Introduction
neuropathic pain, cancer pain, psychiatric, Montgomery-Asberg Depression, MDD, depressive disorders
PARKINSON DISEASE, MULTIPLE SCLEROSIS, DISORDERS
The unpredictable high placebo response rate is one of the major factor associated with the failure of randomized clinical trials in psychiatric disorders, neuropathic pain, cancer pain, multiple sclerosis, Parkinson disease, and more [Several methods to control the placebo response without undermining the observed response to active treatment have been attempted in clinical trials, such as exclusion of placebo responders during placebo lead-in periods [In RCTs, the placebo response usually refers to the degree of clinical improvement reported by patients assigned to the placebo arm, while the placebo effect (PE) represents an improvement in clinical outcomes due to the expectancies of positive treatment or intervention [The propensity weighting methodology was proposed as a novel method of causal inference that aims at reducing imbalances between arms [In this paper, we propose a novel methodology for evaluating the outcomes of a RCT in major depressive disorders (MDD) accounting for the predicted individual propensity probability. The principle is to use the estimated individual propensity to respond to placebo as a weight in the mixed-effect model for repeated measures (MMRM) analysis conducted to assess the TE. The TE is defined as the baseline-corrected change from placebo at study end. The higher is the individual probability of showing a placebo response, the lower will be the contribution of this subject in the assessment of TE. The expected effect of the MMRM weighed analysis will be to enhance the ability to detect a therapeutic signal as the contribution of subjects with high placebo responders will be minimized by the weighting procedure. The overall effect will be to enhance signal detection, with an increase of the effect size due to a better control of the inter-individual variability in the propensity to respond to placebo.The estimation of the individual propensity probability to respond to placebo will be conducted using the Montgomery-Asberg Depression Rating Scale (MADRS) [Among the different methods used to implement AI, the multilayer perceptrons (MLP) artificial neural network (ANN) method has been shown to have superior and robust classification performance with respect to other methodologies, such as logistic analysis, random forest, and support vector machine [