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We aimed to determine the effect of sample size on performance of polygenic hazard score (PHS) models in predicting the age at onset of prostate cancer. Age and genotypes were obtained for 40,861 men from the PRACTICAL consortium. The dataset included 201,590 SNPs per subject, and was split into training (34,444 samples) and testing (6,417 samples) sets. Two PHS model-building strategies were investigated. Established-SNP model considered 65 SNPs that had been associated with prostate cancer in the literature. A stepwise SNP selection was used to develop Discovery-SNP models. The performance of each PHS model was calculated for random sizes of the training set (1 to 30 thousand). The performance of a representative Established-SNP model was estimated for random sizes of the testing set (0.5 to 6 thousand). Mean HR98/50 (hazard ratio of top 2% to the average in the test set) of the Established-SNP model increased from 1.73[95%CI: 1.69-1.77] to 2.41[2.40-2.43] when the number of training samples was increased from 1 to 30 thousand. The corresponding HR98/50 of the Discovery-SNP model increased from 1.05[0.93-1.18] to 2.19[2.16-2.23]. HR98/50 of a representative Established-SNP model using testing set sample sizes of 0.6 and 6 thousand observations were 1.78[1.70-1.85] and 1.73[1.71-1.76], respectively. We estimate that a study population of 20 to 30 thousand men is required to develop Discovery-SNP PHS models for prostate cancer. The required sample size could be reduced to 10 thousand samples, if a set of SNPs associated with the disease has already been established.Author summaryPolygenic hazard scores represent a recent advancement in polygenic prediction to model the age of onset of various diseases, such as Alzheimer’s disease or prostate cancer. These scores accumulate small effect sizes from several tens of genetic variants and can be used to establish an individual’s risk of experiencing an event relative to a control population across time. The largest barrier to the development of polygenic hazard scores is the large number of study subjects needed to develop the underlying models. We sought to understand the effect of varying the total number of samples on the performance of a polygenic hazard score in the context of prostate cancer. We found that the performance of the score did not appreciably change beyond 20 to 30 thousand observations when developing the model from scratch. However, when the discovery of the genetic variants can be borrowed from those already identified in the literature to be associated with the disease, the required number of samples is reduced to 10 thousand with no appreciable detriment in performance. We hope that these results can guide the design of future studies of polygenic scores in other diseases and demonstrate the importance of genome-wide association studies.

BackgroundGenetic risk stratification may inform decisions of whether—and when—a man should undergo prostate cancer (PCa) screening. We previously validated a polygenic hazard score (PHS), a weighted sum of 54 single-nucleotide polymorphism genotypes, for accurate prediction of age of onset of aggressive PCa and improved screening performance. We now assess the potential impact of PHS-informed screening.MethodsUnited Kingdom population data were fit to a continuous model of age-specific PCa incidence. Using hazard ratios estimated from ProtecT trial data, age-specific incidence rates were calculated for percentiles of genetic risk. Incidence of higher-grade PCa (Gleason≥7) was estimated from age-specific data from the linked CAP trial. PHS and incidence data were combined to give a risk-equivalent age, when a man with a given PHS percentile will have risk of higher-grade PCa equivalent to that of a typical man at age 50 (50-years standard). Positive predictive value (PPV) of PSA testing was calculated using PHS-adjusted (PCa-risk-equivalent age) groups identified from ProtecT.ResultsExpected age of onset of higher-grade PCa is modulated by 19 years between the 1st and 99th PHS percentiles. A man with PHS in the 99th percentile reaches 50-years-standard risk at age 41; conversely, a man in the 1st percentile reaches this risk at age 60. PPV of PSA was higher for men with higher PHS-adjusted age.ConclusionsPHS informs PCa screening strategies with individualized estimates of risk-equivalent age for higher-grade PCa. Screening initiation could be adjusted according to a man’s genetic hazard score, improving PPV of PSA screening.

Author(s): Antoniou, Antonis; Anton-Culver, Hoda; Borowsky, Alexander; Broeders, Mireille; Brooks, Jennifer; Chiarelli, Anna; Chiquette, Jocelyne; Cuzick, Jack; Delaloge, Suzette; Devilee, Peter; Dorval, Michael; Easton, Douglas; Eisen, Andrea; Eklund, Martin; Eloy, Laurence; Esserman, Laura; Garcia-Closas, Montserrat; Goldgar, David; Hall, Per; Knoppers, Bartha Maria; Kraft, Peter; La Croix, Andrea; Madalensky, Lisa; Mavaddat, Nasim; Mittman, Nicole; Nabi, Hermann; Olopade, Olufunmilayo; Pashayan, Nora; Schmidt, Marjanka; Shieh, Yiwey; Simard, Jacques; Stover-Fiscallini, Allison; Tice, Jeffrey A; Van't Veer, Laura; Wenger, Neil; Wolfson, Michael; Yau, Christina; Ziv, Elad

Early detection of breast cancer through screening reduces breast cancer mortality. The benefits of screening must also be considered within the context of potential harms (e.g., false positives, overdiagnosis). Furthermore, while breast cancer risk is highly variable within the population, most screening programs use age to determine eligibility. A risk-based approach is expected to improve the benefit-harm ratio of breast cancer screening programs. The PERSPECTIVE I&I (Personalized Risk Assessment for Prevention and Early Detection of Breast Cancer: Integration and Implementation) project seeks to improve personalized risk assessment to allow for a cost-effective, population-based approach to risk-based screening and determine best practices for implementation in Canada. This commentary describes the four inter-related activities that comprise the PERSPECTIVE I&I project. 1: Identification and validation of novel moderate to high-risk susceptibility genes. 2: Improvement, validation, and adaptation of a risk prediction web-tool for the Canadian context. 3: Development and piloting of a socio-ethical framework to support implementation of risk-based breast cancer screening. 4: Economic analysis to optimize the implementation of risk-based screening. Risk-based screening and prevention is expected to benefit all women, empowering them to work with their healthcare provider to make informed decisions about screening and prevention.

Prostate cancer is the most common cancer in men in developed countries, and is a target for risk reduction strategies. The effects of alcohol consumption on prostate cancer incidence and survival remain unclear, potentially due to methodological limitations of observational studies. In this study, we investigated the associations of genetic variants in alcohol-metabolising genes with prostate cancer incidence and survival. We analysed data from 23,868 men with prostate cancer and 23,051 controls from 25 studies within the international PRACTICAL Consortium. Study-specific associations of 68 single nucleotide polymorphisms (SNPs) in 8 alcohol-metabolising genes (Alcohol Dehydrogenases (ADHs) and Aldehyde Dehydrogenases (ALDHs)) with prostate cancer diagnosis and prostate cancer-specific mortality, by grade, were assessed using logistic and Cox regression models, respectively. The data across the 25 studies were meta-analysed using fixed-effect and random-effects models. We found little evidence that variants in alcohol metabolising genes were associated with prostate cancer diagnosis. Four variants in two genes exceeded the multiple testing threshold for associations with prostate cancer mortality in fixed-effect meta-analyses. SNPs within ALDH1A2 associated with prostate cancer mortality were rs1441817 (fixed effects hazard ratio, HRfixed = 0.78; 95% confidence interval (95%CI):0.66,0.91; p values = 0.002); rs12910509, HRfixed = 0.76; 95%CI:0.64,0.91; p values = 0.003); and rs8041922 (HRfixed = 0.76; 95%CI:0.64,0.91; p values = 0.002). These SNPs were in linkage disequilibrium with each other. In ALDH1B1, rs10973794 (HRfixed = 1.43; 95%CI:1.14,1.79; p values = 0.002) was associated with prostate cancer mortality in men with low-grade prostate cancer. These results suggest that alcohol consumption is unlikely to affect prostate cancer incidence, but it may influence disease progression.

