. Objectives To establish if the model named Enhancing Social–Emotional Health and Well-being in the Early Years (E-SEE) Steps can (1) enhance child social emotional well-being and establish whether or not it is cost-effective at 20 months of age when compared with services as usual; and (2) be delivered as a proportionate universal model with fidelity. Design A pragmatic two-arm randomised controlled trial and economic appraisal, with an embedded process evaluation to examine the outcomes, implementation and cost-effectiveness of the intervention, and intervention uptake, compared with services as usual. The study had an external pilot phase (which was originally planned as an internal pilot). Setting The intervention was delivered in community settings by early years children’s services and/or public health staff in four sites. Participants A total of 341 parents of infants aged ≤ 8 weeks were randomised in a ratio of 5 : 1 (intervention, n = 285; control, n = 56). The target sample was 606 parents. Intervention Two Incredible Years® parenting programmes (i.e. infant and toddler) delivered in a proportionate universal model with three levels [one universal (book) and two targeted group-based parenting programmes]. Main outcome measures Child social and emotional well-being (primary outcome) was assessed using the Ages and Stages Questionnaire: Social and Emotional, 2nd edition, at 2, 9 and 18 months after randomisation. Parent depression (secondary key outcome) was assessed using the Patient Health Questionnaire-9 items. Both questionnaires were eligibility screeners for targeted groups. Results The primary outcome analysis provided no evidence that the E-SEE Steps model was effective in enhancing child social and emotional well-being. The adjusted mean difference was 3.02 on the original Ages and Stages Questionnaire: Social and Emotional, 2nd edition, in favour of the control [95% confidence interval –0.03 to 6.08; p = 0.052; N = 321 (intervention, n = 268; control, n = 53)]. Analysis of the key secondary outcome (i.e. parent depression levels as assessed by the Patient Health Questionnaire-9 items) provided weak evidence on the Patient Health Questionnaire-9 items in favour of the intervention (adjusted mean difference –0.61, 95% confidence interval –1.34 to 0.12; p = 0.1). Other secondary outcomes did not differ between arms. The economic analysis showed that the E-SEE Steps model was associated with higher costs and was marginally more effective (0.031 quality-adjusted life-years gained from E-SEE Steps compared with SAU, 95% confidence interval –0.008 to 0.071) than services as usual, resulting in an incremental cost-effectiveness ratio of approximately £20,062 per quality-adjusted life-year compared with services as usual. Overall take-up of the targeted parenting programmes was low. Sites, although enthusiastic, identified barriers to delivering the intervention. Limitations The target sample size was not met and the study was not powered to explore the effectiveness of each level of intervention. Most parents in the sample were well educated and, therefore, the results are unlikely to be generalisable, particularly to those at greatest risk of poor social and emotional well-being. Conclusions The E-SEE Steps proportionate universal model did not enhance child social and emotional well-being, but generated non-significant improvements in parent health outcomes, resulting in considerable uncertainty around the cost-effectiveness of the intervention. The primary and key secondary outcome gave inconsistent signals. Although, with system changes, increased resources and adaptations to the intervention, the model could be implemented, evidence for positive outcomes from the E-SEE Steps model is poor. Future work The universal-level E-SEE Step data (i.e. the Incredible Years book) from the external pilot will be pooled with the main trial data for further exploration up to follow-up 1, which is the time point at which most change was seen. Trial registration This trial is registered as ISRCTN11079129. Funding This project was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme and will be published in full in Public Health Research; Vol. 10, No. 8. See the NIHR Journals Library website for further project information.

Social learning through friendships is important in child development. Autistic children often initiate and engage in social interactions differently than neurotypical peers. LEGO® based therapy is a group intervention which facilitates social interactions with peers using collaborative LEGO® play. A 1:1 cluster randomised controlled trial with autistic children aged 7–15 comparing 12 weeks’ LEGO® based therapy and usual support to usual support alone in 98 mainstream schools (2017–2019) was carried out. The primary outcome was social skills (Social Skills Improvement System) completed by unblinded teachers (not intervention deliverers) at 20 weeks. Analysis used intention-to-treat. Fifty intervention schools (127 participants) and 48 control schools (123 participants) were allocated. Primary analysis included 45 intervention schools (116 participants) and 42 control schools (101 participants). The between-arms difference was 3.74 (p = 0.06, 95% confidence interval: −0.16, 7.63) and 1.68 (p = 0.43, 95% confidence interval: −2.51, 5.87) at 20 and 52 weeks (0.18 and 0.08 standardised effect sizes). Twenty-week outcomes for those receiving per protocol intervention were 4.23 (95% confidence interval 0.27, 8.19) with a standardised effect size of 0.21. Sensitivity estimates were between 3.10 and 4.37 (0.15–0.21 standardised effect sizes). Three unrelated serious adverse events were reported. LEGO® based therapy has a small positive non-significant benefit for social skills at 20 weeks but not 52 weeks. Lay abstract Autism is characterised by keen interests and differences in social interactions and communication. Activities that help autistic children and young people with social skills are commonly used in UK schools. LEGO® based therapy is a new activity that provides interesting and fun social opportunities for children and young people and involves building LEGO® models together. This study looked at LEGO® based therapy for the social skills of autistic children and young people in schools. It was a randomised controlled trial, meaning each school was randomly chosen (like flipping a coin) to either run LEGO® based therapy groups in school over 12 weeks and have usual support from school or other professionals, or only have usual support from school or other professionals. The effect of the LEGO® based therapy groups was measured by asking children and young people, their parents/guardians, and a teacher at school in both arms of the study to complete some questionnaires. The main objective was to see if the teacher’s questionnaire answers about the children and young people’s social skills changed between their first and second completions. The social skills of participants in the LEGO® based therapy groups were found to have improved in a small way when compared to usual support only. The study also found that LEGO® based therapy was not very costly for schools to run and parents/guardians and teachers said they thought it was good for their children and young people. We suggest further research into different potential benefits of LEGO® based therapy.

Background In the UK, around 93,000 (0.8%) children and young people (CYP) are experiencing specific phobias that have a substantial impact on daily life. The current gold-standard treatment—multi-session cognitive behavioural therapy (CBT) – is effective at reducing specific phobia severity; however, CBT is time consuming, requires specialist CBT therapists, and is often at great cost and limited availability. A briefer variant of CBT called one session treatment (OST) has been found to offer similar clinical effectiveness for specific phobia as multi-session CBT. The aim of this study was to assess the cost-effectiveness of OST compared to multi-session CBT for CYP with specific phobias through the Alleviating Specific Phobias Experienced by Children Trial (ASPECT), a two-arm, pragmatic, multi-centre, non-inferiority randomised controlled trial. Methods CYP aged seven to 16 years with specific phobias were recruited nationally via Health and Social Care pathways, remotely randomised to the intervention group (OST) or the control group (CBT-based therapies) and analysed (n = 267). Resource use based on NHS and personal social services perspective and quality adjusted life years (QALYs) measured by EQ-5D-Y were collected at baseline and at six-month follow-up. Incremental cost-effectiveness ratio (ICER) was calculated, and non-parametric bootstrapping was conducted to capture the uncertainty around the ICER estimates. The results were presented on a cost-effectiveness acceptability curve (CEAC). A set of sensitivity analyses (including taking a societal perspective) were conducted to assess the robustness of the primary findings. Results After adjustment and bootstrapping, on average CYP in the OST group incurred less costs (incremental cost was -£302.96 (95% CI -£598.86 to -£28.61)) and maintained similar improvement in QALYs (QALYs gained 0.002 (95% CI − 0.004 to 0.008)). The CEAC shows that the probability of OST being cost-effective was over 95% across all the WTP thresholds. Results of a set of sensitivity analyses were consistent with the primary outcomes. Conclusion Compared to CBT, OST produced a reduction in costs and maintained similar improvement in QALYs. Results from both primary and sensitivity analyses suggested that OST was highly likely to be cost saving. Trial registration ISRCTN19883421 (30/11/2016).

Background and aim Personality functioning is predictive of drug misuse and relapse, yet little is known about the role of personality in engagement with the treatment process. This study aimed to estimate the extent to which broad‐ and facet‐level characteristic adaptations contribute to or hinder treatment engagement, while controlling for psychosocial indicators. Design Multi‐site cross‐sectional survey. Setting In‐patient treatment units covering 80% of residential treatment entries in Greece. Participants A total of 338 service users, 287 (84.9%) male, 51 (15.1%) female, average age 33.4 years. Measurements Expressions of personality functioning (characteristic adaptations) were assessed using the Severity Indices of Personality Problems (SIPP‐118). Treatment engagement was measured using the Client Evaluation of Self and Treatment, in‐patient version (CEST). Findings Dysfunctional levels of relational capacities predicted counselling rapport [β = 1.50, 95% confidence interval (CI) = 0.326–2.69, P = 0.013], treatment participation (β = 2.09, 95% CI = 1.15–3.11, P < 0.001) and treatment satisfaction (β = 1.65, 95% CI = 0.735–2.57, P < 0.001). Counselling rapport was also predicted by dysfunctional levels in self‐control (β = 1.78, 95% CI = 0.899–2.67, P < 0.001), self‐reflective functioning at the facet‐level (β = 2.24, 95% CI = 1.01–3.46, P < 0.001) and aggression regulation (β = 1.43, 95% CI = 0.438–2.42, P = 0.005). Dysfunctional levels on social concordance (β = −1.90, 95% CI = −2.87 to –0.941, P = 0.001), emotional regulation (β = 1.90, 95% CI = 0.87–2.92, P < 0.001) and intimacy (β = 2.04, 95% CI = 1.31–3.05, P < 0.001) were significant predictors of treatment participation. Treatment readiness and desire for help predicted treatment engagement. Conclusions In people attending substance use treatment services, maladaptive interpersonal patterns and relational intimacy, emotional dysregulation and impulse control may be associated with low levels of counselling rapport and treatment participation. Low frustration tolerance and aggressive impulses also appeared to predict low participation.

L.K. is a fellow in the Canadian Institutes of Health Research (CIHR) Strategic Training in Advanced Genetic Epidemiology (STAGE) programme and is supported by the CIHR Doctoral Research Award from the Frederick Banting and Charles Best Canada Graduate Scholarships (GSD-137441). Transdisciplinary Research for Cancer in Lung (TRICL) of the International Lung Cancer Consortium (ILCCO) was supported by the National Institutes of Health (U19-CA148127, CA148127S1). Genotyping for the TRICL-ILCCO OncoArray was supported by in-kind genotyping at Centre for Inherited Disease Research (CIDR) (26820120008i-0–6800068-1). Genotyping for the Head and Neck Cancer OncoArray performed at CIDR was funded by the US National Institute of Dental and Craniofacial Research (NIDCR) grant 1X01HG007780–0. CAPUA study was supported by FIS-FEDER/Spain grant numbers FIS-01/310, FIS-PI03–0365 and FIS-07-BI060604, FICYT/Asturias grant numbers FICYT PB02–67 and FICYT IB09–133, and the University Institute of Oncology (IUOPA), of the University of Oviedo and the Ciber de Epidemiologia y Salud Publica. CIBERESP, SPAIN. The work performed in the CARET study was supported by the National Institute of Health (NIH)/National Cancer Institute (NCI): UM1 CA167462 (PI: Goodman), National Institute of Health UO1-CA6367307 (PIs Omen, Goodman); National Institute of Health R01 CA111703 (PI Chen), National Institute of Health 5R01 CA151989 (PI Doherty). The Liverpool Lung Project is supported by the Roy Castle Lung Cancer Foundation. The Harvard Lung Cancer Study was supported by the NIH (National Cancer Institute) grants CA092824, CA090578 and CA074386. The Multiethnic Cohort Study was partially supported by NIH Grants CA164973, CA033619, CA63464 and CA148127. The work performed in MSH-PMH study was supported by the Canadian Cancer Society Research Institute (020214), Ontario Institute of Cancer and Cancer Care Ontario Chair Award to R.J.H. and G.L. and the Alan Brown Chair and Lusi Wong Programs at the Princess Margaret Hospital Foundation. The Norway study was supported by Norwegian Cancer Society, Norwegian Research Council. The work in TLC study has been supported in part the James & Esther King Biomedical Research Program (09KN-15), National Institutes of Health Specialized Programs of Research Excellence (SPORE) Grant (P50 CA119997) and by a Cancer Center Support Grant (CCSG) at the H. Lee Moffitt Cancer Center and Research Institute, an NCI designated Comprehensive Cancer Center (grant number P30-CA76292). The dataset(s) used for the analyses described were obtained from Vanderbilt University Medical Center’s BioVU, which is supported by institutional funding and by the Vanderbilt CTSA grant UL1 TR000445 from NCATS/NIH. Dr Melinda Aldrich is supported by the by NIH/National Cancer Institute 5K07CA172294. The Copenhagen General Population Study (CGPS) was supported by the Chief Physician Johan Boserup and Lise Boserup Fund, the Danish Medical Research Council and Herlev Hospital. The NELCS study: Grant Number P20RR018787 from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH). Kentucky Lung Cancer Research Initiative (KLCRI) was supported by the Department of Defense (Congressionally Directed Medical Research Program, U.S. Army Medical Research and Materiel Command Program) under award number: 10153006 (W81XWH-11–1-0781). Views and opinions of, and endorsements by the author(s) do not reflect those of the US Army or the Department of Defense. This research was also supported by unrestricted infrastructure funds from the UK Center for Clinical and Translational Science, NIH grant UL1TR000117 and Markey Cancer Center NCI Cancer Center Support Grant (P30 CA177558) Shared Resource Facilities: Cancer Research Informatics, Biospecimen and Tissue Procurement, and Biostatistics and Bioinformatics. The research undertaken by M.D.T., L.V.W. and M.S.A. was partly funded by the National Institute for Health Research (NIHR). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. M.D.T. holds a Medical Research Council Senior Clinical Fellowship (G0902313). The Tampa study was funded by Public Health Service grants P01-CA68384 and R01-DE13158 from the National Institutes of Health. The University of Pittsburgh head and neck cancer case–control study is supported by US National Institutes of Health grants P50 CA097190 and P30 CA047904. The Carolina Head and Neck Cancer Study (CHANCE) was supported by the National Cancer Institute (R01CA90731). The Head and Neck Genome Project (GENCAPO) was supported by the Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP; grants 04/12054–9 and 10/51168–0). The authors thank all the members of the GENCAPO team. This publication presents data from the Head and Neck 5000 study. The study was a component of independent research funded by the National Institute for Health Research (NIHR) under its Programme Grants for Applied Research scheme (RP-PG-0707–10034). The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. Human papillomavirus (HPV) serology was supported by a Cancer Research UK Programme Grant, the Integrative Cancer Epidemiology Programme (grant number: C18281/A19169). The Alcohol-Related Cancers and Genetic Susceptibility Study in Europe (ARCAGE) was funded by the European Commission’s fifth framework programme (QLK1– 2001-00182), the Italian Association for Cancer Research, Compagnia di San Paolo/FIRMS, Region Piemonte and Padova University (CPDA057222). The Rome Study was supported by the Associazione Italiana per la Ricerca sul Cancro (AIRC) awards IG 2011 10491 and IG 2013 14220 to S.B. and by Fondazione Veronesi to S.B. The IARC Latin American study was funded by the European Commission INCO-DC programme (IC18-CT97–0222), with additional funding from Fondo para la Investigacion Cientifica y Tecnologica (Argentina) and the Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (01/01768–2). The IARC Central Europe study was supported by the European Commission’s INCO-COPERNICUS Program (IC15-CT98–0332), US NIH/National Cancer Institute grant CA92039 and World Cancer Research Foundation grant WCRF 99A28. The IARC Oral Cancer Multicenter study was funded by grant S06 96 202489 05F02 from Europe against Cancer; grants FIS 97/0024, FIS 97/0662 and BAE 01/5013 from Fondo de Investigaciones Sanitarias, Spain; the UICC Yamagiwa-Yoshida Memorial International Cancer Study; the National Cancer Institute of Canada; Associazione Italiana per la Ricerca sul Cancro; and the Pan-American Health Organization. Coordination of the EPIC study is financially supported by the European Commission (DG SANCO) and the International Agency for Research on Cancer.

