Evidence map›Paper›PMID 37365584›Full record

ReviewBMC medical research methodology2023

Interpretation of active-control randomised trials: the case for a new analytical perspective involving averted events.

David T Dunn, Oliver T Stirrup, Sheena McCormack, David V Glidden

Open access · goldAbstract readReview
In one paragraph

Review in BMC medical research methodology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
3.4field-weighted citation impact, top 7% of its field
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

7 citing papers in PubMed, 2 syntheses or guidelines pooled it, 10 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Sample size estimation for the averted events ratio.Clinical trials (London, England) · 2026
    Article
  5. Article
  6. Article
  7. 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

4 authors at 3 institutions in 2 countries.

David T DunnInstitute for Global Health, University College London, London, UK. d.dunn@ucl.ac.uk.
Oliver T StirrupInstitute for Global Health, University College London, London, UK.
Sheena McCormackMRC Clinical Trials Unit, University College London, 90 High Holborn, London, WC1V 6LJ, UK.
David V GliddenDepartment of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA.
University College London · GBMRC Clinical Trials Unit at UCL · GBUniversity of California, San Francisco · US

Funding

Statistical methods for clinical trials of novel PrEP agentsR01AI143357 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GLIDDEN, DAVID V. · 2018 to 2021
$483k
Medical Research Council MC_UU_00004/03Medical Research Council MC_UU_00004/07NIAID NIH HHS R01 AI143357
6 · The paper itself

Abstract

Active-control trials, where an experimental treatment is compared with an established treatment, are performed when the inclusion of a placebo control group is deemed to be unethical. For time-to-event outcomes, the primary estimand is usually the rate ratio, or the closely-related hazard ratio, comparing the experimental group with the control group. In this article we describe major problems in the interpretation of this estimand, using examples from COVID-19 vaccine and HIV pre-exposure prophylaxis trials. In particular, when the control treatment is highly effective, the rate ratio may indicate that the experimental treatment is clearly statistically inferior even when it is worthwhile from a public health perspective. We argue that it is crucially important to consider averted events as well as observed events in the interpretation of active-control trials. An alternative metric that incorporates this information, the averted events ratio, is proposed and exemplified. Its interpretation is simple and conceptually appealing, namely the proportion of events that would be averted by using the experimental treatment rather than the control treatment. The averted events ratio cannot be directly estimated from the active-control trial, and requires an additional assumption about either: (a) the incidence that would have been observed in a hypothetical placebo arm (the counterfactual incidence) or (b) the efficacy of the control treatment (relative to no treatment) that pertained in the active-control trial. Although estimation of these parameters is not straightforward, this must be attempted in order to draw rational inferences. To date, this method has been applied only within HIV prevention research, but has wider applicability to treatment trials and other disease areas.

Indexed as

COVID-19HIV InfectionsCOVID-19 VaccinesHumansProportional Hazards ModelsRandomized Controlled Trials as TopicTreatment OutcomeCOVID-19 VaccinesActive-controlAvertedEstimandNon-inferiorityRelative efficacy

Identifiers

PMID37365584
PMCPMC10294491
OpenAlexW4382141266

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.