Review Question - QID 216987

The number of false negatives can be calculated as false negatives = total enrolled * prevalence * (1 - sensitivity) = 1000 * 0.1 * (1 - 0.94) = 6.

The number of enrolled patients who are positive or negative in a study can be estimated using the population prevalence of a disease. Once separated, the probability that a positive patient will be detected correctly by a test is summarized by the test sensitivity, which is defined as true positives / (true positives + false negatives). False negatives are defined as those patients who have a disease but inaccurately test negative. For a screening test to be maximally effective, the sensitivity should be extremely high so that almost all truly positive patients will be detected, resulting in very few false negatives.

Incorrect Answers:
Answer 2: 94 is the number of true positives and can be derived by true positives = total enrolled * prevalence * sensitivity = 1000 * 0.1 * 0.94 = 94.

Answer 3: 135 is the number of false positives and can be derived by false positives = total enrolled * (1 - prevalence) * (1 - specificity) = 1000 * (1 - 0.1) * (1 - 0.85) = 1000 * 0.9 * 0.15 = 135.

Answer 4: 765 is the number of true negatives and can be derived by true negatives = total enrolled * (1 - prevalence) * (specificity) = 1000 * (1 - 0.1) * 0.85 = 1000 * 0.9 * 0.85 = 765.

Answer 5: 771 is the number of total test negatives and can be derived by total negatives = true negatives + false negatives = total enrolled * (1 - prevalence) * (specificity) + total enrolled * prevalence * (1 - sensitivity) = 1000 * (1 - 0.1) * 0.85 + 1000 * 0.1 * (1 - 0.94) = 765 + 6 = 771.

Bullet Summary:
The number of false negatives expected in a study can be calculated using total enrolled * prevalence * (1 - sensitivity).