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Personalised lung cancer risk stratification and lung cancer screening: do general practice electronic medical records have a role?
Jani, Bhautesh Dinesh; Sullivan, Michael K; Hanlon, Peter; Nicholl, Barbara I; Lees, Jennifer S; Brown, Lamorna; MacDonald, Sara; Mark, Patrick B; Mair, Frances S; Sullivan, Frank M.
Afiliação
  • Jani BD; General Practice and Primary Care, School of Health and Wellbeing, University of Glasgow, Glasgow, UK. Bhautesh.jani@glasgow.ac.uk.
  • Sullivan MK; School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK.
  • Hanlon P; General Practice and Primary Care, School of Health and Wellbeing, University of Glasgow, Glasgow, UK.
  • Nicholl BI; General Practice and Primary Care, School of Health and Wellbeing, University of Glasgow, Glasgow, UK.
  • Lees JS; School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK.
  • Brown L; Population and Behavioural Science Division, School of Medicine, University of St Andrews, St Andrews, UK.
  • MacDonald S; General Practice and Primary Care, School of Health and Wellbeing, University of Glasgow, Glasgow, UK.
  • Mark PB; School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK.
  • Mair FS; General Practice and Primary Care, School of Health and Wellbeing, University of Glasgow, Glasgow, UK.
  • Sullivan FM; Population and Behavioural Science Division, School of Medicine, University of St Andrews, St Andrews, UK.
Br J Cancer ; 129(12): 1968-1977, 2023 12.
Article em En | MEDLINE | ID: mdl-37880510
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), BMIsmoking 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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Medicina Geral / Neoplasias Pulmonares Limite: Aged / Humans / Middle aged Idioma: En Revista: Br J Cancer Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Medicina Geral / Neoplasias Pulmonares Limite: Aged / Humans / Middle aged Idioma: En Revista: Br J Cancer Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Reino Unido