Scientific Poster Publication made on June 2017 at the Promoting Statistical Insight Conference, London (UK).
In analgesia randomized clinical trials (RCTs), the magnitude and the variability of the placebo response have a negative influence when testing the statistically significant superiority of active compounds compared to placebo. Furthermore, the magnitude of this effect has tended to increase over time, including in peripheral neuropathic pain (PNP) trials. The main objective of this study was to investigate parameters influencing the placebo response as a way to control this major confounding factor. Eighty-seven PNP patients were enrolled and blindly given a placebo
We
approach: Gaussian processes with a linear kernel. The covariates used in the model were
(pvalue< 0.001).
Using the model predictions as a covariate could thus reduce the placebo variance by 30% in
subsequent PNP studies. This reduction of variance could in turns lead to