Early prediction of clinical and functional outcome in schizophrenia

Abstract The objective of this paper was to investigate the prognostic and predictive value of a small panel of independent and clinically important factors based on symptom improvement, baseline cognitive impairment, and weight change during the early treatment phase. Methods The study sample was based on a double-blind, 6-month continuation study of ziprasidone and olanzapine ( N =94). We developed a parsimonious 6-month GAF prediction function using a logistic regression model, and evaluated its predictive accuracy and performance using bootstrap estimates of c -statistics and error in predicted probability. Results At up to 6 months of follow-up, 52 (55%) of all subjects treated with ziprasidone or olanzapine met the responder criterion of ≥50% improvement in GAF. At Week 2 (acute phase), the majority of ziprasidone (75%) and olanzapine (70%) patients showed greater than 25% improvement in the BPRS psychotic symptom subscale score. These early psychotic symptom responders (Week 2) showed significantly greater improvement in global functioning than early non-responders at all time points (Week 6 and Month 6) (all p 's p 's c -statistics=0.8598). Conclusions Our findings suggest that a parsimonious model incorporating a psychotic symptom assessment score, baseline neurocognitive performance, and risk of weight gain can be developed for predicting patients' likelihood of achieving favorable, long-term treatment outcomes.