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A conceptual framework for addressing treatment withdrawal effects across the evidence pathway
Alexander G Mathioudakis1, Mike Clarke2, Jørgen Vestbo3
1Division of Immunology, Immunity to Infection and Respiratory Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom; The North West Lung Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom.
Background:
Treatment withdrawal effects represent a transient increase in clinical risk following treatment discontinuation that exceeds what would be expected from loss of treatment effect alone. They have been described across multiple therapeutic areas, yet remain insufficiently recognized across evidence generation, synthesis, and translation into practice.
Methodological Challenge:
When unacknowledged, withdrawal effects may distort estimates of benefit and harm in randomized trials and observational studies, obscure treatment-covariate interactions, propagate bias through evidence synthesis, and undermine the applicability of guideline recommendations to routine practice.
Conceptual Framework:
We summarize methodological problems introduced by unrecognized withdrawal effects and propose a conceptual framework highlighting how existing methodological approaches can be applied more explicitly to identify, interpret, and account for withdrawal-related risk across the evidence pathway.
Plain Language Summary:
When some long-term treatments are stopped, patients may feel worse or develop health problems, beyond what would be expected from simply losing the benefit of the treatment. These are called treatment withdrawal effects. They are not rare and can occur after stopping many treatments, but they are not considered enough when studies are designed, analyzed, or used to make recommendations about treatment. This matters because research studies may give false impressions about how well treatments work, or how safe they are, if they do not consider what happens when treatments are interrupted or stopped. For example, if patients worsen soon after stopping a treatment, this may be interpreted as proof that continuing the treatment is beneficial, when it may instead be a withdrawal effect. Evidence reviews and clinical guidelines may then carry this problem forward, leading to recommendations based on an inaccurate picture of benefit and harm. This may mean that some treatments appear more useful or safer than they really are, while others may be undervalued. This article explains how withdrawal effects can affect research at different stages, from individual studies to evidence reviews and treatment guidelines. It also suggests ways to identify and account for these risks. Addressing withdrawal effects more systematically could help research give a more accurate picture of how treatments work, how safe they are, and how they should be used in practice. Because this is a complex problem across the whole research pathway, progress is likely to require international collaboration among researchers, trial teams, pharmaceutical and other healthcare developers, evidence reviewers, guideline developers, regulators, funders, clinicians, and patients.
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