PLoS Medicine (Jul 2021)

Detection of significant antiviral drug effects on COVID-19 with reasonable sample sizes in randomized controlled trials: A modeling study.

  • Shoya Iwanami,
  • Keisuke Ejima,
  • Kwang Su Kim,
  • Koji Noshita,
  • Yasuhisa Fujita,
  • Taiga Miyazaki,
  • Shigeru Kohno,
  • Yoshitsugu Miyazaki,
  • Shimpei Morimoto,
  • Shinji Nakaoka,
  • Yoshiki Koizumi,
  • Yusuke Asai,
  • Kazuyuki Aihara,
  • Koichi Watashi,
  • Robin N Thompson,
  • Kenji Shibuya,
  • Katsuhito Fujiu,
  • Alan S Perelson,
  • Shingo Iwami,
  • Takaji Wakita

DOI
https://doi.org/10.1371/journal.pmed.1003660
Journal volume & issue
Vol. 18, no. 7
p. e1003660

Abstract

Read online

BackgroundDevelopment of an effective antiviral drug for Coronavirus Disease 2019 (COVID-19) is a global health priority. Although several candidate drugs have been identified through in vitro and in vivo models, consistent and compelling evidence from clinical studies is limited. The lack of evidence from clinical trials may stem in part from the imperfect design of the trials. We investigated how clinical trials for antivirals need to be designed, especially focusing on the sample size in randomized controlled trials.Methods and findingsA modeling study was conducted to help understand the reasons behind inconsistent clinical trial findings and to design better clinical trials. We first analyzed longitudinal viral load data for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) without antiviral treatment by use of a within-host virus dynamics model. The fitted viral load was categorized into 3 different groups by a clustering approach. Comparison of the estimated parameters showed that the 3 distinct groups were characterized by different virus decay rates (p-value ConclusionsIn this study, we found that estimated association in observational studies can be biased due to large heterogeneity in viral dynamics among infected individuals, and statistically significant effect in randomized controlled trials may be difficult to be detected due to small sample size. The sample size can be dramatically reduced by recruiting patients immediately after developing symptoms. We believe this is the first study investigated the study design of clinical trials for antiviral treatment using the viral dynamics model.