Identifying severe hypercholesterolemia in participants of ASCVD trials: Implications for trial conduct and opportunistic screening.

BACKGROUND

Cardiovascular outcomes trials depend on adequate event accrual for statistical power. Patients with severe hypercholesterolemia (SH), defined as low-density lipoprotein cholesterol (LDL-C) ≥190 mg/dL, have elevated cardiovascular risk and frequently harbor undiagnosed familial hypercholesterolemia (FH). Lipid-lowering therapies mask diagnostic LDL-C levels at screening.

OBJECTIVE

To determine whether pretreatment LDL-C calculation at trial enrollment could identify undiagnosed SH and facilitate opportunistic FH screening.

METHODS

We applied correction factors to baseline LDL-C to calculate pretreatment LDL-C in ACCELERATE (Assessment of Clinical Effects of Cholesteryl Ester Transfer Protein Inhibition with Evacetrapib in Participants at a High Risk for Vascular Outcomes) participants (n = 11,993) and across 57 trials informing the 2018 Multisociety Blood Cholesterol Guideline. SH was defined as pretreatment LDL-C ≥190 mg/dL; clinically probable FH as SH plus family history of hypercholesterolemia in a first- or second-degree relative. The association between SH and major adverse cardiovascular events (MACE) was examined using multivariable Cox regression.

RESULTS

In ACCELERATE, 15.1% (1809/11,993) had SH and 2.1% (255/11,993) met criteria for probable FH, 3- and 5-fold higher than population prevalences (∼5% and ∼0.4%). Across 57 guideline-informing trials, weighted SH prevalence was 14% (range 0%-77%). Pretreatment LDL-C ≥190 mg/dL was associated with higher MACE incidence among ACCELERATE participants (15.1% vs 13.5%; adjusted hazard ratio 1.19, 95% CI 1.03-1.38, P = .021).

CONCLUSION

SH and probable FH are more prevalent in cardiovascular outcomes trial participants than in the general population, and SH was associated with increased MACE risk. Pretreatment LDL-C calculation at enrollment can enrich trials for higher-risk participants and enable opportunistic identification of probable FH for cascade screening. This dual approach may reduce trial costs whilst identifying a critically underdiagnosed condition.