Sex Gaps in Trials: What the Data Show

What do sex gaps in trials actually mean for patients?

Sex gaps in trials mean that a medicine's effects were measured mostly — or sometimes entirely — in one sex, so the evidence base for the other sex is thinner, older, or missing. For peptide medicines specifically, that gap can affect how confidently a clinician interprets a label, chooses a dose, or monitors for side effects in a female patient.

Here is what the research actually shows about how those gaps form and what they leave behind.

Where the gaps come from

A 2025 systematic review examining FDA-approved drugs from 2015 to 2023 found that sex representation in trials frequently did not match the real-world disease burden carried by women. Women in this study's scope were underenrolled relative to how often they actually develop the conditions being treated. Trial data a prescriber reads may reflect a population that skews male, even when the drug will be prescribed equally — or more often — to female patients.

Trial leadership shapes trial design. A review of oral and maxillofacial surgery trials found gender disparities in who leads research, and leadership influences which outcomes get measured, which subgroups get analyzed, and which side effects get tracked. A trial that never asks a sex-stratified question cannot answer one.

What gaps leave behind

The label may report an overall average effect that blends male and female responses — and those responses can differ by biology, body composition, and hormonal environment. A meta-analysis of rheumatoid arthritis trials found that BMI influenced treatment response to JAK inhibitors, and BMI distributions differ by sex and life stage. When trials do not report sex-stratified subgroup data, that interaction stays invisible.

Underrepresentation compounds across groups. A systematic review of hypertension and diabetes trials found that women from historically underserved populations faced the steepest enrollment gaps — meaning the evidence base is thinnest precisely where clinical complexity is often highest.

What this means in practice

A gap in trial data is not proof that a medicine works differently in women — it is proof that the question was not fully tested. Those are different things. When a clinician says "the trial did not establish" an effect in female patients, that sentence describes a hole in the evidence, not a finding.

Patients can ask their prescriber directly: were women enrolled in the pivotal trials for this medicine, were results reported separately by sex, and does the label note any sex-specific findings? Those questions are answerable from public sources, and asking them is reasonable.

This content is for general health education only and is not medical advice. Consult a qualified healthcare provider before making any decisions about medicines or treatments.

Which disease areas show the largest enrollment gaps for women?

The largest sex gaps in trials appear in cardiovascular disease, PTSD, and certain cancers — disease areas where women carry a substantial share of the real-world burden but have been systematically enrolled at lower rates than men.

A 2024 analysis of FDA-approved drugs from 2015 to 2023 found that sex representation in trials frequently did not match the actual disease burden by sex for the approved indication (FDA drug trial sex representation). Women were underrepresented relative to how often they experience the condition being studied. That mismatch matters because a drug's labeled dose and expected effects are shaped by who was in the trial.

PTSD. Women are diagnosed with PTSD at roughly twice the rate of men in the general population, yet a systematic review of PTSD randomized clinical trials found enrollment patterns that did not reflect that real-world prevalence (PTSD trial sex differences). The review identified predictors of sex imbalance that researchers could use to design more representative studies.

Hypertension and diabetes. A systematic review and meta-analysis of trials conducted at Federally Qualified Health Centers found that women and historically underserved populations were underrepresented in hypertension and diabetes clinical trials, two of the most common chronic conditions affecting women across age groups (hypertension and diabetes trial representation).

Cancer. Strategies to improve enrollment of underrepresented groups in cancer trials — including women from specific racial and ethnic communities — remain an active area of research. Published work identifies "bright spot" sites that successfully increased participation, offering models for broader adoption (cancer trial underrepresentation).

Alzheimer's disease. Women make up the majority of people living with Alzheimer's, yet a call-to-action paper on atypical Alzheimer's variants noted that trial design has not consistently accounted for sex-based differences in disease presentation, which can affect who qualifies to enroll (atypical Alzheimer's trials).

Enrollment numbers alone don't capture trial leadership. An analysis of oral and maxillofacial surgery research found significant gender disparities among principal investigators — the people who design the questions a trial asks (trial leadership gender disparities). Who leads a trial shapes which outcomes get measured, which subgroups get analyzed, and which gaps get noticed.

