Evidence map›Paper›PMID 36939557›Full record

ArticleClinical cancer research : an official journal of the American Association for Cancer Research2023

Accessible Data Collections for Improved Decision Making in Neuro-Oncology Clinical Trials.

Rifaquat Rahman, Steffen Ventz, Robert Redd, Timothy Cloughesy, Brian M Alexander, Patrick Y Wen, Lorenzo Trippa

Open access · greenAbstract read
In one paragraph

Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.7field-weighted citation impact, top 15% of its field
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

9 citing papers in PubMed, 6 citations in OpenAlex.

  1. Trial
  2. Harmonized Estimation of Subgroup-Specific Treatment Effects in Randomized Trials: The Use of External Control Data.Journal of the Royal Statistical Society. Series B, Statistical methodology · 2026
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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

7 authors at 5 institutions in 1 country.

Rifaquat RahmanDepartment of Radiation Oncology, Dana-Farber/Brigham and Women's Cancer Center, Harvard Medical School, Boston, Massachusetts.ORCID 0000-0002-9443-1797
Steffen VentzDivision of Biostatistics, University of Minnesota, Minnesota, Minnesota.ORCID 0000-0003-2229-9560
Robert ReddMS Department of Data Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts.ORCID 0000-0002-1329-5288
Timothy CloughesyNeuro-Oncology Program and Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California.ORCID 0000-0002-8656-7483
Brian M AlexanderDepartment of Radiation Oncology, Dana-Farber/Brigham and Women's Cancer Center, Harvard Medical School, Boston, Massachusetts.ORCID 0000-0003-3903-9175
Patrick Y WenCenter for Neuro-Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts.ORCID 0000-0002-0774-7700
Lorenzo TrippaDepartment of Data Sciences, Dana-Farber Cancer Institute, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.ORCID 0000-0001-5218-5666
Dana-Farber Cancer Institute · USDana-Farber Brigham Cancer Center · USGlobalFoundries (United States) · USUniversity of California, Los Angeles · USUniversity of Minnesota · US

Funding

UCLA SPORE in Brain CancerP50CA211015 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI David A. Nathanson · 2017 to 2026
$25.2M
Statistical Methods and Validation Analyses for the Integration of External Data in Clinical TrialsR01LM013352 · NLM · DANA-FARBER CANCER INST · PI TRIPPA, LORENZO · 2021 to 2024
$1.5M
NCI NIH HHS P50 CA211015NLM NIH HHS R01 LM013352Wellcome Trust
6 · The paper itself

Abstract

Drug development can be associated with slow timelines, particularly for rare or difficult-to-treat solid tumors such as glioblastoma. The use of external data in the design and analysis of trials has attracted significant interest because it has the potential to improve the efficiency and precision of drug development. A recurring challenge in the use of external data for clinical trials, however, is the difficulty in accessing high-quality patient-level data. Academic research groups generally do not have access to suitable datasets to effectively leverage external data for planning and analyses of new clinical trials. Given the need for resources to enable investigators to benefit from existing data assets, we have developed the Glioblastoma External (GBM-X) Data Platform which will allow investigators in neuro-oncology to leverage our data collection and obtain analyses. GBM-X strives to provide an uncomplicated process to use external data, contextualize single-arm trials, and improve inference on treatment effects early in drug development. The platform is designed to welcome interested collaborators and integrate new data into the platform, with the expectation that the data collection can continue to grow and remain updated. With such features, GBM-X is designed to help to accelerate evaluation of therapies, to grow with collaborations, and to serve as a model to improve drug discovery for rare and difficult-to-treat tumors in oncology.

Indexed as

GlioblastomaClinical Trials as TopicData CollectionDecision MakingHumansMedical OncologyNeoplasm Recurrence, Local

Identifiers

PMID36939557
PMCPMC10681026
OpenAlexW4327899672

What OpenQuestion holds

Textmetadata
LicenceTDM
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.