Background: Prostate cancer is a common cancer worldwide with no established modifiable lifestyle factors to guide prevention. The associations between polyunsaturated fatty acids (PUFAs) and prostate cancer risk have been inconsistent. Using Mendelian randomisation, we evaluated associations between PUFAs and prostate cancer risk.Methods: We used individual-level data from a consortium of 22 721 cases and 23 034 controls of European ancestry. Externally-weighted PUFA-specific polygenic risk scores (wPRSs), with explanatory variation ranging from 0.65 to 33.07%, were constructed and used to evaluate associations with prostate cancer risk per one standard deviation (s.d.) increase in genetically-predicted plasma PUFA levels using multivariable-adjusted unconditional logistic regression.Results: No overall association was observed between the genetically-predicted PUFAs evaluated in this study and prostate cancer risk. However, risk reductions were observed for short-chain PUFAs, linoleic (ORLA=0.95, 95%CI=0.92, 0.98) and α-linolenic acids (ORALA=0.96, 95%CI=0.93, 0.98), among men LA=1.04, 95%CI=1.01, 1.07). For long-chain PUFAs (i.e., arachidonic, eicosapentaenoic, and docosapentaenoic acids), increased risks were observed among men AA=1.05, 95%CI=1.02, 1.08; OREPA=1.04, 95%CI=1.01, 1.06; ORDPA=1.05, 95%CI=1.02, 1.08).Conclusion: Results from this study suggest that circulating ω-3 and ω-6 PUFAs may have a different role in the aetiology of early- and late-onset prostate cancer.

Background In men with suspected prostate cancer, an MRI-first diagnostic pathway has been shown to reduce the clinically insignificant cancers and increase the clinically significant cancers detected, whilst obviating the need for approximately one-third of biopsies. We estimate the impact that an MRI-first diagnostic pathway would have on both age-based and precision screening. Methods Adapting a life-table model, we simulated hypothetical cohorts of 4.48 million men in England receiving no screening, age-based screening, or precision screening based on age and polygenic risk profile strategies. We analysed both age-based and precision screening strategies using MRI- and biopsy-first diagnostic pathways. If screened, men had a PSA test every four years, either from age 55 (age-based screening) or from the age that a man reached the risk threshold (precision screening) to age 70. Precision screening risk thresholds were varied between a 2% and 10% 10-year absolute risk of developing prostate cancer. We compared the benefit (prostate cancer deaths prevented) harm (overdiagnosis) trade-offs of different screening strategies. We assessed cost-effectiveness using net monetary benefit and incremental cost-effectiveness ratios (ICER). All analyses were probabilistic, from a health service perspective, and with both costs and benefits discounted at 3.5% per annum. Results An MRI-first diagnostic pathway reduced overdiagnosis in age-based screening by 13.8% and avoided 26.0% of biopsies, whilst preventing 1.8% more deaths from prostate cancer, generating more QALYs and lowering the costs of screening by 8.4%. These gains required a 3.7-fold increase in the number of MRI scans performed in an age-based screening programme. When comparing age-based and precision screening both using an MRI-first diagnostic pathway, precision screening reduced overdiagnosis by a further 10.5% to 71.3% and the number of MRI scans and biopsies by between 22.9% and 57.3%, at 10-year absolute risk thresholds of 2% and 10%, respectively, whilst generating more QALYs at all risk thresholds below 5%. MRI-first precision screening prevented more deaths than biopsy-first age-based screening at a risk threshold of 2%, but prevented between 1.7% and 15.3% fewer deaths from prostate cancer at risk thresholds of 2% and 10%, respectively, when compared with MRI-first age-based screening. All MRI-first precision screening strategies had a higher net monetary benefit than MRI-first age-based screening, whilst all MRI-first precision screening strategies using a risk threshold of 2.5% or greater had ICERs of Conclusion An MRI-first diagnostic pathway could improve the benefit-to-harm profile of screening for prostate cancer and these benefits were compounded by precision screening. Prospective evaluation is necessary to verify these findings. Citation Format: Thomas Callender, Mark Emberton, Steve Morris, Paul Pharoah, Nora Pashayan. MRI-first screening for prostate cancer: A benefit-harm and cost-effectiveness analysis [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3523.

Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (PC, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10(−9); T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55–2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04–6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa(1).

Background Epigenetic markers might be used for risk-stratifying cancer screening and prevention programs in the future. Although the clinical utility of consequent epigenetic tests for risk stratification is yet to be proven, successful adoption into clinical practice also requires the public’s acceptance of such tests. This cross-sectional online survey study sought to learn for the first time about European women’s perceptions, attitudes, and intended behavior regarding a predictive epigenetic test for female cancer (breast, ovarian, cervical, and endometrial) risks. Methods 1675 women (40–75 years) from five European countries (Czech Republic, Germany, United Kingdom, Italy, Sweden), drawn from online panels by the survey sampling company Harris Interactive (Germany), participated in an online survey where they first received online leaflet information on a predictive epigenetic test for female cancer risks and were subsequently queried by an online questionnaire on their desire to know their female cancer risks, their perception of the benefit-to-harm ratio of an epigenetic test predicting female cancer risks, reasons in favor and disfavor of taking such a test, and their intention to take a predictive epigenetic test for female cancer risks. Results Most women desired information on each of their female cancer risks, 56.6% (95% CI: 54.2–59.0) thought the potential benefits outweighed potential harms, and 75% (72.0–77.8) intended to take a predictive epigenetic test for female cancer risks if freely available. Results varied considerably by country with women from Germany and the Czech Republic being more reserved about this new form of testing than women from the other three European countries. The main reason cited in favor of a predictive epigenetic test for female cancer risks was its potential to guide healthcare strategies and lifestyle changes in the future, and in its disfavor was that it may increase cancer worry and coerce unintended lifestyle changes and healthcare interventions. Conclusions A successful introduction of predictive epigenetic tests for cancer risks will require a balanced and transparent communication of the benefit-to-harm ratio of healthcare pathways resulting from such tests in order to curb unjustified expectations and at the same time to prevent unjustified concerns. Electronic supplementary material The online version of this article (10.1186/s12889-019-6994-8) contains supplementary material, which is available to authorized users.

