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dc.contributor.authorJani, Bhautesh Dinesh
dc.contributor.authorSullivan, Michael K
dc.contributor.authorHanlon, Peter
dc.contributor.authorNicholl, Barbara I
dc.contributor.authorLees, Jennifer S
dc.contributor.authorBrown, Lamorna
dc.contributor.authorMacDonald, Sara
dc.contributor.authorMark, Patrick B
dc.contributor.authorMair, Frances S
dc.contributor.authorSullivan, Frank M.
dc.date.accessioned2023-11-15T09:30:11Z
dc.date.available2023-11-15T09:30:11Z
dc.date.issued2023-10-25
dc.identifier296443675
dc.identifierbcce4c74-235c-450d-9b4e-59c18fa860a1
dc.identifier37880510
dc.identifier85174822659
dc.identifier.citationJani , 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/s41416-023-02467-9en
dc.identifier.issn0007-0920
dc.identifier.otherJisc: 1451672
dc.identifier.otherpii: 10.1038/s41416-023-02467-9
dc.identifier.otherORCID: /0000-0002-6206-8196/work/146960642
dc.identifier.otherORCID: /0000-0002-6623-4964/work/146964858
dc.identifier.urihttps://hdl.handle.net/10023/28700
dc.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).en
dc.description.abstractBackground 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.
dc.format.extent10
dc.format.extent674074
dc.language.isoeng
dc.relation.ispartofBritish Journal of Canceren
dc.subjectRC0254 Neoplasms. Tumors. Oncology (including Cancer)en
dc.subject3rd-DASen
dc.subjectSDG 3 - Good Health and Well-beingen
dc.subject.lccRC0254en
dc.titlePersonalised lung cancer risk stratification and lung cancer screening : do general practice electronic medical records have a role?en
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. School of Medicineen
dc.contributor.institutionUniversity of St Andrews. Population and Behavioural Science Divisionen
dc.contributor.institutionUniversity of St Andrews. Sir James Mackenzie Institute for Early Diagnosisen
dc.identifier.doi10.1038/s41416-023-02467-9
dc.description.statusPeer revieweden


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