Personalised lung cancer risk stratification and lung cancer screening : do general practice electronic medical records have a role?
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Background In the United Kingdom (UK), cancer screening invitations are based on general practice (GP) registrations. We hypothesize that GP electronic medical records (EMR) can be utilised to calculate a lung cancer risk score with good accuracy/clinical utility. Methods The development cohort was Secure Anonymised Information Linkage-SAIL (2.3 million GP EMR) and the validation cohort was UK Biobank-UKB (N = 211,597 with GP-EMR availability). Fast backward method was applied for variable selection and area under the curve (AUC) evaluated discrimination. Results Age 55–75 were included (SAIL: N = 574,196; UKB: N = 137,918). Six-year lung cancer incidence was 1.1% (6430) in SAIL and 0.48% (656) in UKB. The final model included 17/56 variables in SAIL for the EMR-derived score: age, sex, socioeconomic status, smoking status, family history, body mass index (BMI), BMI:smoking interaction, alcohol misuse, chronic obstructive pulmonary disease, coronary heart disease, dementia, hypertension, painful condition, stroke, peripheral vascular disease and history of previous cancer and previous pneumonia. The GP-EMR-derived score had AUC of 80.4% in SAIL and 74.4% in UKB and outperformed ever-smoked criteria (currently the first step in UK lung cancer screening pilots). Discussion A GP-EMR-derived score may have a role in UK lung cancer screening by accurately targeting high-risk individuals without requiring patient contact.
Jani , B D , Sullivan , M K , Hanlon , P , Nicholl , B I , Lees , J S , Brown , L , MacDonald , S , Mark , P B , Mair , F S & Sullivan , F M 2023 , ' Personalised lung cancer risk stratification and lung cancer screening : do general practice electronic medical records have a role? ' , British Journal of Cancer , vol. First Online . https://doi.org/10.1038/s41416-023-02467-9
British Journal of Cancer
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DescriptionDr. Bhautesh Dinesh Jani’s time was partly funded by a research grant from the British Medical Association. Chief Scientist Office (CSO, Scotland) funded SAIL data access costs (PCL/18/03). JSL was funded by CSO Postdoctoral Lectureship Award (PCL/20/10). The Medical Research Council fund MKS (MR/V001671/1) and PH (MR/S021949/1).
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