2 ms·

Well. With a bad test, what is necessary is to improve the test. The argument "outcomes are worse off with more absent symptoms testing" is really saying that s

Well. With a bad test, what is necessary is to improve the test. The argument "outcomes are worse off with more absent symptoms testing" is really saying that symptoms is more predictive than the test itself: test is positive if [symptoms & positive result] test is positive or neutral if [no symptoms & should have been screened & positive result] and test is negative if [no symptoms & should not have been screened & positive result] (notice that this does not change the outcome to not testing people without symptoms and without another reason to do so). Until the tests/decision protocols were improved to avoid false positive, this third case should be communicated to the person as a negative result of the test (if we are convinced that the overall outcome is better off if the test should not have been administered at all), but I would find that unethical and dehumanizing and I understand touches on lots of ethical issues: the stress of waiting for a result, the liability of not being an actual false positive, etc. So, I understand, that given the current state of the testing, the decision is to restrict when to do it.

jacquesm 5y ago
You are visibly making progress in your understanding of the problem, for which you are to be commended, especially if you are a complete layperson in this field. Thank you. This test isn't a 'bad test', though applying it in the wrong way can lead to bad outcomes. This is why tests used absent symptoms have to have a false positive rate that is much lower than the base rate at which the disease occurs. These tests - unlike software tests - should not be thought about in absolute terms but in terms of probability, so a positive test indicates a probability that you have a specific disease, but it is very well possible that you do not have it, and a negative test indicates a probability that you do not have it - but it is very well possible that you in fact do have the disease. And the reasons for a false positive or false negative may have nothing to do with the test itself, but could easily be an environmental factor or some benign aspect of the test subject that was not accounted for when designing the test. Whether or not a test is suitable for mass screening hinges on the factors above, the base rate for the disease, the age of the group being tested, in some cases gender and so on. In order to have a positive outcome across the population all these factors have to be taken into account and by the time that you have done so there are - unfortunately - at the moment no miracles to be had. But combinations of knowledge, for instance a genetic pre-disposition to a certain disease + a positive test can have much higher signal to noise ratios than either by themselves. But make no mistake: this is an important development in medical diagnostics and it may very well be that once more evidence has been collected and some of the kinks have been worked out that this particular test or an improved version of it can be applied in a screening setting for one or more of the cancers that we currently have no reliable detection method for and that could be cured if detected early enough given a high enough base rate and a low enough false positive rate. Note that the scientists behind the project are very careful with their statements and that the reporting on this was actually quite neutral and trends to cautious optimism, which I think is warranted, but until the result of the new studies is known it is way too early to shout 'revolution'.

jacquesm 5y ago

You are visibly making progress in your understanding of the problem, for which you are to be commended, especially if you are a complete layperson in this field. Thank you. This test isn't a 'bad test', though applying it in the wrong way can lead to bad outcomes. This is why tests used absent symptoms have to have a false positive rate that is much lower than the base rate at which the disease occurs. These tests - unlike software tests - should not be thought about in absolute terms but in terms of probability, so a positive test indicates a probability that you have a specific disease, but it is very well possible that you do not have it, and a negative test indicates a probability that you do not have it - but it is very well possible that you in fact do have the disease. And the reasons for a false positive or false negative may have nothing to do with the test itself, but could easily be an environmental factor or some benign aspect of the test subject that was not accounted for when designing the test. Whether or not a test is suitable for mass screening hinges on the factors above, the base rate for the disease, the age of the group being tested, in some cases gender and so on. In order to have a positive outcome across the population all these factors have to be taken into account and by the time that you have done so there are - unfortunately - at the moment no miracles to be had. But combinations of knowledge, for instance a genetic pre-disposition to a certain disease + a positive test can have much higher signal to noise ratios than either by themselves. But make no mistake: this is an important development in medical diagnostics and it may very well be that once more evidence has been collected and some of the kinks have been worked out that this particular test or an improved version of it can be applied in a screening setting for one or more of the cancers that we currently have no reliable detection method for and that could be cured if detected early enough given a high enough base rate and a low enough false positive rate. Note that the scientists behind the project are very careful with their statements and that the reporting on this was actually quite neutral and trends to cautious optimism, which I think is warranted, but until the result of the new studies is known it is way too early to shout 'revolution'.