The elusive diagnostic test for endometriosis.

The prevalence of endometriosis in the general population is hard to deﬁne. However, it isnoted to be quite high in patients with infertility or chronic pelvic pain. Laparoscopy isconsidered to be the “gold” standard for the diagnosis of endometriosis. Although manyattempts have been made to use clinical, imaging, and serum markers to arrive at a diagnosiswithout surgery, so far none have proven clinically useful on their own. The value of anonsurgical diagnostic test is even more critical if medical therapy is considered to be aseffective as surgical therapy. In this way, a patient can avoid surgery altogether. There is acertain degree of misclassiﬁcation with all diagnostic tests. The clinician must decide if theclinical and economic consequences of such misclassiﬁcation are acceptable.The evaluation of a diagnostic test requires some familiarity with the measurements used(1). The variability of test results could be due to intrinsic inaccuracies in the technical part ofperforming the test or the observer’s assessment of the result. Standard reports of the value ofa diagnostic test include sensitivity (proportion of patients with the disease that have a positivetest) and speciﬁcity (proportion of patients without the disease that have a negative test). Thosethat are incorrectly labeled as having the disease are the false positives and those that areincorrectly labeled as not having the disease are the false negatives. Sensitivity and speciﬁcityare measures of diagnostic accuracy that are not affected by the prevalence of the condition.Another set of measurements that are important to consider in a test are the predictivevalues of a negative or positive test result (1). The positive predictive value (PPV) is theproportion of those with a positive test that have the disease. The negative predictive value(NPV) is the proportion of those with a negative test that do not have the disease. Ininterpreting the value of the predictive values of a test, it is important to know the pretestprobability of the disease, that is, the frequency of the disease in the patient population. If thepretest probability is very high, such as in a subset of patients with chronic pelvic pain orinfertility, the predictive value of a positive test will be high. Since these results are inﬂuencedby the frequency of disease, they may not necessarily be applicable to a different patientpopulation.Bayes’s theorem can be used to estimate the PPV and NPV of a test for varying populationsif the sensitivity, speciﬁcity, and probability of the disease in the target population are knownor can be well estimated. Using this method, however, implies that the sensitivity andspeciﬁcity of the test do not change for various populations of interest. Although sensitivityand speciﬁcity are not affected by prevalence, they may well be affected by the spectrum ofdisease. It may be the case, for example, that the sensitivity is higher (easier to detect) in apopulation with more advanced disease (2). This would be the case in endometriosis where itis possible to miss the diagnosis of minimal disease but unlikely with more advanced disease.Two other measurements may also be used to evaluate a test: likelihood ratios (LRs) andreceiver operator characteristic (ROC) curves (1). The LR is a ratio of the true positives(sensitivity) to the false positives (1-speciﬁcity) at a particular value of a test. Alternatively,these quantities can be plotted for all observed values of a predictor or test and the curvegenerated (ROC). The area under the ROC curve (AUC) is a common measure of the