Difference Between Sensitivity and Specificity

To put it another way, this test function is primarily concerned with finding the sample members who are truly positive about the property being tested.

Specificity is a parameter that determines the likelihood of actual negatives. The goal of this measurement is to identify the sample members who are truly negative about the property being tested.

Comparison Table Between Sensitivity and Specificity

Parameters of Comparision SensitivitySpecificity
Definition Sensitivity is a metric that determines the likelihood of a positive test result.The likelihood of something being found to be false is measured by specificity.
100% ValueEvery person with the disease is correctly identified by a test with 100 % sensitivity.Every person who does not have the condition is appropriately identified by a test with 100% specificity.
CalculationSensitivity = No. of true positive/ [No. of true positives + No. of false negatives]Specificity = No. of true negative/ [ No. of true negatives + No. of false positive]
ProbabilityProbability of actual positives.Probability of actual negatives.
ExamplesHigh sensitivity test for detection of AIDS-like ELISA.High sensitivity test for detection of AIDS-like Western blot.

What is Sensitivity?

The frequency in which the disease positivity is identified among the patients indicates sensitivity. In fact, sensitivity confirms that the laboratory results are acceptable while testing patients for specific conditions or sickness. 

A sick person's test can result in either positive or negative results. True positive is the positive outcome, while a false negative is a negative consequence.

The following formula is used to calculate sensitivity (in percentages):

Sensitivity = [(TP/TP+FN)] x 100

A test with 100 percent sensitivity cannot produce false-negative results. This implies that every patient suffering from the disease will get a positive test result.

What is Specificity?

The specificity or characteristic feature of a test performed is how many people without the diseases for which it has been designed are negative (in the absence of a disease).

The following formula is used to calculate specificity (as a percentage):Specificity = [(TN/TN+FP)] x 100

There are no false-positive outcomes in a test with 100% specificity. In healthy people, therefore, the test is always negative. Positive outcomes are usually positive.

It is recommended to use a test with 100 percent sensitivity when there is a possibility of a problem. The patient does not have the disease if the result is negative.

Main Differences Between Sensitivity and Specificity

  1. Sensitivity has a higher possibility of true positives, whereas Specificity has a higher probability of true negatives.
  2. The ELISA test for AIDS detection has a high sensitivity, whereas the Western blot test has high specificity.

Conclusion

The statistical measures of a test's sensitivity and specificity are referred to as sensitivity and specificity, respectively. They're commonly used in the medical field.

When there is a suspicion of a condition, it is ideal to use a mixture of a test with 100 percent sensitivity and a test with 100 percent specificity.

References

  1. https://academic.oup.com/bjaed/article-abstract/8/6/221/406440
  2. https://www.bmj.com/content/327/7417/716.short
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