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Snoring and obstructive sleep apnoea (OSA) both seem at least to be associated with narrowing of the upper airway and sleep-induced loss of muscle-tone. Mandibular advancement splints (MAS) have been proposed as a relatively simple method to increase oro- and hypo-pharyngeal dimensions thereby increasing the size of the airway. However, data on their effectiveness are conflicting and there are no clear indications as to which design is most effective or when they should be used. The effects of two designs of splint (types A and B) have been evaluated in 14 and nine subjects, respectively, using the Epworth Sleepiness Score (ESS) and domiciliary sleep monitoring on separate nights. Both splints reduced the median ESS (type A from 12, to 4.5; P = 0.003, type B from 7 to 4; P = 0.005). The apnoea-hypopnoea index was not affected by type A, but was reduced from 7.1 to 0.8; P = 0.005 by type B splints. There was evidence of a small improvement in overnight oxygen saturation for type B splints (P = 0.02). The splints were well tolerated and continued to be used nightly by 18 subjects. Mandibular advancement splints may offer a simple and effective alternative for the treatment of snoring and mild OSA in selected patients. Splint design may have considerable bearing on efficacy. [ABSTRACT FROM AUTHOR]

The effectiveness of screening programmes is critically dependent on the accuracy of the screening test. Where this relies on clinical expertise, there is an imperative to assure that the level of expertise meets expected standards. In cancer screening involving images, the focus is on the reader. Auditing of results is fraught with difficulty because of the time taken to accumulate enough data with confirmed outcomes to identify underperformance before any harm is done. Late recognition can lead to the need for reanalysis and recall of screening participants with loss of confidence in the programme. External Quality Assurance (EQA) is a method that enables clinical expertise to be tested rapidly by using test datasets with confirmed clinical outcome. In the UK, the breast cancer screening programme has had EQA in place for over 30 years. This article describes the development of the first EQA process in lung cancer screening, using the experience gained from running the breast cancer EQA, and the proposed future developments., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Institute of Radiology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Lung cancer is a leading cause of mortality, yet disparities in lung cancer across different sociodemographic groups in the UK remain unclear. This study investigates ethnicity and sociodemographic disparities and differences in lung cancer in a nationally representative English cohort, aiming to highlight inequalities and promote equitable access to diagnostic advancements., Methods: We conducted a population-based cohort study using health care records from QResearch, a large primary care database in England. The study included adults aged 25 and over, spanning the period of 2005-2019. Lung cancer incidence rates were calculated using age-standardized methods. Multinomial logistic regression was applied to assess associations between ethnicity/sociodemographic factors and diagnostic characteristics (histological type, stage, and cancer grade), adjusting for confounders., Findings: From a cohort of over 17.5 million people, we identified disparities in incidence rates across ethnic groups from 2005 to 2019. Analysis of 84,253 lung cancer cases revealed that younger woman and Individuals of Indian, other Asian, Black African, Caribbean and Chinese backgrounds had a significantly higher risks of adenocarcinoma compared with squamous cell carcinoma than their White counterparts (relative risk ratios [RRR] spanning from 1.52 (95% CI 1.18-1.94) to 2.69 (95% CI 1.43-5.05). Men and current smokers were more likely to be diagnosed at an advanced stage than women and never smokers (RRR: 1.72 [95% CI 1.56-1.90]-2.45 [95% CI 2.16-2.78]). Socioeconomic deprivation was associated with higher risks of moderate or poorly differentiated adenocarcinoma compared with well differentiated (RRRs between 1.35 [CI: 1.02-1.79] and 1.37 [1.05-1.80])., Interpretation: Our study highlights significant differences in lung cancer incidence and in lung cancer diagnostic characteristics related to ethnicity, deprivation and other demographic factors. These findings have important implications for the provision of equitable screening and prevention programmes to mitigate health inequalities., Funding: DART (The Integration and Analysis of Data using Artificial Intelligence to Improve Patient Outcomes with Thoracic Diseases) project, Innovate UK (UK Research and Innovation), QResearch® and grants from the NIHR Biomedical Research Centre (Oxford), John Fell Oxford University Press Research Fund, Cancer Research UK, and the Oxford Wellcome Institutional Strategic Support Fund., Competing Interests: JHC reports grants from National Institute for Health Research, John Fell Oxford University Press Research Fund, Cancer Research U.K. (C5255/A18085), Wellcome Institutional Strategic Support Fund (204826/Z/16/Z) and other research councils, during the conduct of the study. JHC is an unpaid director of QResearch, a not-for-profit organisation which is a partnership between the University of Oxford and EMIS Health who supply the QResearch database used for this work. Until 09 August 2023, JHC had a 50% shareholding in ClinRisk Ltd, co-owning it with her husband, who was an executive director. On 9th August 2023, 100% of the share capital was donated to Endeavour Health Care Charitable Trust and the company renamed to Endeavour Predict Ltd. JHC is an unpaid consultant to Endeavour Predict Ltd and her husband is a non-executive director to cover the transition. The company licences software both to the private sector and to NHS bodies or bodies that provide services to the NHS (through GP electronic health record providers, pharmacies, hospital providers and other NHS providers). This software implements algorithms (including QRISK3) developed from access to the QResearch database during her time at the University of Nottingham. CC reports receiving personal fees from ClinRisk Ltd, outside this work. DRB reports receiving payments for speaking and advice for Astra Zeneca, Roche and MDS., (© 2024 Published by Elsevier Ltd.)

Introduction: Using the Pediatric Health Information System, this study compared the relative severity of fractures sustained from trampolines with those from other playground equipment., Methods: Pediatric patients were identified in the Pediatric Health Information System with trampoline-related injuries (TRIs) or playground-related injuries (PRIs) diagnosed as fractures. Adjustments were made for hospital, year of injury, sex, age, race, median household income, and rurality through propensity score weighting. Four injury-related outcome measures were examined as a proxy for injury severity., Results: A total of 133,232 patients met inclusion criteria. In unadjusted univariate analyses, TRIs were associated with greater odds of severe fracture and lower odds of receiving surgical treatment (OR = 0.954) compared with PRIs. After adjustment, TRIs sustained in late childhood and adolescence were more likely to receive surgical management (OR = 1.092 and OR = 1.192, respectively) while TRIs sustained in younger children were less likely (OR = 0.607) than PRIs., Discussion: Youths in late childhood and adolescence are at increased odds of undergoing surgical management after trampoline fractures. Beyond underscoring the risks of trampoline play, our results highlight the importance of considering age in recreational injury epidemiology and the public health safety initiatives aimed at specific age groups., (Copyright © 2024 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Orthopaedic Surgeons.)

