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

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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