M09.01.08 Effective Prevalence

Prevalence is a key concept in medical diagnostics, representing the proportion of individuals within a population who have a particular disease at a given time. This parameter is essential in understanding the accuracy and reliability of diagnostic test results.

Definition of Prevalence

Prevalence quantifies the existing cases of a disease within a population at a specific time. It serves as a relevant measure in determining pre-test probabilities, influencing the positive predictive value (PPV) and negative predictive value (NPV) of diagnostic tests.

2. Impact of Prevalence on Predictive Values

• High Prevalence: When disease prevalence is high within a population, the probability that a positive test result is accurate increases, resulting in a higher PPV.
• Low Prevalence: In populations with low disease prevalence, the probability that a negative test result is accurate increases, resulting in a higher NPV.

Example Scenarios

• High-Prevalence Example: In 80-year-old diabetic patients, the prevalence of kidney failure is significantly higher than in the general population. For this demographic, a positive kidney failure screening test is more likely to be true, illustrating a higher PPV.
• Low-Prevalence Example: In a 15-year-old girl with no risk factors, the prevalence of myocardial infarction is very low. A positive test result for myocardial infarction is likely to be a false positive, leading the physician to repeat the test. A negative result is more reliable, indicating a higher NPV for this population.

3. Distinguishing Prevalence from Incidence

• Incidence reflects the rate of new cases in a population. Increasing the incidence does not affect the PPV or NPV of a screening test, as these metrics depend solely on current prevalence, not on new cases.

4. Prevalence vs. Test Metrics

Prevalence affects only the predictive values (PPV and NPV) but does not impact:

• Sensitivity: The ability of the test to correctly identify those with the disease.
• Specificity: The ability of the test to correctly identify those without the disease.

These metrics are intrinsic properties of the test itself and can only be changed by modifying the test, not by altering prevalence.

Points to Remember

• Prevalence affects the predictive accuracy of test results but not the test’s sensitivity or specificity.
• High prevalence leads to higher PPV, while low prevalence leads to higher NPV.
• Incidence indicates new cases and does not influence the predictive values of existing tests.

Bibliography

• CDC. Principles of Epidemiology in Public Health Practice. Available at: CDC Website.
• Gordis, L. Epidemiology. 5th ed. Elsevier, 2014.
• Rothman, K.J., Greenland, S., Lash, T.L. Modern Epidemiology. 3rd ed. Lippincott Williams & Wilkins, 2008.