tailieunhanh - Báo cáo y học: " Identification of early changes in specific symptoms that predict longer-term response to atypical antipsychotics in the treatment of patients with schizophrenia"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành y học dành cho các bạn tham khảo đề tài: Identification of early changes in specific symptoms that predict longer-term response to atypical antipsychotics in the treatment of patients with schizophrenia | Ruberg et al. BMC Psychiatry 2011 11 23 http 1471-244X 11 23 BMC Psychiatry RESEARCH ARTICLE Open Access Identification of early changes in specific symptoms that predict longer-term response to atypical antipsychotics in the treatment of patients with schizophrenia 1 2 1 2 2 2 Stephen J Ruberg Lei Chen Virginia Stauffer Haya Ascher-Svanum Sara Kollack-Walker Robert R Conley John Kane3 Bruce J Kinon2 Abstract Background To identify a simple decision tree using early symptom change to predict response to atypical antipsychotic therapy in patients with Diagnostic and Statistical Manual Fourth Edition Text Revised chronic schizophrenia. Methods Data were pooled from moderately to severely ill patients n 1494 from 6 randomized double-blind trials N 2543 . Response was defined as a 30 reduction in Positive and Negative Syndrome Scale PANSS Total score by Week 8 of treatment. Analyzed predictors were change in individual PANSS items at Weeks 1 and 2. A decision tree was constructed using classification and regression tree CART analysis to identify predictors that most effectively differentiated responders from non-responders. Results A 2-branch 6-item decision tree was created producing 3 distinct groups. First branch criterion was a 2-point score decrease in at least 2 of 5 PANSS positive items Week 2 . Second branch criterion was a 2-point score decrease in the PANSS excitement item Week 2 . Likely responders met the first branch criteria likely nonresponders did not meet first or second criterion not predictable patients did not meet the first but did meet the second criterion. Using this approach response to treatment could be predicted in most patients 92 with high positive predictive value 79 and high negative predictive value 75 . Predictive findings were confirmed through analysis of data from 2 independent trials. Conclusions Using a data-driven approach we identified decision rules using early change in the scores of selected PANSS items .