Abstract Introduction High-density lipoprotein cholesterol (HDL-C) has traditionally been included in atherosclerotic cardiovascular disease (ASCVD) risk prediction models, such as the pooled cohort equations. However, growing evidence suggests that lipoprotein particle concentration may serve as a more reliable predictor of cardiovascular outcomes than cholesterol content alone. Studies, including the MESA trial, indicate that HDL particle concentration (HDL-P) is a stronger determinant of cardiovascular risk than HDL-C. Larger HDL particles may be dysfunctional, leading to misleading HDL-C levels that do not accurately reflect cardiovascular protection. Adjusting HDL-C for HDL-P may improve risk stratification. We hypothesize that incorporating HDL-P into risk prediction models will refine cardiovascular risk assessment. Purpose This study evaluates the limitations of HDL-C in risk prediction and assesses whether particle-adjusted values provide a more accurate measure of cardiovascular risk when integrated into standard risk calculations. Methods A total of 67 lipid profiles from Scripps Health were analyzed, including traditional lipid concentrations, HDL and LDL particle concentrations, and age at the time of lipid profile collection. Cardiovascular risk was calculated using unadjusted baseline lipid values within the PREVENT risk prediction calculator. To isolate the impact of lipid parameter adjustments on risk estimation, risk factors such as diabetes, smoking, eGFR, SBP, and BMI were held constant across all calculations. The calculations were then repeated using adjusted HDL-C and Total Cholesterol values, accounting for LDL and HDL particle concentrations. Adjusted values were derived using statistical regression models based on real-world data from the Framingham Offspring Study and pooled cohort analyses (DHS, ARIC, MESA, PREVEND). Results After adjustment, 47 patients (70.1%) demonstrated an increase in predicted cardiovascular risk, with an average absolute risk increase of 0.834% and an average relative change of 15.31%. Conversely, 20 patients (29.9%) exhibited a decrease in predicted risk, with an average absolute risk decrease of 0.2785% and an average relative change of 6.72%. The total combined relative risk change across both groups was 22.03%, suggesting that incorporating HDL-P and LDL-P meaningfully alters risk assessment. Conclusions Adjusting for particle concentration significantly influences cardiovascular risk prediction, with the majority of patients experiencing an increase in estimated risk. This supports the hypothesis that HDL-P, rather than HDL-C, provides a more precise assessment of cardiovascular risk. Current risk models relying solely on HDL-C and total cholesterol may misclassify risk, underscoring the need to incorporate particle-adjusted values into predictive algorithms for more accurate cardiovascular risk stratification.
Hassan et al. (Sat,) studied this question.