A meta-analysis derivation of continuous likelihood ratios for diagnosing pleural fluid exudates.

In evaluating pleural effusions, clinicians perform thoraceninstance, recommend measuring pleural fluid-to-serum albumin gradients when patients with congestive heart failure have tesis and pleural fluid analysis most often by Light’s criteria to establish the exudative or transudative nature of the effuan exudative effusion by Light’s criteria (7). A Bayesian approach addresses these limitations of binary sion (1). Light’s criteria (2) dichotomize effusions into exudative or transudative categories with the use of three pleural testing strategies (10). Rather than diagnosing the presence or absence of a condition, a Bayesian strategy uses test results test criteria: pleural fluid-to-serum protein ratio, pleural fluid lactate dehydrogenase (LDH) concentration, and pleural fluidto generate likelihood ratios that increase or decrease a clinician’s pretest estimate of the probability of disease. Likelito-serum LDH ratio. Several other pleural fluid test criteria have similar diagnostic accuracies as compared with each of hood ratios represent the likelihood that a positive test result would be found in a patient with as opposed to without the individual tests within Light’s criteria (3). These criteria include pleural fluid cholesterol, pleural fluid-to-serum cholesdisease (10). Likelihood ratios are usually calculated using a single test result cutoff point. These binary likelihood ratios terol ratio, pleural fluid protein, and pleural fluid-to-serum have values above 1 for test results that increase the likelialbumin gradient. All of these tests dichotomize effusions into hood of an exudative effusion and values below 1 that deexudative or transudative categories by determining whether crease the likelihood. We previously published multilevel the test results are above or below a single cutoff point. likelihood ratios for pleural fluid test criteria commonly used Problems exist, however, with these pleural fluid test criteria to diagnose exudative pleural effusions (11). Multilevel likelias commonly used in clinical practice. First, dichotomizing hood ratios are calculated by using two or more cutoff points effusions into exudates and transudates by using a single for the range of possible test results. These multiple cutoff cutoff point loses much of the information contained in pleupoints demarcate test result intervals that are each associated ral fluid tests, which generate continuous numeric results (4). with a different likelihood that the patient has an exudative Test results just beyond and those extremely beyond a cutoff effusion. Although breaking up continuous test result values point are treated the same in that both establish the presence into ordinal intervals with multiple cutoff points improves of an exudative effusion. This binary diagnostic strategy exdiagnostic precision as compared with using a single cutoff plains why Light’s criteria frequently misclassify as exudates point, they only provide an average value for the range of the pleural effusions associated with congestive heart failure likelihood ratios that exist within each of the test result inter(5–7), which usually have borderline pleural fluid test results vals (4). A more precise diagnostic approach would calculate when in the exudative range. It also contributes to the misclassian exact likelihood ratio for each possible discrete pleural fluid fication that occurs in 1 to 10% of patients with malignant test result. Such discrete likelihood ratios are called continuous pleural effusions who appear to have transudative effusions likelihood ratios (12). Methods for calculating continuous likeby Light’s criteria (8). Second, combining two or more tests lihood ratios have been reported for very few conditions. using a single cutoff point for each test, as done by Light’s In this study, we analyze with logistic regression a multicencriteria, increases sensitivity but decreases specificity because ter registry of pleural fluid test values from patients with estabonly one of the tests needs to be positive to define an exudative lished diagnoses to derive equations that calculate continuous effusion (9). Finally, the lower specificity caused by combining likelihood ratios for pleural fluid test criteria for exudative several criteria encourages physicians to commonly order addieffusions. We also compare continuous likelihood ratios with tional—and usually unnecessary—pleural fluid tests when inimultilevel and binary likelihood ratios to determine whether tial test results do not fit clinical circumstances. Experts, for continuous likelihood ratios provide statistically significant and clinically important advantages.