Alexander Göhler

Utility estimates for decision-analytic modeling in chronic heart failure--health states based on New York Heart Association classes and number of rehospitalizations.

OBJECTIVES For economic evaluations of chronic heart failure (CHF) management strategies, utilities are not currently available for disease proxies commonly used in Markov models. Our objective was to estimate utilities for New York Heart Association (NYHA) classification and number of cardiovascular rehospitalizations. METHODS EuroQol 5D data from the Eplerenone Post-acute Myocardial Infarction Heart Failure Efficacy and Survival Study trial were used to estimate utilities as a function of NYHA classification and number of cardiovascular rehospitalizations. RESULTS In multivariate regression analyses adjusted for age (60 years), female sex and absence of further comorbidities, utilities for NYHA classes I-IV were 0.90, 0.83, 0.74, and 0.60 (P-value < 0.001 for trend). For cardiovascular rehospitalizations 0, 1, 2 and >or=3, the associated utilities were 0.88, 0.85, 0.84, and 0.82 (P-value < 0.001 for trend). CONCLUSIONS NYHA class and number of cardiovascular rehospitalizations are established proxies for CHF progression and can be linked to utilities when used as health states in a Markov model. NYHA class should be used when feasible.

Decision-analytic evaluation of the clinical effectiveness and cost-effectiveness of management programmes in chronic heart failure

While management programmes (MPs) for chronic heart failure (CHF) are clinically effective, their cost‐effectiveness remains uncertain. Thus, this study sought to determine the cost‐effectiveness of MPs.

Prognostic value, clinical effectiveness, and cost-effectiveness of high-sensitivity C-reactive protein as a marker for major cardiac events in asymptomatic individuals: A health technology assessment report

OBJECTIVES The aim of this study was to compare the predictive value, clinical effectiveness, and cost-effectiveness of high-sensitivity C-reactive protein (hs-CRP)-screening in addition to traditional risk factor screening in apparently healthy persons as a means of preventing coronary artery disease. METHODS AND RESULTS The systematic review was performed according to internationally recognized methods. Seven studies on risk prediction, one clinical decision-analytic modeling study, and three decision-analytic cost-effectiveness studies were included. The adjusted relative risk of high hs-CRP-level ranged from 0.7 to 2.47 (p < .05 in four of seven studies). Adding hs-CRP to the prediction models increased the areas under the curve by 0.00 to 0.027. Based on the clinical decision analysis, both individuals with elevated hs-CRP-levels and those with hyperlipidemia have a similar gain in life expectancy following statin therapy. One high-quality economic modeling study suggests favorable incremental cost-effectiveness ratios for persons with elevated hs-CRP and higher risk. However, many model parameters were based on limited evidence. CONCLUSIONS Adding hs-CRP to traditional risk factors improves risk prediction, but the clinical relevance and cost-effectiveness of this improvement remain unclear.

Prognostic value, clinical effectiveness and cost-effectiveness of high sensitivity C-reactive protein as a marker in primary prevention of major cardiac events.

Background In a substantial portion of patients (= 25%) with coronary heart disease (CHD), a myocardial infarction or sudden cardiac death without prior symptoms is the first manifestation of disease. The use of new risk predictors for CHD such as the high-sensitivity C-reactive Protein (hs-CRP) in addition to established risk factors could improve prediction of CHD. As a consequence of the altered risk assessment, modified preventive actions could reduce the number of cardiac death and non-fatal myocardial infarction. Research question Does the additional information gained through the measurement of hs-CRP in asymptomatic patients lead to a clinically relevant improvement in risk prediction as compared to risk prediction based on traditional risk factors and is this cost-effective? Methods A literature search of the electronic databases of the German Institute of Medical Documentation and Information (DIMDI) was conducted. Selection, data extraction, assessment of the study-quality and synthesis of information was conducted according to the methods of evidence-based medicine. Results Eight publications about predictive value, one publication on the clinical efficacy and three health-economic evaluations were included. In the seven study populations of the prediction studies, elevated CRP-levels were almost always associated with a higher risk of cardiovascular events and non-fatal myocardial infarctions or cardiac death and severe cardiovascular events. The effect estimates (odds ratio (OR), relative risk (RR), hazard ratio (HR)), once adjusted for traditional risk factors, demonstrated a moderate, independent association between hs-CRP and cardiac and cardiovascular events that fell in the range of 0.7 to 2.47. In six of the seven studies, a moderate increase in the area under the curve (AUC) could be detected by adding hs-CRP as a predictor to regression models in addition to established risk factors though in three cases this was not statistically significant. The difference [in the AUC] between the models with and without hs-CRP fell between 0.00 and 0.023 with a median of 0.003. A decision-analytic modeling study reported a gain in life-expectancy for those using statin therapy for populations with elevated hs-CRP levels and normal lipid levels as compared to statin therapy for those with elevated lipid levels (approximately 6.6 months gain in life-expectancy for 58 year olds). Two decision-analytic models (three publications) on cost-effectiveness reported incremental cost-effectiveness ratios between Euro 8,700 and 50,000 per life year gained for the German context and between 52,000 and 708,000 for the US context. The empirical input data for the model is highly uncertain. Conclusion No sufficient evidence is available to support the notion that hs-CRP-values should be measured during the global risk assessment for CAD or cardiovascular disease in addition to the traditional risk factors. The additional measurement of the hs-CRP-level increases the incremental predictive value of the risk prediction. It has not yet been clarified whether this increase is clinically relevant resulting in reduction of cardiovascular morbidity and mortality. For people with medium cardiovascular risk (5 to 20% in ten years) additional measurement of hs-CRP seems most likely to be clinical relevant to support the decision as to whether or not additional statin therapy should be initiated for primary prevention. Statin therapy can reduce the occurrence of cardiovascular events for asymptomatic individuals with normal lipid and elevated hs-CRP levels. However, this is not enough to provide evidence for a clinical benefit of hs-CRP-screening. The cost-effectiveness of general hs-CRP-screening as well as screening among only those with normal lipid levels remains unknown at present.

Deterministic Sensitivity Analysis for First-Order Monte Carlo Simulations: A Technical Note

OBJECTIVES Monte Carlo microsimulations have gained increasing popularity in decision-analytic modeling because they can incorporate discrete events. Although deterministic sensitivity analyses are essential for interpretation of results, it remains difficult to combine these alongside Monte Carlo simulations in standard modeling packages without enormous time investment. Our purpose was to facilitate one-way deterministic sensitivity analysis of TreeAge Markov state-transition models requiring first-order Monte Carlo simulations. METHODS AND RESULTS Using TreeAge Pro Suite 2007 and Microsoft Visual Basic for EXCEL, we constructed a generic script that enables one to perform automated deterministic one-way sensitivity analyses in EXCEL employing microsimulation models. In addition, we constructed a generic EXCEL-worksheet that allows for use of the script with little programming knowledge. CONCLUSIONS Linking TreeAge Pro Suite 2007 and Visual Basic enables the performance of deterministic sensitivity analyses of first-order Monte Carlo simulations. There are other potentially interesting applications for automated analysis.