Variability in Contraceptive Clinical Trial Design and the Challenges in Making Comparisons Across Trials

David Portman, David L. Eisenberg, Patty Cason, Brandon Howard

Research output: Contribution to journalComment/debate

Abstract

Clinical trials of contraceptives have often differed in their study designs, making cross-trial comparisons difficult. This brief report outlines some of the technical design features that can vary from trial to trial. For example, the overall number of menstrual cycles in a study has substantial impact on the final efficacy determination; however, the rules related to qualifying cycles can differ based on the length of the study and the statistical analysis plan. In two commonly used methods of calculating efficacy, the Pearl Index and the time-to-event analysis, inclusion of fewer menstrual cycles results in higher calculated failure rates. Statistical analysis plans for contraceptive trials have sometimes excluded menstrual cycles because of an absence of documented vaginal intercourse and the concomitant use of another birth control method. Other design features that have varied between contraceptive trials relate to body mass index inclusion/exclusion criteria and the definition of “on-treatment” pregnancy. In addition, study designs of non-hormonal products can differ from those of hormonal products in their length and rules for qualifying cycles. The Draft Guidance for Hormonal Contraception, published in 2019 by the US Food and Drug Administration (FDA), will hopefully lead to more uniform trial design in the future, particularly for hormonal products. In the meantime, health care providers and patients should be aware of the nuances in trial design that make direct comparisons about relative efficacy challenging.

Original languageEnglish
Pages (from-to)5425-5430
Number of pages6
JournalAdvances in Therapy
Volume38
Issue number11
DOIs
StatePublished - Nov 2021

Keywords

  • Contraception
  • Effectiveness
  • Efficacy determination
  • Life table analysis
  • Pearl Index
  • Study design
  • Time-to-event analysis

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