Evidence map›Paper›PMID 30997716›Full record

ArticleInternational journal of methods in psychiatric research2019

Power behind the throne: A clinical trial simulation study evaluating the impact of controllable design factors on the power of antidepressant trials.

Astrid Chevance, Florian Naudet, Raphaël Gaillard, Philippe Ravaud, Raphaël Porcher

Abstract read
In one paragraph

Article in International journal of methods in psychiatric research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Astrid ChevanceInserm U1153 Team METHODS, University Paris Descartes, Service Hospitalo-Universitaire de Psychiatrie, Centre Hospitalier Sainte-Anne, Paris, France.ORCID 0000-0002-0852-4322
Florian NaudetMeta-research Innovation Center (METRICS), Stanford University, Palo Alto, California.
Raphaël GaillardInserm U894, Centre de Psychiatrie et Neurosciences, University Paris Descartes, Service Hospitalo-Universitaire de Psychiatrie, Centre Hospitalier Sainte-Anne, Paris, France.
Philippe RavaudInserm U1153, Team METHODS, Cochrane France, University Paris Descartes, Centre d'Épidémiologie Clinique, Hôtel-Dieu, Assistance Publique-Hôpitaux de Paris, Paris, France.
Raphaël PorcherInserm U1153, Team METHODS, University Paris Descartes, Centre d'Épidémiologie Clinique, Hôtel-Dieu, Assistance Publique-Hôpitaux de Paris, Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate the impact of controllable design factors on the power of antidepressants trials.

methodsUsing clinical trial simulation (CTS), we analyzed the combined impact on the power of trials of controllable design factors (sample size, outcome metrics, and disease severity at inclusion) and uncontrollable parameters (heterogeneity of diseases labeled "depression" in the source population and selective effects of drugs on items of the Hamilton Depression Rating Scale [HDRS], the most used outcome measurement tool). We elaborated 3,840 scenarios calibrated with real data, particularly the publication bias-corrected effect size.

resultsFor an effect size of 0.26, simulations revealed that in trials with ≤650 participants, power was less than 80%. Among the tested outcome metrics, the "remission" outcome provided more robustness for sample heterogeneity, whereas the continuous outcome "HDRS changes" provided more robustness when investigating drugs with a selective effect on the HDRS items. For the "remission" outcome, the power of trials increased with increasing HDRS threshold at inclusion but decreased with the outcomes "response" and "HDRS changes. Drugs with a selective effect on the HDRS items could not reach the same power as for the reference drug.

conclusionOur study allows for drawing recommendations to avoid underpowered trials of antidepressants.

Indexed as

Models, StatisticalRemission InductionAntidepressive AgentsClinical Trials as TopicDepressive DisorderHumansOutcome Assessment, Health CareResearch DesignAntidepressive Agentsantidepressantsclinical trialsdepressionmethodologymodeling

Identifiers

PMID30997716
PMCPMC6877224

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.