The first step, they say, is admitting you have a problem, and on that front the UK’s Medicines and Healthcare products Regulatory Agency (MHRA) has made some much-needed progress. The agency, which is responsible for approving all clinical trials in the UK, has identified a “notable imbalance” in trials conducted between 2019 and 2023: there were nearly twice as many all-male trials as all-female trials.
This imbalance is hardly surprising: as I documented inInvisible Women, my book on the female data gap, the failure to adequately represent women in clinical trials is a longstanding and global problem. The MHRA’s figures are also in line with a recent US analysis that found male-prevalent diseases receive nearlytwice as muchfundingas female-prevalent diseases, both absolutely and relative to disease burden. So far, so disappointingly standard.
Still, it’s not all bad news. When I originally looked into the clinical trial landscape in the UK back in 2018, I was shocked to find that we were something of an outlier when it came to tackling the data gap in women’s health – and not in a good way. Unlike the EU, the US, Canada and Australia, the UK stood out for its failure to say anything at all on the subject. There were no funding requirements, no approval requirements. We didn’t even collect any data to track the problem. In this context (not to mention the backdrop of the Trump administration’sswerve awayfrom evidence-based research), the fact that the MHRA has – for the first time ever – conducted this research is extremely welcome.
The analysis also found that 90% of trials included both sexes, which might on the face of it seem to be more good news . But here’s where it gets more complicated: the inclusion of both sexes in a trial by no means guarantees that researchers will consider any differences between the sexes. Ananalysis of 10 yearsof preclinical trials in the US showed that, although there was an increase in the number of studies that included both sexes, there was no proportional increase in analysis and reporting by sex. Meanwhile,across a range of disciplines, only 5-14% of studies examine outcomes by sex, andfewer than a thirdof the results from phase three trials are reported by sex in medical journals.
One such trial, published in 2023 in the New England Journal of Medicine, tested an Alzheimer’s drug called lecanemab. You may have read about it: it was lauded across the international press as heralding “the beginning of the end” for Alzheimer’s disease. And indeed, it did sound exciting, not least because it was the first drug that had been found to reduce the rate of cognitive decline in patients. And, yes, the trial did include both sexes, but like thevast majorityof Alzheimer’s research, and despite thewell-documentedsex differences in Alzheimer’s presentation and prevalence, it didn’t do any sex analysis.
And here’s why that matters. The research paper said that lecanemab reduced the rate of cognitive decline in patientsby 27%, from which a reasonable reader may conclude that it had this effect in all patients. But if you looked at the data by sex (which was only provided in a supplementary index) it in fact appeared as though the drug may have had this effect in no patients at all: for men, the mean rate of slowing was much higher (43%), while for women it was much lower (12%). If this data is correct, it’s a clear demonstration of why sex analysis matters for men as much as women: a muddy amalgamation of the numbers is serving no one.
Unfortunately, because the trial was not set up to uncover sex differences, it’s impossible to know whether this disparity is a real effect, so this is no more than a frustratingly suggestive cautionary tale (although it’s worth noting that asubsequent analysispublished last month, which ran 10,000 simulated trials using the study data, found that the sex difference only occurred randomly 12 times). But it is far from an isolated case. A favourite example of mine is the supposed unpredictability of muscle-derived stem cells, which seemingly promoted muscle regeneration on a whim, until someone thought tosex disaggregate the dataand realised they weren’t unpredictable at all, it was just that male and female cells acted differently.
The MHRA’s failure to communicate anything about sex analysis in the trials it studied is a major flaw in its research. More fundamentally, though, the MHRA data actually tells us very little about the representation of women in UK clinical trials at all, because including both sexes in a trial is also not a guarantee that both sexes are represented equally. Indeed, usuallythey are not.
Cardiovascular disease, for example, is the number onekiller of womenglobally. Women are 50% more likely than men to be misdiagnosed after a heart attack. We know far less about female-specific risk factors for developing heart disease, and most risk-prediction models are still based on predominantly male data – meaning that theysystematically labelhigh-risk women as low risk because they don’t fit a male pattern of the disease. But heart-disease trials are not generally exclusively male; it’s just the representation of women in them remains “dismally low”. How many trials in the MHRA’s dataset would merit the same description? We simply don’t know.
The MHRA’s analysis is not perfect. Even in a study of sex-based gaps, there were significant sex-based gaps that leave us in the dark on crucial data points. The state of female representation in 90% of Britain’s clinical trials remains unknown; meanwhile, patients of both sexes are being let down by a failure to track sex analysis. All of which means that, from the perspective of the female data gap, this study has not been done well – but, still, I remain delighted that it has been done at all.
Caroline Criado Perez is the author of Invisible Women: Exposing Data Bias in a World Designed for Men
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