Bayesian modelling and ROC analysis to predict placebo responders using clinical score measured in the initial weeks of treatment in depression trials

British Journal of Clinical Pharmacology

Volumn 63, Issue 5, 2007, Pages 595-613

  Gomeni, Roberto ^a   Merlo Pich, Emilio ^a  

^a GSK   (Italy)

Author keywords

Bayesian hierarchical model; Enrichment strategy; Modelling placebo response; Posterior probability; ROC curve analysis

Indexed keywords

ANTIDEPRESSANT AGENT; PAROXETINE; PLACEBO;

ARTICLE; BAYES THEOREM; CLINICAL TRIAL; DATA ANALYSIS; DEPRESSION; DRUG RESPONSE; HAMILTON SCALE; HUMAN; LEARNING; LOGISTIC REGRESSION ANALYSIS; MATHEMATICAL MODEL; MENTAL PATIENT; METHODOLOGY; PATIENT CODING; PRIORITY JOURNAL; PROGNOSIS; RATING SCALE; RECEIVER OPERATING CHARACTERISTIC; SCORING SYSTEM; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; TREATMENT RESPONSE;

ANTIDEPRESSIVE AGENTS; DEPRESSIVE DISORDER, MAJOR; EPIDEMIOLOGIC METHODS; HUMANS; PLACEBO EFFECT; PSYCHIATRIC STATUS RATING SCALES; RESEARCH DESIGN; TREATMENT OUTCOME;

EID: 34247325672     PISSN: 03065251     EISSN: 13652125     Source Type: Journal    
DOI: 10.1111/j.1365-2125.2006.02815.x     Document Type: Article

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