Social emotional development in infancy is a predictor of outcomes in later life, yet there is little evidence of effectiveness for parenting interventions designed to enhance social emotional wellbeing in infancy. An 18-month two-arm randomized controlled pilot trial evaluated the feasibility of a definitive trial of Incredible Years (IY) Infant and Toddler parent programs delivered in a proportionate universal model, called Enhancing Social-Emotional Health and Wellbeing in the Early Years (E-SEE) Steps. Intervention families received an IY Babies book (universal dose), followed by the IY Infant and/or the Toddler group-based programs, based on parent depression (PHQ-9) and/or child social emotional development (ASQ:SE-2) scores. Control parents received services as usual. Parents from two English local authorities with a child eight-weeks-old or younger participated, and were block randomized using a web-based system. Primary endpoints for the study were feasibility parameters relating to recruitment, retention, intervention fidelity and appropriateness of measures. 205 participants were randomized (152:53, intervention:control). Our target was 288 parents. Trial retention rate was higher than expected, with a completion rate of 88% (n = 181, 137:44) at follow-up 3; equating to 94% of 192 expected participants. Intervention uptake was lower than expected. Fidelity of delivery was acceptable and measures were deemed appropriate. A definitive trial is feasible with design amendments to include: introduction of a child screener for intervention eligibility; enhanced intervention material; revised sample size and random allocation ratio. Our internal pilot became an external pilot due to these changes.

Clinical trial results have recently demonstrated that inhibiting inflammation by targeting the interleukin-1β pathway can offer a significant reduction in lung cancer incidence and mortality, highlighting a pressing and unmet need to understand the benefits of inflammation-focused lung cancer therapies at the genetic level. While numerous genome-wide association studies (GWAS) have explored the genetic etiology of lung cancer, there remains a large gap between the type of information that may be gleaned from an association study and the depth of understanding necessary to explain and drive translational findings. Thus, in this study we jointly model and integrate extensive multiomics data sources, utilizing a total of 40 genome-wide functional annotations that augment previously published results from the International Lung Cancer Consortium (ILCCO) GWAS, to prioritize and characterize single nucleotide polymorphisms (SNPs) that increase risk of squamous cell lung cancer through the inflammatory and immune responses. Our work bridges the gap between correlative analysis and translational follow-up research, refining GWAS association measures in an interpretable and systematic manner. In particular, reanalysis of the ILCCO data highlights the impact of highly associated SNPs from nuclear factor-κB signaling pathway genes as well as major histocompatibility complex mediated variation in immune responses. One consequence of prioritizing likely functional SNPs is the pruning of variants that might be selected for follow-up work by over an order of magnitude, from potentially tens of thousands to hundreds. The strategies we introduce provide informative and interpretable approaches for incorporating extensive genome-wide annotation data in analysis of genetic association studies.

Background Our knowledge of immune-mediated inflammatory disease (IMID) aetiology and pathogenesis has improved greatly over recent years, however, very little is known of the factors that trigger disease relapses (flares), converting diseases from inactive to active states. Focussing on rheumatoid arthritis (RA), the challenge that we will address is why IMIDs remit and relapse. Extrapolating from pathogenetic factors involved in disease initiation, new episodes of inflammation could be triggered by recurrent systemic immune dysregulation or locally by factors within the joint, either of which could be endorsed by overarching epigenetic factors or changes in systemic or localised metabolism. Methods The BIO-FLARE study is a non-randomised longitudinal cohort study that aims to enrol 150 patients with RA in remission on a stable dose of non-biologic disease-modifying anti-rheumatic drugs (DMARDs), who consent to discontinue treatment. Participants stop their DMARDs at time 0 and are offered an optional ultrasound-guided synovial biopsy. They are studied intensively, with blood sampling and clinical evaluation at weeks 0, 2, 5, 8, 12 and 24. It is anticipated that 50% of participants will have a disease flare, whilst 50% remain in drug-free remission for the study duration (24 weeks). Flaring participants undergo an ultrasound-guided synovial biopsy before reinstatement of previous treatment. Blood samples will be used to investigate immune cell subsets, their activation status and their cytokine profile, autoantibody profiles and epigenetic profiles. Synovial biopsies will be examined to profile cell lineages and subtypes present at flare. Blood, urine and synovium will be examined to determine metabolic profiles. Taking into account all generated data, multivariate statistical techniques will be employed to develop a model to predict impending flare in RA, highlighting therapeutic pathways and informative biomarkers. Despite initial recruitment to time and target, the SARS-CoV-2 pandemic has impacted significantly, and a decision was taken to close recruitment at 118 participants with complete data. Discussion This study aims to investigate the pathogenesis of flare in rheumatoid arthritis, which is a significant knowledge gap in our understanding, addressing a major unmet patient need. Trial registration The study was retrospectively registered on 27/06/2019 in the ISRCTN registry 16371380.

Introduction Out-of-hospital cardiac arrest (OHCA) is a major public health problem, leading to a substantial number of deaths in the UK. In response to this, the Yorkshire Ambulance Service NHS Trust (YAS) has introduced red arrest teams (RATs). RAT members attend a three-day training course, focusing on the technical and non-technical skills that are required to effectively team lead an OHCA and provide high quality post-resuscitation care. This evaluation aims to determine the impact of the RATs on survival to 30 days and return of spontaneous circulation (ROSC) at hospital. Methods All adult (≥ 18 years) OHCAs entered onto the YAS computer aided dispatch (CAD) system between 1 October 2015 and 30 September 2017 were included if the patient was resuscitated and the cause of the arrest was considered to be medical in origin. Multi-variable logistic regression models were created to enable adjustment for common predictors of survival and ROSC. Results During the 2-year data collection period, YAS attended 15,151 cardiac arrests. After removing ineligible cases, 5868 cardiac arrests remained. RATs attended 2000/5868 (34.1%) incidents, with each RAT attending a median of 13 cardiac arrests (IQR 7-23, min. 1, max. 78).The adjusted odds ratios suggest that a RAT on scene is associated with a slight increase in the odds of survival to 30 days (OR 1.01, 95% CI 0.74-1.38) and odds of ROSC on arrival at hospital (OR 1.13, 95% CI 0.99-1.29), compared to the odds of not having a RAT present, although neither result is statistically significant. Conclusion The presence of a RAT paramedic was associated with a small increase in survival to 30 days and ROSC on arrival at hospital, although neither were statistically significant. Larger prospective studies are required to determine the effect of roles such as RAT on outcomes from OHCA.

Vomiting and regurgitation are commonly encountered in out-of-hospital cardiac arrest with a reported incidence of 20-30%. Arguably, tracheal intubation is the preferred airway management technique in patients with ongoing airway contamination, but there is evidence that this is difficult to achieve when the airway is soiled. In addition, traditional suctioning techniques have been criticised, and training in the management of contaminated airways is limited. If standard suctioning techniques are not sufficient to maintain a clear airway and provide ventilation, then these patients will die, irrespective of the quality of chest compressions and the timeliness of defibrillation. This has led to the development of a combined suction/laryngoscopy technique to facilitate intubation, known as Suction Assisted Laryngoscopy and Airway Decontamination, and the creation of modified airway manikins to allow for practice in these techniques. However, to date there has only been one study specifically looking at the Suction Assisted Laryngoscopy and Airway Decontamination technique, and the outcomes were self-reported confidence measures of trainees in using the technique. The primary objective of Soiled Airway Tracheal Intubation and the Effectiveness of Decontamination is to determine the difference between paramedic first-pass intubation success, before and after Suction Assisted Laryngoscopy and Airway Decontamination training, in a simulated soiled airway. The primary outcome is the difference in proportions of paramedic first-pass intubation success, before and after Suction Assisted Laryngoscopy and Airway Decontamination training. Paramedic recruitment commenced in July 2018 and the study will enrol 154 paramedics by the end of 2018. The results of this study will contribute to the evidence relating to the Suction Assisted Laryngoscopy and Airway Decontamination technique.

INTRODUCTION: The relationship between Body-Mass-Index (BMI) and lung cancer prognosis is heterogeneous. We evaluated the impact of sex, smoking and race on the relationship between BMI and overall survival (OS) in non-small-cell-lung-cancer (NSCLC). METHODS: Data from 16 individual ILCCO studies were pooled to assess interactions between BMI and the following factors on OS: self-reported race, smoking status and sex, using Cox models (adjusted hazard ratios; aHR) with interaction terms and adjusted penalized smoothing spline plots in stratified analyses. RESULTS: Among 20,937 NSCLC patients with BMI values, females = 47 %; never-smokers = 14 %; White-patients = 76 %. BMI showed differential survival according to race whereby compared to normal-BMI patients, being underweight was associated with poor survival among white patients (OS, aHR = 1.66) but not among black patients (aHR = 1.06; p(interaction) = 0.02). Comparing overweight/obese to normal weight patients, Black NSCLC patients who were overweight/obese also had relatively better OS (p(interaction) = 0.06) when compared to White-patients. BMI was least associated with survival in Asian-patients and never-smokers. The outcomes of female ever-smokers at the extremes of BMI were associated with worse outcomes in both the underweight (p(interaction)

Background Evidence for parenting programs to improve wellbeing in children under three is inconclusive. We investigated the fidelity, impact, and cost-effectiveness of two parenting programs delivered within a longitudinal proportionate delivery model (‘E-SEE Steps’). Methods Eligible parents with a child ≤ 8 weeks were recruited into a parallel two-arm, assessor blinded, randomized controlled, community-based, trial with embedded economic and process evaluations. Post-baseline randomization applied a 5:1 (intervention-to-control) ratio, stratified by primary (child social-emotional wellbeing (ASQ:SE-2)) and key secondary (maternal depression (PHQ-9)) outcome scores, sex, and site. All intervention parents received the Incredible Years® Baby Book (IY-B), and were offered the targeted Infant (IY-I)/Toddler (IY-T) program if eligible, based on ASQ:SE-2/PHQ-9 scores. Control families received usual services. Fidelity data were analysed descriptively. Primary analysis applied intention to treat. Effectiveness analysis fitted a marginal model to outcome scores. Cost-effectiveness analysis involved Incremental Cost-Effectiveness Ratios (ICERs). Results The target sample (N = 606) was not achieved; 341 mothers were randomized (285:56), 322 (94%) were retained to study end. Of those eligible for the IY-I (n = 101), and IY-T (n = 101) programs, 51 and 21 respectively, attended. Eight (of 14) groups met the 80% self-reported fidelity criteria. No significant differences between arms were found for adjusted mean difference scores; ASQ:SE-2 (3.02, 95% CI: -0.03, 6.08, p = 0.052), PHQ-9 (-0.61; 95% CI: -1.34, 0.12, p = 0.1). E-SEE Steps had higher costs, but improved mothers’ Health-related Quality of Life (0.031 Quality Adjusted Life Year (QALY) gain), ICER of £20,062 per QALY compared to control. Serious adverse events (n = 86) were unrelated to the intervention. Conclusions E-SEE Steps was not effective, but was borderline cost-effective. The model was delivered with varying fidelity, with lower-than-expected IY-T uptake. Changes to delivery systems and the individual programs may be needed prior to future evaluation. Trial registration International Standard Randomized Controlled Trial Number: ISRCTN11079129.

