Aggressively reducing cardiac risk factors may not prove to be beneficial for patients with diabetes and in fact, may even harm them, suggests a mathematical model in a recent report.
Almost all treatment guidelines for patients with diabetes suggest aggressively treating high low-density lipoprotein (LDL or "bad" cholesterol) and blood pressure levels to reduce patients' risk of developing heart disease, according to background information in the article. "These recommendations, which are based on the average results of trials evaluating the relative benefits of intensive risk factor control, are not tailored to an individual's underlying cardiovascular disease risk," the authors write. "While this [risk stratification] approach is often advocated in patients without diabetes mellitus, there is an implicit assumption that all patients with diabetes mellitus are at equally high risk, requiring all patients to be treated aggressively."
AdvertisementJustin W. Timbie, Ph.D., of RAND Corp., Arlington, Va., and colleagues constructed a mathematical model to assess whether aggressive treatment would equally benefit all patients with diabetes. They began with data from 30- to 75-year-old participants in the National Health and Nutrition Examination Survey, which provided representative estimates for the nearly 8 million individuals with diabetes in the 1990s. At this time, aggressive cholesterol and blood pressure treatment was uncommon. After excluding participants with low LDL levels and low blood pressure, the average LDL-C level was 151 milligrams per deciliter and the average blood pressure was 144/79 millimeters of mercury.
The researchers then simulated what would happen if these patients underwent increasingly intensive treatment until their LDL-C levels were lowered to 100 milligrams per deciliter and their blood pressure to 130/80 millimeters of mercury. Treating to these targets resulted in estimated gains of 1.5 quality-adjusted life years—years of life in perfect health—for LDL-C levels and 1.35 for blood pressure. These gains declined to 1.42 quality-adjusted life years for LDL-C and to 1.16 for blood pressure after considering treatment-related harms, which include muscle pain from taking statins and the safety hazards of taking multiple medications.
"Most of the total benefit was limited to the first few steps of medication intensification or to tight control for a limited group of very high-risk patients," the authors write. The nearly three-fourths of patients at average risk, however, received very little benefit. "By accounting for treatment-related harms, we identified numerous examples in which intensifying treatment would be contraindicated on the basis of risk-benefit considerations, and many more instances in which the expected benefits would be so small that shared patient-clinician decision making would seem to be the appropriate medical intervention."
"Given the large set of factors that moderate the benefit of treatment intensification, including patients' underlying cardiovascular disease risk, the diminishing efficacy of combination therapy and increasing polypharmacy and adverse effects, we recommend a strategy of tailoring treatments to individual patients on the basis of their expected benefit of intensifying treatment," they conclude. "Current treatment approaches that encourage uniformly lowering risk factors to common target levels can be both inefficient and cause unnecessary harm."(Arch Intern Med. 2010;170:1037-1044. Available pre-embargo to the media at www.jamamedia.org.)
Editor's Note: This work was supported in part by the VA Health Services Research and Development Service and by the Measurement Core of the Michigan Diabetes Research and Training Center. Please see the article for additional information, including other authors, author contributions and affiliations, financial disclosures, funding and support, etc.
Editorial: Models Illuminate Complexity of Clinical Decisions
"Like all models, this one involves numerous assumptions, mysterious concepts, such as disutility and discounting, and statistical approaches unfamiliar to many physicians," writes Andrew L. Avins, M.D., M.P.H., of Northern California Kaiser Permanente Division of Research, Oakland, in an accompanying editorial. "And, like all models, there are assumptions that could be disputed (e.g., specific treatment strategies and baseline estimates of some parameters). However, the lessons to be gleaned from this simulation are profound."
"Most important, the results starkly challenge some fundamental assertions regarding the appropriate treatment of patients with diabetes mellitus," Dr. Avins writes. "Over the years, practice guidelines have advocated increasingly tighter control of blood glucose and cardiovascular risk factors, often relying on logical inference to extend thresholds beyond the available empirical evidence. The model developed by Timbie et al suggests that the diminishing returns of more aggressive therapy might not only be inefficient but potentially harmful."
"The principles illustrated by the model of Timbie et al are general and apply to virtually all preventive interventions," Dr. Avins concludes. "One wonders why such examinations are not generally incorporated into the guideline development process rather than, as in this case, conducted in response to it."(Arch Intern Med. 2010;170:1013-1014. Available pre-embargo to the media at www.jamamedia.org.)
Editor's Note: Dr. Avins was the principal investigator for an observational study of the hepatotoxicity of lovastatin, funded by Merck & Co. Inc, during the period April 2004 to December 2006, for which he received salary support in excess of $10,000. Please see the article for additional information, including author contributions and affiliations, financial disclosures, funding and support, etc.
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