The likelihood ratio (LR) is a test performance characteristic that circumvents the vulnerabilities of predictive values. The LR also reflects the perspective of the clinician receiving a test result, but is independent of disease prevalence. LRs are "the doctor's friend" because they help us make sense out of test results we encounter in clinical practice.

The LR is merely a ratio of likelihoods (LR = L_{1}/L_{2}), comparing how likely a given test result is t occur in patients with disease relative to those without disease. Because we regard clinical findings as test results, we can calculate LRs using the formula:

LR = Likelihood of a clinical finding in patients with disease/Likelihood of the same clinical findings in patients without disease

When LRs are greater than 1, the numerator is large, meaning the test result occurs more frequently in patients with disease than in those without disease (thus, increasing the probability of disease). When LRs are less than 1, the denominator is larger, meaning the test result occur more frequently in patients without disease (thus decreasing the probability of disease). An LR near 1 has no diagnostic utility, because the test result is equally likely to occur in diseased and nondiseased individuals.

When considering dichotomous outcome from a 2 x 2 table, we refer to a LR for a positive clinical finding or test result (LR+) and a LR for a negative test (LR-). LRs can easily be calculated from the classic test performance characteristics of sensitivity and specificity:

How Likelihood Ratios Affect Pretest Probability

Likelihood Ratios and Beside Estimates

Calculating Probability

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