This research was supported by funding from the National Institutes of Health (US NCI R25T CA112355 and R01 CA201358; PI: Witte) and the Canadian Institute for Health Research (Foundation grant FDN 167273, PI: Hung; Canada Research Chair, PI: Hung). The OncoArray project was supported by NIH U19 CA203654 (MPI: Hung, Amos, Brennan, Lin). The Boston Lung Cancer Study was funded by NIH (NCI) U01CA209414 (PI: Christiani). The lung eQTL study at Laval University was supported by the Fondation de l’Institut universitaire de cardiologie et de pneumologie de Québec and the Canadian Institutes of Health Research (MOP − 123369). Y.B. holds a Canada Research Chair in Genomics of Heart and Lung Diseases. The EAGLE study was supported by the Intramural Research Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS. The Multiethnic Cohort Study is supported by National Institutes of Health (CA164973). The CARET study was supported by the National Institutes of Health/National Cancer Institute: UM1 CA167462 (PI: Goodman), U01 CA6367307 (PIs: Omen, Goodman); R01 CA111703 (PI: Chen), 5R01 CA151989-01A1 (PI: Doherty) and U01 CA167462 (PI: Chen). M.B.S. was supported in part by a Cancer Center Support Grant (P30 CA076292) and by NIH P50 CA119997. R.M.M. is supported by a CRUK programme grant, the Integrative Cancer Epidemiology Programme (C18281/A19169), and by the National Institute for Health Research (NIHR) Bristol Biomedical Research Centre based at University Hospitals Bristol NHS Foundation Trust and the University of Bristol., Kachuri, L., Johansson, M., Rashkin, S.R., Graff, R.E., Bossé, Y., Manem, V., Caporaso, N.E., Landi, M.T., Christiani, D.C., Vineis, P., Liu, G., Scelo, G., Zaridze, D., Shete, S.S., Albanes, D., Aldrich, M.C., Tardón, A., Rennert, G., Chen, C., Goodman, G.E., Doherty, J.A., Bickeböller, H., Field, J.K., Davies, M.P., Dawn Teare, M., Kiemeney, L.A., Bojesen, S.E., Haugen, A., Zienolddiny, S., Lam, S., Le Marchand, L., Cheng, I., Schabath, M.B., Duell, E.J., Andrew, A.S., Manjer, J., Lazarus, P., Arnold, S., McKay, J.D., Emami, N.C., Warkentin, M.T., Brhane, Y., Obeidat, M., Martin, R.M., Relton, C., Davey Smith, G., Haycock, P.C., Amos, C.I., Brennan, P., Witte, J.S., Hung, R.J.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

IntroductionThe relationships between morbid obesity, changes in body mass index (BMI) before cancer diagnosis, and lung cancer outcomes by histology (SCLC and NSCLC) have not been well studied.MethodsIndividual level data analysis was performed on 25,430 patients with NSCLC and 2787 patients with SCLC from 16 studies of the International Lung Cancer Consortium evaluating the association between various BMI variables and lung cancer overall survival, reported as adjusted hazard ratios (aHRs) from Cox proportional hazards models and adjusted penalized smoothing spline plots.ResultsOverall survival of NSCLC had putative U-shaped hazard ratio relationships with BMI based on spline plots: being underweight (BMI < 18.5 kg/m2; aHR= 1.56; 95% confidence interval [CI]:1.43-1.70) or morbidly overweight (BMI > 40 kg/m2; aHR= 1.09; 95% CI: 0.95-1.26) at the time of diagnosis was associated with worse stage-specific prognosis, whereas being overweight (25 kg/m2 ≤ BMI < 30 kg/m2; aHR= 0.89; 95% CI: 0.85-0.95) or obese (30 kg/m2 ≤ BMI ≤ 40 kg/m2; aHR= 0.86; 95% CI: 0.82-0.91) was associated with improved survival. Although not significant, a similar pattern was seen with SCLC. Compared with an increased or stable BMI from the period between young adulthood until date of diagnosis, a decreased BMI was associated with worse outcomes in NSCLC (aHR= 1.24; 95% CI: 1.2-1.3) and SCLC patients (aHR=1.26 (95% CI: 1.0-1.6). Decreased BMI was consistently associated with worse outcome, across clinicodemographic subsets.ConclusionsBoth being underweight or morbidly obese at time of diagnosis is associated with lower stage-specific survival in independent assessments of NSCLC and SCLC patients. In addition, a decrease in BMI at lung cancer diagnosis relative to early adulthood is a consistent marker of poor survival.

Introduction: Vomiting and regurgitation are commonly encountered in out-of-hospital cardiac arrest (OHCA), with a reported incidence of 20-30%. This is of concern since patients who have suffered an OHCA are already in extremis. If standard suctioning techniques are not sufficient to maintain a clear airway and provide ventilation, then these patients will die, irrespective of the quality of chest compressions and the timeliness of defibrillation. This study aimed to determine whether a short teaching session of the suction assisted laryngoscopy and airway decontamination (SALAD) technique improved paramedics' ability to successfully intubate a contaminated airway. Methods: A modified airway manikin with the oesophagus connected to a reservoir of 'vomit', and a bilge pump capable of propelling the vomit up into the oropharynx, was used to simulate a soiled airway. The intervention consisted of a brief SALAD training session with a demonstration and opportunity to practice. Participants were randomly allocated into two groups: AAB, who made two pre-training intubation attempts and one post-training attempt, and ABB, who made one pre-training and two post-training attempts, to adjust for improvement in performance due to repetition. Results: In this manikin study, following a brief SALAD training session, more paramedics were able to intubate a soiled airway on their first attempt, compared to those without training (90.2% vs. 53.7%, difference of 36.6%, 95% CI 24-49.1%, p < 0.001). In addition, the mean difference in time taken to perform a successful intubation between groups was statistically significant for attempts 1 and 2 (mean difference 11.71 seconds, 95% CI 1.95-21.47 seconds, p = 0.02), but not attempts 1 and 3 (mean difference -2.52 seconds, 95% CI -11.64-6.61 seconds, p = 0.58). This result is likely to be confounded by the use of tracheal suction, which only occurred in the post-training attempts and added additional time to the intubation attempts. There was no statistically significant difference in success rates on the third attempt between AAB and ABB (89.0% vs. 86.6%, difference 2.4%, 95% CI 7.6-12.4%, p = 0.63). Conclusion: In this study, the use of the SALAD technique significantly improved first attempt success rates when paramedics were intubating a simulated soiled airway.

Background In proportionate or adaptive interventions, the dose or intensity can be adjusted based on individual need at predefined decision stages during the delivery of the intervention. The development of such interventions may require an evaluation of the effectiveness of the individual stages in addition to the whole intervention. However, evaluating individual stages of an intervention has various challenges, particularly the statistical design and analysis. This review aimed to identify the use of trials of proportionate interventions and how they are being designed and analysed in current practice. Methods We searched MEDLINE, Web of Science and PsycINFO for articles published between 2010 and 2015 inclusive. We considered trials of proportionate interventions in all fields of research. For each trial, its aims, design and analysis were extracted. The data synthesis was conducted using summary statistics and a narrative format. Results Our review identified 44 proportionate intervention trials, comprising 28 trial results, 13 protocols and three secondary analyses. These were mostly described as stepped care (n=37) and mainly focussed on mental health research (n=30). The other studies were aimed at finding an optimal adaptive treatment strategy (n=7) in a variety of therapeutic areas. Further terminology used included adaptive intervention, staged intervention, sequentially multiple assignment trial or a two-phase design. The median number of decision stages in the interventions was two and only one study explicitly evaluated the effect of the individual stages. Conclusions Trials of proportionate staged interventions are being used predominantly within the mental health field. However, few studies consider the different stages of the interventions, either at the design or the analysis phase, and how they may interact with one another. There is a need for further guidance on the design, analyses and reporting across trials of proportionate interventions. Trial registration Prospero, CRD42016033781. Registered on 2 February 2016. Electronic supplementary material The online version of this article (10.1186/s13063-019-3206-x) contains supplementary material, which is available to authorized users.

Objectives Previous studies have shown that smokers presented with ST-segment elevation myocardial infarction (STEMI) a decade earlier than non-smokers. However, no account has been made for population smoking trends, an important deficit addressed by this study. Methods The combination of admission data on patients with acute STEMI undergoing percutaneous coronary intervention and demographic data supplied by the Office for National Statistics for the South Yorkshire population between 2009–2012 were analysed to generate incidence rates and rate ratios (RR) to quantify the relative risk of STEMI from smoking, overall and by age group. Results There were 1795 STEMI patients included of which 72.9% were male. 68 patients were excluded as they had no smoking status recorded, leaving 48.5% of the remaining population as current smokers, 27.2% ex-smokers and 24.3% never smokers. Smokers were over-represented with overall smoking prevalence in South Yorkshire calculated at 22.4%. The incidence of STEMI in smokers aged under 50, 50–65 and over 65 years was 59.7, 316.9 and 331.0 per 100 000 patient years at risk compared to 7.0, 60.9 and 106.8 for the combined group of ex- and never smokers. This gave smokers under the age of 50 years an 8.47 (95% CI 6.80 to 10.54) increase in rate compared to non-smokers of the same age, with the 50–65 and over 65 age groups having RRs of 5.20 (95% CI 4.76 to 5.69) and 3.10 (95% CI 2.67 to 3.60), respectively. Conclusions Smoking was associated with an eightfold increased risk of acute STEMI in younger smokers, when compared to ex- and never smokers. Further efforts to reduce smoking in the youngest are needed.

Background Recent meta-analyses show that individuals with high risk variants in CHRNA5 on chromosome 15q25 are likely to develop lung cancer earlier than those with low-risk genotypes. The same high-risk genetic variants also predict nicotine dependence and delayed smoking cessation. It is unclear whether smoking cessation confers the same benefits in terms of lung cancer risk reduction for those who possess CHRNA5 risk variants versus those who do not. Methods Meta-analyses examined the association between smoking cessation and lung cancer risk in 15 studies of individuals with European ancestry who possessed varying rs16969968 genotypes (N = 12,690 ever smokers, including 6988 cases of lung cancer and 5702 controls) in the International Lung Cancer Consortium. Results Smoking cessation (former vs. current smokers) was associated with a lower likelihood of lung cancer (OR = 0.48, 95%CI = 0.30–0.75, p = 0.0015). Among lung cancer patients, smoking cessation was associated with a 7-year delay in median age of lung cancer diagnosis (HR = 0.68, 95%CI = 0.61–0.77, p = 4.9 ∗ 10–10). The CHRNA5 rs16969968 risk genotype (AA) was associated with increased risk and earlier diagnosis for lung cancer, but the beneficial effects of smoking cessation were very similar in those with and without the risk genotype. Conclusion We demonstrate that quitting smoking is highly beneficial in reducing lung cancer risks for smokers regardless of their CHRNA5 rs16969968 genetic risk status. Smokers with high-risk CHRNA5 genotypes, on average, can largely eliminate their elevated genetic risk for lung cancer by quitting smoking- cutting their risk of lung cancer in half and delaying its onset by 7 years for those who develop it. These results: 1) underscore the potential value of smoking cessation for all smokers, 2) suggest that CHRNA5 rs16969968 genotype affects lung cancer diagnosis through its effects on smoking, and 3) have potential value for framing preventive interventions for those who smoke., Highlights • CHRNA5 rs16969968 confers risk for earlier lung cancer diagnosis, but quitting produces benefit regardless of genotype. • Smokers can cut their risk of lung cancer in half and delay its onset by 7 years among those diagnosed. • Precision prevention allows clinicians to provide personalized health benefits of smoking cessation. This is a report on whether smoking cessation confers the same benefits in terms of lung cancer risk reduction for those who possess CHRNA5 risk variants versus those who do not. We determined that quitting smoking is highly beneficial in reducing lung cancer risk levels for smokers regardless of their CHRNA5 rs16969968 genetic risk status. Although CHRNA5 rs16969968 increases risk for earlier lung cancer by 4 years, quitting produces essentially the same benefit for smokers with either high or low genetic risks. Smokers can cut their risk of lung cancer in half and delay its onset by 7 years among those diagnosed. These results are important for smokers to prevent cancer. On average, smokers at all genetic risk levels can largely eliminate their elevated risk for lung cancer by quitting smoking.

Many lung cancer risk prediction models have been published but there has been no systematic review or comprehensive assessment of these models to assess how they could be used in screening. We performed a systematic review of lung cancer prediction models and identified 31 articles that related to 25 distinct models, of which 11 considered epidemiological factors only and did not require a clinical input. Another 11 articles focused on models that required a clinical assessment such as a blood test or scan, and 8 articles considered the 2-stage clonal expansion model. More of the epidemiological models had been externally validated than the more recent clinical assessment models. There was varying discrimination, the ability of a model to distinguish between cases and controls, with an area under the curve between 0.57 and 0.879 and calibration, the model's ability to assign an accurate probability to an individual. In our review we found that further validation studies need to be considered; especially for the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial 2012 Model Version (PLCOM2012) and Hoggart models, which recorded the best overall performance. Future studies will need to focus on prediction rules, such as optimal risk thresholds, for models for selective screening trials. Only 3 validation studies considered prediction rules when validating the models and overall the models were validated using varied tests in distinct populations, which made direct comparisons difficult. To improve this, multiple models need to be tested on the same data set with considerations for sensitivity, specificity, model accuracy, and positive predictive values at the optimal risk thresholds.

