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• W2025674014 abstract "OBJECTIVES: Cost-effectiveness analysis requires estimating gains in life expectancy from effective treatments. Survival is not an endpoint in many clinical trials, because of limited follow-up intervals or statistical power. If databases linking survival to the surrogate markers used in the trials are not available, fragmentary published data based on follow-up studies may suffice. This workshop illustrates methods for using limited published data to estimate life expectancy gains. Participants will be encouraged to share their own experiences in modeling life expectancy.PARTICIPANTS WHO WOULD BENEFIT: Analysts who want to estimate cost-effectiveness based on limited published data.This workshop illustrates methods for using limited published data to estimate life expectancy gains. The example concerns AIDS wasting, in which patients with HIV infection experience significant weight loss. Treatments such as human growth hormone (HGH) and anabolic steroids have been found effective in retarding weight loss or even restoring body weight in patients with AIDS wasting. Published survival curves stratified by weight change from baseline (in ranges such as −10% to −5%) and CD4 cell count were found in the literature. A clinical trial of HGH reported means and standard deviations of weight change from baseline with drug and with placebo. Our task was to use these data to estimate the life expectancy gain with HGH in patients stratified by CD4 cell count. The presenters will demonstrate the following analytic steps: (1) estimating probability distributions of weight change from the clinical trial and using these to estimate the probability that patients would experience each range of weight change; (2) estimating areas under the published survival curves to estimate truncated life expectancies by range of weight change; (3) using the DEALE method to extrapolate survival and life expectancy beyond the trial follow-up period; (4) combining steps (1)-(3) to estimate the gain in life expectancy attributable to treatment; and (5) applying discounting to the survival analysis and life expectancy calculations. As with all life expectancy estimates mediated by surrogate markers, there is no “proof” that weight change caused by treatment will translate into life expectancy gains. In the absence of direct evidence of a survival benefit, however, these methods can be used to estimate potential life expectancy gains." @default.
• W2025674014 created "2016-06-24" @default.
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• W2025674014 date "2001-09-01" @default.
• W2025674014 modified "2023-09-30" @default.
• W2025674014 title "WW5: CREATIVE APPROACHES TO MODELING LIFE EXPECTANCY GAINS FOR ECONOMIC EVALUATION USING PUBLISHED DATA" @default.
• W2025674014 doi "https://doi.org/10.1046/j.1524-4733.2001.40203-4.x" @default.
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