Article

# Noninferiority trial designs for odds ratios and risk differences.

Department of Epidemiology & Biostatistics, University of California San Francisco, 185 Berry Street, Suite 5700, San Francisco, CA 94107-1762, U.S.A..

Statistics in Medicine (Impact Factor: 2.04). 02/2010; 29(9):982-93. DOI: 10.1002/sim.3846 Source: PubMed

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**ABSTRACT:**Since the introduction of protease inhibitors and their combination with two nucleoside reverse transcriptase inhibitors in tri-therapy, there has been a continuous improvement in the efficacy of antiretroviral treatments. Such combinations have been rendered even more effective by the introduction of non-nucleoside reverse transcriptase inhibitors and, more recently, integrase inhibitors. This progress has led to a move away from superiority designs towards noninferiority designs for randomized clinical trials for HIV. Noninferiority trials aim to demonstrate that a new regimen is no worse than the current standard. The methodological issues associated with such designs have been discussed, but recent HIV trials provide us with an opportunity to consider the choice of hypotheses. Recent HIV trials have been overpowered, due to the assumption of lower success rates than observed and the enrollment of a large number of patients. The use of stratified statistical methods for primary endpoint analysis, with sample size calculated by classical methods (without stratification), also increases the statistical power. Some HIV trials have a statistical power close to 99%. Surprisingly, the results of some previous studies or phase II trials are not taken into account when designing the corresponding phase III trials. We discuss alternative hypotheses and designs.AIDS (London, England) 06/2014; · 6.56 Impact Factor - Future Virology 11/2012; 7(11):1055-1063. · 1.00 Impact Factor

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