Testicular germ cell tumour (TGCT) is the most common cancer in young men. Multiplex TGCT families have been well reported and analyses of population cancer registries have demonstrated a four- to eightfold risk to male relatives of TGCT patients. Early linkage analysis and recent large-scale germline exome analysis in TGCT cases demonstrate absence of major high-penetrance TGCT susceptibility gene(s). Serial genome-wide association study analyses in sporadic TGCT have in total reported 49 independent risk loci. To date, it has not been demonstrated whether familial TGCT arises due to enrichment of the same common variants underpinning susceptibility to sporadic TGCT or is due to shared environmental/lifestyle factors or disparate rare genetic TGCT susceptibility factors. Here we present polygenic risk score analysis of 37 TGCT susceptibility single-nucleotide polymorphisms in 236 familial and 3931 sporadic TGCT cases, and 12 368 controls, which demonstrates clear enrichment for TGCT susceptibility alleles in familial compared to sporadic cases (p=0.0001), with the majority of familial cases (84-100%) being attributable to polygenic enrichment. These analyses reveal TGCT as the first rare malignancy of early adulthood in which familial clustering is driven by the aggregate effects of polygenic variation in the absence of a major high-penetrance susceptibility gene.To date, it has been unclear whether familial clusters of testicular germ cell tumour (TGCT) arise due to genetics or shared environmental or lifestyle factors. We present large-scale genetic analyses comparing 236 familial TGCT cases, 3931 isolated TGCT cases, and 12 368 controls. We show that familial TGCT is caused, at least in part, by presence of a higher dose of the same common genetic variants that cause susceptibility to TGCT in general.

BACKGROUND: Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate cancer risk at a genome-wide significant level will improve disease prediction. METHODS: We built polygenic risk scores in a large training set comprising over 25,000 individuals. Initially 65 established prostate cancer susceptibility variants were selected. After LD pruning additional variants were prioritized based on their association with prostate cancer. Six-fold cross validation was performed to assess genetic risk scores and optimize the number of additional variants to be included. The final model was evaluated in an independent study population including 1,370 cases and 1,239 controls. RESULTS: The polygenic risk score with 65 established susceptibility variants provided an area under the curve (AUC) of 0.67. Adding an additional 68 novel variants significantly increased the AUC to 0.68 (P = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-08). All novel variants were located in genomic regions established as associated with prostate cancer risk. CONCLUSIONS: Inclusion of additional genetic variants from established prostate cancer susceptibility regions improves disease prediction.

Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P < 5.0 × 10-8) with PrCa and one locus significantly associated with early-onset PrCa (≤55 years). Our findings include missense variants rs1800057 (odds ratio (OR) = 1.16; P = 8.2 × 10-9; G>C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa 1 .

To further our understanding of inherited susceptibility to Hodgkin lymphoma (HL), we performed a meta-analysis of 7 genome-wide association studies totaling 5325 HL cases and 22 423 control patients. We identify 5 new HL risk loci at 6p21.31 (rs649775

The incidence of cancer is continuing to rise and risk-tailored early diagnostic and/or primary prevention strategies are urgently required. The ideal risk-predictive test should: integrate the effects of both genetic and nongenetic factors and aim to capture these effects using an approach that is both biologically stable and technically reproducible; derive a score from easily accessible biological samples that acts as a surrogate for the organ in question; and enable the effectiveness of risk-reducing measures to be monitored. Substantial evidence has accumulated suggesting that the epigenome and, in particular, DNA methylation-based tests meet all of these requirements. However, the development and implementation of DNA methylation-based risk-prediction tests poses considerable challenges. In particular, the cell type specificity of DNA methylation and the extensive cellular heterogeneity of the easily accessible surrogate cells that might contain information relevant to less accessible tissues necessitates the use of novel methods in order to account for these confounding issues. Furthermore, the engagement of the scientific community with health-care professionals, policymakers and the public is required in order to identify and address the organizational, ethical, legal, social and economic challenges associated with the routine use of epigenetic testing.

Objectives To develop and validate a genetic tool to predict age of onset of aggressive prostate cancer (PCa) and to guide decisions of who to screen and at what age. Design Analysis of genotype, PCa status, and age to select single nucleotide polymorphisms (SNPs) associated with diagnosis. These polymorphisms were incorporated into a survival analysis to estimate their effects on age at diagnosis of aggressive PCa (that is, not eligible for surveillance according to National Comprehensive Cancer Network guidelines; any of Gleason score ≥7, stage T3-T4, PSA (prostate specific antigen) concentration ≥10 ng/L, nodal metastasis, distant metastasis). The resulting polygenic hazard score is an assessment of individual genetic risk. The final model was applied to an independent dataset containing genotype and PSA screening data. The hazard score was calculated for these men to test prediction of survival free from PCa. Setting Multiple institutions that were members of international PRACTICAL consortium. Participants All consortium participants of European ancestry with known age, PCa status, and quality assured custom (iCOGS) array genotype data. The development dataset comprised 31 747 men; the validation dataset comprised 6411 men. Main Outcome Measure Prediction with hazard score of age of onset of aggressive cancer in validation set. Results In the independent validation set, the hazard score calculated from 54 single nucleotide polymorphisms was a highly significant predictor of age at diagnosis of aggressive cancer (z=11.2, P98th centile) were compared with those with average scores (30th-70th centile), the hazard ratio for aggressive cancer was 2.9 (95% confidence interval 2.4 to 3.4). Inclusion of family history in a combined model did not improve prediction of onset of aggressive PCa (P=0.59), and polygenic hazard score performance remained high when family history was accounted for. Additionally, the positive predictive value of PSA screening for aggressive PCa was increased with increasing polygenic hazard score. Conclusions Polygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa.

Background Screening for prostate cancer with prostate specific antigen (PSA) remains controversial. Risk-tailoring based on age and polygenic profile might conserve the benefits of PSA screening whilst reducing overdiagnosis. This study evaluates the cost-effectiveness and benefit-to-harm balance of polygenic risk-tailored screening for prostate cancer. Methods A life-table approach was used. A hypothetical cohort of 4.48 million men in England between the ages of 55 and 70 was followed to the age of 90. Three scenarios were compared: no screening, age-based screening (PSA testing every four years from 55 to 70), and risk-tailored screening based on age and polygenic risk profile (men above the risk threshold receive PSA testing four-yearly from the age they reach the risk threshold to 70). The number of prostate cancer cases, deaths from prostate cancer, overdiagnosed cases, life-years and quality-adjusted life-years (QALYs), incremental cost per QALY, and net monetary benefit were calculated. Sensitivity analyses investigated the impact of parameter uncertainty, and the impact of varying the risk threshold, on outcomes. Costs were estimated from the perspective of the UK National Health Service; both costs and benefits were discounted at 3.5%. Results The incremental cost per additional QALY for age-based screening compared to no screening was £58,254 ($75,899), with 27% simulations having an incremental cost-effectiveness ratio of less than £20,000 ($26,058), the threshold set by the UK National Institute for Health and Care Excellence for an intervention to be considered cost-effective. In risk-tailored screening, as the 10-year absolute risk-threshold was progressively increased from 2.6%, equivalent to the 10-year absolute risk of a 55-year old man, to 7.1%, the corresponding risk of a 69-year old man, the cost per additional QALY gained reduced from £36,065 ($46,989) to £26,210 ($34,149), when compared to no screening. By comparison with age-based screening, risk-tailored screening with a threshold between 2.6% and 7.1% led to 8 (2.5%) and 45 (13%) fewer deaths prevented from prostate cancer per 10,000 men, with a 0.1% rise and 10% reduction in costs, respectively. Raising the risk threshold from 2.6% to 7.1% led to fewer men being screened (cumulative total of 35% of men screened by comparison with 83%), 53% fewer overdiagnosed cases, 22% fewer biopsies and 10% lower costs, at the expense of 10% fewer prostate cancer deaths averted. Conclusion Risk-tailored screening reduces the harms of screening for prostate cancer whilst preserving much of the mortality benefit. This study raises the prospect of risk-tailored population-based screening for prostate cancer; the precise risk-thresholds selected will depend on societal judgements regarding the appropriate trade-offs between harms and benefits. Citation Format: Thomas Callender, Mark Emberton, Steve Morris, Ros Eeles, Zsofia Kote-Jarai, Paul Pharoah, Nora Pashayan. Polygenic risk-tailored screening for prostate cancer: A cost-effectiveness analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2415.

