What is it about?
This study looks at whether men and women need different tools to help doctors spot signs of knee osteoarthritis (KOA) early. Using a large health dataset, the researchers created separate computer models for men and women that included sex-specific factors, like pregnancy history or hormone use. They compared these models to a general one that doesn’t include these extra details. The results showed that for women, using these tailored models helped improve prediction slightly. This suggests that medical tools that account for sex-specific health differences may help doctors give better, more personal care—especially for conditions like KOA, which affect men and women differently.
Featured Image
Photo by Anna Auza on Unsplash
Why is it important?
Knee osteoarthritis affects millions and is expected to reach nearly a billion people by 2050. Women are more likely to get it and often suffer worse symptoms, but most diagnostic tools don’t reflect these differences. This study built separate models for men and women using sex-specific data, like pregnancy and hormone history. It found that models tailored for women worked better than generic ones. The research shows that personalised tools can improve diagnosis, especially for women. It highlights the need to reduce gender bias in healthcare and supports a shift toward more accurate, fair and inclusive medical care.
Perspectives
Working on this article was both challenging and rewarding, as it brought together ideas I’ve been thinking about for a long time—how health tools might unintentionally ignore the very people they’re meant to help. I hope this work makes the idea of sex-specific medical models feel less like a technical detail and more like a human issue that affects how we care for real people, every day. Knee osteoarthritis might not sound like a headline-grabbing condition, but it causes huge pain and loss of mobility for millions, especially women. If this research prompts even one clinician or researcher to look differently at how we design diagnostic tools—or inspires a conversation about fairness in medicine—then it will have done what I hoped for. More than anything, I hope readers find it a useful step toward more inclusive, thoughtful healthcare.
Philippa McCabe
Liverpool John Moores University
Read the Original
This page is a summary of: The influence of sex in diagnostic modelling of knee osteoarthritis, PLOS One, July 2025, PLOS,
DOI: 10.1371/journal.pone.0325681.
You can read the full text:
Contributors
The following have contributed to this page
