The main psychedelic component of magic mushrooms is psilocybin, which shows promise as a treatment for depression and other mental disorders. Psychedelic effects are believed to emerge through stimulation of serotonin 2A receptors (5-HT2ARs) by psilocybin’s active metabolite, psilocin. We here report for the first time the relationship between intensity of psychedelic effects, cerebral 5-HT2AR occupancy and plasma levels of psilocin in humans. Eight healthy volunteers underwent positron emission tomography (PET) scans with the 5-HT2AR agonist radioligand [¹¹C]Cimbi-36: one at baseline and one or two additional scans on the same day after a single oral intake of psilocybin (3–30 mg). 5-HT2AR occupancy was calculated as the percent change in cerebral 5-HT2AR binding relative to baseline. Subjective psychedelic intensity and plasma psilocin levels were measured during the scans. Relations between subjective intensity, 5-HT2AR occupancy, and plasma psilocin levels were modeled using non-linear regression. Psilocybin intake resulted in dose-related 5-HT2AR occupancies up to 72%; plasma psilocin levels and 5-HT2AR occupancy conformed to a single-site binding model. Subjective intensity was correlated with both 5-HT2AR occupancy and psilocin levels as well as questionnaire scores. We report for the first time that intake of psilocybin leads to significant 5-HT2AR occupancy in the human brain, and that both psilocin plasma levels and 5-HT2AR occupancy are closely associated with subjective intensity ratings, strongly supporting that stimulation of 5-HT2AR is a key determinant for the psychedelic experience. Important for clinical studies, psilocin time-concentration curves varied but psilocin levels were closely associated with psychedelic experience.

Like any other medical technology or intervention, diagnostic tests should be thoroughly evaluated before their introduction into daily practice. Increasingly, decision makers, physicians, and other users of diagnostic tests request more than simple measures of a test's analytical or technical performance and diagnostic accuracy; they would also like to see testing lead to health benefits. In this last article of our series, we introduce the notion of clinical utility, which expresses—preferably in a quantitative form—to what extent diagnostic testing improves health outcomes relative to the current best alternative, which could be some other form of testing or no testing at all. In most cases, diagnostic tests improve patient outcomes by providing information that can be used to identify patients who will benefit from helpful downstream management actions, such as effective treatment in individuals with positive test results and no treatment for those with negative results. We describe how comparative randomized clinical trials can be used to estimate clinical utility. We contrast the definition of clinical utility with that of the personal utility of tests and markers. We show how diagnostic accuracy can be linked to clinical utility through an appropriate definition of the target condition in diagnostic-accuracy studies.

BACKGROUND: In recent years, increasing focus has been directed to the methodology for evaluating (new) tests or biomarkers. A key step in the evaluation of a diagnostic test is the investigation into its accuracy. CONTENT: We reviewed the literature on how to assess the accuracy of diagnostic tests. Accuracy refers to the amount of agreement between the results of the test under evaluation (index test) and the results of a reference standard or test. The generally recommended approach is to use a prospective cohort design in patients who are suspected of having the disease of interest, in which each individual undergoes the index and same reference standard tests. This approach presents several challenges, including the problems that can arise with the verification of the index test results by the preferred reference standard test, the choice of cutoff value in case of a continuous index test result, and the determination of how to translate accuracy results to recommendations for clinical use. This first in a series of 4 reports presents an overview of the designs of single-test accuracy studies and the concepts of specificity, sensitivity, posterior probabilities (i.e., predictive values) for the presence of target disease, ROC curves, and likelihood ratios, all illustrated with empirical data from a study on the diagnosis of suspected deep venous thrombosis. Limitations of the concept of the diagnostic accuracy for a single test are also highlighted. CONCLUSIONS: The prospective cohort design in patients suspected of having the disease of interest is the optimal approach to estimate the accuracy of a diagnostic test. However, the accuracy of a diagnostic index test is not constant but varies across different clinical contexts, disease spectrums, and even patient subgroups.