Maximal expected benefits from lowering cholesterol in primary prevention for a high-risk population

Abstract

Aims: The objective of this study was to estimate the maximal clinical benefit that could be reasonably expected from a cholesterol-lowering intervention.

Materials and methods: We used a hypothetical population at high risk of cardiovascular disease events from three risk assessment models including the Framingham risk function, the Score Canada and the Pooled Cohort Risk Assessment Equations. Our source population were all 55-year-old smoking men with diabetes, hypertension and low HDL. From this population, we identified two different subpopulations named “high” and “low”, referring to their cholesterol levels which were set at 8.60 and 4.14 mmol/L respectively. Both subpopulations were identified for each risk assessment model in order to estimate the maximal impact of lowering cholesterol on cardiovascular disease events.

Results: Our extrapolations estimated that the maximal theoretical efficacy of a cholesterol-lowering intervention corresponds to a risk ratio ranging between 0.46 and 0.66 over a 10-year period. The number of events prevented during this period were between 21 and 29 per 100 patients which corresponds to a number needed to treat varying from 3.47 to 4.76.

Conclusions: Our estimation showed the maximal clinical benefit that could be reasonably expected by an intervention that would lower total cholesterol in high-risk patients.

Keywords:

• Cardiovascular disease
• Cholesterol
• High-risk
• Maximal clinical benefit
• Primary prevention
• Risk assessment

Transparency

Declaration of funding

This study was funded by Genome Quebec and Genome Canada through the large-scale genomics applied research project “Personalized medicine strategies for molecular diagnostics and targeted therapeutics of cardiovascular diseases”.

Authors’ contributions: All authors contributed to the design of the study and approved the manuscript.

Declaration of financial/other relationships

F.F.-A., A.C.I. and D.M. have disclosed that they each received a PhD grant from Genome Quebec and Genome Canada. A.M. has disclosed that he has received speaker fees from AstraZeneca, Bayer and Pfizer. D.M. has disclosed that he is a consultant for Amgen Canada, Pfizer Canada, Triton, Dymaxium, Pharmascience, JAMP, Leo Pharm, Athena Research, Baxter, AbbVie, Gilead, Roche, Sanofi, and Bristol-Myers Squib. J.R.G. has disclosed that he has received a Pfizer Canada Inc. Post-Doctoral Mentoree Award and the 2015–2016 Bernie O’Brien Post-Doctoral Fellowship Award for work unrelated to this paper. He has also received honoraria from Sanofi-Aventis and Bio-K + International Inc. A.D. and M.-P.D. have disclosed that they have no significant relationships with or financial interests in any commercial companies related to this study or article. J.-C.T. has disclosed that he has received research grants and honoraria from Servier. J.L.L. has disclosed that he has acted as a consultant and is involved in research projects. He has also received remuneration or is expecting it from the following companies: AstraZeneca, Bio-K + International Inc., Campbell Alliance Group Inc., CUBIST Pharma Inc., GSK, Lundbeck Canada Inc., Merck Canada Inc., Novartis Canada Inc., Pfizer Canada Inc., Sanofi, and ZS Associates.

CMRO peer reviewers on this manuscript have no relevant financial or other relationships to disclose.