**Core Concept**
Positive predictive value (PPV) is a measure of a test's accuracy, indicating the probability that a patient with a positive test result actually has the disease. It is calculated as the number of true positives divided by the sum of true positives and false positives. PPV is influenced by various factors, including the test's sensitivity, specificity, and the prevalence of the disease in the population being tested.

**Why the Correct Answer is Right**
The correct answer is **A. Incidence of disease** because positive predictive value is not directly affected by the incidence of disease. Incidence refers to the rate of new disease cases occurring within a specified time period, whereas PPV is concerned with the accuracy of the test result. In contrast, PPV is influenced by the prevalence of the disease, which is the total number of existing cases at a given time. The other factors, such as specificity (B), sensitivity (D), and prevalence (C), all impact the PPV of a test.

**Why Each Wrong Option is Incorrect**
**Option B:** Specificity is a measure of a test's ability to correctly identify individuals without the disease, but it does not directly affect the PPV.

**Option C:** Prevalence of the disease is a critical factor in determining the PPV of a test, as it influences the ratio of true positives to false positives.

**Option D:** Sensitivity is a measure of a test's ability to correctly identify individuals with the disease, and it does impact the PPV.

**Clinical Pearl / High-Yield Fact**
When interpreting test results, it's essential to consider the prevalence of the disease in the population being tested, as this can significantly affect the positive predictive value of the test.

**Correct Answer:**
✓ Correct Answer: A. Incidence of disease