TY - JOUR
T1 - Personalised lung cancer risk stratification and lung cancer screening
T2 - do general practice electronic medical records have a role?
AU - Jani, Bhautesh Dinesh
AU - Sullivan, Michael K
AU - Hanlon, Peter
AU - Nicholl, Barbara I
AU - Lees, Jennifer S
AU - Brown, Lamorna
AU - MacDonald, Sara
AU - Mark, Patrick B
AU - Mair, Frances S
AU - Sullivan, Frank M.
N1 - Dr. 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).
PY - 2023/10/25
Y1 - 2023/10/25
N2 - BackgroundIn
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.MethodsThe
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.ResultsAge 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).DiscussionA
GP-EMR-derived score may have a role in UK lung cancer screening by
accurately targeting high-risk individuals without requiring patient
contact.
AB - BackgroundIn
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.MethodsThe
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.ResultsAge 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).DiscussionA
GP-EMR-derived score may have a role in UK lung cancer screening by
accurately targeting high-risk individuals without requiring patient
contact.
U2 - 10.1038/s41416-023-02467-9
DO - 10.1038/s41416-023-02467-9
M3 - Article
C2 - 37880510
SN - 0007-0920
VL - First Online
JO - British Journal of Cancer
JF - British Journal of Cancer
ER -