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.
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.
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.
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.
Who cites it
9 citing papers in PubMed, 6 citations in OpenAlex.
- Treatment Effect Reanalysis of the Randomized Individual Screening Trial of Innovative Glioblastoma Therapy in Newly Diagnosed Glioblastoma With External Control Data.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2026Trial
- 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 · 2026Article
- Leveraging External Data for Testing Experimental Therapies with Biomarker Interactions in Randomized Clinical Trials.Biometrika · 2026Article
- Biomarkers for predicting immunotherapy response and resistance in glioblastoma.Frontiers in immunology · 2026Review
- Integrating single-cell transcriptomics with deep learning for glioblastoma treatment.Frontiers in genetics · 2026Review
- Glioblastoma in adults: A Society for Neuro-Oncology (SNO) and European Society of Neuro-Oncology (EANO) consensus review on current management and future directions.Neuro-oncology · 2025Review
- Identifying appropriate external control datasets in support of future glioblastoma clinical trials leveraging external data.Neuro-oncology · 2025Article
- Informative censoring in externally controlled clinical trials: a potential source of bias.ESMO open · 2025Article
- The future of cancer therapy: exploring the potential of patient-derived organoids in drug development.Frontiers in cell and developmental biology · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 5 institutions in 1 country.
Funding
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
Identifiers
What OpenQuestion holds
Registered trials
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.