Association of Original and Revised Pooled Cohort Equations With Cardiovascular and Cerebrovascular Mortality.
Cardiovascular (CVD) and cerebrovascular diseases (CeVD) are leading causes of mortality. The Pooled Cohort Equations (PCE) are widely used for ASCVD risk prediction, but face calibration concerns, particularly in diverse populations. The Revised Pooled Cohort Equations (RPCE) were developed to address these limitations. While prior research has evaluated these models for ASCVD, less is known about their performance for CVD and CeVD mortality outcomes.
This study aimed to comprehensively compare the association of PCE and RPCE with CVD mortality and combined CVD and CeVD mortality, including subgroup analyses by race and gender, within a nationally representative US adult population.
We analyzed 16,584 primary prevention participants (aged 40-79 years) from National Health and Nutrition Examination Survey (1999-2018), linked to National Death Index mortality data. We calculated 10-year ASCVD risk using both PCE and RPCE. Bland-Altman plots assessed score agreement. Cox proportional hazards models evaluated the association of standardized PCE and RPCE scores with CVD and combined CVD and CeVD mortality, adjusting for confounders and stratifying by race and gender.
Both PCE and RPCE were significantly associated with CVD mortality (adjusted hazard ratio (HR) for PCE: 1.91 [95% CI: 1.82-2.01]; RPCE: 1.65 [95% CI: 1.59-1.72]) and combined CVD and CeVD mortality (adjusted HR for PCE: 1.91 [95% CI: 1.82-2.00]; RPCE: 1.65 [95% CI: 1.60-1.72]). Bland-Altman analyses revealed PCE consistently overestimated risk compared to RPCE, with differences increasing at higher risk levels. RPCE demonstrated improved calibration, especially in racially diverse populations, where PCE overestimation was more pronounced.
Both PCE and RPCE are robust prognostic tools for vascular mortality. However, RPCE offers improved calibration, particularly in racially diverse populations, by providing more conservative yet comparably predictive risk estimates. These findings highlight the importance of selecting risk models tailored to target populations to optimize prevention and avoid potential overtreatment.
This study aimed to comprehensively compare the association of PCE and RPCE with CVD mortality and combined CVD and CeVD mortality, including subgroup analyses by race and gender, within a nationally representative US adult population.
We analyzed 16,584 primary prevention participants (aged 40-79 years) from National Health and Nutrition Examination Survey (1999-2018), linked to National Death Index mortality data. We calculated 10-year ASCVD risk using both PCE and RPCE. Bland-Altman plots assessed score agreement. Cox proportional hazards models evaluated the association of standardized PCE and RPCE scores with CVD and combined CVD and CeVD mortality, adjusting for confounders and stratifying by race and gender.
Both PCE and RPCE were significantly associated with CVD mortality (adjusted hazard ratio (HR) for PCE: 1.91 [95% CI: 1.82-2.01]; RPCE: 1.65 [95% CI: 1.59-1.72]) and combined CVD and CeVD mortality (adjusted HR for PCE: 1.91 [95% CI: 1.82-2.00]; RPCE: 1.65 [95% CI: 1.60-1.72]). Bland-Altman analyses revealed PCE consistently overestimated risk compared to RPCE, with differences increasing at higher risk levels. RPCE demonstrated improved calibration, especially in racially diverse populations, where PCE overestimation was more pronounced.
Both PCE and RPCE are robust prognostic tools for vascular mortality. However, RPCE offers improved calibration, particularly in racially diverse populations, by providing more conservative yet comparably predictive risk estimates. These findings highlight the importance of selecting risk models tailored to target populations to optimize prevention and avoid potential overtreatment.
Authors
Lu Lu, Li Li, Sun Sun, Zhang Zhang, Li Li, Yu Yu, Wang Wang, Cao Cao, Hu Hu, Li Li
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