Does reductio ad absurdum have a place in evidence-based medicine?

Understanding the Antidepressant Debate in the Treatment of Major Depressive Disorder

There is a long-standing polemic concerning the usefulness of antidepressants in the treatment of major depressive disorder. In this paper, we propose to highlight some aspects of this controversy by exploring the mutual influence of psychopharmacology and trial methodologies. Indeed, antidepressant efficacy, if not proved, was accepted before antidepressant randomised controlled trials (RCTs) were run. While RCTs became a gold standard to meet the requirements of the regulatory bodies, methodological tools were required to measure outcomes and to test whether antidepressants provide statistically significant benefits as compared with a placebo. All these methodological options have nonetheless introduced fuzziness in our interpretation of study results, in terms of clinical meaningfulness and in terms of transposability to a real life settings. Additionally, selective publication raises concerns about the published literature, and results in many paradoxes. Instead of providing easy answers, the application of the RCT paradigm in MDD raises numerous questions. This is probably in the nature of all scientific studies, but it can be in contradiction with clinicians' expectations, who want to be sure that the treatment will (or will not) work for their individual patients.

From Randomized Controlled Trials of Antidepressant Drugs to the Meta-Analytic Synthesis of Evidence: Methodological Aspects Lead to Discrepant Findings

During the last decade, several meta-analytic studies employing different methodological approaches have had inconsistent conclusions regarding antidepressant efficacy. Herein, we aim to comment on methodological aspects that may have contributed to disparate findings. We initially discuss methodological inconsistencies and limitations related to the conduct of individual antidepressant randomized controlled trials (RCTs), including differences in allocated samples, limitations of psychometric scales, possible explanations for the heightened placebo response rates in antidepressant RCTs across the past two decades as well as the reporting of conflicts of interest. In the second part of this article, we briefly describe the various meta-analyses techniques (e.g., simple random effects meta-analysis and network meta-analysis) and the application of these methods to synthesize evidence related to antidepressant efficacy. Recently published antidepressant metaanalyses often provide discrepant results and similar results often lead to different interpretations. Finally, we propose strategies to improve methodology considering real-world clinical scenarios.

Placebo for depression: we need to improve the quality of scientific information but also reject too simplistic approaches or ideological nihilism

The placebo response plays a major role in psychiatry, particularly in depression. A new network meta-analysis investigates whether the effects of placebo vary in studies comparing fluoxetine and venlafaxine, two widely prescribed antidepressants. Even though data from this article indicate that the effects of placebos do not differ, publication bias cannot be ruled out. The authors use their finding to criticise the paradigm of evidence-based medicine, questioning whether there is anything certain in psychiatry and, more precisely, in the field of antidepressant treatment for major depression. This study stimulates the debate about validity of scientific knowledge in medicine and highlights the importance of considering things from a different perspective. However, the authors' view should be considered with caution. As clinicians, we make decisions every day, integrating individual clinical expertise and patients' preferences and values with the best, up-to-date research data. The quality of scientific information must be improved, but we still think that valid conclusions to help clinical practice can be drawn from a critical and cautious use of the best available, if flawed, evidence.