**Core Concept:** Sensitivity of a screening test is the probability of correctly identifying individuals with the disease or condition. It is calculated as the ratio of true positive to the sum of true positive and false negative values.

**Why the Correct Answer is Right:**
The correct answer is derived from understanding the formula for calculating sensitivity and specificity of a diagnostic test. Sensitivity is expressed as a percentage and can be calculated using the following formula:

Sensitivity = (True Positive / (True Positive + False Negative)) × 100

**Why Each Wrong Option is Incorrect:**
A. False: This option does not represent the correct formula for sensitivity calculation.
B. False: Similar to option A, this option also does not represent the correct formula for sensitivity calculation.
C. True: This option contains the correct formula for sensitivity calculation, but is incomplete as it only includes the numerator (True Positive) without the denominator (True Positive + False Negative).
D. False: This option does not represent the correct formula for sensitivity calculation.

**Clinical Pearl / High-Yield Fact:**
Calculating sensitivity is crucial for understanding the performance of a screening test. High sensitivity indicates that the test is good at identifying patients with the condition, but may result in many false positives, leading to unnecessary further testing and interventions. Low sensitivity may result in missing cases, leading to delayed diagnosis and poor patient outcomes.

**Correct Answer:** C. True: Sensitivity = (True Positive / (True Positive + False Negative)) × 100

Please note that sensitivity is calculated along with specificity to provide a broader understanding of the test's performance in detecting both positive and negative cases.