My argument is not about particular individuals, but about populations as a whole and wholesale screening of those populations. The consensus is that this does not lead to improved patient outcomes across that population, though in individual cases it may very well be the result.
Patient exhibits symptom => perform a not-especially-invasive test Positive test result => invasive test like a biopsy Positive biopsy result => heavy-duty intervention (although I'm not focusing on this part of the chain in what follows)
Both testing and (certain) symptoms have predictive value, and don't completely overlap. So there's something like this going on:
P(actual problem|no additional information) = really really low, which is why they don't scoop out chunks of every organ to test "just in case" every time you go to the doctor
P(actual problem | [symptom AND positive test result]) = generally high enough in at least some cases to justify the risk of the biopsy, which is why it's the standard of care
P(actual problem | just symptom) = probably not super high, which is why the tests are developed
P(actual problem | just a positive test result) = substantially lower than P(actual problem | [symptom AND positive test result]), so in the general case the balance of risk no longer favors the biopsy
In the broadest of strokes, is there anything I've just said that you substantially disagree with?
And that's exactly where the issue with indiscriminate asymptomatic testing lies, that requires much higher quality tests than the ones that can be used in a diagnostic setting once a patient is symptomatic.
To add one more unpopular bit of data to all this: there is some evidence that the indiscriminate testing for certain cancers has gone too far and that it no longer is a net positive. But in the presence of certain mutations those tests are extremely valuable.
https://www.statnews.com/2018/01/01/cancer-screening-misled-...
Biology is messy, and it is quite hard to state up front whether or not a test or a treatment - even if in an experimental setting it is working - will still be a gain if rolled out in a different setting or application. Hence all the trials and studies, that's the only way to really get a grip on this.
I'm quite curious what the outcome of the large scale test the article refers to will be.
We just need to improve the decision making after getting test results (one of these decisions is to decide to not do anything), and more data make improving it easier.