Performance of the revised World Health Organization cardiovascular disease risk prediction models for the Middle East and North Africa: a validation study in the Tehran Lipid and Glucose Study

Abstract

Objectives: We aimed to evaluate the performance of the revised World Health Organization (WHO) models in predicting the 10-year risk of cardiovascular disease (CVD) in Iran, as part of the Middle East and North Africa (MENA) region.

Study Design and Setting: We analyzed data from the Tehran Lipid and Glucose Study (TLGS), including 5162 participants (2241 men) aged 40-80 years without CVD at baseline (the third examination, 2006-2008), for the occurrence of CVD (myocardial infarction (MI), coronary heart disease (CHD) death, and stroke). We assessed the statistical performance of original and regionally recalibrated models, both laboratory-and non-laboratory-based, using discrimination (C-statistic) calibration (calibration plot and observed-toexpected[O:E] ratio) and clinical performance applying net benefit (NB), a measure of true positives (TP) penalized for a weight of false positives (FP), a decimal value representing the expected proportion of TP outcomes among total population.

Results: During the 10-year follow-up, 307 CVD events occurred. The cumulative incidence of CVD was 9.0% (95% CI: 8.0%- 10.0%) in men and 4.0% (3.0%-5.0%) in women. For the laboratory-based model, the C-statistic was 0.72 (0.68-0.75) in men and 0.83 (0.80-0.86) in women; for the nonlaboratory-based model, it was 0.70 (0.66-0.73) and 0.82 (0.79-0.86) for men and women, respectively. The lab model underpredicted the risk (O:E 5 1.20 [1.00-1.33] for men and 1.40 [1.13-1.60] for women). At the risk threshold of 10%, NB for the lab model was 0.03 (0.02-0.04) for men and 0.01 (0.004-0.01) for women; these values became zero or negative for thresholds over 20%. Regionally recalibrated models overestimated the risk (O:E < 1) and showed lower NB. Conclusion: The loss of specificity was not sufficiently offset by the increase in sensitivity provided by the regionally recalibrated models compared to the original models. (c) 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.