ArticleBMJ open2014
The performance of seven QPrediction risk scores in an independent external sample of patients from general practice: a validation study.
Article in BMJ open, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 2 of them syntheses that pooled it.
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Who cites it
38 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Pooled it
- Performance of predictive tools to identify individuals at risk of non-traumatic fracture: a systematic review, meta-analysis, and meta-regression.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2019Pooled it
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- DXA-derived hip shape is associated with hip fracture: a longitudinal study of 38 123 UK Biobank participants.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2026Article
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- Evaluation and Optimization of Diabetic Retinopathy Screenings for Uninsured Latinx Patients in a Resource-Limited Student-Run Free Clinic.Journal of student-run clinics · 2024Article
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- Development and validation of personalised risk prediction models for early detection and diagnosis of primary liver cancer among the English primary care population using the QResearch® database: research protocol and statistical analysis plan.Diagnostic and prognostic research · 2022Article
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- Assessment of QRISK3 as a predictor of cardiovascular disease events in type 2 diabetes mellitus.Frontiers in endocrinology · 2022Article
- One- and 2-year incidence of osteoporotic fracture: a multi-cohort observational study using routinely collected real-world data.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2022Observational
- Modelling tool to support decision-making in the NHS Health Check programme: workshops, systematic review and co-production with users.Health technology assessment (Winchester, England) · 2021Article
- Predicting the risk of prostate cancer in asymptomatic men: a cohort study to develop and validate a novel algorithm.The British journal of general practice : the journal of the Royal College of General Practitioners · 2021Article
- Consistency of variety of machine learning and statistical models in predicting clinical risks of individual patients: longitudinal cohort study using cardiovascular disease as exemplar.BMJ (Clinical research ed.) · 2020Article
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Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo validate the performance of a set of risk prediction algorithms developed using the QResearch database, in an independent sample from general practices contributing to the Clinical Research Data Link (CPRD).
settingProspective open cohort study using practices contributing to the CPRD database and practices contributing to the QResearch database.
participantsThe CPRD validation cohort consisted of 3.3 million patients, aged 25-99 years registered at 357 general practices between 1 Jan 1998 and 31 July 2012. The validation statistics for QResearch were obtained from the original published papers which used a one-third sample of practices separate to those used to derive the score. A cohort from QResearch was used to compare incidence rates and baseline characteristics and consisted of 6.8 million patients from 753 practices registered between 1 Jan 1998 and until 31 July 2013. OUTCOME MEASURES: Incident events relating to seven different risk prediction scores: QRISK2 (cardiovascular disease); QStroke (ischaemic stroke); QDiabetes (type 2 diabetes); QFracture (osteoporotic fracture and hip fracture); QKidney (moderate and severe kidney failure); QThrombosis (venous thromboembolism); QBleed (intracranial bleed and upper gastrointestinal haemorrhage). Measures of discrimination and calibration were calculated.
resultsOverall, the baseline characteristics of the CPRD and QResearch cohorts were similar though QResearch had higher recording levels for ethnicity and family history. The validation statistics for each of the risk prediction scores were very similar in the CPRD cohort compared with the published results from QResearch validation cohorts. For example, in women, the QDiabetes algorithm explained 50% of the variation within CPRD compared with 51% on QResearch and the receiver operator curve value was 0.85 on both databases. The scores were well calibrated in CPRD.
conclusionsEach of the algorithms performed practically as well in the external independent CPRD validation cohorts as they had in the original published QResearch validation cohorts.
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