Lancet Reg Health Am. 2026 Feb 16;56:101403. doi: 10.1016/j.lana.2026.101403. eCollection 2026 Apr.
ABSTRACT
BACKGROUND: Cardiovascular disease (CVD) is the leading cause of mortality in Latin America, yet most CVD risk equations were developed in high-income countries with limited validations in these settings. Here, we externally validated CVD risk prediction models for fatal CVD, and recalibrated the Globorisk-fatal model in Mexican population.
METHODS: We analyzed 112,262 adults ≥40 years, 67% (75,320) female and 33% (36,942) males, mean age 54.6 ± 10.7 years without prior CVD from the Mexico City Prospective Study. The primary outcome was 10-year fatal CVD, including myocardial infarction (MI) and stroke. CVD risk was estimated using the laboratory- and office-based Framingham, Globorisk, Globorisk-LAC, WHO, and SCORE2 equations. Discrimination was assessed with Harrell's c-statistic and AUROCs, calibration with mean estimates, slopes, and calibration curves, and overall performance with Brier scores. Sex-specific recalibration of the Globorisk-fatal model was performed using observed risks of fatal CVD.
FINDINGS: During 10 years of follow-up, 2429 fatal CVD events were recorded (1667 MI, 762 stroke). All models showed good discrimination, with c-statistics ranging from 0.761 to 0.805 in males and 0.797-0.831 in females. The Globorisk-fatal model had the highest c-statistic in females (0.831, 95% CI 0.821-0.841), and the laboratory-based WHO-MI model in males (0.805, 95% CI 0.783-0.827). Despite this, all equations consistently overestimated CVD risk, particularly in females. Calibration analyses revealed systematic overprediction at higher risk levels. Recalibration of the Globorisk-fatal model improved agreement between predicted and observed risks.
INTERPRETATION: CVD risk models showed good discrimination but consistently overestimated risk in this Mexican cohort. The recalibrated Globorisk-fatal model improves risk estimation of fatal CVD in Mexican adults.
FUNDING: This research was supported by Instituto Nacional de Geriatría in Mexico.
PMID:41732703 | PMC:PMC12925590 | DOI:10.1016/j.lana.2026.101403