If the prevalence of fractures increases in a study, what is likely to happen to the sensitivity of a prediction rule?

• A. Increase
• B. Decrease
• C. Remain about the same
• D. Become undetermined

Answer: (C)

When considering how the prevalence of fractures affects the sensitivity of a prediction rule, it's important to understand the concept of sensitivity itself. Sensitivity measures the ability of a test or prediction rule to correctly identify those individuals who have a condition—in this case, fractures.

If the prevalence of fractures increases in a study, it does not inherently alter the accuracy of the prediction rule's ability to detect fractures in those who have them. Sensitivity is influenced more by the characteristics of the test (such as its design and the criteria used for determining a positive or negative outcome) rather than the prevalence of the condition in the population being studied. This means that while more individuals may have fractures, the proportion of true positives identified by the rule relative to the true presence of fractures remains constant.

Therefore, the sensitivity of the prediction rule is likely to remain about the same despite the increase in prevalence. This dynamic illustrates that sensitivity is a measure that is fundamentally tied to the test itself rather than the changing epidemiological landscape of the condition being predicted.