Introduction: In a small percentage of patients, pulmonary nodules found on CT scans are early lung cancers. Lung cancer detected at an early stage has a much better prognosis. The British Thoracic Society guideline on managing pulmonary nodules recommends using multivariable malignancy risk prediction models to assist in management. While these guidelines seem to be effective in clinical practice, recent data suggest that artificial intelligence (AI)-based malignant-nodule prediction solutions might outperform existing models., Methods and Analysis: This study is a prospective, observational multicentre study to assess the clinical utility of an AI-assisted CT-based lung cancer prediction tool (LCP) for managing incidental solid and part solid pulmonary nodule patients vs standard care. Two thousand patients will be recruited from 12 different UK hospitals. The primary outcome is the difference between standard care and LCP-guided care in terms of the rate of benign nodules and patients with cancer discharged straight after the assessment of the baseline CT scan. Secondary outcomes investigate adherence to clinical guidelines, other measures of changes to clinical management, patient outcomes and cost-effectiveness., Ethics and Dissemination: This study has been reviewed and given a favourable opinion by the South Central-Oxford C Research Ethics Committee in UK (REC reference number: 22/SC/0142).Study results will be available publicly following peer-reviewed publication in open-access journals. A patient and public involvement group workshop is planned before the study results are available to discuss best methods to disseminate the results. Study results will also be fed back to participating organisations to inform training and procurement activities., Trial Registration Number: NCT05389774., Competing Interests: Competing interests: FG reports grant funding from NIHR and Innovate UK, consultancy fees from Polarean and has shares in Optellum; SJ has received grant funding from GRAIL, consultancy fees/ honoraria from AstraZeneca and Chiesi, stock options in Optellum Ltd and his spouse is employed by AstraZeneca; RL is funded by the Royal Marsden NIHR BRC, Royal Marsden Cancer charity and SBRI (including QURE.AI). RL’s institution receives compensation for time spent in a secondment role for the lung health check program and as a National Specialty Lead for the National Institute of Health and Care Research. He has received research funding from CRUK, Innovate UK (cofunded by GE Healthcare, Roche and Optellum), SBRI, RM Partners Cancer Alliance and NIHR (coapplicant in grants with Optellum). He has received honoraria from CRUK; WM has received honoraria from Amgen; AN declares grants from Department of Health’s NIHR Biomedical Research Centre's funding scheme and GRAIL, consulting fees from Aidence BV, Faculty Science LTD and MSD; Support for attending meetings from Takeda Limited; Advisory Board participation for Aidence BV and Faculty Science Ltd; JR has received support for travel and accommodation from BTOG, ERS, CRUK, EORTC, ESMO and NCRI; RT has received honoraria from Olympus Medical; DRB has grant from NHS Digital and had received honoraria from MSD and AstraZeneca; DC, FM, JW are Optellum employees and have share options in Optellum. The remaining authors declare no conflicts of interests., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objectives: This study aimed to evaluate the cost-effectiveness of lung cancer screening (LCS) with volume-based low-dose computed tomography (CT) versus no screening for an asymptomatic high-risk population in the United Kingdom (UK), utilising the long-term insights provided by the NELSON study, the largest European randomized control trial investigating LCS., Methods: A cost-effectiveness analysis was conducted using a decision tree and a state-transition Markov model to simulate the identification, diagnosis, and treatments for a lung cancer high-risk population, from a UK National Health Service (NHS) perspective. Eligible participants underwent annual volume CT screening and were compared to a cohort without the option of screening. Screen-detected lung cancers, costs, quality-adjusted life years (QALYs), and the incremental cost-effectiveness ratio (ICER) were predicted., Results: Annual volume CT screening of 1.3 million eligible participants resulted in 96,474 more lung cancer cases detected in early stage, and 73,825 fewer cases in late stage, leading to 53,732 premature lung cancer deaths averted and 421,647 QALYs gained, compared to no screening. The ICER was £5,455 per QALY. These estimates were robust in sensitivity analyses., Limitations: Lack of long-term survival data for lung cancer patients; deficiency in rigorous micro-costing studies to establish detailed treatment costs inputs for lung cancer patients., Conclusions: Annual LCS with volume-based low-dose CT for a high-risk asymptomatic population is cost-effective in the UK, at a threshold of £20,000 per QALY, representing an efficient use of NHS resources with substantially improved outcomes for lung cancer patients, as well as additional societal and economic benefits for society as a whole. These findings advocate evidence-based decisions for the potential implementation of a nationwide LCS in the UK.

Low-dose computed tomography (LDCT) screening for lung cancer substantially reduces mortality from lung cancer, as revealed in randomized controlled trials and meta-analyses. This review is based on the ninth CT screening symposium of the International Association for the Study of Lung Cancer, which focuses on the major themes pertinent to the successful global implementation of LDCT screening and develops a strategy to further the implementation of lung cancer screening globally. These recommendations provide a 5-year roadmap to advance the implementation of LDCT screening globally, including the following: (1) establish universal screening program quality indicators; (2) establish evidence-based criteria to identify individuals who have never smoked but are at high-risk of developing lung cancer; (3) develop recommendations for incidentally detected lung nodule tracking and management protocols to complement programmatic lung cancer screening; (4) Integrate artificial intelligence and biomarkers to increase the prediction of malignancy in suspicious CT screen-detected lesions; and (5) standardize high-quality performance artificial intelligence protocols that lead to substantial reductions in costs, resource utilization and radiologist reporting time; (6) personalize CT screening intervals on the basis of an individual's lung cancer risk; (7) develop evidence to support clinical management and cost-effectiveness of other identified abnormalities on a lung cancer screening CT; (8) develop publicly accessible, easy-to-use geospatial tools to plan and monitor equitable access to screening services; and (9) establish a global shared education resource for lung cancer screening CT to ensure high-quality reading and reporting., (Copyright © 2023 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.)

Background: Screening for lung cancer with low radiation dose computed tomography has a strong evidence base, is being introduced in several European countries and is recommended as a new targeted cancer screening programme. The imperative now is to ensure that implementation follows an evidence-based process that will ensure clinical and cost effectiveness. This European Respiratory Society (ERS) task force was formed to provide an expert consensus for the management of incidental findings which can be adapted and followed during implementation., Methods: A multi-European society collaborative group was convened. 23 topics were identified, primarily from an ERS statement on lung cancer screening, and a systematic review of the literature was conducted according to ERS standards. Initial review of abstracts was completed and full text was provided to members of the group for each topic. Sections were edited and the final document approved by all members and the ERS Science Council., Results: Nine topics considered most important and frequent were reviewed as standalone topics (interstitial lung abnormalities, emphysema, bronchiectasis, consolidation, coronary calcification, aortic valve disease, mediastinal mass, mediastinal lymph nodes and thyroid abnormalities). Other topics considered of lower importance or infrequent were grouped into generic categories, suitable for general statements., Conclusions: This European collaborative group has produced an incidental findings statement that can be followed during lung cancer screening. It will ensure that an evidence-based approach is used for reporting and managing incidental findings, which will mean that harms are minimised and any programme is as cost-effective as possible., Competing Interests: Conflict of interest: All declarations are outside the submitted work. Unless otherwise stated, authors do not make any relevant disclosures. A. Brunelli declares honoraria from AstraZeneca, Ethicon, Medtronic, MSD and Roche. J. Chorostowska declares honoraria from AstraZeneca, MSD, Pfizer, Takeda, Amgen, Grifols, CSL Behring, Novartis, Chiesi, Celon Pharma, Adamed and Mero Biopharma. A. Devaraj declares consulting fees from Boehringer Ingelheim, Roche, Vicore and Brainomix, and personal stock/options in Brainomix. D. Deruysscher declares grants/honoraria from AstraZeneca, BMS, Beigne and Philips. H. Prosch declares grants and honoraria from Boehringer Ingelheim, AstraZeneca, Siemens and MSD. A. Kerpel-Fronius declares honoraria from MSD and Boehringer Ingelheim, and conference expenses from Roche and Bracco. W. van Geffen is local PI for trials funded by MSD and Roche. H-U. Kauczor declares honoraria and grants from Boehringer Ingelheim, Philips, Siemens and MSD, and honoraria from Sanofi. P.M. Putora declares grants to his institution from AstraZeneca and Bayer. M-P. Revel declares honoraria from MSD, Boehringer Ingelheim, GE Healthcare, Bracco and Gleamer, grants from the French Ministry of Health and French Cancer Institute, and software from Aidence, Mevis, Coreline and Gleamer. R. Vliegenthart declares honoraria from Siemens Healthineers and Bayer, and research grants from the Dutch Cancer Foundation, Siemens Heathineers, the Dutch Heart Foundation and the Netherlands Organisation for Scientific Research. A. Snoeckx declares grants from the Foundation Agaist Cancer and the Flemish Cancer Society, and advisory board work for Agfa. G. Veronesi declares honoraria from AstraZeneca, Medtronic and Roche, and grants from INAIL and IARC. D.R. Baldwin declares honoraria for speaking from Roche, MSD and AstraZeneca, and research grants from CRUK, NIHR, Innovate UK, Small Business Research Initiative, NHS Digital, NHS England, Roy Castle Lung Foundation, European Commission Horizon and Yourshire Cancer; and is advisor to the UK National Screening Committee., (This article has been co-published with permission in the European Journal of Cardio-Thoracic Surgery and in the European Respiratory Journal. Copyright © The authors 2023. Published by the European Respiratory Society. All rights reserved. For reproduction rights and permissions contact permissions@ersnet.org. The articles are identical except for minor stylistic and spelling differences in keeping with each journal's style. Either citation can be used when citing this article.)

