Abstract 239: A Field Synopsis of the Role of Race in Clinical Prediction Models for Cardiovascular Disease

Abstract

Introduction: Race and ethnicity-based differences and disparities have been noted in cardiovascular disease (CVD), including inequalities in access to care and differences in genetics and pharmacokinetics that affect response to treatment and development of clinical outcomes. Risk scores commonly used in CVD prevention, such as the Pooled Cohort Equation, include terms for race, yet to date there has been no systematic evaluation of the role of race and ethnicity in clinical prediction models (CPMs). To better understand the potential impact of race-specific clinical decisions encouraged by these models, we conducted a field synopsis of the role of race and ethnicity in CPMs for CVD. Methods: We identified CPMs in the Tufts PACE CPM Database, a systematic review of CVD-related CPMs published from 1/1990-3/2015. We report the proportion of models including the effect of race or ethnicity on CVD incidence or prognosis, summarize the directionality of the effects of race (harm or protection), and explore factors influencing the inclusion of race. Results: Out of 908 CPMs with CVD as either an index condition or outcome, only 24 (3%) contained a coefficient for race, ethnicity or a combination of race and ethnicity, or presented race-stratified equations. Among the overall group of CVD-related models, the racial or ethnic composition of the underlying model development cohort was reported for only 1 out of every 5 models (168/908 models (19%)), but was reported in the majority of models that included race (22/24 (92%)). Among models where the racial composition of the cohort was reported, the proportion of patients of white race was the same (79%) in models that included race vs. excluded race. The inclusion of race/ethnicity as a covariate or stratification variable was more common in models predicting incident CVD versus prognosis for patients with known CVD (9/126 (7%) versus 15/782 (2%), respectively, p<0.001)). Race/ethnicity was included infrequently even in models predicting outcomes in patient populations where racial differences have been documented: heart failure-mortality (2%, 2/107), population sample-CVD (4%, 2/52), and population sample-stroke (0%, 0/26). Among the 23 models that contained a coefficient for race/ethnicity, 11 (48%) indicated a higher risk of the outcome for patients of non-white race, while 12 (52%) indicated higher risk for patients of white race. Conclusions: Race/ethnicity is rarely included in CVD-related CPMs, although racial and ethnic differences in outcome risk have been documented for many conditions, and several commonly used CPMs include race. Model development from cohorts including greater numbers of non-white patients may uncover additional or more consistent racial/ethnic effects.