To assess the accuracy of a test, its outcome must be compared with an independently established gold standard test. The gold standard test is the time honoured diagnostic test that is considered to be the current standard or definitive test for the disease in question. An ideal gold standard test has a sensitivity of 100% (it identifies all individuals with the disease) and a specificity of 100% (it does not falsely identify someone with a condition that does not have the condition). In practice, of course, there are no ideal gold standard tests, and one tries to use a test that is as close as possible to the ideal test. Results on sensitivity and specificity of a new test depend critically on how closely the gold standard approaches the ideal state.
Unfortunately the use of the word 'gold' is often misunderstood to mean the 'perfect' or ideal diagnostic test. This misunderstanding is deepened by the use of the term 'golden standard' by some medical researchers. It is exemplified by a letter to the BMJ by Duggan (1992)
who called for the abolition of the term 'gold standard' on the basis that the phrase smacks of dogma. Versi (1992) countered this by pointing out that the gold standard is not the perfect test but merely the best available test, and gave the Oxford English Dictionary definition which states that it is a "measure to which others conform or by which the accuracy of others is judged ; a thing serving as a basis for comparison." In fact some medical journals have now discontinued use of the term gold standard and instead insist that the term criterion standard be used instead.
Gold standard tests for some diseases may not be used in the clinical practice of medicine at all because the procedure is too invasive or is only applicable after death. For example, the gold standard test for Alzheimer's requires a biopsy on brain tissue - which can only be carried out post-mortem. Such a test would still, however, be used as the standard against which other tests are assessed. As new diagnostic methods become available, the "gold standard" test may change over time. For instance, there is intensive research underway to come up with a new gold standard test for Alzheimer's and other forms of dementia which may utilize chemical markers of the disease, or imaging from brain scans.
FAQs
Sensitivity refers to a test's ability to designate an individual with disease as positive. A highly sensitive test means that there are few false negative results, and thus fewer cases of disease are missed. The specificity of a test is its ability to designate an individual who does not have a disease as negative.
What is the sensitivity and specificity rule? ›
If it turns out that the sensitivity is high then any person who has the disease is likely to be classified as positive by the test. On the other hand, if the specificity is high, any person who does not have the disease is likely to be classified as negative by the test.
What does a low specificity mean? ›
A test with low specificity is more likely to produce a high number of false positives and may incorrectly identify disease or illness in individuals when it is not present. Number of True Negatives: 6. Number of True Negatives + Number of False. Positives = 10. Specificity Value: 6 /10 or 60%
How to remember sensitivity and specificity? ›
Sensitivity vs specificity mnemonic
SnNout: A test with a high sensitivity value (Sn) that, when negative (N), helps to rule out a disease (out). SpPin: A test with a high specificity value (Sp) that, when positive (P) helps to rule in a disease (in).
What is the difference between sensitivity and precision? ›
Sensitivity is defined as the number of relevant reports identified divided by the total number of relevant reports in existence. Precision is defined as the number of relevant reports identified divided by the total number of reports identified.
How to explain sensitivity and specificity? ›
Sensitivity refers to a test's ability to designate an individual with disease as positive. A highly sensitive test means that there are few false negative results, and thus fewer cases of disease are missed. The specificity of a test is its ability to designate an individual who does not have a disease as negative.
What is considered good specificity and sensitivity? ›
For a test to be useful, sensitivity+specificity should be at least 1.5 (halfway between 1, which is useless, and 2, which is perfect).
What does a specificity of 80% mean? ›
A test with 80% specificity correctly reports 80% of patients without the disease as test negative (true negatives) but 20% patients without the disease are incorrectly identified as test positive (false positives).
What does a 90% specificity mean? ›
Sensitivity is the percentage of true positives (e.g. 90% sensitivity = 90% of people who have the target disease will test positive). Specificity is the percentage of true negatives (e.g. 90% specificity = 90% of people who do not have the target disease will test negative).
Is a higher sensitivity better? ›
Low sensitivity is proven to be more consistent and gives you complete control of your mouse movements.
Therefore, the accuracy of the test is equal to 75 divided by 100 or 75%. Sensitivity: From the 50 patients, the test has only diagnosed 25. Therefore, its sensitivity is 25 divided by 50 or 50%. Specificity: From the 50 healthy people, the test has correctly pointed out all 50.
What does specificity mean in statistics? ›
Specificity, which denotes the proportion of subjects correctly given a negative assignment out of all subjects who are actually negative for the outcome, indicates how well a test can classify subjects who truly do not have the outcome of interest.
How to interpret sensitivity analysis? ›
Interpret sensitivity analysis by identifying data patterns, trends, and key relationships. Assess how different inputs or scenarios affect outputs, pinpoint inputs that optimize outcomes, and evaluate output sensitivity to input changes.
What is the example of sensitivity? ›
Examples of sensitivity in a Sentence
I was surprised by her extreme sensitivity about even the smallest suggestions that we made. This is a matter of great political sensitivity. He handled the situation with great sensitivity. Her decision shows a lack of sensitivity.
What is the formula for accuracy? ›
Formula For Precision
As a result, the precision formula is as follows: Precision = True positives/ (True positives + False positives) In the same fashion, students can write the formula of Accuracy, Accuracy = (True positives + True Negatives)/ (True positives + True negatives + False positives + False negatives)
Is it better to be precise or accurate? ›
Precision is independent of accuracy. That means it is possible to be very precise but not very accurate, and it is also possible to be accurate without being precise. The best quality scientific observations are both accurate and precise.
What is the formula for sensitivity and specificity? ›
Sensitivity = [ a / ( a + c ) ] × 100 Specificity = [ d / ( b + d ) ] × 100 Positive predictive value ( PPV ) = [ a / ( a + b ) ] × 100 Negative predictive value ( NPV ) = [ d / ( c + d ) ] × 100 .
What is the rule of specificity? ›
SPECIFICITY PRINCIPLE. The principle of specificity of training states that the way the body responds to physical activity is very specific to the activity itself. For example, someone who jogs can expect that their jogging performance would approve as well as their aerobic conditioning.
What is specificity and sensitivity of a method? ›
Sensitivity and specificity are inversely related: as sensitivity increases, specificity tends to decrease, and vice versa. [3][6] Highly sensitive tests will lead to positive findings for patients with a disease, whereas highly specific tests will show patients without a finding having no disease.
What is sensitivity and specificity of a psychological test? ›
Sensitivity refers to a test's ability to identify the presence of an actual deficit, condition, or disorder—a true positive result. Specificity refers to a test's ability to identify the absence of an actual deficit, condition, or disorder—a true negative result.
who called for the abolition of the term 'gold standard' on the basis that the phrase smacks of dogma. Versi 
