Which statement about likelihood ratio is true?

• A. The ratio used to determine how much a test result changes the probability of disease.
• B. The probability that a positive test result will be associated with a person who has the target condition, and a negative result will be associated with a healthy person.
• C. Only indicates the posttest probability after testing.
• D. Only applies to negative test results.

Answer: (B)

Likelihood ratio expresses how much a test result shifts the odds that a patient has the disease. It does this by comparing how often a given result occurs in people with the disease to how often it occurs in people without the disease. A positive result raises the odds by the positive likelihood ratio, while a negative result lowers the odds by the negative likelihood ratio. You then apply this to the clinician’s pretest probability to obtain a posttest probability using the relationship posttest odds = pretest odds × LR. This approach is distinct from predictive values, which estimate the probability that a person actually has or doesn’t have the disease given a positive or negative result and depend on disease prevalence. So the core idea is that the likelihood ratio quantifies how much a test result changes the probability of disease.