Introduction: Evidence-based medicine is the cornerstone of shared-decision making in healthcare today. The public deserves clear, transparent and trust-worthy information on drug efficacy. Yet today, many drugs are prescribed and used without solid evidence of efficacy. Moreover, meta-analyses are the staple to test for drug efficacy and adverse effects, but spins can lead to unconvincing conclusions. In a shared medical decision-making approach, general practitioners need drug assessment to be based on patient-important outcomes. The aim of project Rebuild the Evidence Base (REB) is to bridge the gap between the data needed in clinical practice and the data available from clinical research. Methods and Analysis: The drugs will be assessed on clinical patient important outcomes and for a population. Using the Cochrane tools, we propose to analyse for each population and outcome : 1) a meta-analysis, based on randomised controlled trials (RCTs) with low risk of bias overall ; 2) Confirmatory RCT with low risk of biais overall; 3) Heterogeneity between RCT, and 4) Publication bias assessment. Depending on the results of these analyses, evidence would be rated according to 4 levels: firm evidence, evidence, results to be confirmed (but no evidence) or lack of evidence. Conclusion: Project REB proposes a method for reading and interpreting randomized clinical trials and their meta-analysis to produce quality data for general practitioners to focus on benefit-risk assessment in the interest of patients. If this data does not exist, it could enable clinical research to better its aim.

Aim: The placebo effect and the specific effect are often thought to add up (additive model). Whether this is true or whether there is an interaction between the two, can modify the external validity of a trial. This assumption of additivity was tested by Kleijnen et al. in 1994 but the data produced since then has not been synthetized. In this review, we aimed to systematically review the literature to determine whether additivity held. Methods: We searched Medline and Psychinfo up to 10/01/2019. Studies using the balanced placebo design (BPD), testing two different strengths of placebos, were included. The presence of interaction was evaluated by comparing each group in BPD with analysis of variance or covariance. Results: 30 studies were included and the overall risk of bias was high: four found evidence of additivity and 16 studies found evidence of interaction (seven had evidence of positive additivity). Conclusion: Evidence of additivity between placebo and specific features of treatments was rare in our sample. For ailments that are placebo-responsive, pragmatic trials should be preferred to increase their external validity.