Genome-wide association studies (GWAS) have identified 76 variants associated with prostate cancer risk predominantly in populations of European ancestry. To identify additional susceptibility loci for this common cancer, we conducted a meta-analysis of > 10 million SNPs in 43,303 prostate cancer cases and 43,737 controls from studies in populations of European, African, Japanese and Latino ancestry. Twenty-three new susceptibility loci were identified at association P < 5 × 10(-8); 15 variants were identified among men of European ancestry, 7 were identified in multi-ancestry analyses and 1 was associated with early-onset prostate cancer. These 23 variants, in combination with known prostate cancer risk variants, explain 33% of the familial risk for this disease in European-ancestry populations. These findings provide new regions for investigation into the pathogenesis of prostate cancer and demonstrate the usefulness of combining ancestrally diverse populations to discover risk loci for disease.

A key challenge of preconception healthcare is identifying how it can best be delivered at a population level. To review current strategies of preconception healthcare, explore methods of preconception healthcare delivery, and develop public health models which reflect different preconception healthcare pathways. Preconception care strategies, programmes and evaluations were identified through a review of Medline and Embase databases. Search terms included: preconception, pre-pregnancy, intervention, primary care, healthcare, model, delivery, program, prevention, trial, effectiveness, congenital disorders OR abnormalities, evaluation, assessment, impact. Inclusion criteria for review articles were: (1) English, (2) human subjects, (3) women of childbearing age, (4) 1980–current data, (5) all countries, (6) both high risk and universal approaches, (7) guidelines or recommendations, (8) opinion articles, (9) experimental studies. Exclusion criteria were: (1) non-human subjects, (2) non-English, (3) outside of the specified timeframe, (4) articles on male healthcare. The results of the literature review were synthesised into public health models of care: (1) primary care; (2) hospital-based and inter-conception care; (3) specific preconception care clinics; and, (4) community outreach. Fifteen evaluations of preconception care were identified. Community programmes demonstrated a significant impact on substance use, folic acid supplementation, diabetes optimization, and hyperphenylalaninemia. An ideal preconception visits entail risk screening, education, and intervention if indicated. Subsequently, four public health models were developed synthesizing preconception care delivery at a population level. Heterogeneity of risk factors, health systems and strategies of care reflect the lack of consensus about the best way to deliver preconception care. The proposed models aim to reflect differing aspects of preconception healthcare delivery.

Using the principles of public health genomics, we examined the opportunities and challenges of implementing personalized prevention programmes for cancer at the population level. Our model-based estimates indicate that polygenic risk stratification can potentially improve the effectiveness and cost-effectiveness of screening programmes. However, compared with 'one-size-fits-all' screening programmes, personalized screening adds further layers of complexity to the organization of screening services and raises ethical, legal and social challenges. Before polygenic inheritance is translated into population screening strategy, evidence from empirical research and engagement with and education of the public and the health professionals are needed.

The substantial heritability of most complex diseases suggests that genetic data could provide useful risk prediction. To date the performance of genetic risk scores has fallen short of the potential implied by heritability, but this can be explained by insufficient sample sizes for estimating highly polygenic models. When risk predictors already exist based on environment or lifestyle, two key questions are to what extent can they be improved by adding genetic information, and what is the ultimate potential of combined genetic and environmental risk scores? Here, we extend previous work on the predictive accuracy of polygenic scores to allow for an environmental score that may be correlated with the polygenic score, for example when the environmental factors mediate the genetic risk. We derive common measures of predictive accuracy and improvement as functions of the training sample size, chip heritabilities of disease and environmental score, and genetic correlation between disease and environmental risk factors. We consider simple addition of the two scores and a weighted sum that accounts for their correlation. Using examples from studies of cardiovascular disease and breast cancer, we show that improvements in discrimination are generally small but reasonable degrees of reclassification could be obtained with current sample sizes. Correlation between genetic and environmental scores has only minor effects on numerical results in realistic scenarios. In the longer term, as the accuracy of polygenic scores improves they will come to dominate the predictive accuracy compared to environmental scores.

Genome-wide association studies (GWAS) have transformed understanding of susceptibility to testicular germ cell tumors (TGCTs), but much of the heritability remains unexplained. Here we report a new GWAS, a meta- A nalysis with previous GWAS and a replication series, totaling 7,319 TGCT cases and 23,082 controls. We identify 19 new TGCT risk loci, roughly doubling the number of known TGCT risk loci to 44. By performing in situ Hi-C in TGCT cells, we provide evidence for a network of physical interactions among all 44 TGCT risk SNPs and candidate causal genes. Our findings implicate widespread disruption of developmental transcriptional regulators as a basis of TGCT susceptibility, consistent with failed primordial germ cell differentiation as an initiating step in oncogenesis. Defective microtubule assembly and dysregulation of KIT-MAPK signaling also feature as recurrently disrupted pathways. Our findings support a polygenic model of risk and provide insight into the biological basis of TGCT.

Individual risk prediction and stratification based on polygenic profiling may be useful in disease prevention. Risk-stratified population screening based on multiple factors including a polygenic risk profile has the potential to be more efficient than age-stratified screening. In this article, we summarize the implications of personalized screening for breast and prostate cancers. We report the opinions of multidisciplinary international experts who have explored the scientific, ethical, and logistical aspects of stratified screening. We have identified (i) the need to recognize the benefits and harms of personalized screening as compared with existing screening methods, (ii) that the use of genetic data highlights complex ethical issues including discrimination against high-risk individuals by insurers and employers and patient autonomy in relation to genetic testing of minors, (iii) the need for transparency and clear communication about risk scores, about harms and benefits, and about reasons for inclusion and exclusion from the risk-based screening process, and (iv) the need to develop new professional competences and to assess cost-effectiveness and acceptability of stratified screening programs before implementation. We conclude that health professionals and stakeholders need to consider the implications of incorporating genetic information in intervention strategies for health-care planning in the future.