Background: Global annual cancer incidence is forecast to rise to 27.5 M by 2040, a 62% increase from 2018. For most cancers, prevention and early detection are the most effective ways of reducing mortality. This study maps trials in cancer screening, prevention, and early diagnosis (SPED) to identify areas of unmet need and highlight research priorities., Methods: A systematic mapping review was conducted to evaluate all clinical trials focused on cancer SPED, irrespective of tumour type. The National Cancer Research Institute (NCRI) portfolio, EMBASE, PubMed and Medline were searched for relevant papers published between 01/01/2007 and 01/04/2020. References were exported into Covidence software and double-screened. Data were extracted and mapped according to tumour site, geographical location, and intervention type., Results: One hundred seventeen thousand seven hundred one abstracts were screened, 5157 full texts reviewed, and 2888 studies included. 1184 (52%) trials focussed on screening, 554 (24%) prevention, 442 (20%) early diagnosis, and 85 (4%) a combination. Colorectal, breast, and cervical cancer comprised 61% of all studies compared with 6.4% in lung and 1.8% in liver cancer. The latter two are responsible for 26.3% of global cancer deaths compared with 19.3% for the former three. Number of studies varied markedly according to geographical location; 88% were based in North America, Europe, or Asia., Conclusions: This study shows clear disparities in the volume of research conducted across different tumour types and according to geographical location. These findings will help drive future research effort so that resources can be directed towards major challenges in cancer SPED., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Introduction: COPD is underdiagnosed, and measurement of spirometry alongside low-dose computed tomography (LDCT) screening for lung cancer is one strategy to increase earlier diagnosis of this disease., Methods: Ever-smokers at high risk of lung cancer were invited to the Yorkshire Lung Screening Trial for a lung health check (LHC) comprising LDCT screening, pre-bronchodilator spirometry and a smoking cessation service. In this cross-sectional study we present data on participant demographics, respiratory symptoms, lung function, emphysema on imaging and both self-reported and primary care diagnoses of COPD. Multivariable logistic regression analysis identified factors associated with possible underdiagnosis and misdiagnosis of COPD in this population, with airflow obstruction defined as forced expiratory volume in 1 s/forced vital capacity ratio <0.70., Results: Out of 3920 LHC attendees undergoing spirometry, 17% had undiagnosed airflow obstruction with respiratory symptoms, representing potentially undiagnosed COPD. Compared to those with a primary care COPD code, this population had milder symptoms, better lung function and were more likely to be current smokers (p≤0.001 for all comparisons). Out of 836 attendees with a primary care COPD code who underwent spirometry, 19% did not have airflow obstruction, potentially representing misdiagnosed COPD, although symptom burden was high., Discussion: Spirometry offered alongside LDCT screening can potentially identify cases of undiagnosed and misdiagnosed COPD. Future research should assess the downstream impact of these findings to determine whether any meaningful changes to treatment and outcomes occur, and to assess the impact on co-delivering spirometry on other parameters of LDCT screening performance such as participation and adherence. Additionally, work is needed to better understand the aetiology of respiratory symptoms in those with misdiagnosed COPD, to ensure that this highly symptomatic group receive evidence-based interventions., Competing Interests: Conflicts of interest: C. Bradley reports that the European Respiratory Society funded their attendance at the ERS International Congress in 2021 as they won a Best Abstract prize. Conflicts of interest: P. Alexandris has nothing to disclose. Conflicts of interest: D.R. Baldwin reports honoraria for presenting from MSD, Roche, BMS and AstraZeneca. Conflicts of interest: R. Booton has nothing to disclose. Conflicts of interest: M. Darby has nothing to disclose. Conflicts of interest: C.J. Eckert has nothing to disclose. Conflicts of interest: R. Gabe has nothing to disclose. Conflicts of interest: N. Hancock has nothing to disclose. Conflicts of interest: S. Janes reports consulting fees from AstraZeneca, Johnson and Johnson, Bard1 (consultancy) and Optellum (advisory board), honoraria from Chiesi for a lecture, and Takeda funded their attendance at conference. Conflicts of interest: M. Kennedy has nothing to disclose. Conflicts of interest: J. Lindop has nothing to disclose. Conflicts of interest: R.D. Neal has nothing to disclose. Conflicts of interest: S. Rogerson has nothing to disclose. Conflicts of interest: B. Shinkins is a member of the the UK National Screening Committee (unpaid). Conflicts of interest: I. Simmonds has nothing to disclose. Conflicts of interest: S. Upperton has nothing to disclose. Conflicts of interest: J. Vestbo reports payment from Boehringer Ingelheim to their hospital for an investigator-initiated clinical trial; consulting fees from AstraZeneca, ALK Abello, Boehringer Ingelheim, GSK, Novartis and TEVA; honoraria for presenting from AstraZeneca, Boehringer Ingelheim, Chiesi, GSK and Novartis; and participant on data safety monitoring board or advisory board for Astra Zeneca and GSK. Conflicts of interest: P.A.J. Crosbie reports consulting fees and stock options from Everest Detection, and honoraria from AstraZeneca, Novartis and North West eHealth. Conflicts of interest: M.E.J. Callister has nothing to disclose., (Copyright ©The authors 2023.)

