Probucol Trial for Secondary Prevention of Atherosclerotic Events in Patients with Coronary Heart Disease (PROSPECTIVE)

Abstract

Aims: Although intensive statin therapy reduced cardiovascular risks, cardiovascular events have not been completely prevented. Probucol is a potent antioxidant and reduces tendon xanthomas in familial hypercholesterolemia patients despite reduction of high-density lipoprotein (HDL)-cholesterol (HDL-C). We investigated whether probucol can reduce cardiovascular events on top of conventional lipid-lowering therapy in patients with coronary heart disease (CHD).

Methods: PROSPECTIVE is a multicenter, randomized, prospective study that recruited 876 Japanese patients with CHD and dyslipidemia with a low-density lipoprotein (LDL)-cholesterol (LDL-C) level of ≥ 140 mg/dL without medication or those treated with lipid-lowering drugs. Lipid-lowering agents were administered during the study period in the control group (n=438), and probucol 500 mg/day was added to lipid-lowering therapy in the probucol group (n=438). Patients were randomly assigned to two treatment groups by adjusting the LDL-C level and presence of diabetes and hypertension and followed up for more than 3 years. The primary end point was a composite of cerebrovascular and cardiovascular events (cardiovascular disease death including sudden death, nonfatal myocardial infarction, nonfatal stroke, hospitalization for unstable angina, hospitalization for heart failure, or coronary revascularization). The secondary end point was carotid intima-media thickness in a subset of patients.

Results: The incidence of the primary end point showed a trend to be lower in the probucol group compared with that in the control group despite reduced HDL-C without serious adverse events. Anti-atherogenic effects of probucol may be attributed to its potent antioxidative function and enhancement of reverse cholesterol transport.

Conclusion: Since there was no statistical significance between the probucol and control groups despite a marked reduction of HDL-C, further studies on the clinical outcomes of probucol on top of conventional therapy may be necessary in the future (UMIN000003307).

Keywords: Antioxidants; Coronary heart disease; Prevention; Probucol; Reverse cholesterol transport.

Supplemental Fig. 1.

Trial profile of PROSPECTIVE

Fig. 1.

Total cholesterol (a), LDL-cholesterol (b), HDL-cholesterol (c), and triglycerides levels (d) over time by treatment group (FAS) Measured values at each visit were shown as least square mean with bars of standard error and analyzed by mixed-effects models with repeated measures (MMRM) with allocation group, visit (at baseline and 3, 12, 24, and 36 months), and interaction between allocation group and visit as fixed effects and patient as a random effect. Comparisons between treatment groups at each visit were made using the least square mean of each group. The MMRM analyses were performed using the Kenward-Roger method for adjusting degrees of freedom in an unstructured (UN) covariance structure. Blue and red circles with bars and lines show the control group (conventional LLT continued) and the test group (LLT plus probucol), respectively.

Fig. 2.

Kaplan–Meier curves for the primary efficacy end point Survival curves were estimated using the Kaplan–Meier method, and the stratified log-rank test was performed to compare the survival rates, using levels of LDL-C, presence or absence of diabetes, and presence or absence of hypertension as the stratified factors. The level of significance was set at p < 0.05 (two-sided). The hazard ratio (HR) and 95% CI were estimated using the Cox proportional hazards model adjusted by allocation factors (levels of LDL-C, presence or absence of diabetes, and presence or absence of hypertension). Blue and red markers with bars and lines show the control group (conventional LLT continued) and the test group (LLT plus probucol), respectively.

Supplemental Fig. 2.

Levels in mean (a) and max (c) IMT and changes from baseline in mean (b) and max (d) IMT over time by treatment group (FAS) Measured values at each visit were shown as least square mean with bars of standard error and analyzed using a mixed-effects models with repeated measures (MMRM) with allocation group, visit (at baseline and 12, 24, and 36 months), and interactions between allocation group and visit defined as fixed effects and patient as a random effect. Comparisons between treatment groups at each visit were made using the least square mean of each group. The MMRM analyses were performed using the Kenward–Roger method for adjusting degrees of freedom in an unstructured (UN) covariance structure.