Development and validation of risk prediction algorithms to estimate future risk of common cancers in men and women: prospective cohort study

BMJ Open
Julia Hippisley-Cox, Carol Coupland

Abstract

To derive and validate a set of clinical risk prediction algorithm to estimate the 10-year risk of 11 common cancers. Prospective open cohort study using routinely collected data from 753 QResearch general practices in England. We used 565 practices to develop the scores and 188 for validation. 4.96 million patients aged 25-84 years in the derivation cohort; 1.64 million in the validation cohort. Patients were free of the relevant cancer at baseline. Cox proportional hazards models in the derivation cohort to derive 10-year risk algorithms. Risk factors considered included age, ethnicity, deprivation, body mass index, smoking, alcohol, previous cancer diagnoses, family history of cancer, relevant comorbidities and medication. Measures of calibration and discrimination in the validation cohort. Incident cases of blood, breast, bowel, gastro-oesophageal, lung, oral, ovarian, pancreas, prostate, renal tract and uterine cancers. Cancers were recorded on any one of four linked data sources (general practitioner (GP), mortality, hospital or cancer records). We identified 228,241 incident cases during follow-up of the 11 types of cancer. Of these 25,444 were blood; 41,315 breast; 32,626 bowel, 12,808 gastro-oesophageal; 32,187 lung; 4...Continue Reading

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Methods Mentioned

BETA
hormone replacement therapy

Software Mentioned

QCancer
QResearch

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