The sex disparity in COVID-19 mortality varies widely and is of uncertain origin. In their recent Article, Takahashi et al. 1 assess immune phenotype in a sample of patients with COVID-19 and conclude that the “immune landscape in COVID-19 patients is considerably different between the sexes”, warranting different vaccine and therapeutic regimes for men and women—a claim that was disseminated widely following the publication 2. Here we argue that these inferences are not supported by their findings and that the study does not demonstrate that biological sex explains COVID-19 outcomes among patients. The study overstates its findings and factors beyond innate sex are treated superficially in analysing the causes of gender or sex disparities in COVID-19 disease outcomes. Takahashi et al. measured more than 100 immune markers in a sample of patients with COVID-19 and uninfected healthcare workers (HCW). They compared male and female patients and HCW both at baseline and longitudinally over the disease course. These comparative analyses, both within sex and between sex, across patients and HCW, at baseline and over time, yielded more than 500 findings 1. Most of the findings in the paper are presented as raw data, unadjusted for possible covariates. Among the more than 200 findings from adjusted analyses, 13 (6%) remained statistically significant after controlling for covariates (primarily age and body mass index (BMI)). This count excludes analyses on antibodies and viral load, as well as comparisons of female HCW (F_HCW) versus male HCW (M_HCW), female patients (F_Pt) versus female HCW and male patients (M_Pt) versus male HCW. There is considerable mismatch between the claims made in the paper and the results presented in the data tables, making it challenging to understand the basis of many of these claims. The discussion section focuses on claims related to ten immune markers, positing a variety of sex differences across diverse analyses (reconstructed in Table 1). The expanded data tables demonstrate that nine of these claims are based on raw data and do not hold true in adjusted analyses. For example, interleukin-18 (IL-18) and IL-8, emphasized in the abstract and discussion as higher in male patients, show a sex difference only in baseline-unadjusted analyses of the smaller cohort. This indicates that these reported sex differences in immunological response are better explained by factors other than biological sex. Similarly, attempting to address the potential role of these markers in disparate outcomes between men and women, Takahashi et al. associate lower levels of activated T cells at baseline with poorer outcomes among men, but not among women, in a subsample of 12 patients who deteriorated during the course of the disease (6 male and 6 female). However, as fig. 4 demonstrates, deteriorated male patients are older 1. After adjusting for age, there are no sex differences in activated T cells among the patient samples.

Although statistical significance is not the only consideration when evaluating study results, the authors use statistical significance to summarize their own results and imply that the central findings remain statistically significant after adjustment. Particularly considering the sweeping scope of the study’s conclusions, combined with the study’s limited sample size, large confidence intervals, few repeat measures for many participants in the longitudinal cohort, and lack of clinical discussion of effect sizes, statistical significance remains an important guidepost for contextualizing the study’s findings. Three findings that are described as sex differences 1 are actually differences within …