Estimation of expected quality adjusted survival by cross-sectional survey
Journal
Statistics in Medicine
Journal Volume
15
Journal Issue
1
Pages
93-102
Date Issued
1996
Author(s)
Abstract
To compare both mortality and quality of life (QOL) across different illnesses, we propose an estimator to calculate the expected quality adjusted survival (QAS) by multiplying the QOL into the survival function. While the survival function can be determined by the usual life table method, the QOL data can be collected by a cross-sectional survey among patients who are currently surviving. The area under the QAS curve is thus the expected utility of health of the specific illness, which may take a common unit of quality adjusted life year ready for outcome evaluation and policy decision. A simulation is performed to demonstrate that the proposed estimator and its standard error are relatively accurate. The limitations and guidelines for using this estimator are also discussed.
SDGs
Other Subjects
area under the curve; article; assay; human; information processing; life table; mortality; quality of life; survival; Bias (Epidemiology); Cross-Sectional Studies; Health Services Research; Humans; Life Tables; Mortality; Quality-Adjusted Life Years; Reproducibility of Results; Survival Analysis; Treatment Outcome
Type
journal article