Background: Lung cancer is the second most common cancer in incidence and the leading cause of cancer deaths worldwide. Meanwhile, lung cancer screening with low-dose CT can reduce mortality. The UK National Screening Committee recommended targeted lung cancer screening on Sept 29, 2022, and asked for more modelling work to be done to help refine the recommendation. This study aims to develop and validate a risk prediction model-the CanPredict (lung) model-for lung cancer screening in the UK and compare the model performance against seven other risk prediction models., Methods: For this retrospective, population-based, cohort study, we used linked electronic health records from two English primary care databases: QResearch (Jan 1, 2005-March 31, 2020) and Clinical Practice Research Datalink (CPRD) Gold (Jan 1, 2004-Jan 1, 2015). The primary study outcome was an incident diagnosis of lung cancer. We used a Cox proportional-hazards model in the derivation cohort (12·99 million individuals aged 25-84 years from the QResearch database) to develop the CanPredict (lung) model in men and women. We used discrimination measures (Harrell's C statistic, D statistic, and the explained variation in time to diagnosis of lung cancer [R 2 D ]) and calibration plots to evaluate model performance by sex and ethnicity, using data from QResearch (4·14 million people for internal validation) and CPRD (2·54 million for external validation). Seven models for predicting lung cancer risk (Liverpool Lung Project [LLP] v2 , LLP v3 , Lung Cancer Risk Assessment Tool [LCRAT], Prostate, Lung, Colorectal, and Ovarian [PLCO] M2012 , PLCO M2014 , Pittsburgh, and Bach) were selected to compare their model performance with the CanPredict (lung) model using two approaches: (1) in ever-smokers aged 55-74 years (the population recommended for lung cancer screening in the UK), and (2) in the populations for each model determined by that model's eligibility criteria., Findings: There were 73 380 incident lung cancer cases in the QResearch derivation cohort, 22 838 cases in the QResearch internal validation cohort, and 16 145 cases in the CPRD external validation cohort during follow-up. The predictors in the final model included sociodemographic characteristics (age, sex, ethnicity, Townsend score), lifestyle factors (BMI, smoking and alcohol status), comorbidities, family history of lung cancer, and personal history of other cancers. Some predictors were different between the models for women and men, but model performance was similar between sexes. The CanPredict (lung) model showed excellent discrimination and calibration in both internal and external validation of the full model, by sex and ethnicity. The model explained 65% of the variation in time to diagnosis of lung cancer R 2 D in both sexes in the QResearch validation cohort and 59% of the R 2 D in both sexes in the CPRD validation cohort. Harrell's C statistics were 0·90 in the QResearch (validation) cohort and 0·87 in the CPRD cohort, and the D statistics were 2·8 in the QResearch (validation) cohort and 2·4 in the CPRD cohort. Compared with seven other lung cancer prediction models, the CanPredict (lung) model had the best performance in discrimination, calibration, and net benefit across three prediction horizons (5, 6, and 10 years) in the two approaches. The CanPredict (lung) model also had higher sensitivity than the current UK recommended models (LLP v2 and PLCO M2012 ), as it identified more lung cancer cases than those models by screening the same amount of individuals at high risk., Interpretation: The CanPredict (lung) model was developed, and internally and externally validated, using data from 19·67 million people from two English primary care databases. Our model has potential utility for risk stratification of the UK primary care population and selection of individuals at high risk of lung cancer for targeted screening. If our model is recommended to be implemented in primary care, each individual's risk can be calculated using information in the primary care electronic health records, and people at high risk can be identified for the lung cancer screening programme., Funding: Innovate UK (UK Research and Innovation)., Translation: For the Chinese translation of the abstract see Supplementary Materials section., Competing Interests: Declaration of interests JH-C is an unpaid director of QResearch, a not-for-profit organisation in a partnership between the University of Oxford and EMIS Health, who supply the QResearch database for this work. JH-C is also a founder and shareholder of ClinRisk, who produce open-source and closed-source software to implement clinical risk algorithms, and was its medical director until May 31, 2019. FVG is a shareholder of Optellums Ltd, an AI company that produces diagnostic algorithms for nodules on CT scans, mainly in lung cancer, and received honoraria from Roche. But these are unrelated to this study. DRB received honoraria from Astra Zeneca, Roche, Bristol Myers Squibb, and MSD, which is not related to this study. CACC received payment from previous consultancy with ClinRisk Ltd, which is outside of the current work. WL and JB have no interests to declare., (Copyright © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: The COVID-19 pandemic has caused significant disruption to health-care services and delivery worldwide. The impact of the pandemic and associated national lockdowns on lung cancer incidence in England have yet to be assessed., Research Question: What was the impact of the first year of the COVID-19 pandemic on the incidence and presentation of lung cancer in England?, Study Design and Methods: In this retrospective observational study, incidence rates for lung cancer were calculated from The National Lung Cancer Audit Rapid Cancer Registration Datasets for 2019 and 2020, using midyear population estimates from the Office of National Statistics as the denominators. Rates were compared using Poisson regression according to time points related to national lockdowns in 2020., Results: Sixty-four thousand four hundred fifty-seven patients received a diagnosis of lung cancer across 2019 (n = 33,088) and 2020 (n = 31,369). During the first national lockdown, a 26% reduction in lung cancer incidence was observed compared with the equivalent calendar period of 2019 (adjusted incidence rate ratio [IRR], 0.74; 95% CI, 0.71-0.78). This included a 23% reduction in non-small cell lung cancer (adjusted IRR, 0.77; 95% CI, 0.74-0.81) and a 45% reduction in small cell lung cancer (adjusted IRR, 0.55; 95% CI, 0.46-0.65) incidence. Thereafter, incidence rates almost recovered to baseline, without overcompensation (adjusted IRR, 0.96; 95% CI, 0.94-0.98)., Interpretation: The incidence rates of lung cancer in England fell significantly by 26% during the first national lockdown in 2020 and did not compensate later in the year., (Copyright © 2023 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.)

Lung cancer screening with low-dose CT was recommended by the UK National Screening Committee (UKNSC) in September, 2022, on the basis of data from trials showing a reduction in lung cancer mortality. These trials provide sufficient evidence to show clinical efficacy, but further work is needed to prove deliverability in preparation for a national roll-out of the first major targeted screening programme. The UK has been world leading in addressing logistical issues with lung cancer screening through clinical trials, implementation pilots, and the National Health Service (NHS) England Targeted Lung Health Check Programme. In this Policy Review, we describe the consensus reached by a multiprofessional group of experts in lung cancer screening on the key requirements and priorities for effective implementation of a programme. We summarise the output from a round-table meeting of clinicians, behavioural scientists, stakeholder organisations, and representatives from NHS England, the UKNSC, and the four UK nations. This Policy Review will be an important tool in the ongoing expansion and evolution of an already successful programme, and provides a summary of UK expert opinion for consideration by those organising and delivering lung cancer screenings in other countries., Competing Interests: Declaration of interests RWL is funded by the Royal Marsden National Institute for Health and Care Research (NIHR) Biomedical Research Centre, Royal Marsden Cancer Charity. RWL's institution receives compensation from NHS England for time spent in a secondment role for the lung health check programme and as a National Specialty Lead for the NIHR. He has received research funding from Cancer Research UK, Innovate UK (co-funded by GE Healthcare, Roche, and Optellum), Small Business Research Initiative for Healthcare (co-applicant with QURE.AI), RM Partners Cancer Alliance, and NIHR (co-applicant in grants with Optellum). He has received honoraria from Cancer Research UK. SHB reports being clinical lead for cancer for the Leeds office of the West Yorkshire Integrated Care Board and received funding from Cancer Research UK for doctoral research. KB receives funding from the Welsh Government via the Health and Care Research Wales-funded Wales Cancer Research Centre (grant number 517190) and Primary and Emergency Care Research Centre (grant number 517195). MEJC reports being principal investigator for Leeds Lung Health Check and the Yorkshire Enhanced Stop Smoking study (funding from Yorkshire Cancer Research). YC reports being the lead for PERFECTS: the first national External Quality Assurance scheme for lung cancer imaging assessment funded by NHS England and NHS Improvement. AD declares a role as Medical Director for Thoracic Radiology at Brainomix. JKF has received fees for participation in speaker's bureau from AstraZeneca and participation on advisory boards from Epigenomics, NUCLEIX, AstraZeneca, and iDNA; and grant support from Janssen Research & Development. SMJ declares paid advisory board membership for 2017–20 with AstraZeneca, Bard1 Bioscience, Achilles Therapeutics, and Jansen; has received assistance for travel to meetings from AstraZeneca; is grant income lead investigator for GRAIL, GSK, and Owlstone; and is a shareholder in Optellum and BARD1 Lifescience. AM declares her role on the National Screening Committee. RLM declares honorarium from AstraZeneca and has been commissioned by Action on Smoking and Health to produce a report on smoking cessation in targeted lung health checks. AN declares grants from UK Department of Health and Social Care's NIHR Biomedical Research Centre's funding scheme and GRAIL (Summit study); consulting fees from Aidence, Faculty Science, and MSD; support for attending meetings from Takeda; advisory board participation with Aidence and Faculty Science; leadership roles for the British Society of Thoracic Imaging, British Lung Foundation, and NHS England Targeted Lung Health Checks Programme. ELO’D reports research funding from Roy Castle Lung Cancer Foundation. SLQ receives funding from Cancer Research UK (grant number C50664/A24460), Barts Charity (MRC&U0036), and University College London Hospital NHS Trust. RR reports advisory boards and consultancy for Inivata, AstraZeneca, and Olympus Medical and research funding support from Owlstone Medical, Victor Dahdaleh Charitable Foundation, Cancer Research UK, and Asthma and Lung UK. RB declares honoraria from Siemens for speaker fees. DRB declares his role as Clinical Advisor to the UK National Screening Committee, UK Department of Health and Social Care, and honoraria from AstraZeneca, MSD, Roche, and Bristol Myers Squibb. PC reports consultancy for Novartis, Everest Detection, AstraZeneca, and North West eHealth; and stock options for Everest Detection. All other authors declare no competing interests., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

It is now widely accepted that lung cancer screening through low-dose computed tomography (LDCT) results in fewer diagnoses at a late stage, and decreased lung cancer mortality. Whilst reducing deaths from lung cancer is an essential prerequisite, this must be balanced against the considerable economic costs accumulated in screening. Multiple health economic models have shown substantial variation in cost per Quality-Adjusted Life Year (QALY), partly driven by the healthcare costs in the country concerned and partly by other modifiable programme components. Recent modelling using UK costs and a targeted approach suggest that most scenarios are within the willingness to pay threshold for the UK. However, identifying the most clinically and cost-effective programme is a priority to minimise the total financial impact. Programme components that influence cost-effectiveness include the method of selection of the eligible population, the participation rate, the interval between rounds of screening, the method of pulmonary nodule management, and the approach to clinical work up. Future research will clarify if a personalised approach to screening, using baseline and subsequent risk to define screening intervals is more cost-effective. The burden of LDCT screening on the medical infrastructure and workforce has to be quantified and carefully managed during implementation.

