I have searched prior posts and I haven’t seen a good explanation that seems to help my seemingly tiny brain grasp this concept.
Highly sensitive tests rule OUT a disease. To me, this means if the test is negative, it’s likely to be a true negative because you are pretty certain that it’s an accurate negative result.
However, I just did a review question that told me sensitivity detects true positives and now I’m confused.
For example, D-dimer is a highly sensitive test. If it’s not elevated, we feel fairly certain the disease we are ruling out is ruled out. Wouldn’t this be a true negative? (Obviously not according to the world, but can someone please ELI5??)
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In medical testing terminology, sensitivity refers to a test’s ability to correctly identify those with the disease (true positive rate). A highly sensitive test will catch most people who have the disease — if you have the disease and you take this test, it’s unlikely to miss it.
On the other hand, specificity refers to a test’s ability to correctly identify those without the disease (true negative rate). A highly specific test will correctly rule out most people who don’t have the disease.
Using your D-dimer example: If a D-dimer test is negative (which rules out blood clots), it’s considered a true negative because of its high sensitivity — if there was a clot, such a sensitive test likely wouldn’t have missed it. The confusion comes from thinking about sensitivity from the perspective of negatives rather than positives: while high sensitivity does make true negatives more likely when the result is negative, its primary definition revolves around accurately identifying positives.
From Google:
> Sensitivity denotes the probability of a positive test result when disease is present. It is calculated as the percentage of individuals with a disease who are correctly categorized as having the disease. A test would be considered sensitive, in general if it is positive for most individuals having the disease.
So theoretically a test that says “positive” for everyone who takes it would detect 100% of the actual positive cases. Now it’s also giving you a ton of incorrect positives too, but the definition of sensitivity used in medical testing doesn’t care about anyone besides the actual positive people. So maybe you are thinking about how “sensitive” in common language usually just means “good at finding what we are looking for”, but that’s not the definition they are using in this context.
Sensitivity is proportion of people tested positive within the positive population. So high sensitivity implies people who are positive are not likely tested negative. When we want to rule out a disease we are trying to make sure people having the disease don’t get false negatives, ie a test with high sensitivity. But on the other hand many people with no disease may also get a positive result. Eg try to imagine asking a person if he is tired to know if he had enough sleep last night, if one said he is not tired you’d know one likely had enough sleep, but tons of other people (eg someone right after workout) may feel tired but had enough sleep
Short Answer – Sensitivity only measures True Positives. There are 3 other possible outcomes, False Positives, True Negatives, and False negatives. Just because a test is really good getting true positives you can’t claim it’s correctly identifying true negatives though.
For example, you have 100 sick people, let’s agree they are all sick. You run your test and you ID 1 sick person and 99 “healthy people”.
Since your 1 sick person was correctly sick, your sensitivity is 100%, but we know the 99 people you claimed were healthy are in fact sick, so all false negatives.
The other concept your missing is ‘specificity’, the rate of true negatives, which in this case is 0%.
In general it’s a trade off, you get great sensitivity or specificity but not both. In the case of medical diagnoses you’d err on the side of specificity, meaning you’re minimizing false negatives at the risk of getting reducing your false positive rate. The idea being it’s better to suspect someone has cancer and give them more tests than to suspect someone is healthy and have them die of cancer.
High sensitivity means just that, highly sensitive to the thing being measured. This means it is very likely to pick up on the thing if it is there = unlikely to miss a true positive, so it’s useful for ruling out the thing.
>For example, D-dimer is a highly sensitive test. If it’s not elevated, we feel fairly certain the disease we are ruling out is ruled out. Wouldn’t this be a true negative?
If the test says negative and you are negative, it’s a true negative.
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