Background: Improving understanding of the genetic basis of disease susceptibility enables us to estimate individuals' risk of developing cancer and offer them disease prevention, including screening, stratified to reflect that risk. Little attention has so far been given to the implementation of stratified screening. This article reviews the issues that would arise in delivering such tailored approaches to prevention in practice. Results: Issues analysed include the organisational context within which implementation of stratified prevention would occur, how the offer of screening would be made, making sure consent is adequately informed, how individuals' risk would be assessed, the age at which risk estimation should occur, and the potential use of genetic data for other purposes. The review also considers how management might differ depending on individuals' risk, how their results would be communicated and their follow-up arranged, and the different issues raised by modification of an existing screening programme, such as that for breast cancer, and the establishment of a new one, for example for prostate cancer. Conclusion: Stratified screening based on genetic testing is a radically new approach to prevention. Various organisational issues would need to be considered before it could be introduced, and a number of questions require further research.

Background The identification of common genetic variants associated with common cancers including breast, prostate and ovarian cancers would allow population stratification by genotype to effectively target screening and treatment. As scientific, clinical and economic evidence mounts there will be increasing pressure for risk-stratified screening programmes to be implemented. Methods This paper reviews some of the main ethical, legal and social issues (ELSI) raised by the introduction of genotyping into risk-stratified screening programmes, in terms of Beauchamp and Childress's four principles of biomedical ethics—respect for autonomy, non-maleficence, beneficence and justice. Two alternative approaches to data collection, storage, communication and consent are used to exemplify the ELSI issues that are likely to be raised. Results Ultimately, the provision of risk-stratified screening using genotyping raises fundamental questions about respective roles of individuals, healthcare providers and the state in organizing or mandating such programmes, and the principles, which underpin their provision, particularly the requirement for distributive justice. Conclusions The scope and breadth of these issues suggest that ELSI relating to risk-stratified screening will become increasingly important for policy-makers, healthcare professionals and a wide diversity of stakeholders.

BackgroundProstate-specific-antigen (PSA) screening resulted in reduced prostate cancer (PCa) mortality in a large clinical trial, but due to a high false-positive rate, among other concerns, many guidelines do not endorse universal screening and instead recommend an individualized decision based on each patient’s risk. Genetic risk may provide key information to guide the decisions of whether and at what age to screen an individual man for PCa.MethodsGenotype, PCa status, and age from 34,444 men of European ancestry from the PRACTICAL consortium database were analyzed to select single-nucleotide polymorphisms (SNPs) associated with prostate cancer diagnosis. These SNPs were then incorporated into a survival analysis to estimate their effects on age at PCa diagnosis. The resulting polygenic hazard score (PHS) is an assessment of individual genetic risk. The final model was validated in an independent dataset comprised of 6,417 men with screening PSA and genotype data. PHS was calculated for these men to test for prediction of PCa-free survival. PHS was also combined with age-specific PCa incidence data from the U.S. population to generate a PCa-Risk (PCaR) age that relates a given man’s risk to that of the population average. PHS and PCaR age were evaluated for prediction of positive predictive value (PPV) of PSA screening.FindingsPHS calculated from 54 SNPs was very highly predictive of age at PCa diagnosis for men in the validation set (p =10−53). PPV of PSA screening varied from 0.18 to 0.52 for men with low and high genetic risk, respectively. PHS modulates PCa-free survival curves by an estimated 20 years between men in the 1st or 99th percentiles of genetic risk.InterpretationPolygenic hazard scores give personalized genetic risk estimates and can inform the decisions of whether and at what age to screen a man for PCa.FundingDepartment of Defense #W81XWH-13-1-0391

Precision medicine, an emerging approach for disease treatment that takes into account individual variability in genes, environment, and lifestyle, is under consideration for preventive interventions, including cancer screening. On September 29, 2015, the National Cancer Institute sponsored a symposium entitled “Precision Cancer Screening in the General Population: Evidence, Epidemiology, and Next Steps”. The goal was two-fold: to share current information on the evidence, practices, and challenges surrounding precision screening for breast, cervical, colorectal, lung, and prostate cancers, and to allow for in-depth discussion among experts in relevant fields regarding how epidemiology and other population sciences can be used to generate evidence to inform precision screening strategies. Attendees concluded that the strength of evidence for efficacy and effectiveness of precision strategies varies by cancer site, that no one research strategy or methodology would be able or appropriate to address the many knowledge gaps in precision screening, and that issues surrounding implementation must be researched as well. Additional discussion needs to occur to identify the high priority research areas in precision cancer screening for pertinent organs and to gather the necessary evidence to determine whether further implementation of precision cancer screening strategies in the general population would be feasible and beneficial. Cancer Epidemiol Biomarkers Prev; 25(11); 1449–55. ©2016 AACR.

Prostate cancer is the most frequently diagnosed cancer in males in developed countries. To identify common prostate cancer susceptibility alleles, we genotyped 211,155 SNPs on a custom Illumina array (iCOGS) in blood DNA from 25,074 prostate cancer cases and 24,272 controls from the international PRACTICAL Consortium. Twenty-three new prostate cancer susceptibility loci were identified at genome-wide significance (P < 5 × 10(-8)). More than 70 prostate cancer susceptibility loci, explaining ∼30% of the familial risk for this disease, have now been identified. On the basis of combined risks conferred by the new and previously known risk loci, the top 1% of the risk distribution has a 4.7-fold higher risk than the average of the population being profiled. These results will facilitate population risk stratification for clinical studies.

Background Epidemiological studies have observed a positive association between an earlier age at sexual development and prostate cancer, but markers of sexual maturation in boys are imprecise and observational estimates are likely to suffer from a degree of uncontrolled confounding. To obtain causal estimates, we examined the role of pubertal development in prostate cancer using genetic polymorphisms associated with Tanner stage in adolescent boys in a Mendelian randomization (MR) approach. Methods We derived a weighted genetic risk score for pubertal development, combining 13 SNPs associated with male Tanner stage. A higher score indicated a later puberty onset. We examined the association of this score with prostate cancer risk, stage and grade in the UK-based ProtecT case-control study (n = 2,927), and used the PRACTICAL consortium (n = 43,737) as a replication sample. Results In ProtecT, the puberty genetic score was inversely associated with prostate cancer grade (odds ratio (OR) of high- vs. low-grade cancer, per tertile of the score: 0.76; 95 % CI, 0.64–0.89). In an instrumental variable estimation of the causal OR, later physical development in adolescence (equivalent to a difference of one Tanner stage between pubertal boys of the same age) was associated with a 77 % (95 % CI, 43–91 %) reduced odds of high Gleason prostate cancer. In PRACTICAL, the puberty genetic score was associated with prostate cancer stage (OR of advanced vs. localized cancer, per tertile: 0.95; 95 % CI, 0.91–1.00) and prostate cancer-specific mortality (hazard ratio amongst cases, per tertile: 0.94; 95 % CI, 0.90–0.98), but not with disease grade. Conclusions Older age at sexual maturation is causally linked to a reduced risk of later prostate cancer, especially aggressive disease. Electronic supplementary material The online version of this article (doi:10.1186/s12916-016-0602-x) contains supplementary material, which is available to authorized users.

