Abstract

As biomarkers are lacking, multi‐item questionnaire‐based tools like the Positive and Negative Syndrome Scale (PANSS) are used to quantify disease severity in schizophrenia. Analyzing composite PANSS scores as continuous data discards information and violates the numerical nature of the scale. Here a longitudinal analysis based on Item Response Theory is presented using PANSS data from phase III clinical trials. Latent disease severity variables were derived from item‐level data on the positive, negative, and general PANSS subscales each. On all subscales, the time course of placebo responses were best described with Weibull models, and dose‐independent functions with exponential models to describe the onset of the full effect were used to describe paliperidone's effect. Placebo and drug effect were most pronounced on the positive subscale. The final model successfully describes the time course of treatment effects on the individual PANSS item‐levels, on all PANSS subscale levels, and on the total score level.

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