Which statement best describes the purpose of likelihood ratios (LR+ and LR−) in diagnostic testing?

Which statement best describes the purpose of likelihood ratios (LR+ and LR−) in diagnostic testing?

• A. They measure the test's overall accuracy.
• B. They determine the disease prevalence in the population.
• C. They test how much a test shifts probability from pretest to post-test.
• D. They replace the need for pretest probability.

Answer: (C)

Likelihood ratios quantify how much a diagnostic test result shifts the probability of disease. They translate what you already suspect before testing (pretest probability) into a new probability after seeing the test result (post-test probability). The math is often described in terms of odds: post-test odds equal pretest odds multiplied by the LR. A large LR for a positive result (LR+) means a positive result greatly increases the chance of disease, while a small LR for a negative result (LR−, well below 1) means a negative result greatly decreases the chance. This concept helps clinicians update their assessment with each test, rather than relying on a single accuracy figure or on prevalence alone.

Likelihood ratios quantify how much a diagnostic test result shifts the probability of disease. They translate what you already suspect before testing (pretest probability) into a new probability after seeing the test result (post-test probability). The math is often described in terms of odds: post-test odds equal pretest odds multiplied by the LR. A large LR for a positive result (LR+) means a positive result greatly increases the chance of disease, while a small LR for a negative result (LR−, well below 1) means a negative result greatly decreases the chance. This concept helps clinicians update their assessment with each test, rather than relying on a single accuracy figure or on prevalence alone.