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Can a ‘true’ effect be built on a ‘wrong’ model?

Published online by Cambridge University Press:  02 January 2018

Florian Naudet*
Affiliation:
INSERM U669, Paris, Université de Rennes 1, Unité de Recherche Universitaire EM-425 Behavior and Basal Ganglia, Rennes, and Centre Hospitalier Guillaume Régnier, Service Hospitalo-Universitaire de Psychiatrie, Rennes, France. Email: floriannaudet@gmail.com
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Abstract

Type
Columns
Copyright
Copyright © Royal College of Psychiatrists, 2012 

Thase et al use a sophisticated model to assess the ‘true’ effect of active antidepressant therapy v. placebo. Reference Thase, Larsen and Kennedy1

Health authorities generally evaluate the efficacy of new medications from randomised controlled trials (RCTs) v. placebo which are well documented and rely on such a simple statistical paradigm that they can resist the major financial conflicts of interest inherent in the evaluation of pharmaceuticals. Concerning antidepressants, these studies generally identify small, average drug–placebo differences. Reference Kirsch, Deacon, Huedo-Medina, Scoboria, Moore and Johnson2

Using statistical modelling, other authors have addressed the question of outcome measurement Reference Moncrieff and Kirsch3 and found that efficacy is better understood as a large effect in a subgroup of patients. This is consistent with the common clinical viewpoint.

However, Thase et al's model leads to a curious phenomenon: everything happens as if some patients were considered as non-benefiters, whereas their final score is markedly less than the score for patients considered as benefiters. As they state, ‘Essentially, all models are wrong, but some are useful’ a ‘true’ effect of active antidepressant v. placebo be built on such a ‘wrong’ model?

Surely not for a health authority. Nevertheless, it could be useful for researchers and clinicians as it generates hypotheses on the manner in which antidepressants are different from placebo. In this view, it is necessary to go further and compare the characteristics of benefiters with non-benefiters with two additional perspectives:

  1. 1 to perform RCTs in populations of benefiters in order to maximise the signal and to minimise the noise – this could help to limit the number of ‘negative studies’;

  2. 2 to use antidepressants only in this subpopulation of treatment benefiters and to propose alternatives to other patients (e.g. psychotherapy, repetitive transcranial magnetic stimulation, electroconvulsive therapy).

Finally, Thase et al's model is based on RCTs which if applied to major depressive disorder raises fundamental questions regarding internal Reference Ioannidis4 and external validity. Reference Naudet, Maria and Falissard5 Even if a ‘true’ effect of active antidepressants exists, I'm not sure that it could be derived from RCTs.

Footnotes

Declaration of interest

F.N. was a reviewer for the first draft of Thase et al's manuscript. The above comments were in his review but were not included in their paper.

References

1 Thase, ME, Larsen, KG, Kennedy, SH. Assessing the ‘true’ effect of active antidepressant therapy v. placebo in major depressive disorder: use of a mixture model. Br J Psychiatry 2011; 199: 501–7.CrossRefGoogle ScholarPubMed
2 Kirsch, I, Deacon, BJ, Huedo-Medina, TB, Scoboria, A, Moore, TJ, Johnson, BT. Initial severity and antidepressant benefits: a meta-analysis of data submitted to the Food and Drug Administration. PLoS Med 2008; 5: e45.CrossRefGoogle ScholarPubMed
3 Moncrieff, J, Kirsch, I. Efficacy of antidepressants in adults. BMJ 2005; 331: 155–7.CrossRefGoogle ScholarPubMed
4 Ioannidis, JP. Effectiveness of antidepressants: an evidence myth constructed from a thousand randomized trials? Philos Ethics Humanit Med 2008; 3: 14.CrossRefGoogle ScholarPubMed
5 Naudet, F, Maria, AS, Falissard, B. Antidepressant response in major depressive disorder: a meta-regression comparison of randomized controlled trials and observational studies. PLoS One 2011; 6: e20811.CrossRefGoogle ScholarPubMed
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