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The usefulness of information on HDL-cholesterol: potential pitfalls of conventional assumptions

Overview of attention for article published in Trials, May 2001
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Title
The usefulness of information on HDL-cholesterol: potential pitfalls of conventional assumptions
Published in
Trials, May 2001
DOI 10.1186/cvm-2-3-107
Pubmed ID
Authors

Curt D Furberg

Abstract

Treatment decisions related to disease prevention are often based on two conventional and related assumptions. First, an intervention-induced change in a surrogate marker (such as high-density lipoprotein [HDL]-cholesterol) in the desired direction translates into health benefits (such as reduction in coronary events). Second, it is unimportant which interventions are used to alter surrogate markers, since an intervention benefit is independent of the means by which it is achieved. The scientific foundation for these assumptions has been questioned. In this commentary, the appropriateness of relying on low levels of HDL-cholesterol for treatment decisions is reviewed. The Veterans Affairs - HDL-Cholesterol Intervention Trial (VA-HIT) investigators recently reported that only 23% of the gemfibrozil-induced relative reduction in risk of coronary events observed in the trial could be explained by changes in HDL-cholesterol between baseline and the 1-year visit. Thus, 77% of the health benefit to the participants was unexplained. Other possible explanations are that gemfibrozil has multiple mechanisms of action, disease manifestations are multifactorial, and laboratory measurements of HDL-cholesterol are imprecise. The wisdom of relying on levels and changes in surrogate markers such as HDL-cholesterol to make decisions about treatment choices should questioned. It seems better to rely on direct evidence of health benefits and to prescribe specific interventions that have been shown to reduce mortality and morbidity. Since extrapolations based on surrogate markers may not be in patients' best interest, the practice of medicine ought to be evidence-based.

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Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 50%
Researcher 1 50%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 1 50%
Agricultural and Biological Sciences 1 50%