Introduction: The COVID-19 pandemic has prompted researchers to conduct non-randomized studies in an effort to find an off-label drug that can effectively combat the virus and its effects. While these studies can expedite the drug approval process, researchers must carefully design and analyze such studies in order to perform rigorous science that is reproducible and credible. This article focuses on several key design and analysis considerations that can improve the scientific rigor of non-randomized studies of off-label drugs. Areas covered: The aim of this article is to provide an overview of best approaches that should be considered for non-randomized studies on off-label drugs. We discuss these approaches in detail and use a non-randomized study by Rivera et al. in Cancer Discovery as an example of methods that have been undertaken for COVID-19. Expert opinion: While non-randomized studies are inherently biased, they may be unavoidable in situations such as the COVID-19 pandemic, where researchers need to find an effective treatment quickly. We believe that a well-formed experimental design, high-quality data collection, and a well-thought-out statistical and data analysis plan are sufficient to produce rigorous and credible results for making an optimal decision.
All Science Journal Classification (ASJC) codes
- Pharmacology (medical)