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

doi:10.1038/s41416-023-02467-9

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 journal › Article › peer-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 language	English
Number of pages	10
Journal	British Journal of Cancer
Volume	First Online
Early online date	25 Oct 2023
DOIs	https://doi.org/10.1038/s41416-023-02467-9
Publication status	E-pub ahead of print - 25 Oct 2023

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This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

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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, First Online. Advance online publication. https://doi.org/10.1038/s41416-023-02467-9

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

abstract = "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.",

author = "Jani, \{Bhautesh Dinesh\} and Sullivan, \{Michael K\} and Peter Hanlon and Nicholl, \{Barbara I\} and Lees, \{Jennifer S\} and Lamorna Brown and Sara MacDonald and Mark, \{Patrick B\} and Mair, \{Frances S\} and Sullivan, \{Frank M.\}",

note = "Dr. Bhautesh Dinesh Jani{\textquoteright}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).",

year = "2023",

month = oct,

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doi = "10.1038/s41416-023-02467-9",

language = "English",

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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.

UR - https://www.scopus.com/pages/publications/85174822659

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 -

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

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