Importance: Annual low-dose computed tomographic (LDCT) screening reduces lung cancer mortality, but harms could be reduced and cost-effectiveness improved by reusing the LDCT image in conjunction with deep learning or statistical models to identify low-risk individuals for biennial screening., Objective: To identify low-risk individuals in the National Lung Screening Trial (NLST) and estimate, had they been assigned a biennial screening, how many lung cancers would have been delayed 1 year in diagnosis., Design, Setting, and Participants: This diagnostic study included participants with a presumed nonmalignant lung nodule in the NLST between January 1, 2002, and December 31, 2004, with follow-up completed on December 31, 2009. Data were analyzed for this study from September 11, 2019, to March 15, 2022., Exposures: An externally validated deep learning algorithm that predicts malignancy in current lung nodules using LDCT images (Lung Cancer Prediction Convolutional Neural Network [LCP-CNN]; Optellum Ltd) was recalibrated to predict 1-year lung cancer detection by LDCT for presumed nonmalignant nodules. Individuals with presumed nonmalignant lung nodules were hypothetically assigned annual vs biennial screening based on the recalibrated LCP-CNN model, Lung Cancer Risk Assessment Tool (LCRAT + CT [a statistical model combining individual risk factors and LDCT image features]), and the American College of Radiology recommendations for lung nodules, version 1.1 (Lung-RADS)., Main Outcomes and Measures: Primary outcomes included model prediction performance, the absolute risk of a 1-year delay in cancer diagnosis, and the proportion of people without lung cancer assigned a biennial screening interval vs the proportion of cancer diagnoses delayed., Results: The study included 10 831 LDCT images from patients with presumed nonmalignant lung nodules (58.7% men; mean [SD] age, 61.9 [5.0] years), of whom 195 were diagnosed with lung cancer from the subsequent screen. The recalibrated LCP-CNN had substantially higher area under the curve (0.87) than LCRAT + CT (0.79) or Lung-RADS (0.69) to predict 1-year lung cancer risk (P < .001). If 66% of screens with nodules were assigned to biennial screening, the absolute risk of a 1-year delay in cancer diagnosis would have been lower for recalibrated LCP-CNN (0.28%) than LCRAT + CT (0.60%; P = .001) or Lung-RADS (0.97%; P < .001). To delay only 10% of cancer diagnoses at 1 year, more people would have been safely assigned biennial screening under LCP-CNN than LCRAT + CT (66.4% vs 40.3%; P < .001)., Conclusions and Relevance: In this diagnostic study evaluating models of lung cancer risk, a recalibrated deep learning algorithm was most predictive of 1-year lung cancer risk and had least risk of 1-year delay in cancer diagnosis among people assigned biennial screening. Deep learning algorithms could prioritize people for workup of suspicious nodules and decrease screening intensity for people with low-risk nodules, which may be vital for implementation in health care systems.

This European Respiratory Society guideline is dedicated to the provision of good quality recommendations in lung cancer care. All the clinical recommendations contained were based on a comprehensive systematic review and evidence syntheses based on eight PICO (Patients, Intervention, Comparison, Outcomes) questions. The evidence was appraised in compliance with the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach. Evidence profiles and the GRADE Evidence to Decision frameworks were used to summarise results and to make the decision-making process transparent. A multidisciplinary Task Force panel of lung cancer experts formulated and consented the clinical recommendations following thorough discussions of the systematic review results. In particular, we have made recommendations relating to the following quality improvement measures deemed applicable to routine lung cancer care: 1) avoidance of delay in the diagnostic and therapeutic period, 2) integration of multidisciplinary teams and multidisciplinary consultations, 3) implementation of and adherence to lung cancer guidelines, 4) benefit of higher institutional/individual volume and advanced specialisation in lung cancer surgery and other procedures, 5) need for pathological confirmation of lesions in patients with pulmonary lesions and suspected lung cancer, and histological subtyping and molecular characterisation for actionable targets or response to treatment of confirmed lung cancers, 6) added value of early integration of palliative care teams or specialists, 7) advantage of integrating specific quality improvement measures, and 8) benefit of using patient decision tools. These recommendations should be reconsidered and updated, as appropriate, as new evidence becomes available., Competing Interests: Conflict of interest: T.G. Blum reports an unrestricted grant from Stiftung Oskar-Helene-Heim (Berlin, Germany), through which staff support for the work of the current Task Force was provided. R.L. Morgan declares no competing interests. V. Durieux declares no competing interests. J. Chorostowska-Wynimko declares grants to the National Institute of Tuberculosis and Lung Diseases from Pfizer and to the Polish Respiratory Society from AstraZeneca; consulting fees from AstraZeneca, Pfizer, Amgen, Takeda, Merck Sharp & Dohme, Roche and Roche Diagnostica; payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from AstraZeneca, Pfizer, CelonPharma, Amgen, Takeda, Novartis, Bristol Myers Squibb, Merck Sharp & Dohme, Roche, Roche Diagnostica and Amoy; support for attending meetings and/or travel from Bristol Myers Squibb, AstraZeneca, Merck Sharp & Dohme, Pfizer and Amgen; participation on a data safety monitoring board or advisory board for AstraZeneca, Pfizer, Takeda, Merck Sharp & Dohme, Roche and Roche Diagnostica, all in the 36 months prior to manuscript submission; and is Secretary General of the European Respiratory Society and a member of the Executive Committees of the Polish Respiratory Society and the Polish Coalition for Personalized Medicine. D.R. Baldwin declares payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Bristol Myers Squibb, AstraZeneca, Roche and Merck Sharp & Dohme, all in the 36 months prior to manuscript submission. J. Boyd is an employee of the European Lung Foundation. C. Faivre-Finn reports research grants from AstraZeneca and Elekta; payment or honoraria for presentations from AstraZeneca; support for attending meetings and/or travel from Elekta and AstraZeneca; and participation on a data safety monitoring board or advisory board for AstraZeneca and Merck Sharp & Dohme, all in the 36 months prior to manuscript submission. F. Galateau-Salle declares no competing interests. F. Gamarra declares no competing interests. B. Grigoriu declares support for attending meetings and/or travel from Roche and AstraZeneca; and participation on a data safety monitoring board or advisory board for AstraZeneca, all in the 36 months prior to manuscript submission. G. Hardavella declares no competing interests. M. Hauptmann declares no competing interests. E. Jakobsen declares no competing interests. D. Jovanovic declares payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Merck Sharp & Dohme, Roche, Boehringer Ingelheim, WCBIP 2020 and AstraZeneca; payment for expert testimony relating to the health effects of air pollution from SO2 released by Serbia Zijin Copper mining and smelting complex and the two biggest Serbian power plants, all in the 36 months prior to manuscript submission; and is a member of the editorial boards of the Journal of Thoracic Disease and the AME Surgical Journal, and a committee member of the National Ecological Association (NEA), Serbia. P. Knaut declares no competing interests. G. Massard declares a speaker's fee from Pneumo Update Europe, in the 36 months prior to manuscript submission. J. McPhelim declares advisory board payments from AstraZeneca, Janssen-Cilag and Bristol Myers Squibb, all in the 36 months prior to manuscript submission. A-P. Meert declares no competing interests. R. Milroy declares no competing interests. R. Muhr declares no competing interests. L. Mutti declares no competing interests. M. Paesmans declares no competing interests. P. Powell is an employee of the European Lung Foundation. P.M. Putora declares research grants to their institution from AstraZeneca, Takeda and Bayer; and a speaker's fee from Janssen-Cilag, all in the 36 months prior to manuscript submission. J. Rawlinson declares travel/accommodation support from the BTOG to attend the annual meeting in Dublin as patient advocate/steering committee member; travel/accommodation support from the European Respiratory Society to attend a screening meeting in Barcelona (patient representative) and European Lung Foundation patient event at the European Respiratory Society Congress Madrid 2019; travel/accommodation support from the NCRI to attend a conference in Glasgow (consumer member); travel/accommodation support from the EORTC to attend the Patient Days event as a speaker and patient panel member; and has been a Non-Executive Director (lay member) at Sandwell and West Birmingham Clinical Commissioning Group, UK. A.L. Rich declares no competing interests. D. Rigau is a methodologist for the European Respiratory Society. D. de Ruysscher declares grants to their institution from AstraZeneca and BeiGene; payment to their institution for lectures, presentations, speakers bureaus, manuscript writing or educational events from AstraZeneca; and payment to their institution for participation on an advisory board from AstraZeneca, all in the 36 months prior to manuscript submission. J-P. Sculier declares no competing interests. A. Schepereel declares a research grant to their institution from Bristol Myers Squibb; payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from AstraZeneca, Bristol Myers Squibb and Leo Pharma; support for attending meetings and/or travel from AstraZeneca, Bristol Myers Squibb, Merck Sharp & Dohme and Roche; and payment for participation on a data safety monitoring board or advisory board from AstraZeneca, Bristol Myers Squibb and Merck Sharp & Dohme, all in the 36 months prior to manuscript submission. D. Subotic declares no competing interests. P. Van Schil declares consulting fees paid to their institution by AstraZeneca and Merck Sharp & Dohme; payment to their institution for lectures, presentations, speakers bureaus, manuscript writing or educational events from AstraZeneca; and travel expenses related to participation in data safety monitoring or advisory boards for the LungART Trial and the Pearls Trial, all in the 36 months prior to manuscript submission; and is the President-elect of the International Association for the Study of Lung Cancer and the Treasurer of the Belgian Association for Cardio-Thoracic Surgery. T. Tonia is a methodologist for the European Respiratory Society. C. Williams is an employee of the European Lung Foundation. T. Berghmans declares consulting fees from InhaTarget; payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Janssen; and participation on a data safety monitoring board or advisory board for Janssen and Roche, all in the 36 months prior to manuscript submission., (Copyright ©The authors 2023. For reproduction rights and permissions contact permissions@ersnet.org.)

