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Selection of eligible participants for screening for lung cancer using primary care data

O’Dowd, Emma L.; Ten Haaf, Kevin; Kaur, Jaspreet; Duffy, Stephen W.; Hamilton, William; Hubbard, Richard B.; Field, John K.; Callister, Matthew E.; Janes, Sam M.; de Koning, Harry; Rawlinson, Janette; Baldwin, David R.

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Emma L. O’Dowd

Kevin Ten Haaf

Stephen W. Duffy

William Hamilton

Blf/Gsk Professor of Epidemiological Resp Research

John K. Field

Matthew E. Callister

Sam M. Janes

Harry de Koning

Janette Rawlinson

David R. Baldwin


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 (LLPv2) and Prostate Lung Colorectal and Ovarian (modified 2012) (PLCOm2012) models. Lung cancer occurrence over 5-6 years was measured in ever-smokers aged 50-80 years and compared with 5-year (LLPv2) and 6-year (PLCOm2012) 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, LLPV2 produced a c-statistic of 0.700 (0.694-0.710), but mean predicted risk was over-estimated (predicted: 4.61%, actual: 0.9%). PLCOm2012 showed similar performance (c-statistic: 0.679 (0.673-0.685), predicted risk: 3.76%. Applying risk-thresholds of 1% (LLPv2) and 0.15% (PLCOm2012), 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.


O’Dowd, E. L., Ten Haaf, K., Kaur, J., Duffy, S. W., Hamilton, W., Hubbard, R. B., …Baldwin, D. R. (2022). Selection of eligible participants for screening for lung cancer using primary care data. Thorax, 77(9), 882-890.

Journal Article Type Article
Acceptance Date Sep 24, 2021
Online Publication Date Oct 29, 2021
Publication Date Sep 1, 2022
Deposit Date Oct 5, 2021
Publicly Available Date Oct 29, 2021
Journal Thorax
Print ISSN 0040-6376
Electronic ISSN 1468-3296
Publisher BMJ Publishing Group
Peer Reviewed Peer Reviewed
Volume 77
Issue 9
Pages 882-890
Keywords Lung Cancer; screening; eligibility; selection criteria
Public URL
Publisher URL
Additional Information This article has been accepted for publication in Thorax, 2021 following peer review, and the Version of Record can be accessed online at