Natalie Hanson, Ph.D.

Sex-disaggregated research data remains a critical gap in women’s health

Only 25% Of Trials Address Female Differences

Today, only about 25% of clinical trials actually perform and report sex- and gender-based analyses – these are formal checks on whether outcomes differ between women and men. In majority of clinical trials, researchers never fully analyze whether the treatment behaves differently in male and female bodies, even when both are included as participants.

Why is that important? Imagine testing a new car safety system on a group of people, then declaring it safe for everyone without ever checking whether it works for people of different heights, weights, or body shapes. That is essentially what we do with many drugs and medical devices.

The first hurdle is (and remains) getting women into clinical trials. We do have better representation than we used to; women now make up close to half of participants overall for drug trial. But representation is not the same as understanding. If we do not break the data down by sex, we still have crucial gaps.

This post is about why that seemingly technical step – what the industry calls sex-disaggregating research data – is one of the most important and still overlooked steps that creates ongoing barriers to our understanding of women’s bodies.

What “Sex‑Disaggregated” Actually Means

Sex-disaggregated analysis sounds like jargon, but the core idea is simple – don’t blend everything together.

In a typical randomized trial, researchers compare an intervention group (for example, people getting a new drug) to a control group (people getting standard treatment or placebo) and look at outcomes like “Did they live longer?” or “Did their blood pressure improve?”.

A sex-disaggregated approach adds three basic steps:

1. Count who is in the trial, by sex. Report how many women and men took part, not just overall totals.
2. Report the main outcomes separately for women and for men such as survival curves, side-effect rates, or response rates by sex.
3. Test whether the differences are real, not random. Use standard statistical methods to ask whether the treatment effect differs meaningfully between women and men.

When trials do this, they sometimes see that the benefit is similar across sexes. But in other cases, they find important differences in who responds, at what dose, and with what risks. Without sex-disaggregated analysis, those insights remain invisible.

Making these changes doesn’t have to be a major disruption to clinical trial execution. Design and statistical analysis of trial data can support sex-specific analyses with careful planning, and modest increases in sample size.

Progress Is Real, Even If Incomplete

I’ve committed to sharing good news in this post, so I will say that – while change is slow – there are some signs of progress. Over the past few decades, a combination of policy, advocacy, and scientific pressure has changed the landscape in positive ways.

Some of the key shifts:

• Regulatory mandates. In the United States, legislation and guidance from agencies like the NIH and FDA have pushed sponsors to improve representation by sex and to be more transparent about sex-specific data. More recently, draft FDA guidance has affirmed the need for “representative enrollment” and signaled that inadequate sex representation could even trigger regulatory delays or demands.
• Better representation in trials. For drugs approved since 2014, the average share of female participants in the trials that supported approval sits around 51%, which is an improvement from earlier decades where participation was ~30%, though some therapeutic areas are still doing better than others.
• Expectations for sex-disaggregated reporting. International guidelines such as the SAGER (Sex and Gender Equity in Research) recommendations explicitly call for reporting outcomes by sex and gender in clinical research. Some journals like The Lancet now require sex/gender analysis or a justification for its absence, and Nature now associates proper SAGER analysis with research quality. While these guidelines have been widely endorsed, they aren’t strictly enforced – but pressure for researchers to comply continues to grow.
• Diverse research leadership matters. Studies in cardiology and heart failure trials suggest that when women are among the first or senior authors, trials are more likely to address sex differences in trial design and findings analysis. This underscores the value of diversity not only among participants, but also among the people designing and interpreting the research.

All of this progress sets the stage for the next step – moving from “we included women” to “we meaningfully analyzed outcomes by sex and gender as a matter of routine.” And that is the foundation we need to change innovation, care delivery, and health outcomes for women.