Evidence map›Paper›PMID 41080207›Full record

ArticleNeuro-oncology practice2025

Disparities in patient enrollment of spinal oncology clinical trials.

Emily Xu, James M Schuster, Anish Butala, Gabrielle W Peters, Alvand Hassankhani, Hayley M Knollman, Colbey W Freeman, Neil R Malhotra

Abstract read
In one paragraph

Article in Neuro-oncology practice, 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

8 authors.

Emily XuDepartment of Neurosurgery, University of Pennsylvania, Philadelphia, PA, USA.
James M SchusterDepartment of Neurosurgery, University of Pennsylvania, Philadelphia, PA, USA.
Anish ButalaDepartment of Radiation Oncology, University of Pennsylvania, Philadelphia, PA, USA.
Gabrielle W PetersDepartment of Radiation Oncology, University of Pennsylvania, Philadelphia, PA, USA.
Alvand HassankhaniDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Hayley M KnollmanDivision of Hematology and Oncology, University of Pennsylvania, Philadelphia, PA, USA.
Colbey W FreemanDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Neil R MalhotraDepartment of Neurosurgery, University of Pennsylvania, Philadelphia, PA, USA.ORCID https://orcid.org/0000-0002-0754-6423

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Subpopulation underrepresentation in clinical trials contributes to biases in clinical data and systemic healthcare inequities. We aim to evaluate reporting and representation, as well as the effect of geography and socioeconomic trends, in spinal oncology trials. Methods: Data were collected from completed spinal oncology trials registered on ClinicalTrials.gov from 2000 to 2023. A total of 42 trials with 5679 participants were included. The demographics of participants were compared with national spinal tumor incidence data and demographic data from patients undergoing spinal oncology surgery at a quaternary care center. Results: Only 50% of clinical trials reported race and 28.6% reported the ethnicity of participants, with privately funded trials less likely to report ethnicity (25% vs. 66.7%, Conclusions: There has been progress in diversifying spinal oncology trials, but there are still large racial, ethnic, and geographic disparities in the composition of clinical trial patients. Major reporting lapses hinder understanding the gaps in equitable enrollment.

Indexed as

clinical trialshealthcare equityspinal oncology

Identifiers

PMID41080207
PMCPMC12508755

What OpenQuestion holds

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Registered trials

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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.