Drug attitude as predictor for effectiveness in first-episode schizophrenia: Results of an open randomized trial (EUFEST)

Abstract

Effectiveness has become more and more important as a comprehensive outcome measure for (long-term) treatment in schizophrenia. Early predictors to identify patients at a high risk for not succeeding the initiated treatment would be very useful. Discontinuation of the initiated treatment was used as criterion for effectiveness and patients' drug attitude was shown to be predictive for non-adherence or discontinuation of long-term treatment in schizophrenia. Accordingly, the predictive validity of the Drug Attitude Inventory (DAI) for effectiveness should be evaluated. Based on a sub-sample of patients from the EUFEST study for whom DAI assessments were available significant predictors for effectiveness as measured by discontinuation of initiated treatment were identified based on a logistic and a Cox-regression analysis. A Receiver-Operating Characteristic- (ROC-) analysis was conducted for the DAI, prognostic / diagnostic parameters (sensitivity, specificity) were calculated and a cut-off value suggested. In a sample of 228 first-episode patients, the DAI score was the most powerful predictor for effectiveness (p<0.001) besides two other significant predictors (PANSS-positive score and sexual side effects). The ROC-analysis revealed an area under the curve of 0.64 (p<0.001). The suggested cut-off point of about 20 yielded a sensitivity of 70-75% and a specificity of 40-45%. Study results indicate that the Drug Attitude Inventory, filled in by patients early in treatment seems to be a valid predictor for effectiveness as measured by discontinuation of the initiated treatment. DAI scores could also serve as an (differential) indicator for the need of enhanced treatment monitoring. These findings have to be validated in other (first-episode) samples.