Evidence map›Paper›PMID 34279730›Full record

ArticleEuropean journal of epidemiology2021

Improving the reporting of non-inferiority trials by incorporating non-efficacy benefits: not all non-inferiority trials are created equal.

Sergio A Acuna, Fahima Dossa, Tyler R Chesney

Abstract read
PubMed Publisher
In one paragraph

Article in European journal of epidemiology, 2021. 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. Clinical equivalence and non-inferiority within health technology assessment.The European journal of health economics : HEPAC : health economics in prevention and care · 2026
    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

3 authors.

Sergio A AcunaDivision of General Surgery, Department of Surgery, University of Toronto, 2075 Bayview Avenue, Room H3-17, Toronto, ON, M4N 3M5, Canada. sergio.acuna@utoronto.ca.ORCID http://orcid.org/0000-0002-6266-2136
Fahima DossaDivision of General Surgery, Department of Surgery, University of Toronto, 2075 Bayview Avenue, Room H3-17, Toronto, ON, M4N 3M5, Canada.
Tyler R ChesneyDivision of General Surgery, Department of Surgery, University of Toronto, 2075 Bayview Avenue, Room H3-17, Toronto, ON, M4N 3M5, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-inferiority trials are used to test if a novel intervention is not worse than a standard treatment by more than a prespecified amount, the non-inferiority margin (ΔNI). The ΔNI indicates the amount of efficacy loss in the primary outcome that is acceptable in exchange for non-efficacy benefits in other outcomes. However, non-inferiority designs are sometimes used when non-efficacy benefits are absent. Without non-efficacy benefits, loss in efficacy cannot be easily justified. Further, non-efficacy benefits are scarcely defined or considered by trialists when determining the magnitude of and providing justification for the non-inferiority margin. This is problematic as the importance of a treatment's non-efficacy benefits are critical to understanding the results of a non-inferiority study. Here we propose the routine reporting in non-inferiority trial protocols and publications of non-efficacy benefits of the novel intervention along with the reporting of non-inferiority margins and their justification. The justification should include the specific trade-off between the accepted loss in efficacy (ΔNI) and the non-efficacy benefits of the novel treatment and should describe whether patients and other relevant stakeholders were involved in the definition of the ΔNI.

Indexed as

Clinical trialNon-inferioritySample size calculationStudy design

Identifiers

What OpenQuestion holds

Textmetadata
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.