Which statement best describes what a likelihood ratio expresses?

Which statement best describes what a likelihood ratio expresses?

• A. The ratio of true positives to false negatives.
• B. The value that expresses how many times more likely a positive test result is in diseased individuals compared with non-diseased individuals.
• C. The proportion of true positives among all positives.
• D. The probability of disease after a positive test.

Answer: (B)

Likelihood ratios show how much a test result changes the odds of disease by comparing how often a positive result occurs in people with disease to how often it occurs in those without. In other words, it describes how many times more likely a positive test is among diseased individuals than among non-diseased ones. For a positive result, this is calculated as sensitivity divided by (1 minus specificity), and values greater than one strengthen the case for disease while values less than one argue against it. This differs from the proportion of true positives among positives (which is a PPV) and from simply the ratio of true positives to false negatives or from the probability of disease after a positive test (post-test probability).

Likelihood ratios show how much a test result changes the odds of disease by comparing how often a positive result occurs in people with disease to how often it occurs in those without. In other words, it describes how many times more likely a positive test is among diseased individuals than among non-diseased ones. For a positive result, this is calculated as sensitivity divided by (1 minus specificity), and values greater than one strengthen the case for disease while values less than one argue against it. This differs from the proportion of true positives among positives (which is a PPV) and from simply the ratio of true positives to false negatives or from the probability of disease after a positive test (post-test probability).