Biomedical subjects

Ari Gnanasakthy

Publications and source records attributed to Ari Gnanasakthy.

4 recordsLinked to original sources

PubMed2005

Conducting economic evaluations alongside multinational clinical trials: toward a research consensus.

Demand for economic evaluations in multinational clinical trials is increasing, but there is little consensus about how such studies should be conducted and reported. At a workshop in Durham, North Carolina, we sought to identify areas of agreement about how the primary findings of economic evaluations in multinational clinical trials should be generated and presented. In this paper, we propose a framework for classifying multinational economic evaluations according to (a) the sources of an analyst's estimates of resource use and clinical effectiveness and (b) the analyst's method of estimating costs. We review existing studies in the cardiology literature in the context of the proposed framework. We then describe important methodological and practical considerations in conducting multinational economic evaluations and summarize the advantages and disadvantages of each approach. Finally, we describe opportunities for future research. Delineation of the various approaches to multinational economic evaluation may assist researchers, peer reviewers, journal editors, and decision makers in evaluating the strengths and limitations of particular studies.

Clinical Trials as Topic↗

PubMed2004

Multinational economic evaluation of valsartan in patients with chronic heart failure: results from the Valsartan Heart Failure Trial (Val-HeFT).

BACKGROUND: The Valsartan Heart Failure Trial (Val-HeFT) compared valsartan versus placebo in 5010 patients taking prescribed background therapy for New York Heart Association class II to IV heart failure. Valsartan reduced the risk of heart failure hospitalization and improved clinical signs and symptoms of heart failure. We sought to compare resource use, costs, and health outcomes among patients taking prescribed therapy for heart failure and randomly assigned to receive valsartan or placebo. METHODS: Measures of resource use were based on data collected during the trial. Unit cost estimates were collected from individual countries and converted to 1999 US dollars. Total costs were estimated for hospitalizations, inpatient and outpatient physician services, ambulance transportation, deaths outside the hospital, and outpatient cardiovascular medications. RESULTS: Mean follow-up was 23 months. Mean costs for heart failure hospitalizations were 423 dollars lower among patients receiving valsartan (95% CI, -706 to -146). Mean total costs were 9008 dollars for patients receiving valsartan and 8464 dollars for patients receiving placebo, a net incremental cost of 545 dollars (95% CI, -149 to 1148), including the cost of valsartan. There was an overall reduction in total costs of 929 dollars (95% CI, -3243 to 1533) among patients not receiving an ACE inhibitor at baseline but a slight increase in costs of 334 dollars (95% CI, -497 to 1199) among those receiving an ACE inhibitor without a beta-blocker and a 1246 dollars increase (95% CI, 54 to 2230) in patients receiving both an ACE inhibitor and a beta-blocker at baseline. CONCLUSIONS: Valsartan provided clinical benefits at a mean incremental cost of 285 dollars per year during the trial. In patients not taking ACE inhibitors, valsartan was economically attractive, increasing survival while reducing or marginally increasing overall costs.

Adrenergic beta-Antagonists↗

PubMed2003

Comparison of hospital costing methods in an economic evaluation of a multinational clinical trial.

OBJECTIVES: To develop and evaluate strategies for estimating hospitalization costs in multinational clinical trials. METHODS: Hospital cost estimates for eleven diagnoses were collected from twelve countries participating in a trial of therapies for congestive heart failure. Estimates were combined with U.S.-based diagnosis-related group weights to compute country-specific unit cost estimates for all reasons for hospitalization. Variations of hospital costing methods were developed. The unit cost method assigns a country-specific unit cost estimate to each hospitalization. The other methods adjust for length of stay using a daily cost (DC) estimate for each diagnosis, based on either the mean length of stay (DC-mean method) or the median length of stay (DC-median method) for each diagnosis in each country. Additional modifications were explored through adjustment of the distribution of daily costs incurred during a hospital stay. RESULTS: The mean cost for all hospitalizations was dollars 10,242 (SD, 10,042) using the unit cost method, dollars 10,242 (SD, 12,760) using the standard DC-mean method, and dollars 13,967 (SD, 18,762) using the standard DC-median method. In comparisons of costs for all 5,486 hospitalizations incurred by a subset of 2,352 patients in the trial, the unit cost method provided 92% power to detect a dollars 1,000 cost difference. The standard DC-mean method provided 76% power, and the standard DC-median method provided 44% power. CONCLUSIONS: Hospital costing methods that adjust for differences in length of stay require a significantly larger sample to attain comparable statistical power as methods that assign unadjusted unit cost estimates to hospitalization events.

Clinical Trials as Topic↗

PubMedDate not supplied

Using multiple anchor- and distribution-based estimates to evaluate clinically meaningful change on the Functional Assessment of Cancer Therapy-Biologic Response Modifiers (FACT-BRM) instrument.

OBJECTIVE: The interpretation of health-related quality of life (HRQL) data from clinical trials can be enhanced by understanding the degree of change in HRQL scores that is considered meaningful. Our objectives were to combine distribution-based and two anchor-based approaches to identify minimally important differences (MIDs) for the 27-item Trial Outcome Index (TOI), the seven-item Social Well-Being (SWB) subscale, and the six-item Emotional Well-being (EWB) subscale from the Functional Assessment of Cancer Therapy-Biological Response Modifiers (FACT-BRM) instrument. METHODS: Distribution-based MIDs were based on the standard error of measurement. Anchor-based approaches utilized patient-reported global rating of change (GRC) and change in physician-reported performance status rating (PSR). Correlations and weighted kappa statistics were used to assess association and agreement between the two anchors. FACT-BRM changes were evaluated for three time periods: baseline to month 1, month 2 to month 3, and month 5 to month 6. RESULTS: Association between GRC and change in PSR was poor. Correlation between the anchors and HRQL change scores was largest at month 1 and decreased through month 6. Combining results from all approaches, the MIDs identified were 5-8 points for the TOI, 2 points for the SWB subscale, and 2-3 points for the EWB subscale. CONCLUSIONS: We combined patient-reported estimates, physician-reported estimates, and distribution-based estimates to derive MIDs for HRQL outcomes from the FACT-BRM. These results will enable interpretation of treatment group effects in a clinical trial setting, and they can be used to estimate sample size or power when designing future studies.

Adolescent↗