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Quality adjusted survival analysis: A neglected application of the quality of well-being scale
Authors:Robert M. Kaplan PH.D  J. Allen McCutchan M.D  Ana M. Navarro PH.D.  John P. Anderson PH.D.  J. Hampton Atkinson M.D.  James Chandler M.D.
Affiliation:HIV Neurobehavioral Research Center [HNRC] group is affiliated with the University of California, San Diego, the Naval Hospital, San Diego, and the San Diego VA Medical Center
Abstract:Abstract

Background In survival analysis, those who are alive are statistically coded as 1.0 while those who are dead are coded as 0.0. Since everyone who remains alive is given the same score, a person confined to bed with an irreversible coma is alive and is counted the same as someone who is active and asymtomatic. The Quality of Well-being (QWB) scale defines levels of wellness on the continuum between death and optimum function and integrates morbidity and mortality into the same number. This paper demonstrates the effect of including mortality in QWB estimates for male adults with HIV infection.

Method This study involves follow-up of a cohort of 386 male adults participating in the San Diego HIV Neurobehavioral Research Center (HNRC). Patients were evaluated using the QWB at enrollment and at six month intervals. All patients were classified into three stages of HIV disease according to the Center for Disease Control (CDC) classification: CDC IV (symptomatic HIV disease), CDC II or III (asymptomatic infection) and uninfected male controls.

Results QWB scores were calculated with and without mortality included for men in each CDC class who completed a one year (N = 148) or two year follow-up (N = 60). At each evaluation, there were significant differences among CDC classes and inclusion of deaths increased the variance accounted for by CDC class at each evaluation.

Conclusions HIV infection has significant impacts upon both morbidity and mortality. Survival analysis captures only the mortality dimension, while quality adjusted survival analysis using the QWB includes both dimensions. We propose quality adjusted survival analysis as a more sensitive method for assessing outcome in HIV disease and other health conditions.
Keywords:
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