Publisher's version (útgefin grein)., Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (rg = 0.57, p = 4.6 × 10−8), breast and ovarian cancer (rg = 0.24, p = 7 × 10−5), breast and lung cancer (rg = 0.18, p =1.5 × 10−6) and breast and colorectal cancer (rg = 0.15, p = 1.1 × 10−4). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis., The authors in this manuscript were working on behalf of BCAC, CCFR, CIMBA, CORECT, GECCO, OCAC, PRACTICAL, CRUK, BPC3, CAPS, PEGASUS, TRICL-ILCCO, ABCTB, APCB, BCFR, CONSIT TEAM, EMBRACE, GC-HBOC, GEMO, HEBON, kConFab/AOCS Mod SQuaD, and SWE-BRCA. The breast cancer genome-wide association analyses: BCAC is funded by Cancer Research UK [C1287/A16563, C1287/A10118], the European Union’s Horizon 2020 Research and Innovation Programme (grant numbers 634935 and 633784 for BRIDGES and B-CAST, respectively), and by the European Community’s Seventh Framework Programme under grant agreement number 223175 (grant number HEALTH-F2-2009-223175) (COGS). The EU Horizon 2020 Research and Innovation Programme funding source had no role in study design, data collection, data analysis, data interpretation, or writing of the report. Genotyping of the OncoArray was funded by the NIH Grant U19 CA148065, and Cancer UK Grant C1287/A16563 and the PERSPECTIVE project supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research (grant GPH-129344) and, the Ministère de l’Économie, Science et Innovation du Québec through Genome Québec and the PSR-SIIRI-701 grant, and the Quebec Breast Cancer Foundation. Funding for the iCOGS infrastructure came from: the European Community’s Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, C8197/A16565), the National Institutes of Health (CA128978), and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065, and 1U19 CA148112—the GAME-ON initiative), the Department of Defence (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, and Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. The DRIVE Consortium was funded by U19 CA148065. The Australian Breast Cancer Family Study (ABCFS) was supported by grant UM1 CA164920 from the National Cancer Institute (USA). The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. The ABCFS was also supported by the National Health and Medical Research Council of Australia, the New South Wales Cancer Council, the Victorian Health Promotion Foundation (Australia), and the Victorian Breast Cancer Research Consortium. J.L.H. is a National Health and Medical Research Council (NHMRC) Senior Principal Research Fellow. M.C.S. is a NHMRC Senior Research Fellow. The ABCS study was supported by the Dutch Cancer Society [grants NKI 2007-3839; 2009 4363]. The Australian Breast Cancer Tissue Bank (ABCTB) is generously supported by the National Health and Medical Research Council of Australia, The Cancer Institute NSW and the National Breast Cancer Foundation. The ACP study is funded by the Breast Cancer Research Trust, UK. The AHS study is supported by the intramural research program of the National Institutes of Health, the National Cancer Institute (grant number Z01-CP010119), and the National Institute of Environmental Health Sciences (grant number Z01-ES049030). The work of the BBCC was partly funded by ELAN-Fond of the University Hospital of Erlangen. The BBCS is funded by Cancer Research UK and Breast Cancer Now and acknowledges NHS funding to the NIHR Biomedical Research Centre, and the National Cancer Research Network (NCRN). The BCEES was funded by the National Health and Medical Research Council, Australia and the Cancer Council Western Australia and acknowledges funding from the National Breast Cancer Foundation (JS). For the BCFR-NY, BCFR-PA, and BCFR-UT this work was supported by grant UM1 CA164920 from the National Cancer Institute. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government or the BCFR. For BIGGS, ES is supported by NIHR Comprehensive Biomedical Research Centre, Guy’s & St. Thomas’ NHS Foundation Trust in partnership with King’s College London, United Kingdom. IT is supported by the Oxford Biomedical Research Centre. BOCS is supported by funds from Cancer Research UK (C8620/A8372/A15106) and the Institute of Cancer Research (UK). BOCS acknowledges NHS funding to the Royal Marsden/Institute of Cancer Research NIHR Specialist Cancer Biomedical Research Centre. The BREast Oncology GAlician Network (BREOGAN) is funded by Acción Estratégica de Salud del Instituto de Salud Carlos III FIS PI12/02125/Cofinanciado FEDER; Acción Estratégica de Salud del Instituto de Salud Carlos III FIS Intrasalud (PI13/01136); Programa Grupos Emergentes, Cancer Genetics Unit, Instituto de Investigacion Biomedica Galicia Sur. Xerencia de Xestion Integrada de Vigo-SERGAS, Instituto de Salud Carlos III, Spain; Grant 10CSA012E, Consellería de Industria Programa Sectorial de Investigación Aplicada, PEME I + D e I + D Suma del Plan Gallego de Investigación, Desarrollo e Innovación Tecnológica de la Consellería de Industria de la Xunta de Galicia, Spain; Grant EC11-192. Fomento de la Investigación Clínica Independiente, Ministerio de Sanidad, Servicios Sociales e Igualdad, Spain; and Grant FEDER-Innterconecta. Ministerio de Economia y Competitividad, Xunta de Galicia, Spain. The BSUCH study was supported by the Dietmar-Hopp Foundation, the Helmholtz Society and the German Cancer Research Center (DKFZ). The CAMA study was funded by Consejo Nacional de Ciencia y Tecnología (CONACyT) (SALUD-2002-C01-7462). Sample collection and processing was funded in part by grants from the National Cancer Institute (NCI R01CA120120 and K24CA169004). CBCS is funded by the Canadian Cancer Society (grant # 313404) and the Canadian Institutes of Health Research. CCGP is supported by funding from the University of Crete. The CECILE study was supported by Fondation de France, Institut National du Cancer (INCa), Ligue Nationale contre le Cancer, Agence Nationale de Sécurité Sanitaire, de l’Alimentation, de l’Environnement et du Travail (ANSES), Agence Nationale de la Recherche (ANR). The CGPS was supported by the Chief Physician Johan Boserup and Lise Boserup Fund, the Danish Medical Research Council, and Herlev and Gentofte Hospital. The CNIO-BCS was supported by the Instituto de Salud Carlos III, the Red Temática de Investigación Cooperativa en Cáncer and grants from the Asociación Española Contra el Cáncer and the Fondo de Investigación Sanitario (PI11/00923 and PI12/00070). COLBCCC is supported by the German Cancer Research Center (DKFZ), Heidelberg, Germany. D.T. was in part supported by a postdoctoral fellowship from the Alexander von Humboldt Foundation. The American Cancer Society funds the creation, maintenance, and updating of the CPS-II cohort. The CTS was initially supported by the California Breast Cancer Act of 1993 and the California Breast Cancer Research Fund (contract 97-10500) and is currently funded through the National Institutes of Health (R01 CA77398, UM1 CA164917, and U01 CA199277). Collection of cancer incidence data was supported by the California Department of Public Health as part of the statewide cancer reporting program mandated by California Health and Safety Code Section 103885. H.A.C eceives support from the Lon V Smith Foundation (LVS39420). The University of Westminster curates the DietCompLyf database funded by Against Breast Cancer Registered Charity No. 1121258 and the NCRN. The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by: Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l’Education Nationale, Institut National de la Santé et de la Recherche Médicale (INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ), Federal Ministry of Education and Research (BMBF) (Germany); the Hellenic Health Foundation, the Stavros Niarchos Foundation (Greece); Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); Health Research Fund (FIS), PI13/00061 to Granada, PI13/01162 to EPIC-Murcia, Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, ISCIII RETIC (RD06/0020) (Spain); Cancer Research UK (14136 to EPIC-Norfolk; C570/A16491 and C8221/A19170 to EPIC-Oxford), Medical Research Council (1000143 to EPIC-Norfolk, MR/M012190/1 to EPIC-Oxford) (United Kingdom). The ESTHER study was supported by a grant from the Baden Württemberg Ministry of Science, Research and Arts. Additional cases were recruited in the context of the VERDI study, which was supported by a grant from the German Cancer Aid (Deutsche Krebshilfe). FHRISK is funded from NIHR grant PGfAR 0707-10031. The GC-HBOC (German Consortium of Hereditary Breast and Ovarian Cancer) is supported by the German Cancer Aid (grant no 110837, coordinator: Rita K. Schmutzler, Cologne). This work was also funded by the European Regional Development Fund and Free State of Saxony, Germany (LIFE - Leipzig Research Centre for Civilization Diseases, project numbers 713-241202, 713-241202, 14505/2470, and 14575/2470). The GENICA was funded by the Federal Ministry of Education and Research (BMBF) Germany grants 01KW9975/5, 01KW9976/8, 01KW9977/0, and 01KW0114, the Robert Bosch Foundation, Stuttgart, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, the Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), Bochum, as well as the Department of Internal Medicine, Evangelische Kliniken Bonn gGmbH, Johanniter Krankenhaus, Bonn, Germany. The GEPARSIXTO study was conducted by the German Breast Group GmbH. The GESBC was supported by the Deutsche Krebshilfe e. V. [70492] and the German Cancer Research Center (DKFZ). GLACIER was supported by Breast Cancer Now, CRUK and Biomedical Research Centre at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. The HABCS study was supported by the Claudia von Schilling Foundation for Breast Cancer Research, by the Lower Saxonian Cancer Society, and by the Rudolf-Bartling Foundation. The HEBCS was financially supported by the Helsinki University Central Hospital Research Fund, Academy of Finland (266528), the Finnish Cancer Society, and the Sigrid Juselius Foundation. The HERPACC was supported by MEXT Kakenhi (No. 170150181 and 26253041) from the Ministry of Education, Science, Sports, Culture and Technology of Japan, by a Grant-in-Aid for the Third Term Comprehensive 10-Year Strategy for Cancer Control from Ministry Health, Labour and Welfare of Japan, by Health and Labour Sciences Research Grants for Research on Applying Health Technology from Ministry Health, Labour and Welfare of Japan, by National Cancer Center Research and Development Fund, and “Practical Research for Innovative Cancer Control (15ck0106177h0001)” from Japan Agency for Medical Research and development, AMED, and Cancer Bio Bank Aichi. The HMBCS was supported by a grant from the Friends of Hannover Medical School and by the Rudolf Bartling Foundation. The HUBCS was supported by a grant from the German Federal Ministry of Research and Education (RUS08/017), and by the Russian Foundation for Basic Research and the Federal Agency for Scientific Organizations for support the Bioresource collections and RFBR grants 14-04-97088, 17-29-06014, and 17-44-020498. ICICLE was supported by Breast Cancer Now, CRUK, and Biomedical Research Centre at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. Financial support for KARBAC was provided through the regional agreement on medical training and clinical research (A.L.F.) between Stockholm County Council and Karolinska Institutet, the Swedish Cancer Society, The Gustav V Jubilee foundation and Bert von Kantzows foundation. The KARMA study was supported by Märit and Hans Rausings Initiative Against Breast Cancer. The KBCP was financially supported by the special Government Funding (E.V.O.) of Kuopio University Hospital grants, Cancer Fund of North Savo, the Finnish Cancer Organizations, and by the strategic funding of the University of Eastern Finland. kConFab is supported by a grant from the National Breast Cancer Foundation, and previously by the National Health and Medical Research Council (NHMRC), the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania and South Australia, and the Cancer Foundation of Western Australia. Financial support for the AOCS was provided by the United States Army Medical Research and Materiel Command [DAMD17-01-1-0729], Cancer Council Victoria, Queensland Cancer Fund, Cancer Council New South Wales, Cancer Council South Australia, The Cancer Foundation of Western Australia, Cancer Council Tasmania and the National Health and Medical Research Council of Australia (NHMRC; 400413, 400281, 199600). G.C.-T. and P.W. are supported by the NHMRC. RB was a Cancer Institute NSW Clinical Research Fellow. The KOHBRA study was partially supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), and the National R&D Program for Cancer Control, Ministry of Health & Welfare, Republic of Korea (HI16C1127; 1020350; 1420190). LAABC is supported by grants (1RB-0287, 3PB-0102, 5PB-0018, 10PB-0098) from the California Breast Cancer Research Program. Incident breast cancer cases were collected by the USC Cancer Surveillance Program (CSP) which is supported under subcontract by the California Department of Health. The CSP is also part of the National Cancer Institute’s Division of Cancer Prevention and Control Surveillance, Epidemiology, and End Results Program, under contract number N01CN25403. L.M.B.C. is supported by the ‘Stichting tegen Kanker’. D.L. is supported by the FWO. The MABCS study is funded by the Research Centre for Genetic Engineering and Biotechnology “Georgi D. Efremov” and supported by the German Academic Exchange Program, DAAD. The MARIE study was supported by the Deutsche Krebshilfe e.V. [70-2892-BR I, 106332, 108253, 108419, 110826, 110828], the Hamburg Cancer Society, the German Cancer Research Center (DKFZ) and the Federal Ministry of Education and Research (BMBF) Germany [01KH0402]. MBCSG is supported by grants from the Italian Association for Cancer Research (AIRC) and by funds from the Italian citizens who allocated the 5/1000 share of their tax payment in support of the Fondazione IRCCS Istituto Nazionale Tumori, according to Italian laws (INT-Institutional strategic projects “5 × 1000”). The MCBCS was supported by the NIH grants CA192393, CA116167, CA176785 an NIH Specialized Program of Research Excellence (SPORE) in Breast Cancer [CA116201], and the Breast Cancer Research Foundation and a generous gift from the David F. and Margaret T. Grohne Family Foundation. MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further supported by Australian NHMRC grants 209057 and 396414, and by infrastructure provided by Cancer Council Victoria. Cases and their vital status were ascertained through the Victorian Cancer Registry (VCR) and the Australian Institute of Health and Welfare (AIHW), including the National Death Index and the Australian Cancer Database. The MEC was support by NIH grants CA63464, CA54281, CA098758, CA132839, and CA164973. The MISS study is supported by funding from ERC-2011-294576 Advanced grant, Swedish Cancer Society, Swedish Research Council, Local hospital funds, Berta Kamprad Foundation, Gunnar Nilsson. The MMHS study was supported by NIH grants CA97396, CA128931, CA116201, CA140286, and CA177150. MSKCC is supported by grants from the Breast Cancer Research Foundation and Robert and Kate Niehaus Clinical Cancer Genetics Initiative. The work of MTLGEBCS was supported by the Quebec Breast Cancer Foundation, the Canadian Institutes of Health Research for the “CIHR Team in Familial Risks of Breast Cancer” program – grant # CRN-87521 and the Ministry of Economic Development, Innovation and Export Trade – grant # PSR-SIIRI-701. MYBRCA is funded by research grants from the Malaysian Ministry of Higher Education (UM.C/HlR/MOHE/06) and Cancer Research Malaysia. MYMAMMO is supported by research grants from Yayasan Sime Darby LPGA Tournament and Malaysian Ministry of Higher Education (RP046B-15HTM). The NBCS has been supported by the Research Council of Norway grant 193387/V50 (to A.-L. Børresen-Dale and V.N. Kristensen) and grant 193387/H10 (to A.-L. Børresen-Dale and V.N. Kristensen), South Eastern Norway Health Authority (grant 39346 to A.-L. Børresen-Dale and 27208 to V.N. Kristensen) and the Norwegian Cancer Society (to A.-L. Børresen-Dale and 419616 - 71248 - PR-2006-0282 to V.N. Kristensen). It has received funding from the K.G. Jebsen Centre for Breast Cancer Research (2012-2015). The NBHS was supported by NIH grant R01CA100374. Biological sample preparation was conducted the Survey and Biospecimen Shared Resource, which is supported by P30 CA68485. The Northern California Breast Cancer Family Registry (NC-BCFR) and Ontario Familial Breast Cancer Registry (OFBCR) were supported by grant UM1 CA164920 from the National Cancer Institute (USA). The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. The Carolina Breast Cancer Study was funded by Komen Foundation, the National Cancer Institute (P50 CA058223, U54 CA156733, and U01 CA179715), and the North Carolina University Cancer Research Fund. The NGOBCS was supported by Grants-in-Aid for the Third Term Comprehensive Ten-Year Strategy for Cancer Control from the Ministry of Health, Labor and Welfare of Japan, and for Scientific Research on Priority Areas, 17015049 and for Scientific Research on Innovative Areas, 221S0001, from the Ministry of Education, Culture, Sports, Science, and Technology of Japan. The NHS was supported by NIH grants P01 CA87969, UM1 CA186107, and U19 CA148065. The NHS2 was supported by NIH grants UM1 CA176726 and U19 CA148065. The OBCS was supported by research grants from the Finnish Cancer Foundation, the Academy of Finland (grant number 250083, 122715 and Center of Excellence grant number 251314), the Finnish Cancer Foundation, the Sigrid Juselius Foundation, the University of Oulu, the University of Oulu Support Foundation, and the special Governmental EVO funds for Oulu University Hospital-based research activities. The ORIGO study was supported by the Dutch Cancer Society (RUL 1997-1505) and the Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL CP16). The PBCS was funded by Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. Genotyping for PLCO was supported by the Intramural Research Program of the National Institutes of Health, NCI, Division of Cancer Epidemiology and Genetics. The PLCO is supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics and supported by contracts from the Division of Cancer Prevention, National Cancer Institute, National Institutes of Health. The POSH study is funded by Cancer Research UK (grants C1275/A11699, C1275/C22524, C1275/A19187, C1275/A15956, and Breast Cancer Campaign 2010PR62, 2013PR044. PROCAS is funded from NIHR grant PGfAR 0707-10031. The RBCS was funded by the Dutch Cancer Society (DDHK 2004-3124, DDHK 2009-4318). The SASBAC study was supported by funding from the Agency for Science, Technology and Research of Singapore (A*STAR), the US National Institute of Health (NIH) and the Susan G. Komen Breast Cancer Foundation. The SBCGS was supported primarily by NIH grants R01CA64277, R01CA148667, UMCA182910, and R37CA70867. Biological sample preparation was conducted the Survey and Biospecimen Shared Resource, which is supported by P30 CA68485. The scientific development and funding of this project were, in part, supported by the Genetic Associations and Mechanisms in Oncology (GAME-ON) Network U19 CA148065. The SBCS was supported by Sheffield Experimental Cancer Medicine Centre and Breast Cancer Now Tissue Bank. The SCCS is supported by a grant from the National Institutes of Health (R01 CA092447). Data on SCCS cancer cases used in this publication were provided by the Alabama Statewide Cancer Registry; Kentucky Cancer Registry, Lexington, KY; Tennessee Department of Health, Office of Cancer Surveillance; Florida Cancer Data System; North Carolina Central Cancer Registry, North Carolina Division of Public Health; Georgia Comprehensive Cancer Registry; Louisiana Tumor Registry; Mississippi Cancer Registry; South Carolina Central Cancer Registry; Virginia Department of Health, Virginia Cancer Registry; Arkansas Department of Health, Cancer Registry, 4815 W. Markham, Little Rock, AR 72205. The Arkansas Central Cancer Registry is fully funded by a grant from National Program of Cancer Registries, Centers for Disease Control and Prevention (CDC). Data on SCCS cancer cases from Mississippi were collected by the Mississippi Cancer Registry which participates in the National Program of Cancer Registries (NPCR) of the Centers for Disease Control and Prevention (CDC). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the CDC or the Mississippi Cancer Registry. SEARCH is funded by Cancer Research UK [C490/A10124, C490/A16561] and supported by the UK National Institute for Health Research Biomedical Research Centre at the University of Cambridge. The University of Cambridge has received salary support for PDPP from the NHS in the East of England through the Clinical Academic Reserve. SEBCS was supported by the BRL (Basic Research Laboratory) program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology (2012-0000347). SGBCC is funded by the NUS start-up Grant, National University Cancer Institute Singapore (NCIS) Centre Grant and the NMRC Clinician Scientist Award. Additional controls were recruited by the Singapore Consortium of Cohort Studies-Multi-ethnic cohort (SCCS-MEC), which was funded by the Biomedical Research Council, grant number: 05/1/21/19/425. The Sister Study (SISTER) is supported by the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences (Z01-ES044005 and Z01-ES049033). The Two Sister Study (2SISTER) was supported by the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences (Z01-ES044005 and Z01-ES102245), and, also by a grant from Susan G. Komen for the Cure, grant FAS0703856. SKKDKFZS is supported by the DKFZ. The SMC is funded by the Swedish Cancer Foundation. The SZBCS was supported by Grant PBZ_KBN_122/P05/2004. The TBCS was funded by The National Cancer Institute, Thailand. The TNBCC was supported by a Specialized Program of Research Excellence (SPORE) in Breast Cancer (CA116201), a grant from the Breast Cancer Research Foundation, a generous gift from the David F. and Margaret T. Grohne Family Foundation. The TWBCS is supported by the Taiwan Biobank project of the Institute of Biomedical Sciences, Academia Sinica, Taiwan. The UCIBCS component of this research was supported by the NIH [CA58860, CA92044] and the Lon V Smith Foundation [LVS39420]. The UKBGS is funded by Breast Cancer Now and the Institute of Cancer Research (ICR), London. ICR acknowledges NHS funding to the NIHR Biomedical Research Centre. The UKOPS study was funded by The Eve Appeal (The Oak Foundation) and supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre. The US3SS study was supported by Massachusetts (K.M.E., R01CA47305), Wisconsin (P.A.N., R01 CA47147) and New Hampshire (L.T.-E., R01CA69664) centers, and Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. The USRT Study was funded by Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. The WAABCS study was supported by grants from the National Cancer Institute of the National Institutes of Health (R01 CA89085 and P50 CA125183 and the D43 TW009112 grant), Susan G. Komen (SAC110026), the Dr. Ralph and Marian Falk Medical Research Trust, and the Avon Foundation for Women. The WHI program is funded by the National Heart, Lung, and Blood Institute, the US National Institutes of Health and the US Department of Health and Human Services (HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, and HHSN271201100004C). This work was also funded by NCI U19 CA148065-01. D.G.E. is supported by the all Manchester NIHR Biomedical research center Manchester (IS-BRC-1215-20007). HUNBOCS, Hungarian Breast and Ovarian Cancer Study was supported by Hungarian Research Grant KTIA-OTKA CK-80745, NKFI_OTKA K-112228. C.I. received support from the Nontherapeutic Subject Registry Shared Resource at Georgetown University (NIH/NCI P30-CA-51008) and the Jess and Mildred Fisher Center for Hereditary Cancer and Clinical Genomics Research. K.M. is supported by CRUK C18281/A19169. City of Hope Clinical Cancer Community Research Network and the Hereditary Cancer Research Registry, supported in part by Award Number RC4CA153828 (PI: J Weitzel) from the National Cancer Institute and the office of the Directory, National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The colorectal cancer genome-wide association analyses: Colorectal Transdisciplinary Study (CORECT): The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the CORECT Consortium, nor does mention of trade names, commercial products or organizations imply endorsement by the US Government or the CORECT Consortium. We are incredibly grateful for the contributions of Dr. Brian Henderson and Dr. Roger Green over the course of this study and acknowledge them in memoriam. We are also grateful for support from Daniel and Maryann Fong. ColoCare: we thank the many investigators and staff who made this research possible in ColoCare Seattle and ColoCare Heidelberg. ColoCare was initiated and developed at the Fred Hutchinson Cancer Research Center by Drs. Ulrich and Grady. CCFR: the Colon CFR graciously thanks the generous contributions of their study participants, dedication of study staff, and financial support from the U.S. National Cancer Institute, without which this important registry would not exist. Galeon: GALEON wishes to thank the Department of Surgery of University Hospital of Santiago (CHUS), Sara Miranda Ponte, Carmen M Redondo, and the staff of the Department of Pathology and Biobank of CHUS, Instituto de Investigación Sanitaria de Santiago (IDIS), Instituto de Investigación Sanitaria Galicia Sur (IISGS), SERGAS, Vigo, Spain, and Programa Grupos Emergentes, Cancer Genetics Unit, CHUVI Vigo Hospital, Instituto de Salud Carlos III, Spain. MCCS: this study was made possible by the contribution of many people, including the original investigators and the diligent team who recruited participants and continue to work on follow-up. We would also like to express our gratitude to the many thousands of Melbourne residents who took part in the study and provided blood samples. SEARCH: We acknowledge the contributions of Mitul Shah, Val Rhenius, Sue Irvine, Craig Luccarini, Patricia Harrington, Don Conroy, Rebecca Mayes, and Caroline Baynes. The Swedish low-risk colorectal cancer study: we thank Berith Wejderot and the Swedish low-risk colorectal cancer study group. Genetics & Epidemiology of Colorectal Cancer Consortium (GECCO): we thank all those at the GECCO Coordinating Center for helping bring together the data and people that made this project possible. ASTERISK: we are very grateful to Dr. Bruno Buecher without whom this project would not have existed. We also thank all those who agreed to participate in this study, including the patients and the healthy control persons, as well as all the physicians, technicians and students. DACHS: we thank all participants and cooperating clinicians, and Ute Handte-Daub, Renate Hettler-Jensen, Utz Benscheid, Muhabbet Celik, and Ursula Eilber for excellent technical assistance. HPFS, NHS and PHS: we acknowledge Patrice Soule and Hardeep Ranu of the Dana-Farber Harvard Cancer Center High-Throughput Polymorphism Core who assisted in the genotyping for NHS, HPFS, and PHS under the supervision of Dr. Immaculata Devivo and Dr. David Hunter, Qin (Carolyn) Guo, and Lixue Zhu who assisted in programming for NHS and HPFS and Haiyan Zhang who assisted in programming for the PHS. We thank the participants and staff of the Nurses’ Health Study and the Health Professionals Follow-Up Study, for their valuable contributions as well as the following state cancer registries for their help: A.L., A.Z., A.R., C.A., C.O., C.T., D.E., F.L., G.A., I.D., I.L., I.N., I.A., K.Y., L.A., M.E., M.D., M.A., M.I., N.E., N.H., N.J., N.Y., N.C., N.D., O.H., O.K., O.R., P.A., R.I., S.C., T.N., T.X., V.A., W.A., W.Y. In addition, this study was approved by the Connecticut Department of Public Health (DPH) Human Investigations Committee. Certain data used in this publication were obtained from the DPH. We assume full responsibility for analyses and interpretation of these data. PLCO: we thank Drs. Christine Berg and Philip Prorok, Division of Cancer Prevention, National Cancer Institute, the Screening Center investigators and staff or the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial, Mr. Tom Riley and staff, Information Management Services Inc., Ms. Barbara O’Brien and staff, Westat Inc. and Drs. Bill Kopp, Wen Shao and staff, SAIC-Frederick. Most importantly, we acknowledge the study participants for their contributions for making this study possible. The statements contained herein are solely those of the authors and do not represent or imply concurrence or endorsement by NCI. PMH: we thank the study participants and staff of the Hormones and Colon Cancer study. WHI: we thank the WHI investigators and staff for their dedication, and the study participants for making the program possible. A full listing of WHI investigators can be found at https://cleo.whi.org/researchers/Documents%20%20Write%20a%20Paper/WHI%20Investigator%20Short20List.pdf. CORECT: The CORECT Study was supported by the National Cancer Institute, National Institutes of Health (NCI/NIH), U.S. Department of Health and Human Services (grant numbers U19 CA148107, R01 CA81488, P30 CA014089, R01 CA197350; P01 CA196569; and R01 CA201407) and National Institutes of Environmental Health Sciences, National Institutes of Health (grant number T32 ES013678). The ATBC Study was supported by the US Public Health Service contracts (N01-CN-45165, N01-RC-45035, N01-RC-37004, and HHSN261201000006C) from the National Cancer Institute. The Cancer Prevention Study-II Nutrition Cohort is funded by the American Cancer Society. ColoCare: This work was supported by the National Institutes of Health (grant numbers R01 CA189184, U01 CA206110, 2P30CA015704-40 (Gilliland)), the Matthias Lackas-Foundation, the German Consortium for Translational Cancer Research, and the EU TRANSCAN initiative. Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO): funding for GECCO was provided by the National Cancer Institute, National Institutes of Health, U.S. Department of Health and Human Services (grant numbers U01 CA137088, R01 CA059045, and U01 CA164930). This research was funded in part through the NIH/NCI Cancer Center Support Grant P30 CA015704. The Colon Cancer Family Registry (CFR) Illumina GWAS was supported by funding from the National Cancer Institute, National Institutes of Health (grant numbers U01 CA122839, R01 CA143247). The Colon CFR/CORECT Affymetrix Axiom GWAS and OncoArray GWAS were supported by funding from National Cancer Institute, National Institutes of Health (grant number U19 CA148107 to S.G.). The Colon CFR participant recruitment and collection of data and biospecimens used in this study were supported by the National Cancer Institute, National Institutes of Health (grant number UM1 CA167551) and through cooperative agreements with the following Colon CFR centers: Australasian Colorectal Cancer Family Registry (NCI/NIH grant numbers U01 CA074778 and U01/U24 CA097735), USC Consortium Colorectal Cancer Family Registry (NCI/NIH grant numbers U01/U24 CA074799), Mayo Clinic Cooperative Family Registry for Colon Cancer Studies (NCI/NIH grant number U01/U24 CA074800), Ontario Familial Colorectal Cancer Registry (NCI/NIH grant number U01/U24 CA074783), Seattle Colorectal Cancer Family Registry (NCI/NIH grant number U01/U24 CA074794), and University of Hawaii Colorectal Cancer Family Registry (NCI/NIH grant number U01/U24 CA074806), Additional support for case ascertainment was provided from the Surveillance, Epidemiology and End Results (SEER) Program of the National Cancer Institute to Fred Hutchinson Cancer Research Center (Control Nos. N01-CN-67009 and N01-PC-35142, and Contract No. HHSN2612013000121), the Hawai’i Department of Health (Control Nos. N01-PC-67001 and N01-PC-35137, and Contract No. HHSN26120100037C, and the California Department of Public Health (contracts HHSN261201000035C awarded to the University of Southern California, and the following state cancer registries: A.Z., C.O., M.N., N.C., N.H., and by the Victoria Cancer Registry and Ontario Cancer Registry. ESTHER/VERDI was supported by grants from the Baden–Württemberg Ministry of Science, Research and Arts and the German Cancer Aid. MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria. GALEON: FIS Intrasalud (PI13/01136). The MCCS was further supported by Australian NHMRC grants 509348, 209057, 251553, and 504711 and by infrastructure provided by Cancer Council Victoria. Cases and their vital status were ascertained through the Victorian Cancer Registry (VCR) and the Australian Institute of Health and Welfare (AIHW), including the National Death Index and the Australian Cancer Database. MSKCC: the work at Sloan Kettering in New York was supported by the Robert and Kate Niehaus Center for Inherited Cancer Genomics and the Romeo Milio Foundation. Moffitt: This work was supported by funding from the National Institutes of Health (grant numbers R01 CA189184, P30 CA076292), Florida Department of Health Bankhead-Coley Grant 09BN-13, and the University of South Florida Oehler Foundation. Moffitt contributions were supported in part by the Total Cancer Care Initiative, Collaborative Data Services Core, and Tissue Core at the H. Lee Moffitt Cancer Center & Research Institute, a National Cancer Institute-designated Comprehensive Cancer Center (grant number P30 CA076292). SEARCH: Cancer Research UK (C490/A16561). The Spanish study was supported by Instituto de Salud Carlos III, co-funded by FEDER funds –a way to build Europe– (grants PI14-613 and PI09-1286), Catalan Government DURSI (grant 2014SGR647), and Junta de Castilla y León (grant LE22A10-2). The Swedish Low-risk Colorectal Cancer Study: the study was supported by grants from the Swedish research council; K2015-55 × -22674-01-4, K2008-55 × -20157-03-3, K2006-72 × -20157-01-2 and the Stockholm County Council (ALF project). CIDR genotyping for the Oncoarray was conducted under contract 268201200008I (to K.D.), through grant 101HG007491-01 (to C.I.A.). The Norris Cotton Cancer Center - P30CA023108, The Quantitative Biology Research Institute - P20GM103534, and the Coordinating Center for Screen Detected Lesions - U01CA196386 also supported efforts of C.I.A. This work was also supported by the National Cancer Institute (grant numbers U01 CA1817700, R01 CA144040). ASTERISK: a Hospital Clinical Research Program (PHRC) and supported by the Regional Council of Pays de la Loire, the Groupement des Entreprises Françaises dans la Lutte contre le Cancer (GEFLUC), the Association Anne de Bretagne Génétique and the Ligue Régionale Contre le Cancer (LRCC). COLO2&3: National Institutes of Health (grant number R01 CA060987). DACHS: This work was supported by the German Research Council (BR 1704/6-1, BR 1704/6-3, BR 1704/6-4, CH 117/1-1, HO 5117/2-1, HE 5998/2-1, KL 2354/3-1, RO 2270/8-1, and BR 1704/17-1), the Interdisciplinary Research Program of the National Center for Tumor Diseases (NCT), Germany, and the German Federal Ministry of Education and Research (01KH0404, 01ER0814, 01ER0815, 01ER1505A, and 01ER1505B). DALS: National Institutes of Health (grant number R01 CA048998 to M.L.S). HPFS is supported by National Institutes of Health (grant numbers P01 CA055075, UM1 CA167552, R01 137178, and P50 CA127003), NHS by the National Institutes of Health (grant numbers UM1 CA186107, R01 CA137178, P01 CA087969, and P50 CA127003), NHSII by the National Institutes of Health (grant numbers R01 050385CA and UM1 CA176726), and PHS by the National Institutes of Health (grant number R01 CA042182). MEC: National Institutes of Health (grant numbers R37 CA054281, P01 CA033619, and R01 CA063464). OFCCR: National Institutes of Health, through funding allocated to the Ontario Registry for Studies of Familial Colorectal Cancer (grant number U01 CA074783); see Colon CFR section above. As subset of ARCTIC, OFCCR is supported by a GL2 grant from the Ontario Research Fund, the Canadian Institutes of Health Research, and the Cancer Risk Evaluation (CaRE) Program grant from the Canadian Cancer Society Research Institute. T.J.H. and B.W.Z. are recipients of Senior Investigator Awards from the Ontario Institute for Cancer Research, through generous support from the Ontario Ministry of Research and Innovation. PLCO: Intramural Research Program of the Division of Cancer Epidemiology and Genetics and supported by contracts from the Division of Cancer Prevention, National Cancer Institute, NIH, DHHS. Additionally, a subset of control samples was genotyped as part of the Cancer Genetic Markers of Susceptibility (CGEMS) Prostate Cancer GWAS, Colon CGEMS pancreatic cancer scan (PanScan), and the Lung Cancer and Smoking study. The prostate and PanScan study datasets were accessed with appropriate approval through the dbGaP online resource (http://cgems.cancer.gov/data/) accession numbers phs000207.v1.p1 and phs000206.v3.p2, respectively, and the lung datasets were accessed from the dbGaP website (http://www.ncbi.nlm.nih.gov/gap) through accession number phs000093.v2.p2. Funding for the Lung Cancer and Smoking study was provided by National Institutes of Health (NIH), Genes, Environment and Health Initiative (GEI) Z01 CP 010200, NIH U01 HG004446, and NIH GEI U01 HG 004438. For the lung study, the GENEVA Coordinating Center provided assistance with genotype cleaning and general study coordination, 23 and the Johns Hopkins University Center for Inherited Disease Research conducted genotyping. PMH: National Institutes of Health (grant number R01 CA076366). VITAL: National Institutes of Health (grant number K05-CA154337). WHI: The WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts HHSN268201600018C, HHSN268201600001C, HHSN268201600002C, HHSN268201600003C, and HHSN268201600004C. The head and neck cancer genome-wide association analyses: The study was supported by NIH/NCI: P50 CA097190, and P30 CA047904, Canadian Cancer Society Research Institute (no. 020214) and Cancer Care Ontario Research Chair to R.H. The Princess Margaret Hospital Head and Neck Cancer Translational Research Program is funded by the Wharton family, Joe’s Team, Gordon Tozer, Bruce Galloway and the Elia family. Geoffrey Liu was supported by the Posluns Family Fund and the Lusi Wong Family Fund at the Princess Margaret Foundation, and the Alan B. Brown Chair in Molecular Genomics. This publication presents data from Head and Neck 5000 (H&N5000). H&N5000 was a component of independent research funded by the UK National Institute for Health Research (NIHR) under its Programme Grants for Applied Research scheme (RP-PG-0707-10034). The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. Human papillomavirus (HPV) in H&N5000 serology was supported by a Cancer Research UK Programme Grant, the Integrative Cancer Epidemiology Programme (grant number: C18281/A19169). National Cancer Institute (R01-CA90731); National Institute of Environmental Health Sciences (P30ES10126). The authors thank all the members of the GENCAPO team/The Head and Neck Genome Project (GENCAPO) was supported by the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) (Grant numbers 04/12054-9 and 10/51168-0). CPS-II recruitment and maintenance is supported with intramural research funding from the American Cancer Society. Genotyping performed at the Center for Inherited Disease Research (CIDR) was funded through the U.S. National Institute of Dental and Craniofacial Research (NIDCR) grant 1 × 01HG007780-0. The University of Pittsburgh head and neck cancer case-control study is supported by National Institutes of Health grants P50 CA097190 and P30 CA047904. The Carolina Head and Neck Cancer Study (CHANCE) was supported by the National Cancer Institute (R01-CA90731). The Head and Neck Genome Project (GENCAPO) was supported by the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) (Grant numbers 04/12054-9 and 10/51168-0). The authors thank all the members of the GENCAPO team. The HN5000 study was funded by the National Institute for Health Research (NIHR) under its Programme Grants for Applied Research scheme (RP-PG-0707-10034), the views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. The Toronto study was funded by the Canadian Cancer Society Research Institute (020214) and the National Cancer Institute (U19-CA148127) and the Cancer Care Ontario Research Chair. The alcohol-related cancers and genetic susceptibility study in Europe (ARCAGE) was funded by the European Commission’s 5th Framework Program (QLK1-2001-00182), the Italian Association for Cancer Research, Compagnia di San Paolo/FIRMS, Region Piemonte, and Padova University (CPDA057222). The Rome Study was supported by the Associazione Italiana per la Ricerca sul Cancro (AIRC) IG 2011 10491 and IG2013 14220 to S.B., and Fondazione Veronesi to S.B. The IARC Latin American study was funded by the European Commission INCO-DC programme (IC18-CT97-0222), with additional funding from Fondo para la Investigacion Cientifica y Tecnologica (Argentina) and the Fundação de Amparo à Pesquisa do Estado de São Paulo (01/01768-2). We thank Leticia Fernandez, Instituto Nacional de Oncologia y Radiobiologia, La Habana, Cuba and Sergio and Rosalina Koifman, for their efforts with the IARC Latin America study São Paulo center. The IARC Central Europe study was supported by European Commission’s INCO-COPERNICUS Program (IC15- CT98-0332), NIH/National Cancer Institute grant CA92039, and the World Cancer Research Foundation grant WCRF 99A28. The IARC Oral Cancer Multicenter study was funded by grant S06 96 202489 05F02 from Europe against Cancer; grants FIS 97/0024, FIS 97/0662, and BAE 01/5013 from Fondo de Investigaciones Sanitarias, Spain; the UICC Yamagiwa-Yoshida Memorial International Cancer Study; the National Cancer Institute of Canada; Associazione Italiana per la Ricerca sul Cancro; and the Pan-American Health Organization. Coordination of the EPIC study is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The lung cancer genome-wide association analyses: Transdisciplinary Research for Cancer in Lung (TRICL) of the International Lung Cancer Consortium (ILCCO) was supported by (U19-CA148127, CA148127S1, U19CA203654, and Cancer Prevention Research Institute of Texas RR170048). The ILCCO data harmonization is supported by Cancer Care Ontario Research Chair of Population Studies to R. H. and Lunenfeld-Tanenbaum Research Institute, Sinai Health System. The TRICL-ILCCO OncoArray was supported by in-kind genotyping by the Centre for Inherited Disease Research (26820120008i-0-26800068-1). The CAPUA study was supported by FIS-FEDER/Spain grant numbers FIS-01/310, FIS-PI03-0365, and FIS-07-BI060604, FICYT/Asturias grant numbers FICYT PB02-67 and FICYT IB09-133, and the University Institute of Oncology (IUOPA), of the University of Oviedo and the Ciber de Epidemiologia y Salud Pública. CIBERESP, SPAIN. The work performed in the CARET study was supported by the National Institute of Health/National Cancer Institute: UM1 CA167462 (PI: Goodman), National Institute of Health UO1-CA6367307 (PIs Omen, Goodman); National Institute of Health R01 CA111703 (PI Chen), National Institute of Health 5R01 CA151989-01A1(PI Doherty). The Liverpool Lung project is supported by the Roy Castle Lung Cancer Foundation. The Harvard Lung Cancer Study was supported by the NIH (National Cancer Institute) grants CA092824, CA090578, CA074386. The Multi-ethnic Cohort Study was partially supported by NIH Grants CA164973, CA033619, CA63464, and CA148127. The work performed in MSH-PMH study was supported by The Canadian Cancer Society Research Institute (020214), Ontario Institute of Cancer and Cancer Care Ontario Chair Award to R.J.H. and G.L. and the Alan Brown Chair and Lusi Wong Programs at the Princess Margaret Hospital Foundation. NJLCS was funded by the State Key Program of National Natural Science of China (81230067), the National Key Basic Research Program Grant (2011CB503805), the Major Program of the National Natural Science Foundation of China (81390543). The Norway study was supported by Norwegian Cancer Society, Norwegian Research Council. The Shanghai Cohort Study (SCS) was supported by National Institutes of Health R01 CA144034 (PI: Yuan) and UM1 CA182876 (PI: Yuan). The Singapore Chinese Health Study (SCHS) was supported by National Institutes of Health R01 CA144034 (PI: Yuan) and UM1 CA182876 (PI: Yuan). The work in TLC study has been supported in part the James & Esther King Biomedical Research Program (09KN-15), National Institutes of Health Specialized Programs of Research Excellence (SPORE) Grant (P50 CA119997), and by a Cancer Center Support Grant (CCSG) at the H. Lee Moffitt Cancer Center and Research Institute, an NCI designated Comprehensive Cancer Center (grant number P30-CA76292). The Vanderbilt Lung Cancer Study—BioVU dataset used for the analyses described was obtained from Vanderbilt University Medical Center’s BioVU, which is supported by institutional funding, the 1S10RR025141-01 instrumentation award, and by the Vanderbilt CTSA grant UL1TR000445 from NCATS/NIH. Dr. Aldrich was supported by NIH/National Cancer Institute K07CA172294 (PI: Aldrich) and Dr. Bush was supported by NHGRI/NIH U01HG004798 (PI: Crawford). The Copenhagen General Population Study (CGPS) was supported by the Chief Physician Johan Boserup and Lise Boserup Fund, the Danish Medical Research Council and Herlev Hospital. The NELCS study: Grant Number P20RR018787 from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH). The Kentucky Lung Cancer Research Initiative was supported by the Department of Defense [Congressionally Directed Medical Research Program, U.S. Army Medical Research and Materiel Command Program] under award number: 10153006 (W81XWH-11-1-0781). Views and opinions of, and endorsements by the author(s) do not reflect those of the US Army or the Department of Defense. This research was also supported by unrestricted infrastructure funds from the UK Center for Clinical and Translational Science, NIH grant UL1TR000117 and Markey Cancer Center NCI Cancer Center Support Grant (P30 CA177558) Shared Resource Facilities: Cancer Research Informatics, Biospecimen and Tissue Procurement, and Biostatistics and Bioinformatics. The M.D. Anderson Cancer Center study was supported in part by grants from the NIH (P50 CA070907, R01 CA176568) (to X.W.), Cancer Prevention & Research Institute of Texas (RP130502) (to X.W.), and The University of Texas MD Anderson Cancer Center institutional support for the Center for Translational and Public Health Genomics. The deCODE study of smoking and nicotine dependence was funded in part by a grant from NIDA (R01- DA017932). The study in Lodz center was partially funded by Nofer Institute of Occupational Medicine, under task NIOM 10.13: Predictors of mortality from non-small cell lung cancer—field study. Genetic sharing analysis was funded by NIH grant CA194393. The research undertaken by M.D.T., L.V.W., and M.S.A. was partly funded by the National Institute for Health Research (NIHR). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. M.D.T. holds a Medical Research Council Senior Clinical Fellowship (G0902313). The work to assemble the FTND GWAS meta-analysis was supported by the National Institutes of Health (NIH), National Institute on Drug Abuse (NIDA) grant number R01 DA035825 (Principal Investigator [PI]: DBH). The study populations included COGEND (dbGaP phs000092.v1.p1 and phs000404.v1.p1), COPDGene (dbGaP phs000179.v3.p2), deCODE Genetics, EAGLE (dbGaP phs000093.vs.p2), and SAGE. dbGaP phs000092.v1.p1). See Hancock et al. Transl Psychiatry 2015 (PMCID: PMC4930126) for the full listing of funding sources and other acknowledgments. The Resource for the Study of Lung Cancer Epidemiology in North Trent (ReSoLuCENT)study was funded by the Sheffield Hospitals Charity, Sheffield Experimental Cancer Medicine Centre and Weston Park Hospital Cancer Charity. The ovarian cancer genome-wide association analysis: The Ovarian Cancer Association Consortium (OCAC) is supported by a grant from the Ovarian Cancer Research Fund thanks to donations by the family and friends of Kathryn Sladek Smith (PPD/RPCI.07). The scientific development and funding for this project were in part supported by the US National Cancer Institute GAME-ON Post-GWAS Initiative (U19-CA148112). This study made use of data generated by the Wellcome Trust Case Control consortium that was funded by the Wellcome Trust under award 076113. The results published here are in part based upon data generated by The Cancer Genome Atlas Pilot Project established by the National Cancer Institute and National Human Genome Research Institute (dbGap accession number phs000178.v8.p7). The OCAC OncoArray genotyping project was funded through grants from the U.S. National Institutes of Health (CA1X01HG007491-01 (C.I.A.), U19-CA148112 (T.A.S.), R01-CA149429 (C.M.P.), and R01-CA058598 (M.T.G.); Canadian Institutes of Health Research (MOP-86727 (L.E.K.) and the Ovarian Cancer Research Fund (A.B.). The COGS project was funded through a European Commission’s Seventh Framework Programme grant (agreement number 223175 - HEALTH-F2-2009-223175) and through a grant from the U.S. National Institutes of Health (R01-CA122443 (E.L.G)). Funding for individual studies: AAS: National Institutes of Health (RO1-CA142081); AOV: The Canadian Institutes for Health Research (MOP-86727); AUS: The Australian Ovarian Cancer Study Group was supported by the U.S. Army Medical Research and Materiel Command (DAMD17-01-1-0729), National Health & Medical Research Council of Australia (199600, 400413 and 400281), Cancer Councils of New South Wales, Victoria, Queensland, South Australia and Tasmania and Cancer Foundation of Western Australia (Multi-State Applications 191, 211, and 182). The Australian Ovarian Cancer Study gratefully acknowledges additional support from Ovarian Cancer Australia and the Peter MacCallum Foundation; BAV: ELAN Funds of the University of Erlangen-Nuremberg; BEL: National Kankerplan; BGS: Breast Cancer Now, Institute of Cancer Research; BVU: Vanderbilt CTSA grant from the National Institutes of Health (NIH)/National Center for Advancing Translational Sciences (NCATS) (ULTR000445); CAM: National Institutes of Health Research Cambridge Biomedical Research Centre and Cancer Research UK Cambridge Cancer Centre; CHA: Innovative Research Team in University (PCSIRT) in China (IRT1076); CNI: Instituto de Salud Carlos III (PI12/01319); Ministerio de Economía y Competitividad (SAF2012); COE: Department of Defense (W81XWH-11-2-0131); CON: National Institutes of Health (R01-CA063678, R01-CA074850; and R01-CA080742); DKE: Ovarian Cancer Research Fund; DOV: National Institutes of Health R01-CA112523 and R01-CA87538; EMC: Dutch Cancer Society (EMC 2014-6699); EPC: The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l’Education Nationale, Institut National de la Santé et de la Recherche Médicale (INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ), Federal Ministry of Education and Research (BMBF) (Germany); the Hellenic Health Foundation (Greece); Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); ERC-2009-AdG 232997 and Nordforsk, Nordic Centre of Excellence programme on Food, Nutrition and Health (Norway); Health Research Fund (FIS), PI13/00061 to Granada, PI13/01162 to EPIC-Murcia, Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, ISCIII RETIC (RD06/0020) (Spain); Swedish Cancer Society, Swedish Research Council and County Councils of Skåne and Västerbotten (Sweden); Cancer Research UK (14136 to EPIC-Norfolk; C570/A16491 and C8221/A19170 to EPIC-Oxford), Medical Research Council (1000143 to EPIC-Norfolk, MR/M012190/1 to EPIC-Oxford) (United Kingdom); GER: German Federal Ministry of Education and Research, Programme of Clinical Biomedical Research (01 GB 9401) and the German Cancer Research Center (DKFZ); GRC: This research has been co-financed by the European Union (European Social Fund—ESF) and Greek national funds through the Operational Program “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF)—Research Funding Program of the General Secretariat for Research & Technology: SYN11_10_19 NBCA. Investing in knowledge society through the European Social Fund; GRR: Roswell Park Cancer Institute Alliance Foundation, P30 CA016056; HAW: U.S. National Institutes of Health (R01-CA58598, N01-CN-55424, and N01-PC-67001); HJO: Intramural funding; Rudolf-Bartling Foundation; HMO: Intramural funding; Rudolf-Bartling Foundation; HOC: Helsinki University Research Fund; HOP: Department of Defense (DAMD17-02-1-0669) and NCI (K07-CA080668, R01-CA95023, P50-CA159981 MO1-RR000056 R01-CA126841); HUO: Intramural funding; Rudolf-Bartling Foundation; JGO: JSPS KAKENHI grant; JPN: Grant-in-Aid for the Third Term Comprehensive 10-Year Strategy for Cancer Control from the Ministry of Health, Labour and Welfare; KRA: This study (Ko-EVE) was supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), and the National R&D Program for Cancer Control, Ministry of Health & Welfare, Republic of Korea (HI16C1127; 0920010); LAX: American Cancer Society Early Detection Professorship (SIOP-06-258-01-COUN) and the National Center for Advancing Translational Sciences (NCATS), Grant UL1TR000124; LUN: ERC-2011-AdG 294576-risk factors cancer, Swedish Cancer Society, Swedish Research Council, Beta Kamprad Foundation; MAC: National Institutes of Health (R01-CA122443, P30-CA15083, P50-CA136393); Mayo Foundation; Minnesota Ovarian Cancer Alliance; Fred C. and Katherine B. Andersen Foundation; Fraternal Order of Eagles; MAL: Funding for this study was provided by research grant R01- CA61107 from the National Cancer Institute, Bethesda, MD, research grant 94 222 52 from the Danish Cancer Society, Copenhagen, Denmark; and the Mermaid I project; MAS: Malaysian Ministry of Higher Education (UM.C/HlR/MOHE/06) and Cancer Research Initiatives Foundation; MAY: National Institutes of Health (R01-CA122443, P30-CA15083, and P50-CA136393); Mayo Foundation; Minnesota Ovarian Cancer Alliance; Fred C. and Katherine B. Andersen Foundation; MCC: Cancer Council Victoria, National Health and Medical Research Council of Australia (NHMRC) grants number 209057, 251533, 396414, and 504715; MDA: DOD Ovarian Cancer Research Program (W81XWH-07-0449); MEC: NIH (CA54281, CA164973, CA63464); MOF: Moffitt Cancer Center, Merck Pharmaceuticals, the state of Florida, Hillsborough County, and the city of Tampa; NCO: National Institutes of Health (R01-CA76016) and the Department of Defense (DAMD17-02-1-0666); NEC: National Institutes of Health R01-CA54419 and P50-CA105009 and Department of Defense W81XWH-10-1-02802; NHS: UM1 CA186107, P01 CA87969, R01 CA49449, R01-CA67262, UM1 CA176726; NJO: National Cancer Institute (NIH-K07 CA095666, R01-CA83918, NIH-K22-CA138563, and P30-CA072720) and the Cancer Institute of New Jersey; If Sara Olson and/or Irene Orlow is a co-author, please add NCI CCSG award (P30-CA008748) to the funding sources; NOR: Helse Vest, The Norwegian Cancer Society, The Research Council of Norway; NTH: Radboud University Medical Centre; OPL: National Health and Medical Research Council (NHMRC) of Australia (APP1025142) and Brisbane Women’s Club; ORE: OHSU Foundation; OVA: This work was supported by Canadian Institutes of Health Research grant (MOP-86727) and by NIH/NCI 1 R01CA160669-01A1; PLC: Intramural Research Program of the National Cancer Institute; POC: Pomeranian Medical University; POL: Intramural Research Program of the National Cancer Institute; PVD: Canadian Cancer Society and Cancer Research Society GRePEC Program; RBH: National Health and Medical Research Council of Australia; RMH: Cancer Research UK, Royal Marsden Hospital; RPC: National Institute of Health (P50-CA159981, R01-CA126841); SEA: Cancer Research UK (C490/A10119 C490/A10124); UK National Institute for Health Research Biomedical Research Centres at the University of Cambridge; SIS: NIH, National Institute of Environmental Health Sciences, Z01-ES044005 and Z01-ES049033; SMC: The bbSwedish Research Council-SIMPLER infrastructure; the Swedish Cancer Foundation; SON: National Health Research and Development Program, Health Canada, grant 6613-1415-53; SRO: Cancer Research UK (C536/A13086, C536/A6689) and Imperial Experimental Cancer Research Centre (C1312/A15589); STA: NIH grants U01 CA71966 and U01 CA69417; SWE: Swedish Cancer foundation, WeCanCureCancer and VårKampMotCancer foundation; SWH: NIH (NCI) grant R37-CA070867; TBO: National Institutes of Health (R01-CA106414-A2), American Cancer Society (CRTG-00-196-01-CCE), Department of Defense (DAMD17-98-1-8659), Celma Mastery Ovarian Cancer Foundation; TOR: NIH grants R01-CA063678 and R01 CA063682; UCI: NIH R01-CA058860 and the Lon V Smith Foundation grant LVS39420; UHN: Princess Margaret Cancer Centre Foundation-Bridge for the Cure; UKO: The UKOPS study was funded by The Eve Appeal (The Oak Foundation) and supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre; UKR: Cancer Research UK (C490/A6187), UK National Institute for Health Research Biomedical Research Centres at the University of Cambridge; USC: P01CA17054, P30CA14089, R01CA61132, N01PC67010, R03CA113148, R03CA115195, N01CN025403, and California Cancer Research Program (00-01389V-20170, 2II0200); VAN: BC Cancer Foundation, VGH & UBC Hospital Foundation; VTL: NIH K05-CA154337; WMH: National Health and Medical Research Council of Australia, Enabling Grants ID 310670 & ID 628903. Cancer Institute NSW Grants 12/RIG/1-17 & 15/RIG/1-16; WOC: National Science Centren (N N301 5645 40). The Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Warsaw, Poland. The University of Cambridge has received salary support for PDPP from the NHS in the East of England through the Clinical Academia Reserve. The prostate cancer genome-wide association analyses: we pay tribute to Brian Henderson, who was a driving force behind the OncoArray project, for his vision and leadership, and who sadly passed away before seeing its fruition. We also thank the individuals who participated in these studies enabling this work. The ELLIPSE/PRACTICAL (http//:practical.icr.ac.uk) prostate cancer consortium and his collaborating partners were supported by multiple funding mechanisms enabling this current work. ELLIPSE/PRACTICAL Genotyping of the OncoArray was funded by the US National Institutes of Health (NIH) (U19 CA148537 for ELucidating Loci Involved in Prostate Cancer SuscEptibility (ELLIPSE) project and X01HG007492 to the Center for Inherited Disease Research (CIDR) under contract number HHSN268201200008I). Additional analytical support was provided by NIH NCI U01 CA188392 (F.R.S.). Funding for the iCOGS infrastructure came from the European Community’s Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, and C8197/A16565), the National Institutes of Health (CA128978) and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065, and 1U19 CA148112; the GAME-ON initiative), the Department of Defense (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. This work was supported by the Canadian Institutes of Health Research, European Commission’s Seventh Framework Programme grant agreement n° 223175 (HEALTH-F2-2009-223175), Cancer Research UK Grants C5047/A7357, C1287/A10118, C1287/A16563, C5047/A3354, C5047/A10692, C16913/A6135, C5047/A21332 and The National Institute of Health (NIH) Cancer Post-Cancer GWAS initiative grant: No. 1 U19 CA148537-01 (the GAME-ON initiative). We also thank the following for funding support: The Institute of Cancer Research and The Everyman Campaign, The Prostate Cancer Research Foundation, Prostate Research Campaign UK (now Prostate Action), The Orchid Cancer Appeal, The National Cancer Research Network UK, and The National Cancer Research Institute (NCRI) UK. We are grateful for support of NIHR funding to the NIHR Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. The Prostate Cancer Program of Cancer Council Victoria also acknowledge grant support from The National Health and Medical Research Council, Australia (126402, 209057, 251533, 396414, 450104, 504700, 504702, 504715, 623204, 940394, and 614296), VicHealth, Cancer Council Victoria, The Prostate Cancer Foundation of Australia, The Whitten Foundation, PricewaterhouseCoopers, and Tattersall’s. E.A.O., D.M.K., and E.M.K. acknowledge the Intramural Program of the National Human Genome Research Institute for their support. The BPC3 was supported by the U.S. National Institutes of Health, National Cancer Institute (cooperative agreements U01-CA98233 to D.J.H., U01-CA98710 to S.M.G., U01-CA98216 to E.R., and U01-CA98758 to B.E.H., and Intramural Research Program of NIH/National Cancer Institute, Division of Cancer Epidemiology and Genetics). CAPS GWAS study was supported by the Swedish Cancer Foundation (grant no 09-0677, 11-484, 12-823), the Cancer Risk Prediction Center (CRisP; www.crispcenter.org), a Linneus Centre (Contract ID 70867902) financed by the Swedish Research Council, Swedish Research Council (grant no K2010-70 × -20430-04-3, 2014-2269). The Hannover Prostate Cancer Study was supported by the Lower Saxonian Cancer Society. PEGASUS was supported by the Intramural Research Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health. RAPPER was supported by the NIHR Manchester Biomedical Research Center, Cancer Research UK (C147/A25254, C1094/A18504) and the EU’s 7th Framework Programme Grant/Agreement no 60186. Overall: this research has been conducted using the UK Biobank Resource (application number 16549). NHS is supported by UM1 CA186107 (NHS cohort infrastructure grant), P01 CA87969, and R01 CA49449. NHSII is supported by UM1 CA176726 (NHSII cohort infrastructure grant), and R01-CA67262. A.L.K. is supported by R01 MH107649. We would like to thank the participants and staff of the NHS and NHSII for their valuable contributions as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, WY. The authors assume full responsibility for analyses and interpretation of these data.

