Evaluation of screening tests for detecting Chlamydia trachomatis: bias associated with the patient-infected-status algorithm.

In recent years, the evaluation of nucleic acid amplification tests (NAATs) for detecting Chlamydia trachomatis and Neisseria gonorrhea is based on a methodology called the patient-infected-status algorithm (PISA). In the simplest version of PISA, 4 test-specimen combinations (comparator tests) are used to define the gold standard. If a person shows a positive result by any 2 or more of these 4 comparator tests, the person is classified as infected; otherwise, the person is considered to be uninfected. A new test is then compared with this diagnostic algorithm. PISA-based sensitivity and specificity estimates of nucleic acid amplification tests have been published in the medical and microbiologic literature and have been included in FDA-approved package inserts of NAATs for detecting C. trachomatis. Using simulations, we compare 2 versions of the patient-infected-status algorithm with latent-class models and an imperfect gold standard. We show that the PISA can produce highly biased test-performance parameter estimates. In a series of simulated scenarios, none of the 95% confidence intervals for PISA-based estimates of sensitivity and prevalence contained the true values. In addition, the PISA-based estimates of sensitivity and specificity change markedly as the true prevalence changes. We recommend that PISA should not be used for estimating the sensitivity and specificity of tests.