Minimum clinically important difference in the positive and negative syndrome scale with data from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE)

摘要

Context: Establishing the minimum clinically important difference in the Positive and Negative Syndrome Scale (PANSS) is important to the interpretation of the research and clinical work conducted with this scale. Method: This study employed both anchor-based and distributive methods to estimate the minimum clinically important difference for the PANSS by using data from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) schizophrenia trial, a large, multicenter trial for patients with schizophrenia. By using an equipercentile method, data from 1,442 individuals linked PANSS scores with both clinician and patient ratings on the Clinical Global Impressions scale (CGI). Data were also used to investigate the magnitude of the standard error of measurement (SEM), offering another estimate of the minimum clinically important difference. Results: Cross-sectional, clinician-rated CGI-Severity of illness scores of 1 through 7 linked to PANSS scores of 32.4, 42.2, 57.5, 74.5, 93.0, 110.9, and 131.0, respectively. The minimum clinically important difference for PANSS scores using this scale equaled a 15.3-point (34.0%) change from baseline. A 1.96 SEM on the PANSS corresponded to a 16.5-point (36.2%) change from baseline. The minimum clinically important difference for a subsample with above-median baseline PANSS scores was 38% higher than a sample with lower baseline scores. With the patient-rated CGI as the anchor, PANSS scores were higher for CGI scores of 1 through 4, and the minimum clinically important difference was lower, 11.2 points (24.6%). Conclusion: Minimum clinically important difference estimates from a longer-term effectiveness trial were consistent with previous efforts from shorter-term efficacy trials. Minimum clinically important difference estimates can help clinicians and researchers design future studies and interpret treatment change in future research and clinical work.