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Am J Epidemiol. 2009 Feb 15;169(4):515-21. doi: 10.1093/aje/kwn345. Epub 2008 Dec 18.

A little bit pregnant: modeling how the accurate detection of pregnancy can improve HIV prevention trials.

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  • 1Department of Obstetrics and Gynecology, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA. cschreiber@obgyn.upenn.edu

Abstract

The prevalence of unplanned pregnancies contributes to the methodological challenges of human immunodeficiency virus (HIV) prevention trials. In this paper, the authors discuss the incidence of pregnancy, including chemical pregnancy, and how the different methods of pregnancy diagnosis could affect the statistical power and calculated outcomes of HIV prevention trials. Study sample size inflation factors are estimated to aid in the design of clinical trials.The authors used published data of women attempting pregnancy as well as data from HPTN 055 (www.HPTN.org/research_studies/hptn055.asp) to estimate the percentage of early study discontinuation that would be associated with 3 diagnostic methods for pregnancy in a hypothetical clinical trial. They classified chemical pregnancies as false-positive pregnancy tests and showed the sample size adjustment that would be necessary in clinical trial design because of the early discontinuations associated with pregnancy. There is a greater than 3-fold difference in the number of falsely positive pregnancy tests that will be detected, depending upon the diagnostic method used. The number of incident pregnancies may render HIV prevention trial sample sizes inadequate by as much as 50%. Pregnancy prevention and precise pregnancy diagnosis are critical to the statistical power and integrity of HIV prevention trials.

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