Common genetic susceptibility variants could be used for risk stratification in risk-tailored cancer screening and prevention programmes. Combining genetic variants with environmental risk factors would improve risk stratification. Epigenetic changes are surrogate markers of environmental exposures during individual's lifetime. Integrating epigenetic markers, in lieu of environmental exposure data, with genetic markers would potentially improve risk stratification. Epigenetic changes are reversible and acquired gradually, providing potentials for prevention and early detection strategies. The epigenetic changes are tissue-specific and stage-of-development-specific, raising challenges in choice of sample and timing for evaluation of cancer-associated changes. The Horizon 2020 funded research programme, FORECEE, using empirical data, will investigate the value of integration of epigenomics with genomics for risk prediction and prevention of women-specific cancers.

To date, risk profiles based on the known common susceptibility variants have limited value in predicting the risk of disease, but they could be used for risk stratification in prevention programs at a population level. We illustrate the potential utility of polygenic risk stratification using the case of population-based screening for prostate and breast cancer. We compared the number of individuals eligible for screening and the number of cases potentially detectable by screening in a population undergoing screening based on age alone with a population undergoing stratified screening based on age and polygenic risk profile. Stratified-screening strategies based on age and genetic risk would potentially improve the efficiency of screening programs and reduce their adverse consequences. Organizational, ethical, legal and social issues need to be addressed before stratified-screening programs could be implemented.

Background This study aims to estimate the burden of cancer in England and Wales using disability-adjusted life years (DALYs) and to determine if the ranking of relative importance changes with metric used. Methods DALYs are the sum of years of life lost due to mortality and years lost due to disability. Annual DALYs due to cancer were calculated using cancer registration, mortality, disability weights and World Health Organization methodology. Results There were 8 605 362 DALYs due to cancer (3242 DALYs/100 000 population/year). Of the total, 47% corresponded to lung, prostate and colorectal cancers in males and 56% to breast, lung, colorectal and ovarian cancers in females. Mortality (86% of DALYs) contributed predominantly to DALYs. Individuals of 65–75 years contributed to 28% of DALYs. Among females, lung cancer ranked highest by death rates, whereas the highest DALYs were from breast cancer. Conclusions Highest DALYs were due to lung, breast, prostate and colorectal cancers in England and Wales. The addition of the disability component changes the relative position of some of the top cancers. Although metrics based on deaths alone capture most effects of cancer on population health levels, important additional perspectives, relevant to the planning of services, can be gained from burden of disease analyses.

Globally, health inequities between Indigenous and non-Indigenous populations exist. The disparity in health outcomes between Indigenous and non-Indigenous Australians is exemplified by cervical cancer. Current evidence suggests that Indigenous women have higher age standardised incidence and mortality than non-Indigenous women when adjusted for stage at diagnosis and co-morbidities; however, there is little information pertaining to national estimates of cervical cancer in Indigenous women. In this paper we review available evidence on the difference in occurrence and case fatality of cervical cancer among Indigenous and non-Indigenous Australian women. The Australian Bureau of Statistics, Australian Institute of Health and Welfare, and State- or Territory-based Cancer Registries were utilised to collect surveillance data. To corroborate existing data, further available journal literature was identified through Medline and Embase. All papers selected for review were cross-referenced to identify further relevant studies. The most recent national estimate of age-standardised cervical cancer incidence rate was 16.9 and 7.1 per 100,000 women-years in Indigenous and non-Indigenous women respectively (incidence ratio 2.4). The Indigenous age-standardised mortality rate was 9.9 per 100,000 women years (95% CI 7.1-13.3), over 5 times the non-Indigenous rate. Cervical cancer incidence, in both Indigenous and non-Indigenous women, has decreased since 1991. Despite the decline, age-standardised incidence among Indigenous women is still higher than non-Indigenous women. The pattern of cervical cancer incidence and survival corroborates the health inequities that exist in Australia. Indigenous women are more likely than non-Indigenous women to develop cervical cancer and are less likely to survive it. Similar patterns exist in Indigenous populations worldwide, such as New Zealander Maoris and Canadian Aboriginals, suggesting that high rates of cervical cancer incidence and mortality may be a symptom of social and economic inequity.

Purpose This study aims to validate a biostatistical approach to predict the likely effectiveness of screening in reducing advanced disease in the absence of data on incident screen and interval cancers. Methods We derived the predicted relative reduction in advanced stage disease following screening from the expected proportion of advanced disease following screening and the observed proportion of advanced disease detected clinically among the controls. We compared the predicted estimates to those observed in a randomised trial. Results Using our method, the predicted estimates of relative reduction in node positive breast cancer following screening were comparable to the observed estimates for the age groups 50–59 and 60–69 in the screening study (predicted 32% vs. observed 40% (p = 0.274) and predicted 34% vs. observed 45% (p = 0.068), respectively). However, for the age groups 40–49 and 70–74 the predicted values were overestimates of the likely effectiveness of screening compared to the observed values (predicted 38% vs. observed 16% (p = 0.014) and predicted 34% vs. observed 0% (p = 0.001), respectively). Conclusion When the number of cancer cases is more than hundred, the method of prediction using only prevalence screen data may be accurate. Where cancers are less common, for example in small populations or young age groups, further data from interval cancers or incidence screens may be necessary.

We performed an in-depth and well-powered investigation of genetic variation across the cancer susceptibility region at chromosome 8q24 (127.6-129.0 Mb) to search for novel risk variants associated with prostate cancer (PCa) risk in the European ancestry population. We combined genotyped and imputed data from the PRACTICAL/ELLIPSE OncoArray and iCOGS consortia consisting of 71,535 PrCa cases and 52,935 controls of European ancestry. Variants with high imputation quality score (>0.8) were retained for a total of 5,600 overlapping variants between the two datasets. Associations of genetic variants with PCa risk were evaluated using unconditional logistic regression with adjustment for country and ten principal components. The marginal risk estimates for the 5,600 variants that passed quality control were combined by a fixed effects meta-analysis. A meta-stepwise selection was performed on variants marginally associated with PCa risk from the meta results (P Citation Format: Marco Matejcic, Edward J. Saunders, Tokhir Dadaev, Mark Brook, Ali Amin Al Olama, Fredrick R. Schumacher, Sonja I. Berndt, Sara Benlloch, Kenneth Muir, Koveela Govindasami, Victoria L. Stevens, Susan M. Gapstur, Catherine M. Tangen, Jyotsna Batra, Judith Clements, APCB (Australian Prostate Cancer Bio Resource), Henrik Gronberg, Nora Pashayan, Johanna Schleutker, Demetrius Albanes, Alicja Wolk, Catharine West, Lorelei Mucci, Peter Kraft, Géraldine Cancel-Tassin, Stella Koutros, Karina Dalsgaard Sorensen, Lovise Maehle, Eli Marie Grindedal, Sara Strom, David E. Neal, Freddie C. Hamdy, Jenny L. Donovan, Ruth C. Travis, Robert J. Hamilton, Sue Ann Ingles, Barry Rosenstein, Yong-Jie Lu, Graham G. Giles, Adam S. Kibel, Ana Vega, Jeanette Bensen, Manolis Kogevinas, Fredrik Wiklund, Stephen Chanock, Douglas F. Easton, Rosalind A. Eeles, Zsofia Kote-Jarai, David V. Conti, Christopher A. Haiman. Germline variation at 8q24 and prostate cancer risk in men of European ancestry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 227.

