Journal
ARCHIVES OF INTERNAL MEDICINE
Volume 170, Issue 12, Pages 1037-1044Publisher
AMER MEDICAL ASSOC
DOI: 10.1001/archinternmed.2010.150
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Funding
- VA Health Services Research and Development Service [IIR 06-253]
- National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health [P60 DK-20572]
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Background: Lowering low-density lipoprotein cholesterol (LDL-C) and blood pressure (BP) in patients with diabetes mellitus (DM) can significantly reduce the risk of cardiovascular disease (CVD). However, to our knowledge, previous studies have not assessed variability in both the benefit and harm from pursuing LDL-C and BP target levels. Methods: Our sample comprised individuals 30 to 75 years old with DM participating in the National Health and Nutrition Examination Survey III. We used Monte Carlo methods to simulate a treat-to-target strategy, in which patients underwent treatment intensification with the goal of achieving LDL-C and BP target levels of 100 mg/dL and 130/80 mm Hg, respectively. Patients received up to 5 titrations of statin therapy and 8 titrations of antihypertensive therapy. Treatment adverse effects and polypharmacy risks and burdens were incorporated using disutilities. Health outcomes were simulated using a Markov model. Results: Treating to targets resulted in gains of 1.50 (for LDL-C) and 1.35 (for BP) quality-adjusted life-years (QALYs) of lifetime treatment-related benefit, which declined to 1.42 and 1.16 QALYs after accounting for treatment-related harms. 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. However, because of treatment-related disutility, intensifying beyond the first step (LDL-C) or third step (BP) resulted in either limited benefit or net harm for patients with below-average risk. Conclusion: The benefits and harms from aggressive risk factor modification vary widely across the US population of individuals with DM, depending on a patient's underlying CVD risk, suggesting that a personalized approach could maximize a patient's net benefit from treatment.
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