The headline is broadly defensible, but the qualifications matter. Effect sizes vary by population, the strongest claims rest on shorter trials, and credible voices push back on how it's typically framed.
if the incidence of breast cancer in the wild population is one in 700 that means that out of 4,000 women say five of them would have breast cancers is what you'd expect if the sensitivity of the test is 73 percent which sounds high that means it's sapore below means which is what the sensitivity is of a mammogram 73 percent it means that if you get a positive test result you still have a sub one percent chance of having breast cancer
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when we say a mammogram has an eighty percent sensitivity here's what we mean if there are a hundred woman who have cancer so there's a hundred women and we absolutely know that they have breast cancer and we subject them to a mammogram 80 of them will test positive 80 of them will have a true positive and 20 of them will test falsely negative
that means the positive and negative predictive value of this test in isolation are very poor like less than 20%