Depressive symptoms are the strongest predictors of short-term declines in health status in patients with heart failure.

OBJECTIVES: The purpose of this study was to assess whether depressive symptoms are independently associated with changes in heart failure (HF)-specific health status. BACKGROUND: Depression is common in patients with HF, but the impact of depressive symptoms on the health status of these patients over time is unknown. METHODS: We conducted a multicenter prospective cohort study of outpatients with HF. Data from 460 patients who completed a baseline Medical Outcomes Study-Depression Questionnaire and both a baseline and follow-up (6 +/- 2 weeks) Kansas City Cardiomyopathy Questionnaire (KCCQ) were analyzed. The KCCQ measures HF-specific health status, including symptoms, physical and social function, and quality of life. Multivariable regression was used to evaluate depressive symptoms as a predictor of change in KCCQ scores, adjusting for baseline KCCQ scores and other patient variables. The primary outcome was change in KCCQ summary scores (range 0 to 100; higher scores indicate better health status; 5 points is a clinically meaningful change). RESULTS: Approximately 30% (139/460) of the patients had significant depressive symptoms at baseline. Depressed patients had markedly lower baseline KCCQ summary scores (beta = -19.6; p < 0.001). After adjustment for potential confounders, depressed patients were at risk for significant worsening of their HF symptoms, physical and social function, and quality of life (average change in KCCQ summary score = -7.1 points; p < 0.001). Depressive symptoms were the strongest predictor of decline in health status in the multivariable models. CONCLUSIONS: Depressive symptoms are a strong predictor of short-term worsening of HF-specific health status. The recognition and treatment of depression may be an important component of HF care.

Design and analysis of unit cost estimation studies: How many hospital diagnoses? How many countries?

We evaluated three questions that commonly arise when unit costing exercises for multinational trials are conducted: (1). In countries where investigators plan to collect hospital unit cost estimates for a selected set of diagnoses, how should one estimate unit costs for the remaining diagnoses observed in the trial for which cost data were not collected? (2). For how many hospital diagnoses should estimates be obtained? (3). For how many countries should they be obtained? We addressed these questions using unit cost data collected in four western European countries and three relative value measures from the US Medicare diagnosis-related group (DRG) payment system. We found that the arithmetic mean length of stay from the US DRG payment system was a good predictor of unit costs in four countries in Europe. We also found that the imputation error decreased as the number of hospital diagnoses and countries sampled increased, but that the rate of reduction in error shrank. Finally, we found that - given the existence of a reliable method for cost imputation - from a pure information standpoint, it is better to obtain estimates for fewer hospital diagnoses from more countries than the reverse.

Economic evaluation of the randomized aldactone evaluation study (RALES): treatment of patients with severe heart failure.

PURPOSE: To use data from the Randomized Aldactone Evaluation Study (RALES) to compare clinical outcomes and costs as part of the assessment of the economic implications of spironolactone treatment of advanced heart failure. METHODS: RALES was a randomized, double-blinded, placebo-controlled trial that enrolled participants who had severe heart failure and a left ventricular ejection fraction of no more than 35% and who were receiving standard therapy, including an angiotensin-converting enzyme inhibitor, a loop diuretic, and, in some cases, digoxin. We used a decision analytic model that incorporated data from participants in RALES as well as cost data from five countries that participated in the study. Costs were calculated for nonfatal hospitalizations, ambulatory care, spironolactone therapy, and death. The primary health outcome was quality-adjusted life-years saved (QALYS). Outcomes were evaluated for the first 35 months of observation in RALES. RESULTS: Spironolactone therapy during the first 35 months of follow-up in RALES increased quality-adjusted survival time (0.13 QALYS, 95% CI, 0.07 to 0.18) without increasing costs ($713 savings, 95% CI, $2,123 savings to $783 in costs). Spironolactone therapy either dominated placebo or had a ratio of cost per QALYS that was unlikely to exceed $20,300. These results were robust in both one-way and multiway sensitivity analyses. CONCLUSIONS: Even after implementation of current clinical guidelines, addition of spironolactone therapy provides an opportunity to further reduce the large clinical and economic burden of patients with heart failure.

Cost and cost-effectiveness studies in heart failure research.

BACKGROUND: Heart failure is a major and increasing cause of death and disability and accounts for significant resource use. In the United States alone, the prevalence is 4.6 million, with an incidence rate of 550,000 new cases a year and approximately 957,000 hospitalizations a year. METHODS AND RESULTS: Methods of evaluating cost and outcome and of comparing cost with outcome are reviewed. Economic and cost-effectiveness studies in heart failure research, especially those related to clinical trials, are reviewed in the therapeutic areas of digoxin, angiotension-converting enzyme inhibition, beta blockers, disease management, and transplantation. CONCLUSION: In an era in which economic constraints on medical resource use limit the ability to give all services to all patients, economic studies can help guide more rational decision making. Economic studies in heart failure can be expected to improve and so help society to make better, more informed choices.