Personalised lung cancer risk stratification and lung cancer screening: do general practice electronic medical records have a role?

Bhautesh Dinesh Jani*, Michael K Sullivan, Peter Hanlon, Barbara I Nicholl, Jennifer S Lees, Lamorna Brown, Sara MacDonald, Patrick B Mark, Frances S Mair, Frank M. Sullivan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

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.

Original languageEnglish
Number of pages10
JournalBritish Journal of Cancer
VolumeFirst Online
Early online date25 Oct 2023
DOIs
Publication statusE-pub ahead of print - 25 Oct 2023

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