A novel way to quantify schizophrenia symptoms in clinical trials. (19th September 2020) - Medvedev, Oleg N.; Berk, Michael; Dean, Olivia M.; Brown, Ellie; Sandham, Margaret H.; Dipnall, Joanna F.; McNamara, Robert K.; Sumich, Alexander; Krägeloh, Christian U.; Narayanan, Ajit; Siegert, Richard J.
Abstract: Background: A major problem in quantifying symptoms of schizophrenia is establishing a reliable distinction between enduring and dynamic aspects of psychopathology. This is critical for accurate diagnosis, monitoring and evaluating treatment effects in both clinical practice and trials. Materials and methods: We applied Generalizability Theory, a robust novel method to distinguish between dynamic and stable aspects of schizophrenia symptoms in the widely used Positive and Negative Symptom Scale (PANSS) using a longitudinal measurement design. The sample included 107 patients with chronic schizophrenia assessed using the PANSS at five time points over a 24‐week period during a multi‐site clinical trial of N‐Acetylcysteine as an add‐on to maintenance medication for the treatment of chronic schizophrenia. Results: The original PANSS and its three subscales demonstrated good reliability and generalizability of scores (G = 0.77‐0.93) across sample population and occasions making them suitable for assessment of psychosis risks and long‐lasting change following a treatment, while subscales of the five‐factor models appeared less reliable. The most enduring symptoms represented by the PANSS were poor attention, delusions, blunted affect and poor rapport. More dynamic symptoms with 40%‐50% of variance explained by patient transient state including grandiosity, preoccupation, somatic concerns, guilt feeling and hallucinatory behaviour. Conclusions: Identified dynamic symptoms are more amendable to change and should be the primary target of interventions aiming at effectively treating schizophrenia. Separating out the dynamic symptoms would increase assay sensitivity in trials, reduce the signal to noise ratio and increase the potential to detect the effects of novel therapies in clinical trials.