Withdrawal effects confounding in clinical trials: another sign of a needed paradigm shift in psychopharmacology research

Abstract

Randomized controlled trials’ ability to produce evidence useful for people to decide whether to take, continue taking, or stop taking psychotropic drugs has been intensely critiqued, along with the trials’ commercial, ideological, and regulatory contexts. This article applies the critique to the topic of withdrawal effects confounding the outcomes of relapse-prevention trials where prescribed psychotropic drugs are discontinued. Until recently, the complexity and reach of withdrawal and post-withdrawal effects were neglected by mainstream psychiatry, but not by lay users of prescribed psychotropics. This article discusses withdrawal effects as part of the pharmacology of psychotropic drugs but shaped by psychosocial factors, and possibly shaping the presentation of psychological distress generally. It outlines biases and misconceptions in assumptions, design, and reporting of general efficacy trials and findings from a recent review of 80 discontinuation trials. In theory, relapse-prevention trials are tautological and exaggerate efficacy. In publications, they pay little attention to the central feature of their design, favor abrupt or rapid discontinuations, do not attend to environmental factors, and provide insufficient data to allow re-analyses. Thus, relapse-prevention RCTs likely confound the detection of their main outcome of interest: “relapse.” Using slower tapers, active placebo controls, and specific covariates in analyses would reduce the risk of withdrawal confounding, and better reporting would reduce the opaqueness of trials. The crisis in psychopharmacology is fueled partly by the disconnect between claims of therapeutic efficacy from so-called best-evidence methods despite unchanging population-level indicators of psychiatric sickness. Only by “stacking the deck” against trial sponsors’ hoped-for outcomes can psychopharmacology trials regain scientific credibility.

The role of lumateperone in the treatment of schizophrenia

“…Future clinical trials to detect relapse will benefit from the careful design, checking cognitive 85 and other adverse effects, 78,86,87 cautious discontinuation, and measurement of environmental influences to minimize the confounding effects of withdrawal. 88…”

“…34,83,84 Future directions Future clinical trials to detect relapse will benefit from the careful design, checking cognitive 85 and other adverse effects, 78,86,87 cautious discontinuation, and measurement of environmental influences to minimize the confounding effects of withdrawal. 88 When data from multiple centers without financial interest in lumateperone for schizophrenia are available, well-conducted systematic reviews 34,83,84 can be conducted. Future reviews will be enhanced by the inclusion of postmarketing surveillance for adverse effects.…”

From theory to practice: challenges and rewards of implementing ketogenic metabolic therapy in mental health

“…It is crucial to emphasize that the field of KMT for mental health care is still evolving, and attempting to profile and determine who should or should not have access to KMT based on incomplete research findings or naïve clinical practices in the real world can be premature and potentially detrimental. Until clinical practice among prescribers working with this population matures, it becomes clear that, particularly in the context of psychiatric medications, a clear understanding of who does and does not benefit may not yet be possible ( 11 ). This will be a continued area of research as scientists attempt to discern what phenotypes and presentations of mental illness benefit most.…”

Dispositions and Causality Assessment in Pharmacovigilance: Proposing the Dx3 Approach for Assessing Causality with Small Data Sets

“…Within this approach, therefore, evidence of a plausible mechanism of action is better evidence of causality than the mere identification of a correlation [ 9 ]. This view has been adopted by the medical community [ 10 – 14 ], including in issues of drug safety [ 15 , 16 ]. The Dx3 approach applies the same framework to causality assessment in pharmacovigilance.…”