Which of the following best defines the sensitivity of a screening test?

Explanation

## Definition of Sensitivity **Key Point:** Sensitivity is the ability of a test to correctly identify individuals WITH the disease. ### Mathematical Formula $$\text{Sensitivity} = \frac{TP}{TP + FN}$$ Where: - TP = True Positives (diseased individuals who test positive) - FN = False Negatives (diseased individuals who test negative) ### Clinical Interpretation **High-Yield:** A highly sensitive test has few false negatives — it is good at **ruling OUT disease** (negative result is reassuring). Sensitive tests are preferred for: - Serious, treatable conditions - Early detection programs - Screening asymptomatic populations ### Comparison with Specificity | Parameter | Definition | Formula | Clinical Use | |-----------|-----------|---------|---------------| | **Sensitivity** | Proportion of diseased who test positive | TP/(TP+FN) | Rule OUT disease (high sensitivity = low false negatives) | | **Specificity** | Proportion of non-diseased who test negative | TN/(TN+FP) | Rule IN disease (high specificity = low false positives) | **Clinical Pearl:** A screening test should have high sensitivity to avoid missing cases in the asymptomatic population. A confirmatory test should have high specificity to avoid unnecessary treatment of false positives. [cite:Park 26e Ch 10]