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Cardiovascular risk prediction in type 2 diabetes: a comparison of 22 risk scores in primary care settings

Diabetologia, 2022-04, Vol.65 (4), p.644-656 [Peer Reviewed Journal]

The Author(s) 2022 ;2022. The Author(s). ;The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0012-186X ;EISSN: 1432-0428 ;DOI: 10.1007/s00125-021-05640-y ;PMID: 35032176

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  • Title:
    Cardiovascular risk prediction in type 2 diabetes: a comparison of 22 risk scores in primary care settings
  • Author: Dziopa, Katarzyna ; Asselbergs, Folkert W. ; Gratton, Jasmine ; Chaturvedi, Nishi ; Schmidt, Amand F.
  • Subjects: Adolescent ; Calibration ; Cardiovascular disease ; Cardiovascular diseases ; Cardiovascular Diseases - epidemiology ; Congestive heart failure ; Coronary artery disease ; Diabetes ; Diabetes mellitus (non-insulin dependent) ; Diabetes Mellitus, Type 2 - complications ; Fibrillation ; Heart Disease Risk Factors ; Human Physiology ; Humans ; Internal Medicine ; Literature reviews ; Medicine ; Medicine & Public Health ; Metabolic Diseases ; Predictions ; Primary care ; Primary Health Care ; Prospective Studies ; Risk Assessment ; Risk Factors
  • Is Part Of: Diabetologia, 2022-04, Vol.65 (4), p.644-656
  • Description: 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. Graphical abstract
  • Publisher: Berlin/Heidelberg: Springer Berlin Heidelberg
  • Language: English
  • Identifier: ISSN: 0012-186X
    EISSN: 1432-0428
    DOI: 10.1007/s00125-021-05640-y
    PMID: 35032176
  • Source: MEDLINE
    Springer Nature OA/Free Journals
    ProQuest Central
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