**Core Concept**
Sensitivity is a statistical measure used to evaluate the performance of a diagnostic test by assessing its ability to correctly identify individuals with a specific disease or condition. It is calculated as the number of true positives (correctly identified cases) divided by the sum of true positives and false negatives (missed cases). In essence, sensitivity reflects the proportion of actual positives that are correctly identified by the test.

**Why the Correct Answer is Right**
The correct answer, **A. True positive**, is the numerator in the formula for calculating sensitivity. This is because sensitivity specifically measures the test's ability to correctly identify individuals with the disease, which is reflected in the true positive rate. When a test has high sensitivity, it means that most of the people who actually have the disease will test positive. This is crucial in clinical settings where early detection is key to effective management and treatment.

**Why Each Wrong Option is Incorrect**
**Option B:** False positive, which is the number of individuals without the disease who test positive, is not relevant to the calculation of sensitivity. Sensitivity is concerned with the correct identification of cases, not the incorrect identification of non-cases.

**Option C:** True negative, which is the number of individuals without the disease who test negative, is also not relevant to the calculation of sensitivity. Sensitivity focuses on the correct identification of cases, not the correct identification of non-cases.

**Option D:** False negative, which is the number of individuals with the disease who test negative, is actually a component of the denominator in the sensitivity formula. However, it is not the numerator, and therefore, it is not the correct answer.

**Clinical Pearl / High-Yield Fact**
A useful mnemonic to remember the distinction between sensitivity and specificity is: "SnSn = True Positives / (True Positives + False Negatives)" and "SpSp = True Negatives / (True Negatives + False Positives)". This highlights the importance of understanding the definitions and calculations for these key statistical measures in diagnostic testing.

**✓ Correct Answer: A. True positive**