Reference list of studies included in this systematic review. (PDF 46 kb)

DNase I hypersensitive sites (DHS) are abundant in regulatory elements, such as promoter, enhancer and transcription factor binding sites. Many studies have revealed that disease-associated variants were concentrated in DHS-related regions. However, limited studies are available on the roles of DHS-related variants in lung cancer. In this study, we performed a large-scale case–control study with 20 871 lung cancer cases and 15 971 controls to evaluate the associations between regulatory genetic variants in DHS and lung cancer susceptibility. The expression quantitative trait loci (eQTL) analysis and pathway-enrichment analysis were performed to identify the possible target genes and pathways. In addition, we performed motif-based analysis to explore the lung-cancer-related motifs using sequence kernel association test. Two novel variants, rs186332 in 20q13.3 (C>T, odds ratio [OR] = 1.17, 95% confidence interval [95% CI]: 1.10–1.24, P = 8.45 × 10−7) and rs4839323 in 1p13.2 (T>C, OR = 0.92, 95% CI: 0.89–0.95, P = 1.02 × 10−6) showed significant association with lung cancer risk. The eQTL analysis suggested that these two SNPs might regulate the expression of MRGBP and SLC16A1, respectively. What’s more, the expression of both MRGBP and SLC16A1 was aberrantly elevated in lung tumor tissues. The motif-based analysis identified 10 motifs related to the risk of lung cancer (P < 1.71 × 10−4). Our findings suggested that variants in DHS might modify lung cancer susceptibility through regulating the expression of surrounding genes. This study provided us a deeper insight into the roles of DHS-related genetic variants for lung cancer.

