External validation and comparison of six cardiovascular risk prediction models in the Prospective Urban Rural Epidemiology (PURE)-Colombia study.

ABSTRACT

AIMS: To external validate the SCORE2, AHA/ACC Pooled Cohort Equation (PCE), Framingham Risk Score (FRS), Non-Laboratory INTERHEART Risk Score (NL-IHRS), Globorisk-LAC, and WHO prediction models and compare their discrimination and calibration capacity. METHODS: Validation in individuals aged 40-69 years with at least 10 years follow-up and without baseline use of statins or cardiovascular diseases from the Prospective Urban Rural Epidemiology prospective cohort study (PURE)-Colombia. For discrimination, the C-statistic, and Receiver Operating Characteristic curves with the integrated area under the curve (AUCi) were used and compared. For calibration, the smoothed time-to-event method was used, choosing a recalibration factor based on the integrated calibration index (ICI). In the NL-IHRS, linear regressions were used. RESULTS: In 3,802 participants (59.1% women), baseline risk ranged from 4.8% (SCORE2 women) to 55.7% (NL-IHRS). After a mean follow-up of 13.2 years, 234 events were reported (4.8 cases per 1000 person-years). The C-statistic ranged between 0.637 (0.601-0.672) in NL-IHRS and 0.767 (0.657-0.877) in AHA/ACC PCE. Discrimination was similar between AUCi. In women, higher overprediction was observed in the Globorisk-LAC (61%) and WHO (59%). In men, higher overprediction was observed in FRS (72%) and AHA/ACC PCE (71%). Overestimations were corrected after multiplying by a factor derived from the ICI. CONCLUSIONS: Six prediction models had a similar discrimination capacity, supporting their use after multiplying by a correction factor. If blood tests are unavailable, NL-IHRS is a reasonable option. Our results suggest that these models could be used in other countries of Latin America after correcting the overestimations with a multiplying factor.

Detecting people at high risk of cardiovascular disease and implementing preventive interventions in this population is a key strategy in primary prevention. Recently, new risk calculation tools have been developed, but before their application and routine use in populations different from those where it was developed, it's necessary to validate them. The recommendations for predicting cardiovascular risk in Colombia's guidelines are based on studies with noteworthy limitations. This study involving 3,802 healthy individuals in Colombia supports the recommendation of using these prediction models. The estimation result should be multiplied by a correction factor, because most of the prediction models overestimate cardiovascular risk. For example, the correction factors suggested in women for AHA/ACC PCE and SCORE2 are 0.54 and 0.75, respectively. In men, the correction factors suggested in AHA/ACC PCE and SCORE2 are 0.28 and 0.61, respectively. Therefore, the present study with a contemporary population provides additional evidence to update these recommendations in Colombia and perhaps in Latin America.