This study aimed to investigate the incidence trends of colorectal cancer by sex and subsite, in East Anglia from 1971 to 2005.Using data from the Eastern Cancer Registration and Information Centre, we examined the time trends and the effect of age, period of diagnosis and birth cohort on the incidence of colorectal cancer by sex and subsite.Between 1971 and 2005, 23875 males and 22651 females were registered with colorectal cancer in East Anglia. During this period, the increase in the incidence trends was higher among males, more recent periods of diagnosis, and proximal colon. Cohort effects were statistically significant in distal and rectal cancers in males (p0.001 and p=0.05, respectively), and in proximal colon in females (p0.001). Period effects were statistically significant across all subsites and both sexes (p0.001 for all).Period effects were significant across all subsites for both sexes, whereas cohort effects varied in their significance levels depending on subsite and sex. We suggest that the period effect may be due to an increase in the use of colonoscopy for diagnostic or opportunistic screening, and the cohort effect may be due to aetiological differences in CRC between sexes and subsites.

Objective This paper aims to investigate whether the stage shift (where more cancers are detected at an earlier stage) in prostate-specific antigen (PSA)-detected cancers differs by Gleason score. Methods Between 2002 and 2005, 1514 men aged 50–69 years were identified with prostate cancer following community-based PSA testing as part of the ProtecT study. In the same period, 2021 men aged 50–69 years with clinically diagnosed prostate cancer were registered at a population-based cancer registry in the East of England. Using logistic regression analysis and controlling for age, the odds ratio (OR) for advanced stage (TNM stage T3 and above) prostate cancer among the PSA-detected group was compared with the clinically diagnosed tumours. The evidence that stage shift differs by Gleason score was assessed using the likelihood ratio test for interaction. Results Advanced stage disease among the PSA-detected cancers was less common than among the clinically detected cancers (OR = 0.47, 95% CI 0.39–0.56). PSA-detected tumours had a substantial shift to earlier-stage disease where the Gleason score was Conclusion The observed stage shift could be partially explained by length bias or overdiagnosis. These findings may have implications on understanding pathways of prostate cancer progression and on identifying potential targets for screening, pending further investigation of complexities of associations between PSA testing, Gleason score, and stage.

Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10−8 seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type–specific expression quantitative trait locus and enhancer–gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10−5 in the three-cancer meta-analysis. Significance: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052–67. ©2016 AACR. This article is highlighted in the In This Issue feature, p. 932

Background The recruitment process for public health specialty training includes an assessment centre (AC) with three components, Rust Advanced Numerical Reasoning Appraisal (RANRA),Watson-Glaser Critical Thinking Appraisal (WGCT) and a Situation Judgement Test (SJT), which determines invitation to a selection centre (SC). The scores are combined into a total recruitment (TR) score that determines the offers of appointment. Methods A prospective cohort study using anonymous record linkage to investigate the association between applicant's scores in the recruitment process and registrar's progress through training measured by results of Membership Faculty Public Health (MFPH) examinations and outcomes of the Annual Review of Competence Progression (ARCP). Results Higher scores in RANRA, WGCT, AC, SC and TR were all significantly associated with higher adjusted odds of passing Part A MFPH exam at the first attempt. Higher scores in AC, SC and TR were significantly associated with passing Part B exam at the first attempt. Higher scores in SJT, AC and SC were significantly associated with satisfactory ARCP outcomes. Conclusions The current UK national recruitment and selection process for public health specialty training has good predictive validity. The individual components of the process are testing different skills and abilities and together they are providing additive value.

Background Several mapping algorithms have been published with the EORTC-QLQ-C30 for estimating EQ-5D-3L utilities. However, none are available with EQ-5D-5L. Moreover, a comparison between mapping algorithms in the same set of patients has not been performed for these two instruments simultaneously. In this prospective data set of 100 non-small cell lung cancer (NSCLC) patients, we investigate three mapping algorithms using the EQ-5D-3L and EQ-5D-5L and compare their performance. Methods A prospective non-interventional cohort of 100 NSCLC patients were followed up for 12 months. EQ-5D-3L, EQ-5D-5L and EORTC-QLQ-C30 were assessed monthly. EQ-5D-5L was completed at least 1 week after EQ-5D-3L. A random effects linear regression model, a beta-binomial (BB) and a Limited Variable Dependent Mixture (LVDM) model were used to determine a mapping algorithm between EQ-5D-3L, EQ-5D-5L and QLQ-C30. Simulation and cross validation and other statistical measures were used to compare the performances of the algorithms. Results Mapping from the EQ-5D-5L was better: lower AIC, RMSE, MAE and higher R2 were reported with the EQ-5D-5L than with EQ-5D-3L regardless of the functional form of the algorithm. The BB model proved to be more useful for both instruments: for the EQ-5D-5L, AIC was –485, R2 of 75 %, MAE of 0.075 and RMSE was 0.092. This was –385, 69 %, 0.099 and 0.113 for EQ-5D-3L respectively. The mean observed vs. predicted utilities were 0.572 vs. 0.577 and 0.515 vs. 0.523 for EQ-5D-5L and EQ-5D-3L respectively, for OLS; for BB, these were 0.572 vs. 0.575 and 0.515 vs. 0.518 respectively and for LVDMM 0.532 vs 0.515 and 0.569 vs 0.572 respectively. Less over-prediction at poorer health states was observed with EQ-5D-5L. Conclusions The BB mapping algorithm is confirmed to offer a better fit for both EQ-5D-3L and EQ-5D-5L. The results confirm previous and more recent results on the use of BB type modelling approaches for mapping. It is recommended that in studies where EQ-5D utilities have not been collected, an EQ-5D-5L mapping algorithm is used.

BACKGROUND. Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate cancer risk at a genome-wide significant level will improve disease prediction. METHODS. We built polygenic risk scores in a large training set comprising over 25,000 individuals. Initially 65 established prostate cancer susceptibility variants were selected. After LD pruning additional variants were prioritized based on their association with prostate cancer. Six-fold cross validation was performed to assess genetic risk scores and optimize the number of additional variants to be included. The final model was evaluated in an independent study population including 1,370 cases and 1,239 controls. RESULTS. The polygenic risk score with 65 established susceptibility variants provided an area under the curve (AUC) of 0.67. Adding an additional 68 novel variants significantly increased the AUC to 0.68 (P = 0.0012) and the net reclassification index with 0.21 (P = 8.5 E-08). All novel variants were located in genomic regions established as associated with prostate cancer risk. CONCLUSIONS. Inclusion of additional genetic variants from established prostate cancer susceptibility regions improves disease prediction.

