SCISIPBIO: Maximizing the Value of Sex-Inclusive Research Policies through Analytical Rigor

Arkansas Childrens Hospital Research Institute, Little Rock AR

Investigators

Abstract

Historically, preclinical research has focused disproportionately on males. This bias has limited the progress of science to advance national health and welfare. In 2016, to encourage inclusion of both males and females in research, the National Institutes of Health implemented a policy requiring the consideration of sex as a biological variable (SABV) in all funded studies. Although inclusion of females in research has improved, sex-based data are often not being analyzed using rigorous approaches. Our preliminary analysis of SABV-compliant studies showed that when authors report sex-specific effects, they tested statistically for such effects only 29% of the time. Instead, claims of sex-specific findings typically rest on assertion alone. Our previous findings indicate clearly that the implementation of SABV has not been rigorous and that the process of peer review of SABV-compliant research needs to improve. False claims of sex differences can lead to the wasting of resources on ‘differences’ that do not exist, and to inequities in access to effective treatments. Similarly, false claims of non-differences can lead to missed opportunities to provide effective health care for people of all sexes and genders. The intended goals of SABV, namely to enhance reproducibility and to facilitate sex-based precision medicine, are not being met. In this project we will determine the impact of inappropriate analytical approaches on the accurate reporting of sex-specific effects, identify factors that inform decisions about analytical approaches to sex-based data, and disseminate tools for designing and evaluating studies that consider SABV. We will use a mixed method approach that includes analyses of published journal articles, interviews with scientists, and outreach. We will conduct a large-scale analysis of the biomedical literature to show how inappropriate statistical approaches to sex-based data are impacting the rigorous implementation of SABV. Second, we will conduct semi-structured interviews with authors of some of those publications to identify the factors that facilitate best practices. Together, these methods will inform the development of a workflow for appropriate analysis of sex-based data. Third, we will make our optimized workflow publicly available and disseminate it widely. In addition, we will partner with journal editors to develop a simple tool that can be used by reviewers to evaluate the validity of sex-specific findings. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.