TY - JOUR
T1 - Cardiovascular risk prediction in type 2 diabetes
T2 - a comparison of 22 risk scores in primary care settings
AU - Dziopa, Katarzyna
AU - Asselbergs, Folkert W.
AU - Gratton, Jasmine
AU - Chaturvedi, Nishi
AU - Schmidt, Amand F.
N1 - Funding Information: KD is supported by a PhD studentship from the National Productivity Investment Fund–MRC Doctoral Training Programme (grant no. MR/S502522/1). FWA is supported by UCL Hospitals NIHR Biomedical Research Centre. JG is supported by BHF grant FS/17/70/33482. AFS is supported by BHF grant PG/18/5033837 and the UCL BHF Research Accelerator AA/18/6/34223. NC is supported by MRC Unit grant MRC_UU_00019/1. Funding Information: This study was carried out as part of the CALIBER ? programme (https://www.ucl.ac.uk/health-informatics/caliber). CALIBER, led from the UCL Institute of Health Informatics, is a research resource consisting of anonymised, coded variables extracted from linked electronic health records, methods and tools, specialised infrastructure, and training and support. This study is based in part on data from the Clinical Practice Research Datalink obtained under license from the UK Medicines and Healthcare products Regulatory Agency. The data are provided by patients and collected by the NHS as part of their care and support. The interpretation and conclusions contained in this study are those of the authors alone. Copyright ? (2020), re-used with the permission of the Health & Social Care Information Centre. All rights reserved. This study and its results have been published previously in medRxiv (https://doi.org/10.1101/2020.10.08.20209015) and an abstract was presented at the ESC Congress in August 2021. The authors declare that there are no relationships or activities that might bias, or be perceived to bias, their work. Publisher Copyright: © 2022, The Author(s).
PY - 2022/4/1
Y1 - 2022/4/1
N2 - AIMS/HYPOTHESIS: We aimed to compare the performance of risk prediction scores for CVD (i.e., coronary heart disease and stroke), and a broader definition of CVD including atrial fibrillation and heart failure (CVD+), in individuals with type 2 diabetes.METHODS: Scores were identified through a literature review and were included irrespective of the type of predicted cardiovascular outcome or the inclusion of individuals with type 2 diabetes. Performance was assessed in a contemporary, representative sample of 168,871 UK-based individuals with type 2 diabetes (age ≥18 years without pre-existing CVD+). Missing observations were addressed using multiple imputation.RESULTS: We evaluated 22 scores: 13 derived in the general population and nine in individuals with type 2 diabetes. The Systemic Coronary Risk Evaluation (SCORE) CVD rule derived in the general population performed best for both CVD (C statistic 0.67 [95% CI 0.67, 0.67]) and CVD+ (C statistic 0.69 [95% CI 0.69, 0.70]). The C statistic of the remaining scores ranged from 0.62 to 0.67 for CVD, and from 0.64 to 0.69 for CVD+. Calibration slopes (1 indicates perfect calibration) ranged from 0.38 (95% CI 0.37, 0.39) to 0.74 (95% CI 0.72, 0.76) for CVD, and from 0.41 (95% CI 0.40, 0.42) to 0.88 (95% CI 0.86, 0.90) for CVD+. A simple recalibration process considerably improved the performance of the scores, with calibration slopes now ranging between 0.96 and 1.04 for CVD. Scores with more predictors did not outperform scores with fewer predictors: for CVD+, QRISK3 (19 variables) had a C statistic of 0.68 (95% CI 0.68, 0.69), compared with SCORE CVD (six variables) which had a C statistic of 0.69 (95% CI 0.69, 0.70). Scores specific to individuals with diabetes did not discriminate better than scores derived in the general population: the UK Prospective Diabetes Study (UKPDS) scores performed significantly worse than SCORE CVD (p value <0.001).CONCLUSIONS/INTERPRETATION: CVD risk prediction scores could not accurately identify individuals with type 2 diabetes who experienced a CVD event in the 10 years of follow-up. All 22 evaluated models had a comparable and modest discriminative ability.
AB - AIMS/HYPOTHESIS: We aimed to compare the performance of risk prediction scores for CVD (i.e., coronary heart disease and stroke), and a broader definition of CVD including atrial fibrillation and heart failure (CVD+), in individuals with type 2 diabetes.METHODS: Scores were identified through a literature review and were included irrespective of the type of predicted cardiovascular outcome or the inclusion of individuals with type 2 diabetes. Performance was assessed in a contemporary, representative sample of 168,871 UK-based individuals with type 2 diabetes (age ≥18 years without pre-existing CVD+). Missing observations were addressed using multiple imputation.RESULTS: We evaluated 22 scores: 13 derived in the general population and nine in individuals with type 2 diabetes. The Systemic Coronary Risk Evaluation (SCORE) CVD rule derived in the general population performed best for both CVD (C statistic 0.67 [95% CI 0.67, 0.67]) and CVD+ (C statistic 0.69 [95% CI 0.69, 0.70]). The C statistic of the remaining scores ranged from 0.62 to 0.67 for CVD, and from 0.64 to 0.69 for CVD+. Calibration slopes (1 indicates perfect calibration) ranged from 0.38 (95% CI 0.37, 0.39) to 0.74 (95% CI 0.72, 0.76) for CVD, and from 0.41 (95% CI 0.40, 0.42) to 0.88 (95% CI 0.86, 0.90) for CVD+. A simple recalibration process considerably improved the performance of the scores, with calibration slopes now ranging between 0.96 and 1.04 for CVD. Scores with more predictors did not outperform scores with fewer predictors: for CVD+, QRISK3 (19 variables) had a C statistic of 0.68 (95% CI 0.68, 0.69), compared with SCORE CVD (six variables) which had a C statistic of 0.69 (95% CI 0.69, 0.70). Scores specific to individuals with diabetes did not discriminate better than scores derived in the general population: the UK Prospective Diabetes Study (UKPDS) scores performed significantly worse than SCORE CVD (p value <0.001).CONCLUSIONS/INTERPRETATION: CVD risk prediction scores could not accurately identify individuals with type 2 diabetes who experienced a CVD event in the 10 years of follow-up. All 22 evaluated models had a comparable and modest discriminative ability.
KW - Adolescent
KW - Cardiovascular Diseases/epidemiology
KW - Diabetes Mellitus, Type 2/complications
KW - Heart Disease Risk Factors
KW - Humans
KW - Primary Health Care
KW - Prospective Studies
KW - Risk Assessment
KW - Risk Factors
UR - http://www.scopus.com/inward/record.url?scp=85123105171&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/s00125-021-05640-y
DO - https://doi.org/10.1007/s00125-021-05640-y
M3 - Article
C2 - 35032176
SN - 0012-186X
VL - 65
SP - 644
EP - 656
JO - Diabetologia
JF - Diabetologia
IS - 4
ER -