Randomised controlled trials, including the National Lung Screening Trial (NLST) and the NELSON trial, have shown reduced mortality with lung cancer screening with low-dose CT compared with chest radiography or no screening. Although research has provided clarity on key issues of lung cancer screening, uncertainty remains about aspects that might be critical to optimise clinical effectiveness and cost-effectiveness. This Review brings together current evidence on lung cancer screening, including an overview of clinical trials, considerations regarding the identification of individuals who benefit from lung cancer screening, management of screen-detected findings, smoking cessation interventions, cost-effectiveness, the role of artificial intelligence and biomarkers, and current challenges, solutions, and opportunities surrounding the implementation of lung cancer screening programmes from an international perspective. Further research into risk models for patient selection, personalised screening intervals, novel biomarkers, integrated cardiovascular disease and chronic obstructive pulmonary disease assessments, smoking cessation interventions, and artificial intelligence for lung nodule detection and risk stratification are key opportunities to increase the efficiency of lung cancer screening and ensure equity of access., Competing Interests: Declaration of interests ES reports advisory board payment or honoraria from Merck Sharp & Dohme in which she provides expert advice on an ad-hoc basis and speaker honoraria from AstraZeneca. DRB reports speaker honoraria from MSD, Bristol Myers Squibb, AstraZeneca, and Roche. RV reports research grants from Siemens Healthineers, Dutch Heart Foundation, Dutch Cancer Foundation, and the Netherlands Organisation for Health Research and Development, and speaker honoraria from Siemens Healthineers and Bayer. FJF reports research grants from the William M Wood Foundation and the American Roentgen Ray Society, and in-kind research support from Boston Scientific. SJA and PL declare no competing interests., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Pulmonary nodules are a common finding on CT scans of the chest. In the United Kingdom, management should follow British Thoracic Society Guidelines, which were published in 2015. This review covers key aspects of nodule management also looks at new and emerging evidence since then.

Background: Optimising smoking cessation services within a low radiation-dose computed tomography (LDCT) lung cancer screening programme has the potential to improve cost-effectiveness and overall efficacy of the programme. However, evidence on the optimal design and integration of cessation services is limited. We co-developed a personalised cessation and relapse prevention intervention incorporating medical imaging collected during lung cancer screening. The intervention is designed to initiate and support quit attempts among smokers attending screening as part of the Yorkshire Enhanced Stop Smoking study (YESS: ISRCTN63825779). Patients and public were involved in the development of an intervention designed to meet the needs of the target population., Methods: An iterative co-development approach was used. Eight members of the public with a history of smoking completed an online survey to inform the visual presentation of risk information in subsequent focus groups for acceptability testing. Three focus groups (n = 13) were conducted in deprived areas of Yorkshire and South Wales with members of the public who were current smokers or recent quitters (within the last year). Exemplar images of the heart and lungs acquired by LDCT, absolute and relative lung cancer risk, and lung age were shown. Data were analysed thematically, and discussed in stakeholder workshops. Draft versions of the intervention were developed, underpinned by the Extended Parallel Processing Model to increase self-efficacy and response-efficacy. The intervention was further refined in a second stakeholder workshop with a patient panel., Results: Individual LDCT scan images of the lungs and heart, in conjunction with artistic impressions to facilitate interpretation, were considered by public participants to be most impactful in prompting cessation. Public participants thought it important to have a trained practitioner guiding them through the intervention and emphasising the short-term benefits of quitting. Presentation of absolute and relative risk of lung cancer and lung age were considered highly demotivating due to reinforcement of fatalistic beliefs., Conclusion: An acceptable personalised intervention booklet utilising LDCT scan images has been developed for delivery by a trained smoking cessation practitioner. Our findings highlight the benefit of co-development during intervention development and the need for further evaluation of effectiveness., (© 2022. The Author(s).)

Several countries mandate informed or shared decision-making for low-dose CT (LDCT) lung cancer screening, but knowledge is limited about the type of information and presentation techniques used to support decision-making in practice. This review aimed to characterize the content, format, mode, and presentation methods of decision support tools (DSTs) for LDCT lung cancer screening. DSTs reported within peer-reviewed articles (January 2000-April 2021) were identified systematically from PubMed, PsycInfo, EMBASE, and CINAHL Plus. Inclusion criteria revolved around the development or evaluation of a resource or tool intended to support individual or shared decision-making for LDCT lung cancer screening. The data-charting and extraction framework was based on the International Patient Decision Aids Standards instrument and Template for Intervention Description and Reporting. Extracted data were organized within two categories: (1) study characteristics and context, format, and mode of DST use and (2) DST content and presentation methods. This review identified 22 DSTs in paper, video, or electronic formats across 26 articles. Most DSTs (n = 13) focused on knowledge exchange, whereas seven used interactive techniques to support values clarification (eg, Likert scales) and nine DSTs guided deliberation (eg, suggested discussion topics). The DSTs addressed similar topics, but the detail, quantification of probability, and presentation methods varied considerably. None described all the potential screening harms and results. The heterogeneity in DST design may affect the quality of decision-making, particularly for participants with lower literacy and numeracy. Evidence-based consensus guidelines for DST content and presentation methods should be developed collaboratively with screening-eligible adults., (Copyright © 2021 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.)

