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The performance of seven QPrediction risk scores in an independent external sample of patients from general practice: a validation study

OBJECTIVES: To 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). SETTING: Prospective open cohort study using practices contributing to the CP...

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Autores principales: Hippisley-Cox, Julia, Coupland, Carol, Brindle, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4156807/
https://www.ncbi.nlm.nih.gov/pubmed/25168040
http://dx.doi.org/10.1136/bmjopen-2014-005809
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author Hippisley-Cox, Julia
Coupland, Carol
Brindle, Peter
author_facet Hippisley-Cox, Julia
Coupland, Carol
Brindle, Peter
author_sort Hippisley-Cox, Julia
collection PubMed
description OBJECTIVES: To 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). SETTING: Prospective open cohort study using practices contributing to the CPRD database and practices contributing to the QResearch database. PARTICIPANTS: The 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. RESULTS: Overall, 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. CONCLUSIONS: Each 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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spelling pubmed-41568072014-09-17 The performance of seven QPrediction risk scores in an independent external sample of patients from general practice: a validation study Hippisley-Cox, Julia Coupland, Carol Brindle, Peter BMJ Open Epidemiology OBJECTIVES: To 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). SETTING: Prospective open cohort study using practices contributing to the CPRD database and practices contributing to the QResearch database. PARTICIPANTS: The 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. RESULTS: Overall, 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. CONCLUSIONS: Each of the algorithms performed practically as well in the external independent CPRD validation cohorts as they had in the original published QResearch validation cohorts. BMJ Publishing Group 2014-08-28 /pmc/articles/PMC4156807/ /pubmed/25168040 http://dx.doi.org/10.1136/bmjopen-2014-005809 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions 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. See: http://creativecommons.org/licenses/by-nc/4.0/
spellingShingle Epidemiology
Hippisley-Cox, Julia
Coupland, Carol
Brindle, Peter
The performance of seven QPrediction risk scores in an independent external sample of patients from general practice: a validation study
title The performance of seven QPrediction risk scores in an independent external sample of patients from general practice: a validation study
title_full The performance of seven QPrediction risk scores in an independent external sample of patients from general practice: a validation study
title_fullStr The performance of seven QPrediction risk scores in an independent external sample of patients from general practice: a validation study
title_full_unstemmed The performance of seven QPrediction risk scores in an independent external sample of patients from general practice: a validation study
title_short The performance of seven QPrediction risk scores in an independent external sample of patients from general practice: a validation study
title_sort performance of seven qprediction risk scores in an independent external sample of patients from general practice: a validation study
topic Epidemiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4156807/
https://www.ncbi.nlm.nih.gov/pubmed/25168040
http://dx.doi.org/10.1136/bmjopen-2014-005809
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