Background: Unnecessary intervention and overtreatment of indolent disease are common challenges in clinical management of prostate cancer. Improved tools to distinguish lethal from indolent disease are critical. Methods: We performed a genome-wide survival analysis of cause-specific death in 24,023 prostate cancer patients (3,513 disease-specific deaths) from the PRACTICAL and BPC3 consortia. Top findings were assessed for replication in a Norwegian cohort (CONOR). Results: We observed no significant association between genetic variants and prostate cancer survival. Conclusions: Common genetic variants with large impact on prostate cancer survival were not observed in this study. Impact: Future studies should be designed for identification of rare variants with large effect sizes or common variants with small effect sizes. Cancer Epidemiol Biomarkers Prev; 24(11); 1796–800. ©2015 AACR.

Background: We derived estimates of overdiagnosis by polygenic risk groups and examined whether polygenic risk-stratified screening for prostate cancer reduces overdiagnosis. Methods: We calculated the polygenic risk score based on genotypes of 66 known prostate cancer loci for 4967 men from the Finnish section of the European Randomised Study of Screening for Prostate Cancer. We stratified the 72 072 men in the trial into those with polygenic risk below and above the median. Using a maximum likelihood method based on interval cancers, we estimated the mean sojourn time (MST) and episode sensitivity. For each polygenic risk group, we estimated the proportion of screen-detected cancers that are likely to be overdiagnosed from the difference between the observed and expected number of screen-detected cancers. Results: Of the prostate cancers, 74% occurred among men with polygenic risk above population median. The sensitivity was 0.55 (95% confidence interval (CI) 0.45–0.65) and MST 6.3 (95% CI 4.2–8.3) years. The overall overdiagnosis was 42% (95% CI 37–52) of the screen-detected cancers, with 58% (95% CI 54–65) in men with the lower and 37% (95% CI 31–47) in those with higher polygenic risk. Conclusion: Targeting screening to men at higher polygenic risk could reduce the proportion of cancers overdiagnosed.

Background: Genome-wide association studies have identified multiple genetic variants associated with prostate cancer risk which explain a substantial proportion of familial relative risk. These variants can be used to stratify individuals by their risk of prostate cancer. Methods: We genotyped 25 prostate cancer susceptibility loci in 40,414 individuals and derived a polygenic risk score (PRS). We estimated empirical odds ratios (OR) for prostate cancer associated with different risk strata defined by PRS and derived age-specific absolute risks of developing prostate cancer by PRS stratum and family history. Results: The prostate cancer risk for men in the top 1% of the PRS distribution was 30.6 (95% CI, 16.4–57.3) fold compared with men in the bottom 1%, and 4.2 (95% CI, 3.2–5.5) fold compared with the median risk. The absolute risk of prostate cancer by age of 85 years was 65.8% for a man with family history in the top 1% of the PRS distribution, compared with 3.7% for a man in the bottom 1%. The PRS was only weakly correlated with serum PSA level (correlation = 0.09). Conclusions: Risk profiling can identify men at substantially increased or reduced risk of prostate cancer. The effect size, measured by OR per unit PRS, was higher in men at younger ages and in men with family history of prostate cancer. Incorporating additional newly identified loci into a PRS should improve the predictive value of risk profiles. Impact: We demonstrate that the risk profiling based on SNPs can identify men at substantially increased or reduced risk that could have useful implications for targeted prevention and screening programs. Cancer Epidemiol Biomarkers Prev; 24(7); 1121–9. ©2015 AACR.

This population-based study examines prognostic factors and survival trends among adults (15–99 years) diagnosed with small intestinal cancer in England and Wales during 1971–1990 and followed up to 1995. During this period, the 1- and 5-year age-standardised relative survival rates for small intestinal cancers combined were 42% and 23%, respectively. Duodenal tumours, adenocarcinomas, men, patients with advanced age and the most deprived patients had the poorest prognosis. For all small bowel tumours combined, the excess risk of death fell significantly by 6–9% every 4 years over the 20-year period (adjusted excess hazard ratio (EHR) 0.91 at 1 year after diagnosis, 0.94 at 5 years). For duodenal tumours, the EHR fell by about 14% (95% CI 5–22%) every 4 years between 1979 and 1990, and a similar trend for jejunal tumours was of borderline significance. Further population-based investigations linking survival data to individual data on diagnostic methods and types of treatment are needed.

The PHG Foundation led a multidisciplinary program, which used results from COGS research identifying genetic variants associated with breast, ovarian and prostate cancers to model risk-stratified prevention for breast and prostate cancers. Implementing such strategies would require attention to the use and storage of genetic information, the development of risk assessment tools, new protocols for consent and programs of professional education and public engagement.

There is growing evidence that inclusion of genetic information about known common susceptibility variants may enable population risk-stratification and personalized prevention for common diseases including cancer. This would require the inclusion of genetic testing as an integral part of individual risk assessment of an asymptomatic individual. Front line health professionals would be expected to interact with and assist asymptomatic individuals through the risk stratification process. In that case, additional knowledge and skills may be needed. Current guidelines and frameworks for genetic competencies of non-specialist health professionals place an emphasis on rare inherited genetic diseases. For common diseases, health professionals do use risk assessment tools but such tools currently do not assess genetic susceptibility of individuals. In this article, we compare the skills and knowledge needed by non-genetic health professionals, if risk-stratified prevention is implemented, with existing competence recommendations from the UK, USA and Europe, in order to assess the gaps in current competences. We found that health professionals would benefit from understanding the contribution of common genetic variations in disease risk, the rationale for a risk-stratified prevention pathway, and the implications of using genomic information in risk-assessment and risk management of asymptomatic individuals for common disease prevention.

OBJECTIVES: To examine the impact of routine urinalysis at admission on inpatient care at a hospital in Lebanon, where physicians perceive it to be a valuable diagnostic tool, in a country where preventive services are underdeveloped and where the epidemiology of kidney diseases possibly differs from that of the western world. SETTING: American University Hospital, a tertiary teaching hospital in Beirut, Lebanon. METHODS: A retrospective medical record review of all adult patients admitted over 2 weeks to the medicine and surgery wards of the American University Hospital. Outcomes measured were frequency of routine urinalysis versus urinalysis for a clinical indication, investigation of abnormal test results, and implications of test results on clinical management. RESULTS: 367 (79%) of 462 study patients underwent urinalysis. 266 (73%) patients had routine urinalysis. Abnormal results were found in 97(37%) routine tests and 67 (66%) of those clinically indicated urinalysis (p

The success of genome wide association studies (GWAS) in identifying common genetic variants that are associated with the risk of common complex diseases has raised expectations about genetic profiling for personalised therapeutic and public health interventions. Questions remain whether genetic profiling can help in targeting screening at genetically defined subpopulations to improve the benefit that harm ratio of screening programmes. Multiple genetic loci contribute to the increased risk of common diseases. For example, to date more than 20 loci have been implicated with type 2 diabetes (McCarthy 2010), more than 30 with prostate cancer and 18 with breast cancer (Varghese and Easton 2010). The risk alleles at these loci individually confer a modest increase in risk of disease (usually per-allele relative risks of less than 1.5) and the risk alleles appear to interact multiplicatively on the relative risk scale (Hingorani et al. 2010). Consequently, the susceptibility variants identified by GWAS explain only a small proportion of heritability of common diseases.