Updating risk prediction tools a case study in prostate cancer Bisex chat in english online

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This paper reports the results of the derivation and validation of the new algorithms based on the QResearch database linked to cancer registrations, mortality and hospital episode statistics.We undertook a prospective cohort study in a large population of primary care patients from an open cohort study using the QResearch database (V.38).The algorithms could be integrated into clinical computer systems and used to identify high-risk patients.This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial.Measures of calibration and discrimination in the validation cohort.Outcomes Incident cases of blood, breast, bowel, gastro-oesophageal, lung, oral, ovarian, pancreas, prostate, renal tract and uterine cancers.The QResearch database is a large pseudonymised database of electronic health records from over 750 general practices in the UK which has been described in detail elsewhere (Over 99% of people in the UK are registered with general practices and have information routinely recorded on an ongoing basis when they consult their general practitioner (GP) or other primary care professional, receive prescriptions and from referrals to secondary care.

Patients were censored at the earliest date of the diagnosis of cancer, death, deregistration with the practice, last upload of computerised data, or the study end date (1 October 2013).In particular, we were interested to quantify the absolute risk of cancer in (1) patients with a positive family history of specific cancers, previous cancers or a chronic disease which might increase cancer risk and might require additional surveillance and (2) those with potentially modifiable risk factors (such as smoking and alcohol) for whom quantification of absolute risk might be useful to support efforts to lower risk.We decided to focus on the 11 most commonly occurring cancers in men and women in England.Methods 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.

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