Completed PRISMA 2009 checklist. (PDF 201 kb)

The development of cancer is driven by the accumulation of many oncogenesis-related genetic alterations and tumorigenesis is triggered by complex networks of involved genes rather than independent actions. To explore the epistasis existing among oncogenesis-related genes in lung cancer development, we conducted pairwise genetic interaction analyses among 35,031 SNPs from 2027 oncogenesis-related genes. The genotypes from three independent genome-wide association studies including a total of 24,037 lung cancer patients and 20,401 healthy controls with Caucasian ancestry were analyzed in the study. Using a two-stage study design including discovery and replication studies, and stringent Bonferroni correction for multiple statistical analysis, we identified significant genetic interactions between SNPs in RGL1:RAD51B (OR=0.44, p value=3.27x10-11 in overall lung cancer and OR=0.41, p value=9.71x10-11 in non-small cell lung cancer), SYNE1:RNF43 (OR=0.73, p value=1.01x10-12 in adenocarcinoma) and FHIT:TSPAN8 (OR=1.82, p value=7.62x10-11 in squamous cell carcinoma) in our analysis. None of these genes have been identified from previous main effect association studies in lung cancer. Further eQTL gene expression analysis in lung tissues provided information supporting the functional role of the identified epistasis in lung tumorigenesis. Gene set enrichment analysis revealed potential pathways and gene networks underlying molecular mechanisms in overall lung cancer as well as histology subtypes development. Our results provide evidence that genetic interactions between oncogenesis-related genes play an important role in lung tumorigenesis and epistasis analysis, combined with functional annotation, provides a valuable tool for uncovering functional novel susceptibility genes that contribute to lung cancer development by interacting with other modifier genes.