The evidence base is still growing. Not every disease area has been audited for sex-based enrollment gaps, and the studies above vary in scope, time period, and methodology. Where data are missing, that absence is itself a gap worth naming.

This section is for general health education only and does not constitute medical advice. Consult a qualified healthcare provider about any treatment decision.

How does PTSD research illustrate the enrollment problem?

PTSD research shows sex gaps in trials with unusual clarity: women are diagnosed with PTSD at roughly twice the rate of men, yet clinical trials testing treatments have historically enrolled far more men than women, creating a mismatch between who gets the disease and who generates the evidence.

A 2025 analysis of PTSD randomized clinical trials examined enrollment patterns across decades of studies and found that trial design choices — not just participant availability — predicted how many women ended up in the data. Trials recruiting from military or veteran settings enrolled predominantly men, because those settings skew male. Trials recruiting from community mental health settings enrolled more women. The disease burden stayed the same. The setting changed the science.

This matters for anyone reading a PTSD treatment study. If a peptide or drug was tested mostly in male veterans, the dose-response data, the side-effect profile, and the definition of "response" all come from that group. Women in this study — or women absent from this study — may experience the treatment differently, and the trial simply cannot tell you how.

Three concrete problems follow from this pattern:

• Who counts as a responder. Symptom scales and outcome measures get validated on the populations that dominate trials. If women were underrepresented during validation, the scale may miss how women in this study actually report symptoms.
• Subgroup power. Even when women are enrolled, trials sized for a mostly-male sample often lack enough female participants to detect whether the treatment works differently by sex. The trial did not establish equivalence — it just lacked the numbers to find a difference.
• Generalization creep. Results get summarized in ways that erase the enrollment gap. A headline reads "treatment works for PTSD" when the data come from a population that was 80% male.

The PTSD enrollment analysis found that enrollment patterns shifted over time as funding agencies began requiring sex-disaggregated reporting — a sign that policy pressure can move the needle, even if the gap has not closed.

For women seeking evidence about any peptide medicine studied in a PTSD context, the first question to ask is not "did this work?" but "who was in the trial, and does that group resemble me in ways that matter biologically?"

This section is for general health education only and does not constitute medical advice. Consult a qualified clinician before making any treatment decisions.

Do community-based trial sites close the gap for women and underserved groups?

Community-based trial sites do close some sex gaps in trials, but the evidence shows the gains are uneven and depend heavily on disease area, site funding, and how "community-based" is defined. That caveat matters before anyone draws broad conclusions.

A systematic review and meta-analysis of hypertension and diabetes clinical trials conducted at Federally Qualified Health Centers (FQHCs) — clinics that receive federal funding specifically to serve low-income and underserved communities — found that women made up a majority of enrolled participants across those trials. This contrasts sharply with the broader FDA drug-approval record, where a 2015–2023 analysis found that sex representation in trials frequently did not match the actual disease burden women carry for many approved indications.

Community sites can shift enrollment. They do not automatically fix every gap.

Several structural factors shape whether a community site actually reaches underserved women:

• Trial design upstream of the site. A PTSD trial analysis found that enrollment sex ratios were predictable from design choices made before a single participant walked through the door — eligibility criteria, outcome measures, and recruitment language all filtered who could enroll.
• Who leads the research. A review of oral and maxillofacial surgery trials documented that women remain underrepresented in principal investigator roles, and leadership composition shapes which populations a team prioritizes and reaches.
• Active outreach versus passive access. A cancer trial "bright spots" analysis identified that sites achieving strong underrepresented-group enrollment shared specific practices — patient navigators, community health workers, and partnerships with trusted local organizations — rather than simply being located in a diverse neighborhood.

The FQHC review also noted that even when women enrolled in higher numbers, data were rarely disaggregated by race, ethnicity, age group, or reproductive status. A trial can look representative on one axis while remaining blind on others. Women in this study were counted; they were not always characterized in ways that make the results usable across different life stages or backgrounds.

Community-based sites are one piece of a larger structural problem. They work best when paired with inclusive eligibility criteria, diverse research leadership, and disaggregated reporting — none of which any single site controls alone.

This content is for general health education only and is not medical advice. Consult a qualified healthcare provider about any medical condition or treatment decision.

How does trial leadership affect who gets studied?

