Evidence map›Paper›PMID 40628175›Full record

ArticleEuropean journal of cancer (Oxford, England : 1990)2025

Reproducibility of statistically significant phase III oncology trials: An In Silico meta-epidemiological analysis.

Alexander D Sherry, Pavlos Msaouel, Avital M Miller, Timothy A Lin, Joseph Abi Jaoude, Ramez Kouzy, Adina H Passy, Tomer Meirson, Nikolaos Ignatiadis, Zachary R McCaw and 2 more

Abstract read
In one paragraph

Article in European journal of cancer (Oxford, England : 1990), 2025. 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

12 authors.

Alexander D SherryDepartment of Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Radiation Oncology, Mayo Clinic, Rochester, MN, USA. Electronic address: sherry.alexander2@mayo.edu.
Pavlos MsaouelDepartment of Genitourinary Medical Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Avital M MillerDepartment of Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Timothy A LinDepartment of Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Joseph Abi JaoudeDepartment of Radiation Oncology, Stanford University, Stanford, CA, USA.
Ramez KouzyDepartment of Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Adina H PassyDepartment of Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Tomer MeirsonDavidoff Cancer Center, Rabin Medical Center-Beilinson Hospital, Petach Tikva, Israel.
Nikolaos IgnatiadisDepartment of Statistics and Data Science Institute, University of Chicago, Chicago, IL, USA.
Zachary R McCawInsitro, South San Francisco, CA, USA; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Erik van ZwetDepartment of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands.
Ethan B LudmirDepartment of Gastrointestinal Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Kathrin Milbury · 1985 to 2026
$290.8M
NCI NIH HHS P30 CA016672
6 · The paper itself

Abstract

purposeThe conventional assumption that P values ≤ 0.05 imply reproducible effects has come under recent criticism. This concern is particularly relevant in oncology, as phase III oncology trials, which directly inform practice, are usually not repeated. Using advanced modeling techniques, we investigated the relationship between P values and reproducibility in oncology.

methodsWe obtained the signal-to-noise ratio distribution in phase III oncology using outcomes from 632 two-arm superiority trials enrolling 496,219 patients. With this distribution, we estimated successful replication probability as the probability that a replicate trial, having the same design, effect size, and standard error, would have a two-sided P ≤ 0.05 and the same effect directionality as the original trial. We also estimated the following: the probability that the estimated effect had the same direction as the true effect (i.e., correct sign probability); the probability that the 95 % CI covered the true effect (i.e., coverage probability), and the ratio of the observed estimated effect to the true effect (i.e., exaggeration factor).

resultsThe median exaggeration factor across all trials was 1.09 (IQR, 0.80-1.61). When P ≤ 0.05 in the original trial, mean correct sign probabilities were ≥ 97 % and mean coverage probabilities were between 93 % and 96 %. However, effects at P of 0.05, 0.01, and 0.001 had mean replication probabilities of 43 % (95 % CI: 35-45 %), 60 % (95 % CI: 53-61 %), and 77 % (95 % CI: 71-79 %), respectively. For trials with an overall survival primary endpoint that led directly to regulatory approval, the median replication probability was 66 %. A user-friendly web interface is provided to facilitate estimation of replication probabilities of individual trials.

conclusionsWhile the direction of observed effects is likely correct when P ≤ 0.05, treatment effects at P of 0.05 in phase III oncology trials are unlikely to be replicated successfully. By itself, statistical significance should not be equated with high replication probability.

Indexed as

Clinical Trials, Phase III as TopicComputer SimulationMedical OncologyNeoplasmsHumansReproducibility of ResultsCancerClinical trialsPhase IIIP valuesReplicationReproducibilityResearch

Identifiers

PMID40628175
PMCPMC12256131

What Socratic holds

Textmetadata
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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 Socratic graph.