Introduction: Inherited susceptibility to lung cancer risk in never-smokers is poorly understood. The major reason for this gap in knowledge is that this disease is relatively uncommon (except in Asians), making it difficult to assemble an adequate study sample. In this study we conducted a genome-wide association study on the largest, to date, set of European-descent never-smokers with lung cancer. Methods: We conducted a two-phase (discovery and replication) genome-wide association study in never-smokers of European descent. We further augmented the sample by performing a meta-analysis with never-smokers from the recent OncoArray study, which resulted in a total of 3636 cases and 6295 controls. We also compare our findings with those in smokers with lung cancer. Results: We detected three genome-wide statistically significant single nucleotide polymorphisms rs31490 (odds ratio [OR]: 0.769, 95% confidence interval [CI]: 0.722-0.820; p value 5.31 x 10(-16)), rs380286 (OR: 0.770, 95% CI: 0.723-0.820; p value 4.32 x 10(-16)), and rs4975616 OR: 0.778, 95% CI: 0.730-0.829; p value 1.04 x 10(-14)). All three mapped to Chromosome 5 CLPTM1L-TERT region, previously shown to be associated with lung cancer risk in smokers and in never-smoker Asian women, and risk of other cancers including breast, ovarian, colorectal, and prostate. Conclusions: We found that genetic susceptibility to lung cancer in never-smokers is associated to genetic variants with pan-cancer risk effects. The comparison with smokers shows that top variants previously shown to be associated with lung cancer risk only confer risk in the presence of tobacco exposure, underscoring the importance of gene-environment interactions in the etiology of this disease. (C) 2019 International Association for the Study of Lung Cancer. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Background In individually randomised trials we might expect interventions delivered in groups or by care providers to result in clustering of outcomes for participants treated in the same group or by the same care provider. In partially nested randomised controlled trials (pnRCTs) this clustering only occurs in one trial arm, commonly the intervention arm. It is important to measure and account for between-cluster variability in trial design and analysis. We compare analysis approaches for pnRCTs with continuous outcomes, investigating the impact on statistical inference of cluster sizes, coding of the non-clustered arm, intracluster correlation coefficient (ICCs), and differential variance between intervention and control arm, and provide recommendations for analysis. Methods We performed a simulation study assessing the performance of six analysis approaches for a two-arm pnRCT with a continuous outcome. These include: linear regression model; fully clustered mixed-effects model with singleton clusters in control arm; fully clustered mixed-effects model with one large cluster in control arm; fully clustered mixed-effects model with pseudo clusters in control arm; partially nested homoscedastic mixed effects model, and partially nested heteroscedastic mixed effects model. We varied the cluster size, number of clusters, ICC, and individual variance between the two trial arms. Results All models provided unbiased intervention effect estimates. In the partially nested mixed-effects models, methods for classifying the non-clustered control arm had negligible impact. Failure to account for even small ICCs resulted in inflated Type I error rates and over-coverage of confidence intervals. Fully clustered mixed effects models provided poor control of the Type I error rates and biased ICC estimates. The heteroscedastic partially nested mixed-effects model maintained relatively good control of Type I error rates, unbiased ICC estimation, and did not noticeably reduce power even with homoscedastic individual variances across arms. Conclusions In general, we recommend the use of a heteroscedastic partially nested mixed-effects model, which models the clustering in only one arm, for continuous outcomes similar to those generated under the scenarios of our simulations study. However, with few clusters (3–6), small cluster sizes (5–10), and small ICC (≤0.05) this model underestimates Type I error rates and there is no optimal model. Electronic supplementary material The online version of this article (10.1186/s12874-018-0559-x) contains supplementary material, which is available to authorized users.

Study aimThis study aims to determine the impact of the red arrest teams (RATs) on survival to 30 days and return of spontaneous circulation (ROSC) at hospital.MethodsA retrospective cohort study analysing routinely collected data was undertaken. All adult (≥18 years) OHCAs entered onto the YAS computer aided dispatch (CAD) system between the 1st October, 2015 and 30th September, 2017 were included if the patient was resuscitated, and the cause of the arrest was considered to be medical in origin. Multivariable logistic regression models were created to enable adjustment for common predictors of survival and ROSC.ResultsDuring the 2-year data collection period, 15,151 cardiac arrests that were attended by Yorkshire Ambulance Service. After removing ineligible cases, 5,868 cardiac arrests remained. RATs attended 2,000/5,868 (34.1%) incidents, with each RAT attending a median of 13 cardiac arrests (IQR 7–23, minimum 1, maximum 78).The adjusted odds ratios suggest that a RAT on scene is associated with a slight increase in the odds of survival to 30 days (OR 1.01, 95%CI 0.74–1.38) and odds of ROSC on arrival at hospital (OR 1.13, 95%CI 0.99–1.29), compared to the odds of not having a RAT present, although neither results are statistically significant.ConclusionThe presence of a RAT paramedic was associated with a small increase in survival to 30 days and ROSC on arrival at hospital, although neither were statistically significant. Larger prospective studies are required to determine the effect of roles such as RAT on outcomes from OHCA

IntroductionSpecific phobias (intense, enduring fears of an object or situation that lead to avoidance and severe distress) are highly prevalent among children and young people. Cognitive–behavioural therapy (CBT) is a well-established, effective intervention, but it can be time consuming and costly because it is routinely delivered over multiple sessions during several months. Alternative methods of treating severe and debilitating phobias in children are needed, like one-session treatment (OST), to reduce time and cost, and to prevent therapeutic drift and help children recover quickly. Our study explores whether (1) outcomes with OST are ‘no worse’ than outcomes with multisession CBT, (2) OST is acceptable to children, their parents and the practitioners who use it and (3) OST offers good value for money to the National Health Service (NHS) and to society.MethodA pragmatic, non-inferiority, randomised controlled trial will compare OST with multisession CBT-based therapy on their clinical and cost-effectiveness. The primary clinical outcome is a standardised behavioural task of approaching the feared stimulus at 6 months postrandomisation. The outcomes for the within-trial cost-effectiveness analysis are quality-adjusted life years based on EQ-5D-Y, and individual-level costs based of the intervention and use of health and social service care. A nested qualitative evaluation will explore children’s, parents’ and practitioners’ perceptions and experiences of OST. A total of 286 children, 7–16 years old, with DSM-IV diagnoses of specific phobia will be recruited via gatekeepers in the NHS, schools and voluntary youth services, and via public adverts.Ethics and disseminationThe trial received ethical approval from North East and York Research Ethics Committee (Reference: 17/NE/0012). Dissemination plans include publications in peer-reviewed journals, presentations in relevant research conferences, local research symposia and seminars for children and their families, and for professionals and service managers.Trial registration numberISRCTN19883421;Pre-results.

CAPUA study was supported by FIS-FEDER/Spain grant numbers FIS-01/310, FIS-PI03-0365, and FIS-07-BI060604, FICYT/Asturias grant numbers FICYT PB02-67 and FICYT IB09-133, and the University Institute of Oncology (IUOPA), of the University of Oviedo and the Ciber de Epidemiología y Salud Pública. CIBERESP, SPAIN (...), Ferreiro-Iglesias, A., Lesseur, C., McKay, J., Hung, R.J., Han, Y., Zong, X., Christiani, D., Johansson, M., Xiao, X., Li, Y., Qian, D.C., Ji, X., Liu, G., Caporaso, N., Scelo, G., Zaridze, D., Mukeriya, A., Kontic, M., Ognjanovic, S., Lissowska, J., Szołkowska, M., Swiatkowska, B., Janout, V., Holcatova, I., Bolca, C., Savic, M., Ognjanovic, M., Bojesen, S.E., Wu, X., Albanes, D., Aldrich, M.C., Tardon, A., Fernandez-Somoano, A., Fernandez-Tardon, G., Le Marchand, L., Rennert, G., Chen, C., Doherty, J., Goodman, G., Bickeböller, H., Wichmann, H.-E., Risch, A., Rosenberger, A., Shen, H., Dai, J., Field, J.K., Davies, M., Woll, P., Teare, M.D., Kiemeney, L.A., van der Heijden, E.H.F.M., Yuan, J.-M., Hong, Y.-C., Haugen, A., Zienolddiny, S., Lam, S., Tsao, M.-S., Johansson, M., Grankvist, K., Schabath, M.B., Andrew, A., Duell, E., Melander, O., Brunnström, H., Lazarus, P., Arnold, S., Slone, S., Byun, J., Kamal, A., Zhu, D., Landi, M.T., Amos, C.I., Brennan, P.

Supported by FIS-FEDER/Spain grant numbers FIS-01/310, FIS-PI03-0365, and FIS-07-BI060604, FICYT/Asturias grant numbers FICYT PB02-67 and FICYT IB09-133, and the University Institute of Oncology (IUOPA) of the University of Oviedo and the Ciber de Epidemiologia y Salud Pública., Ji, X., Bossé, Y., Landi, M.T., Gui, J., Xiao, X., Qian, D., Joubert, P., Lamontagne, M., Li, Y., Gorlov, I., de Biasi, M., Han, Y., Gorlova, O., Hung, R.J., Wu, X., McKay, J., Zong, X., Carreras-Torres, R., Christiani, D.C., Caporaso, N., Johansson, M., Liu, G., Bojesen, S.E., Le Marchand, L., Albanes, D., Bickeböller, H., Aldrich, M.C., Bush, W.S., Tardon, A., Rennert, G., Chen, C., Teare, M.D., Field, J.K., Kiemeney, L.A., Lazarus, P., Haugen, A., Lam, S., Schabath, M.B.,,rew, A.S., Shen, H., Hong, Y.-C., Yuan, J.-M., Bertazzi, P.A., Pesatori, A.C., Ye, Y., Diao, N., Su, L., Zhang, R., Brhane, Y., Leighl, N., Johansen, J.S., Mellemgaard, A., Saliba, W., Haiman, C., Wilkens, L., Fernandez-Somoano, A., Fernandez-Tardon, G., van der Heijden, E.H.F.M., Kim, J.H., Dai, J., Hu, Z., Davies, M.P.A., Marcus, M.W., Brunnström, H., Manjer, J., Melander, O., Muller, D.C., Overvad, K., Trichopoulou, A., Tumino, R., Doherty, J., Goodman, G.E., Cox, A., Taylor, F., Woll, P., Brüske, I., Manz, J., Muley, T., Risch, A., Rosenberger, A., Grankvist, K., Johansson, M., Shepherd, F., Tsao, M.-S., Arnold, S.M., Haura, E.B., Bolca, C., Holcatova, I., Janout, V., Kontic, M., Lissowska, J., Mukeria, A., Ognjanovic, S., Orlowski, T.M., Scelo, G., Swiatkowska, B., Zaridze, D., Bakke, P., Skaug, V., Zienolddiny, S., Duell, E.J., Butler, L.M., Koh, W.-P., Gao, Y.-T., Houlston, R., McLaughlin, J., Stevens, V., Nickle, D.C., Obeidat, M., Timens, W., Zhu, B., Song, L., Artigas, M.S., Tobin, M.D., Wain, L.V., Gu, F., Byun, J., Kamal, A., Zhu, D., Tyndale, R.F., Wei, W.-Q., Chanock, S., Brennan, P., Amos, C.I.

Item does not contain fulltext PURPOSE: Radon is a risk factor for lung cancer and uranium miners are more exposed than the general population. A genome-wide interaction analysis was carried out to identify genomic loci, genes or gene sets that modify the susceptibility to lung cancer given occupational exposure to the radioactive gas radon. METHODS: Samples from 28 studies provided by the International Lung Cancer Consortium were pooled with samples of former uranium miners collected by the German Federal Office of Radiation Protection. In total, 15,077 cases and 13,522 controls, all of European ancestries, comprising 463 uranium miners were compared. The DNA of all participants was genotyped with the OncoArray. We fitted single-marker and in multi-marker models and performed an exploratory gene-set analysis to detect cumulative enrichment of significance in sets of genes. RESULTS: We discovered a genome-wide significant interaction of the marker rs12440014 within the gene CHRNB4 (OR = 0.26, 95% CI 0.11-0.60, p = 0.0386 corrected for multiple testing). At least suggestive significant interaction of linkage disequilibrium blocks was observed at the chromosomal regions 18q21.23 (p = 1.2 x 10(-6)), 5q23.2 (p = 2.5 x 10(-6)), 1q21.3 (p = 3.2 x 10(-6)), 10p13 (p = 1.3 x 10(-5)) and 12p12.1 (p = 7.1 x 10(-5)). Genes belonging to the Gene Ontology term "DNA dealkylation involved in DNA repair" (GO:0006307; p = 0.0139) or the gene family HGNC:476 "microRNAs" (p = 0.0159) were enriched with LD-blockwise significance. CONCLUSION: The well-established association of the genomic region 15q25 to lung cancer might be influenced by exposure to radon among uranium miners. Furthermore, lung cancer susceptibility is related to the functional capability of DNA damage signaling via ubiquitination processes and repair of radiation-induced double-strand breaks by the single-strand annealing mechanism.

Background: External pilot or feasibility studies can be used to estimate key unknown parameters to inform the design of the definitive randomised controlled trial (RCT). However, there is little consensus on how large pilot studies need to be, and some suggest inflating estimates to adjust for the lack of precision when planning the definitive RCT.Methods: We use a simulation approach to illustrate the sampling distribution of the standard deviation for continuous outcomes and the event rate for binary outcomes. We present the impact of increasing the pilot sample size on the precision and bias of these estimates, and predicted power under three realistic scenarios. We also illustrate the consequences of using a confidence interval argument to inflate estimates so the required power is achieved with a pre-specified level of confidence. We limit our attention to external pilot and feasibility studies prior to a two-parallel-balanced-group superiority RCT.Results: For normally distributed outcomes, the relative gain in precision of the pooled standard deviation (SDp) is less than 10% (for each five subjects added per group) once the total sample size is 70. For true proportions between 0.1 and 0.5, we find the gain in precision for each five subjects added to the pilot sample is less than 5% once the sample size is 60. Adjusting the required sample sizes for the imprecision in the pilot study estimates can result in excessively large definitive RCTs and also requires a pilot sample size of 60 to 90 for the true effect sizes considered here.Conclusions: We recommend that an external pilot study has at least 70 measured subjects (35 per group) when estimating the SDp for a continuous outcome. If the event rate in an intervention group needs to be estimated by the pilot then a total of 60 to 100 subjects is required. Hence if the primary outcome is binary a total of at least 120 subjects (60 in each group) may be required in the pilot trial. It is very much more efficient to use a larger pilot study, than to guard against the lack of precision by using inflated estimates. © 2014 Teare et al.; licensee BioMed Central Ltd.