If disease prevalence increases, what happens to the positive predictive value of a fixed test?

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Multiple Choice

If disease prevalence increases, what happens to the positive predictive value of a fixed test?

Explanation:
The main idea here is that positive predictive value (PPV) depends on how common the disease is in the population. PPV is the probability that someone who tests positive actually has the disease. When prevalence goes up, there are more true cases in the tested group, so a positive result is more likely to be a true positive. With a fixed test (constant sensitivity and specificity), PPV increases as prevalence increases. This can be seen in the formula PPV = (Se × Prev) / [(Se × Prev) + (1 − Sp) × (1 − Prev)]. As Prev (prevalence) rises, the numerator grows while the contribution of false positives (the (1 − Sp) × (1 − Prev) term in the denominator) becomes a smaller share of the total, pushing PPV higher. For example, using reasonable Se and Sp values, raising prevalence from low to moderate levels shifts PPV upward significantly, reflecting more true disease in the tested group. Thus, increasing disease prevalence leads to an increase in the positive predictive value.

The main idea here is that positive predictive value (PPV) depends on how common the disease is in the population. PPV is the probability that someone who tests positive actually has the disease. When prevalence goes up, there are more true cases in the tested group, so a positive result is more likely to be a true positive.

With a fixed test (constant sensitivity and specificity), PPV increases as prevalence increases. This can be seen in the formula PPV = (Se × Prev) / [(Se × Prev) + (1 − Sp) × (1 − Prev)]. As Prev (prevalence) rises, the numerator grows while the contribution of false positives (the (1 − Sp) × (1 − Prev) term in the denominator) becomes a smaller share of the total, pushing PPV higher. For example, using reasonable Se and Sp values, raising prevalence from low to moderate levels shifts PPV upward significantly, reflecting more true disease in the tested group.

Thus, increasing disease prevalence leads to an increase in the positive predictive value.

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