Abstract
Drug trials for negative symptoms in schizophrenia select patients based on the severity and stability of negative symptoms, using criteria that are not suitable for trials of acute exacerbation of schizophrenia. Here we present a method to prognostically enrich subjects having a predefined factor structure in PANSS and apply it to the measurement of negative symptoms specifically in trials of acute schizophrenia. A vector of 1335 elements based on between- and within-item variances, covariances, and differences of PANSS items was created to calculate an index of heterogeneity and to enrich for a predetermined symptom construct in PANSS. Using prerandomization PANSS scores across N = 4876 subjects in 13 trials of acute schizophrenia, we demonstrate an ability to select for a subpopulation having the greatest amount of variance explained across the 7-items of the Marder PANSS negative symptom (MPNS) construct. Network analyses on subjects enriched for MPNS construct confirm that negative symptoms were most influential in overall psychopathology, distinct from subjects without the MPNS construct. As expected for D2 antagonists, drug-placebo differences on negative symptoms with lurasidone were not specific to the subpopulation having the MPNS construct. In contrast, the novel TAAR1 agonist ulotaront demonstrated specific improvements in negative symptoms which were greatest in the MPNS subpopulation. These results demonstrate the utility of a novel prognostic enrichment strategy that can address heterogeneity in clinical trials, where patients can be selected on the basis of a greater likelihood of having the measured symptom construct (negative symptoms) related to the disorder (schizophrenia). ClinicalTrials.gov Identifiers: NCT0296938, NCT00088634, NCT00549718, NCT00615433, NCT00790192.
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