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

ABSTRACT: 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).Prospective open cohort study using practices contributing to the CPRD database and practices contributing to the QResearch database.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.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.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.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.

SUBMITTER: Hippisley-Cox J

PROVIDER: S-EPMC4156807 | biostudies-other | 2014

REPOSITORIES: biostudies-other

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

Hippisley-Cox Julia J Coupland Carol C Brindle Peter P

BMJ open 20140828 8

<h4>Objectives</h4>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).<h4>Setting</h4>Prospective open cohort study using practices contributing to the CPRD database and practices contributing to the QResearch database.<h4>Participants</h4>The CPRD validation cohort consisted of 3.3 million patients, aged 25-99 years registered at 357 gene ...[more]

PMID: 25168040

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Project description:Two clinical scoring systems, the status epilepticus severity score (STESS) and the epidemiology-based mortality score in status epilepticus (EMSE), are used to predict mortality in patients with status epilepticus (SE). The aim of this study was to compare the outcome-prediction function of the two scoring systems regarding in-hospital mortality using a multicenter large cohort of adult patients with SE. Moreover, we studied the potential role of these two scoring systems in predicting the functional outcome in patients with SE.The SE cohort consisted of patients from the epilepsy centers of eight academic tertiary medical centers in South Korea. The clinical and electroencephalography data for all adult patients with SE from January 2013 to December 2014 were derived from a prospective SE database. The primary outcome variable was defined as in-hospital death. The secondary outcome variable was defined as a poor functional outcome, i.e., a score of 1-3 on the Glasgow Outcome Scale, at discharge.Among the 120 non-hypoxic patients with SE recruited into the study, 16 (13.3%) died in the hospital and 64 (53.3%) were discharged with a poor functional outcome. The receiver-operating characteristic (ROC) curve for prediction of in-hospital death based on the STESS had an area under the curve of 0.673 with an optimal cutoff value for discrimination (best match for both sensitivity (0.56) and specificity (0.70)) that was ? 4 points. The two combinations of elements of the EMSE system (EMSE-ALDEg and EMSE-ECLEg) predicted not only in-hospital mortality with the best match for sensitivity (more than 0.6) and specificity (more than 0.6), but also a poor functional outcome with the best match for both sensitivity (>0.7) and specificity (>0.6). STESS did not predict a poor functional outcome (area under the ROC, 0.581; P = 0.23).Although the EMSE is a clinical scoring system that focuses on individual mortality, we did not find differences between the EMSE and STESS in the prediction of in-hospital death. The EMSE was useful in predicting poor functional outcome, as it was significantly better than STESS.

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Project description:Cirrhosis poses an increased risk of postoperative mortality, yet it remains challenging to accurately risk stratify patients in clinical practice. The VOCAL-Penn cirrhosis surgical risk score was recently developed and internally validated in the national Veterans Affairs health system; however, to date this score has not been evaluated in independent cohorts. The goal of this study was to compare the predictive performance of the VOCAL-Penn to the Mayo risk, Model for End-Stage Liver Disease (MELD), and MELD-sodium (MELD-Na) scores in 2 large health systems. We performed a retrospective cohort study of patients with cirrhosis undergoing surgical procedures of interest at the Beth Israel Deaconess Medical Center or University of Pennsylvania Health System from January 1, 2008, to October 1, 2015. The outcomes of interest were 30-day and 90-day postoperative mortality. Concordance statistics (C-statistics), calibration curves, Brier scores, and the index of prediction accuracy (IPA) were compared for each predictive model. A total of 855 surgical procedures were identified. The VOCAL-Penn score had the numerically highest C-statistic for 90-day postoperative mortality (eg, 0.82 versus 0.79 Mayo versus 0.78 MELD-Na versus 0.79 MELD), although differences were not statistically significant. Calibrations were excellent for the VOCAL-Penn, MELD, and MELD-Na; however, the Mayo score consistently overestimated risk. The VOCAL-Penn had the lowest Brier score and highest IPA at both time points, suggesting superior overall predictive model performance. In subgroup analyses of patients with higher MELD scores, the VOCAL-Penn had significantly higher C-statistics compared with the MELD and MELD-Na. The VOCAL-Penn score (www.vocalpennscore.com) has excellent discrimination and calibration for postoperative mortality among diverse patients with cirrhosis. Overall performance is superior to the Mayo, MELD, and MELD-Na scores. In contrast to the MELD/MELD-Na, the VOCAL-Penn retains excellent discrimination among patients with higher MELD scores.

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Dataset Information

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

Publications

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

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