What are the test performance characteristics of various medical testing parameter ?

The test performance characteristics of medical testing parameters are essential indicators of a test’s accuracy, precision, and clinical usefulness. The main test performance characteristics include:

1. Sensitivity: Sensitivity measures the ability of a test to correctly identify individuals with the condition or disease (true positives). It is calculated as the number of true positives divided by the sum of true positives and false negatives. Sensitivity indicates the test’s ability to detect the condition when it is present.
2. Specificity: Specificity measures the ability of a test to correctly identify individuals without the condition or disease (true negatives). It is calculated as the number of true negatives divided by the sum of true negatives and false positives. Specificity indicates the test’s ability to exclude the condition when it is absent.
3. Positive Predictive Value (PPV): PPV represents the probability that a positive test result is correct and indicates the likelihood of having the condition when the test is positive. It is calculated as the number of true positives divided by the sum of true positives and false positives.
4. Negative Predictive Value (NPV): NPV represents the probability that a negative test result is correct and indicates the likelihood of not having the condition when the test is negative. It is calculated as the number of true negatives divided by the sum of true negatives and false negatives.
5. Accuracy: Accuracy measures how well a test correctly classifies both positive and negative results. It is calculated as the sum of true positives and true negatives divided by the total number of test results.
6. Precision (Positive and Negative): Precision, also known as positive and negative likelihood ratio, assesses how much a test result increases or decreases the likelihood of having the condition. Positive precision is the ratio of sensitivity to (1 – specificity), and negative precision is (1 – sensitivity) divided by specificity.
7. Diagnostic Odds Ratio (DOR): The DOR is the ratio of the odds of a positive test result in the diseased group compared to the non-diseased group. A higher DOR indicates a better discriminatory power of the test.
8. Receiver Operating Characteristic (ROC) Curve: The ROC curve graphically represents the trade-off between sensitivity and specificity at various decision thresholds. The area under the ROC curve (AUC) quantifies the overall diagnostic accuracy of the test.
9. Analytical Sensitivity: Analytical sensitivity, also called limit of detection (LOD), is the lowest concentration or value that a test can accurately measure. It indicates how well the test can detect low levels of analytes.
10. Analytical Specificity: Analytical specificity, also called limit of quantification (LOQ), is the lowest concentration or value that a test can accurately measure and quantify. It indicates the ability to differentiate analytes from interfering substances.

It is important to interpret test performance characteristics in the context of the specific clinical setting and the population being tested. Different tests may have varying performance characteristics, and their clinical utility may vary based on factors such as disease prevalence and the purpose of testing.

About the author

Dr. Sambhu Chakraborty is a distinguished consultant in quality accreditation for laboratories and hospitals. With a leadership portfolio that includes directorial roles in two laboratory organizations and a consulting firm, as well as chairmanship in a prominent laboratory organization, Dr. Chakraborty is a respected voice in the field. For further engagement or inquiries, Dr. Chakraborty can be contacted through email at director@iaqmconsultants.com and info@sambhuchakraborty.com. Additional resourcesand contact information are available on his websites, https://www.quality-pathshala.com and https://www.sambhuchakraborty.com, or via WhatsApp at +919830051583