Ignoring and conflating sex and gender in cardiovascular research limits the application of evidence-based interventions

This invited commentary refers to ‘Effectiveness of patient decision aids for cardiovascular decisions: systematic review with sex/gender-based analysis’, by K.B. Lewis et al., https://doi.org/10.1093/eurjcn/zvaf103. Until early in the 1900’s interventional research participation was mainly limited to men. Currently there continues to be a sex and gender mismatch between populations and research. Which includes historical and landmark cardiovascular studies limited to men, the absence of sex-disaggregated data, and limited use of biological variables. Research shortfalls continue despite evidence that both sex and gender impact outcomes.1 Lewis et al.2 presented a systematic literature review on the effectiveness of cardiovascular patient decision aids between people who were given decision aids and those who were not. Their meta-analysis of 32 trials captured attributes of decision quality and decision-making processes as primary outcomes. They found no differences between groups on decision quality. People exposed to patient decision making aids had significant improvements on decision-making process outcomes (greater knowledge, accurate risk perceptions, feeling more informed, clearer values, and less clinician-controlled decision-making). Secondary outcomes assessed sex and gender considerations within those studies. Unfortunately, while all studies reported sex or gender, less than half used appropriate terms consistently. 53% of studies did not report on methods used to determine sex or gender. Reporting sex or gender analysis was sub-optimal, with 22% of studies using sex or gender as variable in multivariable regressions relating to decision quality and decision-making processes. Only 18% of studies discussed the influence of sex or gender on findings. They concluded that patient decision making aids for cardiovascular-related prevention, screening and treatment decisions were superior to usual care. Yet, the consideration of sex or gender in included studies was poor. Both sex and gender impact decision-making. Lewis et al. provided multiple examples as to how sex alters cardiovascular risks, outcomes, and treatment decisions.1 Several factors differ by biologic sex including risk-tolerance, attending to symptoms, and the systematic bias of healthcare. For instance, compared to males, females are less risk-tolerant in making health related decisions.3 Compared to males and females, intersex people more often experience providers with poor understanding of their unique needs and more discrimination that can carry over to the information they receive to make decisions.4–6 Regarding gender, women more often than men prioritize emotional and social implications of decisions and consider empathy of providers.3 Evidence shows that people who do not identify as men or women experience more discrimination and access healthcare less. They are more likely to have more unmet health needs, and experience depression and anxiety than men or women, with little known about decision-making in specific gender diverse groups.7 Unfortunately, even the supporting information provided here may not be accurate, with errors in reporting sex and gender in the supporting literature. It is imperative to note that sex and gender are just one set of indicators impacting decision-making, and overlapping disadvantages amplify issues related to social status.4 Lewis et al,1 performed a robust systematic review summarizing the existing evidence on cardiovascular patient decision making aids, but their ability to report on sex and gender implications of these interventions was hampered by the lack of appropriate terms, inclusion, and sex and gender disaggregated data. Important to the context of their findings, we must consider that repeated calls for more inclusive cardiovascular research have yet to be actioned. The reporting of sex or gender within abstracts and titles remains limited.8 Despite the urgent call for increased research focus on non-male cardiovascular illness factors, treatments, and decision-making in 2010 by the EuroHeart project, inclusion to research for non-males/men remains low.9 A scoping review focusing on the participation of the female sex in cardiovascular research trials, identified that out of 10 trials only 3 had female inclusion rates of 50% or higher.10 Recent guideline altering pharmaceutical heart failure trials on Sodium-glucose co-transporter-2 inhibitors, only identified 35.7% participants as female.11 How are cardiovascular patient decision making aids which are specific to sex and gender risks, treatments, and outcomes to be created without the adequate evidence? Sex and Gender Equity in Research (SAGER) Guidelines12 comprehensively provides the ‘how to’ in reporting sex and gender information within research studies. These guidelines highlight the appropriate use of the terms sex and gender, call for research in all organisms (able to differentiate by sex) to be conducted and reported to enable sex-related differences in the results, and the differentiation of subjects by gender should be enabled.13 Sex and gender are important consideration to health and decision making. It is critical that we advance cardiovascular science with studies and interventions that consider both to decrease health inequalities. There are broad differences in biologic, roles, identities, and behaviours that are influenced by sex and gender. To create optimal interventions for a diverse population there is a pressing need to identify diverse needs, use research methodology as defined by SAGAR, and careful design of interventions responsive to these findings. Rosalynn C Austin (Ph.D. BN MSc BSc (Conceptualization [equal]; Investigation [supporting]; Writing—original draft [lead]; Writing—review & editing [equal])) and Kelly L Wierenga (PhD (Conceptualization [equal]; Investigation [lead]; Writing—original draft [supporting]; Writing—review & editing [equal])) There is no funding for this work. This commentary does not contain new data.