Clinical trials using HIV-1 RNA-based primary endpoints: statistical analysis and potential biases.

Important note: Information in this article was accurate in 1999. The state of the art may have changed since the publication date.

Clinical trials using HIV-1 RNA-based primary endpoints: statistical analysis and potential biases.

J Acquir Immune Defic Syndr Hum Retrovirol. 1999 Mar 1;20(3):220-7. Unique Identifier : AIDSLINE MED/99174787
Marschner IC; Betensky RA; DeGruttola V; Hammer SM; Kuritzkes DR; Center for Biostatistics in AIDS Research and Department of; Biostatistics, Harvard School of Public Health, Boston,; Massachusetts 02115, USA.

Abstract: Clinical trial endpoints based on magnitude of reduction in HIV-1 RNA levels provide an important complement to endpoints based on percentage of patients achieving complete virologic suppression. However, interpretation of magnitude of reduction can be biased by measurement limitations of virologic assays, particularly lower and upper limits of quantification. Using data from two AIDS Clinical Trials Group (ACTG) studies, widely used crude methods of analyzing HIV-1 RNA reductions were compared with methods that take into account censoring of HIV-1 RNA measurements. Such methods include Kaplan-Meier and censored regression analyses. It was found that standard crude methods of analysis consistently underestimated treatment effects. In some cases, the bias induced by crude methods masked statistically significant differences between treatment arms. Although statistically significant, adjustment for baseline HIV-1 RNA levels had little effect on estimated treatment differences. Furthermore, convenient parametric analyses performed as well as more complex nonparametric analyses. It is concluded that conveniently implemented censored data analyses should be conducted in preference to widely used crude analyses of magnitude of HIV-1 RNA reduction. To obtain complete information about virologic response to antiretroviral therapy, such analyses of magnitude of virologic response should be used to complement analyses of the percentage of patients having complete virologic suppression.

Keywords: JOURNAL ARTICLE Bias (Epidemiology) *Clinical Trials Data Interpretation, Statistical Human HIV Infections/*DRUG THERAPY/EPIDEMIOLOGY/*VIROLOGY HIV-1/*GENETICS *Outcome and Process Assessment (Health Care) RNA, Viral/*ANALYSIS Support, U.S. Gov't, P.H.S.
990630
A9960981

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