Evidence map›Paper›PMID 40580109›Full record

ArticleNeuro-oncology2025

Assessing time-trend bias in glioblastoma prognosis over 2 decades of clinical trials.

Giacomo Sferruzza, Karthik Desingu, Andrés Cubero Cruz, Gaetano Finocchiaro

Abstract read
In one paragraph

Article in Neuro-oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Giacomo SferruzzaVita-Salute San Raffaele University, Milan, Italy.ORCID 0000-0003-2360-4803
Karthik DesinguDepartment of Biomedical Engineering, Yale University, New Haven, Connecticut, USA.
Andrés Cubero CruzDepartment of Biomedical Engineering, Yale University, New Haven, Connecticut, USA.
Gaetano FinocchiaroNeurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.ORCID 0000-0003-3583-4040

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe time-trend bias represents a potential limitation in the use of external controls in glioblastoma (GBM) trials. In this study, we assessed whether outcomes for newly diagnosed GBM (ndGBM) patients treated with the standard Stupp protocol in clinical trials have changed over the past 2 decades.

methodsWe retrieved individual patient-survival pseudo-data from Stupp-protocol arms reported in trials published over the last 20 years. Survival distributions were approximated using Weibull distributions, and an Accelerated Failure Time model was used to evaluate any potential time-trend by correcting for identified key prognostic factors.

resultsMGMT methylation status and Karnofsky Performance Status emerged as the main determinants of survival differences among clinical trials. Both in a multivariable regression that included all candidate prognostic factors and after adjustment for the main determinants, the publication year showed no impact on the outcome of the Stupp-protocol control arms. The performance of the model was validated using 3 independent Phase III cohorts, providing additional evidence for the absence of time-trend bias.

conclusionsNo evidence of time-trend bias was observed in Phase III GBM trials over the past 2 decades once major prognostic factors were accounted for.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsBrain NeoplasmsGlioblastomaBiasClinical Trials as TopicClinical Trials, Phase III as TopicDNA Modification MethylasesFemaleHumansMaleMiddle AgedPrognosisSurvival RateTime FactorsDNA Modification Methylasesglioblastomahistorical controlsStupp protocoltime-trend bias

Identifiers

PMID40580109
PMCPMC12908477

What Socratic 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 Socratic graph.