Who leads a trial shapes who gets studied. Sex gaps in trials shrink measurably when women hold principal investigator roles—and the research on trial leadership proves that connection.

A 2024 analysis of oral and maxillofacial surgery trials found that female principal investigators enrolled significantly more female participants than male-led trials did, oral surgery leadership study. Leadership composition is not symbolic. It is structural, with direct effects on the data produced.

Why does this happen? Several mechanisms appear in the literature:

• Study design choices. Investigators tend to design eligibility criteria around populations they know well. Male-dominated leadership teams have historically written protocols that exclude people who menstruate, are pregnant, or have hormonal variability—categories that map onto female biology but are not identical to gender identity.
• Outcome measure selection. When trial teams do not include researchers familiar with sex-specific symptom patterns, the measures they choose may miss effects that matter to women in this study. The dementia anxiety review found that patient-reported outcome tools used in dementia trials were rarely validated across sex or age subgroups, leaving gaps in what those trials could actually detect.
• Recruitment networks. Investigators recruit through their professional and community networks. A cancer trials bright-spots analysis found that sites with diverse leadership were more likely to have community partnerships that reached underrepresented groups—including women from racial and ethnic minorities who face compounded exclusion.

The pattern is not uniform across disease areas. A systematic review of hypertension and diabetes trials at federally qualified health centers found that women were actually enrolled at rates closer to their disease burden in some conditions. The gap is not fixed or inevitable. It varies by specialty, funding source, and who is running the study.

Sex is biological; gender is social; the two are related but not the same, and trial leadership affects both. A team that includes women does not automatically include researchers who study sex-based physiology, and a male investigator can absolutely design a rigorous sex-stratified trial. The PTSD enrollment study found that trial characteristics—not just investigator sex—predicted whether sex differences in enrollment appeared. Protocol design is the lever that matters most.

What this means for you as a reader: when you look up a peptide medicine, check whether the trial reported results separately for female and male participants. If it did not, the label may reflect an average that does not represent your biology, your life stage, or your health history.

This content is for general health education only and is not medical advice. Consult a qualified clinician before making any decisions about your care.

What evidence gaps remain in Alzheimer's and cancer research?

Research on peptides for Alzheimer's disease and cancer carries significant sex gaps in trials, leaving the evidence base for women thin in both disease areas. That is the short answer — the longer one requires looking at where the data actually break down.

Alzheimer's disease

Trials for Alzheimer's treatments have historically enrolled participants who fit a narrow clinical picture: older adults with the most common, memory-focused form of the disease. A 2025 call to action published in a peer-reviewed journal found that people with atypical variants of Alzheimer's — forms that affect language, vision, or movement rather than memory first — are routinely excluded from trials. Women are diagnosed with Alzheimer's at higher rates than men, yet the trials generating peptide-related evidence often do not report outcomes broken down by sex. When sex-disaggregated data are missing, researchers cannot determine whether women in a given study responded differently, experienced different side effects, or reached different endpoints. The trial simply did not establish those answers.

A separate systematic review on dementia trials found that anxiety — a symptom affecting quality of life significantly in people living with dementia — is measured inconsistently across studies, with tools not always validated for a dementia population. That inconsistency makes it harder to compare results across trials, including any involving peptide-based approaches.

Cancer

Enrollment patterns in cancer trials show a related problem. A 2025 analysis of FDA-approved drugs from 2015 to 2023 (source) found that sex representation in trials frequently did not match the actual disease burden in the population — meaning the people most affected by a cancer were not always the people studied. A review of strategies for underrepresented populations in cancer trials (source) identified structural barriers — transportation, language, distrust built from historical exclusion — as key reasons enrollment stays skewed.

What this means practically:

• Women in these studies were often not analyzed as a distinct group, so effect sizes specific to women are frequently unavailable.
• Age and life stage data are rarely reported alongside sex, making it impossible to know whether findings apply to postmenopausal women, younger women, or women managing other conditions at the same time.
• Peptide medicines being studied in these disease areas inherit these gaps from the broader trial infrastructure.

Caregivers and clinicians reading trial summaries should ask directly: did this study report outcomes by sex? If the answer is no, the evidence applies to a mixed population — and that distinction matters.

This section is for general health education only and does not constitute medical advice. Speak with a qualified healthcare provider about any treatment decisions.