## **Core Concept**
The positive predictive value (PPV) is a measure used in clinical epidemiology to determine the probability that a person with a positive test result actually has the disease. It is an important concept in assessing the utility of diagnostic tests. The PPV is calculated based on the sensitivity and specificity of the test, as well as the prevalence of the disease in the population being tested.

## **Why the Correct Answer is Right**
The positive predictive value (PPV) is calculated as the number of true positive results divided by the sum of true positive and false positive results. This can be represented as: PPV = TP / (TP + FP), where TP is the number of true positives and FP is the number of false positives. Therefore, the denominator of the PPV is the sum of true positives and false positives, which directly corresponds to all individuals who test positive (TP + FP).

## **Why Each Wrong Option is Incorrect**
- **Option A:** This option does not accurately represent the denominator of PPV. The denominator of PPV is not the sum of true positives, true negatives, false positives, and false negatives, which would represent the total population.
- **Option B:** This option suggests the denominator is the sum of true negatives and false negatives, which is incorrect. This sum represents individuals who test negative, not those who test positive.
- **Option D:** This option implies the denominator is the total number of people with the disease (true positives and false negatives), which is not correct for calculating PPV.

## **Clinical Pearl / High-Yield Fact**
A key point to remember is that the positive predictive value (PPV) increases with the prevalence of the disease in the population. This means that a test will be more accurate in predicting disease in populations where the disease is more common. Conversely, in low-prevalence populations, even a test with high sensitivity and specificity can have a low PPV.

## **Correct Answer:** C. TP + FP.