Objectives: Successful lung cancer screening delivery requires sensitive, timely reporting of low-dose computed tomography (LDCT) scans, placing a demand on radiology resources. Trained non-radiologist readers and computer-assisted detection (CADe) software may offer strategies to optimise the use of radiology resources without loss of sensitivity. This report examines the accuracy of trained reporting radiographers using CADe support to report LDCT scans performed as part of the Lung Screen Uptake Trial (LSUT)., Methods: In this observational cohort study, two radiographers independently read all LDCT performed within LSUT and reported on the presence of clinically significant nodules and common incidental findings (IFs), including recommendations for management. Reports were compared against a 'reference standard' (RS) derived from nodules identified by study radiologists without CADe, plus consensus radiologist review of any additional nodules identified by the radiographers., Results: A total of 716 scans were included, 158 of which had one or more clinically significant pulmonary nodules as per our RS. Radiographer sensitivity against the RS was 68-73.7%, with specificity of 92.1-92.7%. Sensitivity for detection of proven cancers diagnosed from the baseline scan was 83.3-100%. The spectrum of IFs exceeded what could reasonably be covered in radiographer training., Conclusion: Our findings highlight the complexity of LDCT reporting requirements, including the limitations of CADe and the breadth of IFs. We are unable to recommend CADe-supported radiographers as a sole reader of LDCT scans, but propose potential avenues for further research including initial triage of abnormal LDCT or reporting of follow-up surveillance scans., Key Points: • Successful roll-out of mass screening programmes for lung cancer depends on timely, accurate CT scan reporting, placing a demand on existing radiology resources. • This observational cohort study examines the accuracy of trained radiographers using computer-assisted detection (CADe) software to report lung cancer screening CT scans, as a potential means of supporting reporting workflows in LCS programmes. • CADe-supported radiographers were less sensitive than radiologists at identifying clinically significant pulmonary nodules, but had a low false-positive rate and good sensitivity for detection of confirmed cancers., (© 2022. The Author(s).)

Lung cancer screening is effective if offered to people at increased risk of the disease. Currently, direct contact with potential participants is required for evaluating risk. A way to reduce the number of ineligible people contacted might be to apply risk-prediction models directly to digital primary care data, but model performance in this setting is unknown., Method: The Clinical Practice Research Datalink, a computerised, longitudinal primary care database, was used to evaluate the Liverpool Lung Project V.2 (LLP v2 ) and Prostate Lung Colorectal and Ovarian (modified 2012) (PLCO m2012 ) models. Lung cancer occurrence over 5-6 years was measured in ever-smokers aged 50-80 years and compared with 5-year (LLP v2 ) and 6-year (PLCO m2012 ) predicted risk., Results: Over 5 and 6 years, 7123 and 7876 lung cancers occurred, respectively, from a cohort of 842 109 ever-smokers. After recalibration, LLP V2 produced a c-statistic of 0.700 (0.694-0.710), but mean predicted risk was over-estimated (predicted: 4.61%, actual: 0.9%). PLCO m2012 showed similar performance (c-statistic: 0.679 (0.673-0.685), predicted risk: 3.76%. Applying risk-thresholds of 1% (LLP v2 ) and 0.15% (PLCO m2012 ), would avoid contacting 42.7% and 27.4% of ever-smokers who did not develop lung cancer for screening eligibility assessment, at the cost of missing 15.6% and 11.4% of lung cancers., Conclusion: Risk-prediction models showed only moderate discrimination when applied to routinely collected primary care data, which may be explained by quality and completeness of data. However, they may substantially reduce the number of people for initial evaluation of screening eligibility, at the cost of missing some lung cancers. Further work is needed to establish whether newer models have improved performance in primary care data., Competing Interests: Competing interests: KtH reports grants from Cancer Research UK, during the conduct of the study; grants from European Union (Horizon 2020), grants from University of Zurich, Switzerland, non-financial support from International Association for the Study of Lung Cancer, non-financial support from International Association for the Study of Lung Cancer, non-financial support from Russian Society of Clinical Oncology, non-financial support and other from Biomedical Research In Endstage And Obstructive Lung Disease Hannover (BREATH), grants from NIH/National Cancer Institute, outside the submitted work. WH is Co-PI of CanTest Collaborative, funded by Cancer Research UK. RBH reports personal fees from Galapagos, outside the submitted work. SMJ reports grants from GRAIL, personal fees from AstraZeneca, personal fees from BARD1 Bioscience, personal fees from Achilles Therapeutics, grants from Owlstone, other from Optellum, personal fees from Johnson and Johnson, other from AstraZeneca, outside the submitted work. HJdK reports grants from Cancer Research UK, during the conduct of the study; grants from European Union (Horizon 2020), personal fees from University of Zurich, Switzerland / MSD, personal fees from IPSOS London, grants from NIH/National Cancer Institute, personal fees from Teva, Copenhagen, Denmark, outside the submitted work. DRB reports grants from Cancer Research UK, during the conduct of the study; personal fees from Roche, personal fees from AstraZeneca, personal fees from MSD, personal fees from BMS, outside the submitted work., (© Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Many countries are introducing low-dose computed tomography screening programmes for people at high risk of lung cancer. Effective communication strategies that convey risks and benefits, including unfamiliar concepts and outcome probabilities based on population risk, are critical to achieving informed choice and mitigating inequalities in uptake., Methods: This study investigated the acceptability of an aspect of NHS England's communication strategy in the form of a leaflet that was used to invite and inform eligible adults about the Targeted Lung Health Check (TLHC) programme. Acceptability was assessed in terms of how individuals engaged with, comprehended and responded to the leaflet. Semi-structured, 'think aloud' interviews were conducted remotely with 40 UK screening-naïve current and former smokers (aged 55-73). The verbatim transcripts were analysed thematically using a coding framework based on the Dual Process Theory of cognition., Results: The leaflet helped participants understand the principles and procedures of screening and fostered cautiously favourable intentions. Three themes captured the main results of the data analysis: (1) Response-participants experienced anxiety about screening results and further investigations, but the involvement of specialist healthcare professionals was reassuring; (2) Engagement-participants were rapidly drawn to information about lung cancer prevalence, and benefits of screening, but deliberated slowly about early diagnosis, risks of screening and less familiar symptoms of lung cancer; (3) Comprehension-participants understood the main principles of the TLHC programme, but some were confused by its rationale and eligibility criteria. Radiation risks, abnormal screening results and numerical probabilities of screening outcomes were hard to understand., Conclusion: The TLHC information leaflet appeared to be acceptable to the target population. There is scope to improve aspects of comprehension and engagement in ways that would support informed choice as a distributed process in lung cancer screening., Patient or Public Contribution: The insight and perspectives of patient representatives directly informed and improved the design and conduct of this study., (© 2022 The Authors. Health Expectations published by John Wiley & Sons Ltd.)

Trolley problems have persisted as a popular method to examine moral decision-making in the face of many criticisms. One such criticism is that thought experiments provide unrealistically abundant contextual information, leading to mental simulation. Recent work utilizing virtual reality technology has reduced contextual information with mixed results. However, this work has not departed entirely from the thought experiment tradition, often providing written or verbal descriptions of the trolley problem before or during the simulation. This approach may still allow for mental simulation prior to decision-making. The goal of the current study is to examine whether or not this criticism is relevant for the classic version of the trolley problem. One hundred and nineteen participants were randomly assigned to either receive prior contextual information about the trolley problem or receive no information. All participants then entered a virtual reality simulation of the classic trolley problem. We examined decision-making from an affective and autonomic nervous system perspective. We found no effect on any measure in response to the reduction of contextual information. There were, however, surprising gender differences in decision-making and autonomic response. Further, we discuss how these findings relate to competing dual-process models of moral decision-making.

