Which statement about likelihood ratios is correct?

• A. It is the ratio used to determine how much a test result will increase or decrease the probability that an individual has the condition from the pretest probability.
• B. It is the probability that the test will be positive if the disease is present.
• C. It is the proportion of true positives among all positive results.
• D. It applies only to negative results.

Answer: (A)

Likelihood ratios express how much a test result changes the likelihood that a patient has the condition. They come in two forms: one for a positive result and one for a negative result, and they are used to move from the pretest probability to the post-test probability. In practice, you convert the pretest probability to pretest odds, multiply by the appropriate likelihood ratio, and convert back to a post-test probability. For example, a positive result with a high likelihood ratio markedly increases the probability of disease, while a negative result with a low likelihood ratio markedly decreases it.

So the statement that this ratio is used to determine how much a test result will increase or decrease the probability from the pretest probability is the best description. The other statements describe different concepts: one describes sensitivity (probability the test is positive if the disease is present), another describes positive predictive value (proportion of true positives among positive results), and the last wrongly says likelihood ratios apply only to negative results.