Evidence map›Paper›PMID 42723605›Full record

ArticleClinical trials (London, England)2026

New oncology trial designs and equipoise: Commentary on Heynemann et al.

Jonathan Kimmelman

Abstract readComment
In one paragraph

Article in Clinical trials (London, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Jonathan KimmelmanDepartment of Equity, Ethics and Policy, School of Population and Global Health, McGill University, Montreal, QC, Canada.ORCID 0000-0003-1614-6779

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This essay responds to Heymemann et al.'s analysis of the applicability of clinical equipoise to emerging trial methods in cancer. Briefly, I argue that equipoise presses study designers to conduct trials at the point of maximum community uncertainty. Accordingly, equipoise encourages maximum information gain per patient enrolled (or inversel, minimal patient burden per gain in information). As such, equipoise is as much a condition for the ethical conduct of new study designs as it is for old ones. I close by suggesting that, whereas Heymemann et al. suggest new trial designs present a challenge to the operationalization of equipoise, I argue that equipoise presents a challenge for those wishing to operationalize new trial designs.

Indexed as

Clinical Trials as TopicMedical OncologyNeoplasmsResearch DesignTherapeutic EquipoiseHumansadaptive trialsclinical trialsequipoiseoncologyplatform trialsseamless trials

Identifiers

PMID42723605
PMCPMC13624336

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.