Lung cancer is the leading cause of cancer death in Europe. Screening by means of low-dose computed tomography (LDCT) can shift detection to an earlier stage and reduce lung cancer mortality in high-risk individuals. However, to date, Poland, Croatia, Italy, and Romania are the only European countries to commit to large-scale implementation of targeted LDCT screening. Using a health systems approach, this article evaluates key factors needed to enable the successful implementation of screening programs across Europe. Recent literature on LDCT screening was reviewed for 10 countries (Belgium, Croatia, France, Germany, Italy, the Netherlands, Poland, Spain, Sweden, and United Kingdom) and complemented by 17 semistructured interviews with local experts. Research findings were mapped against a health systems framework adapted for lung cancer screening. The European policy landscape is highly variable, but potential barriers to implementation are similar across countries and consistent with those reported for other cancer screening programs. While consistent quality and safety of screening must be ensured across all screening centers, system factors are also important. These include appropriate data infrastructure, targeted recruitment methods that ensure equity in participation, sufficient capacity and workforce training, full integration of screening with multidisciplinary care pathways, and smoking cessation programs. Stigma and underlying perceptions of lung cancer as a self-inflicted condition are also important considerations. Building on decades of implementation research, governments now have a unique opportunity to establish effective, efficient, and equitable lung cancer screening programs adapted to their health systems, curbing the impact of lung cancer on their populations., (© 2022 The Authors.)

Objectives: We propose a risk-tailored approach for management of lung cancer screening results. This approach incorporates individual risk factors and low-dose computed tomography (LDCT) image features into calculations of immediate and next-screen (1-y) risks of lung cancer detection, which in turn can recommend short-interval imaging or 1-year or 2-year screening intervals., Methods: We first extended the "LCRAT+CT" individualized risk calculator to predict lung cancer risk after either a negative or abnormal LDCT screen result. To develop the abnormal screen portion, we analyzed 18,129 abnormal LDCT results in the National Lung Screening Trial (NLST), including lung cancers detected immediately (n = 649) or at the next screen (n = 235). We estimated the potential impact of this approach among NLST participants with any screen result (negative or abnormal)., Results: Applying the draft National Health Service (NHS) England protocol for lung screening to NLST participants referred 76% of participants to a 2-year interval, but delayed diagnosis for 40% of detectable cancers. The Lung Cancer Risk Assessment Tool+Computed Tomography (LCRAT+CT) risk model, with a threshold of less than 0.95% cumulative lung cancer risk, would also refer 76% of participants to a 2-year interval, but would delay diagnosis for only 30% of cancers, a 25% reduction versus the NHS protocol. Alternatively, LCRAT+CT, with a threshold of less than 1.7% cumulative lung cancer risk, would also delay diagnosis for 40% of cancers, but would refer 85% of participants for a 2-year interval, a 38% further reduction in the number of required 1-year screens beyond the NHS protocol., Conclusions: Using individualized risk models to determine management in lung cancer screening could substantially reduce the number of screens or increase early detection., (Copyright © 2021. Published by Elsevier Inc.)

Background: Research from the International Cancer Benchmarking Partnership (ICBP) demonstrates that international variation in lung cancer survival persists, particularly within early stage disease. There is a lack of international consensus on the critical contributing components to variation in lung cancer outcomes and the steps needed to optimise lung cancer services. These are needed to improve the quality of options for and equitable access to treatment, and ultimately improve survival., Methods: Semi-structured interviews were conducted with 9 key informants from ICBP countries. An international clinical network representing 6 ICBP countries (Australia, Canada, Denmark, England, Ireland, New Zealand, Northern Ireland, Scotland & Wales) was established to share local clinical insights and examples of best practice. Using a modified Delphi consensus model, network members suggested and rated recommendations to optimise the management of lung cancer. Calls to Action were developed via Delphi voting as the most crucial recommendations, with Good Practice Points included to support their implementation., Results: Five Calls to Action and thirteen Good Practice Points applicable to high income, comparable countries were developed and achieved 100% consensus. Calls to Action include (1) Implement cost-effective, clinically efficacious, and equitable lung cancer screening initiatives; (2) Ensure diagnosis of lung cancer within 30 days of referral; (3) Develop Thoracic Centres of Excellence; (4) Undertake an international audit of lung cancer care; and (5) Recognise improvements in lung cancer care and outcomes as a priority in cancer policy., Conclusion: The recommendations presented are the voice of an expert international lung cancer clinical network, and signpost key considerations for policymakers in countries within the ICBP but also in other comparable high-income countries. These define a roadmap to help align and focus efforts in improving outcomes and management of lung cancer patients globally.

The concept of cure from cancer is important to patients, but can be difficult to communicate in terms that are meaningful. This is because there are a number of definitions of cure that are applied by clinicians, patients and the public, and by policymakers that have a different meaning and significance. In this article, we provide a narrative review of the evidence concerning cure in lung cancer and show how the different definitions may apply in different settings. A better understanding of the various concepts of cure will improve communication with patients on this important topic. This article is based on previously conducted studies and does not contain any new studies with human participants or animals performed by any of the authors., (© 2021. The Author(s).)

Background: The NLST reported a significant 20% reduction in lung cancer mortality with three annual low-dose CT (LDCT) screens and the Dutch-Belgian NELSON trial indicates a similar reduction. We present the results of the UKLS trial., Methods: From October 2011 to February 2013, we randomly allocated 4 055 participants to either a single invitation to screening with LDCT or to no screening (usual care). Eligible participants (aged 50-75) had a risk score (LLPv2) ≥ 4.5% of developing lung cancer over five years. Data were collected on lung cancer cases to 31 December 2019 and deaths to 29 February 2020 through linkage to national registries. The primary outcome was mortality due to lung cancer. We included our results in a random-effects meta-analysis to provide a synthesis of the latest randomised trial evidence., Findings: 1 987 participants in the intervention and 1 981 in the usual care arms were followed for a median of 7.3 years (IQR 7.1-7.6), 86 cancers were diagnosed in the LDCT arm and 75 in the control arm. 30 lung cancer deaths were reported in the screening arm, 46 in the control arm, (relative rate 0.65 [95% CI 0.41-1.02]; p=0.062). The meta-analysis indicated a significant reduction in lung cancer mortality with a pooled overall relative rate of 0.84 (95% CI 0.76-0.92) from nine eligible trials., Interpretation: The UKLS trial of single LDCT indicates a reduction of lung cancer death of similar magnitude to the NELSON and NLST trials and was included in a meta-analysis of nine randomised trials which provides unequivocal support for lung cancer screening in identified risk groups., Funding: NIHR Health Technology Assessment programme; NIHR Policy Research programme; Roy Castle Lung Cancer Foundation., Competing Interests: JKF has received fees from AstraZeneca (Speaker's Bureau) and advisory boards of Epigenomics; NUCLEIX Ltd. AstraZeneca, iDNA; Grant Support: Janssen Research & Development, LLC. RCR is on the advisory boards of AstraZeneca and Roche. DRB has received speaker remuneration from AstraZeneca, Roche, MSD, BMS, Johnson and Johnson. KB has received personal fees from Astra Zeneca outside the submitted work. TE receives research support from AstraZeneca, Bayer, Pfizer; is employed by Roche (from March 2020) and was employed by AstraZeneca (to March 2020) and has stock in AstraZeneca and Roche; is a trustee of Macmillan Cancer Support.  AN has current grants and contracts with BRC, DART; Honoraria Aidence BV, AstraZeneca; Support from BLF, and as the clinical lead for NTLHC. No competing interests from all other co-authors., (© 2021 The Authors.)