Question
A new test was developed for detection of COVID-19. The data is as follows:
| Test Result |
Disease + |
Disease – |
Total |
| Positive |
60 |
40 |
100 |
| Negative |
100 |
1800 |
1900 |
| Total |
160 |
1840 |
2000 |
What is the sensitivity of the test as per the information provided above?
| A. |
20.5%
|
| B. |
37.5%
|
| C. |
60%
|
| D. |
97%
|
Show Answer
|
Correct Answer » B
Explanation
|
|
Clinical Reasoning for the Correct Answer
– Sensitivity = (True Positives) ÷ (True Positives + False Negatives)
– True Positives (TP) = number of sick people who tested positive = 60
– False Negatives (FN) = number of sick people who tested negative = 100
– Sensitivity = 60 / (60 + 100) = 60 / 160 = 0.375 = 37.5%
Why Option A is incorrect:
– 20.5% is not a value derived from the given data; may confuse with a distractor.
– If dividing FP by total negative, result is 40/1940 ≈ 2.1% (irrelevant).
Why Option C is incorrect:
– 60% is the proportion of true positives among all positive test results (i.e., PPV).
– Positive Predictive Value (PPV) = TP / (TP + FP) = 60 / 100 = 60%
Why Option D is incorrect:
– 97% is close to specificity, not sensitivity.
– Specificity = TN / (TN + FP) = 1800 / (1800 + 40) = 1800 / 1840 = ~97.8%
