We know men and woman are very different, however when it comes to diagnosis we often analyse them in the same way, which we’re now discovering can lead to some dire outcomes.
I recently read an article in The Pathologist which highlights this gender diagnosis challenge, particularly in relation to coronary artery disease (CAD). As the article reveals, CAD is one of the leading causes of morbidity and mortality for both men and women, however given the symptoms present very differently in men and women, diagnosing CAD in women presents a huge challenge.
“The challenges to spotting CAD have historically meant that doctors rely on a progressive testing pathway that begins with non-invasive imaging for women deemed to be at low risk of diseases, with more intensive examinations…in those at higher risk. But this ends in a testing catch-22: because of the diagnostic uncertainty of imaging procured, women with a low likelihood of disease are being tested too much, exposing them to risks and complications – while those with a higher likelihood who get false negatives from imaging tests may never receive more extensive examinations that would accurately indicate the presence of disease.”
Whilst we’ve made so many great strides in terms of patient testing, diagnosis and treatment, this example highlights the fact that in many respects a “one size fits all” approach still exists in health.
Understandably, more focus has been placed on simply being able to test for, then diagnose conditions, and in a lot of respects there is little discrimination between how symptoms present themselves in men and women.
We’ve come a long way in more accurately and efficiently diagnosing patients, but it’s time to go deeper. We need a greater level of customisation and sophistication in our diagnoses, so that more targeted care can be given.
This won’t be easy. To do this requires education and consensus across multiple healthcare streams, not only to understand the differences in symptoms between men and women, but to be able to quickly document and analyse them.
The expert panel that reviewed the CAD challenge suggested that doctors incorporate a new age, sex, and gene expression score (ASGES) assay into their evaluations of patients with potential obstructive CAD:
The ASGES algorithm allow the reliable determination of obstructive CAD risk-based only on a patient’s age, sex, and a single whole blood draw, but it even highlights sex-specific differences in CAD-associated gene expression.
By applying this level of granularity to the assessment of patients, not only will diagnosis become more accurate, it will provide doctors with more reliable information, and patients with less invasive and time-consuming testing.
The progress made with CAD is reassuring, and is encouraging for women who may now be tested and diagnosed more effectively, however it is only one example. There are many unchartered territories when it comes to gender-specific testing and diagnosis that need to be explored before we can claim success.