ArticleSeminars in oncology
The Veterans Precision Oncology Data Commons: Transforming VA data into a national resource for research in precision oncology.
Article in Seminars in oncology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 13 citations in OpenAlex.
- Trends in lung cancer survival: superior outcomes in US Veterans compared with the general population.JNCI cancer spectrum · 2026Article
- Building Research Infrastructure to Develop Greater Learning Efficiencies (BRIDGE).Studies in health technology and informatics · 2024Article
- Transfer Learning for Mortality Prediction in Non-Small Cell Lung Cancer with Low-Resolution Histopathology Slide Snapshots.Studies in health technology and informatics · 2024Article
- A Case for Accelerating Standards to Achieve the FAIR Principles of Environmental Health Research Experimental Data.Environmental health perspectives · 2023Article
- Case Studies for Overcoming Challenges in Using Big Data in Cancer.Cancer research · 2023Review
- Ten lessons for data sharing with a data commons.Scientific data · 2023Article
- Efforts to enhance reproducibility in a human performance research project.F1000Research · 2023Article
- ProjectFlow: a configurable workflow management application for point of care research.JAMIA open · 2021Article
- Development of a Multi-Study Repository to Support Research on Veteran Health: The VA Cooperative Studies Program Epidemiology Center-Durham (CSPEC-Durham) Data and Specimen Repository.Frontiers in public health · 2021Article
- The Veterans Affairs Precision Oncology Data Repository, a Clinical, Genomic, and Imaging Research Database.Patterns (New York, N.Y.) · 2020Article
- External validation of a prognostic model for mortality among patients with non-small-cell lung cancer using the Veterans Precision Oncology Data Commons.Seminars in oncologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors at 5 institutions in 1 country.
Funding
Abstract
The Department of Veterans Affairs (VA) has a strong track record providing high-quality, evidence-based care to cancer patients. In order to accelerate discoveries that will further improve care for Veterans with cancer, the VA has partnered with the Center for Translational Data Science at the University of Chicago and the Open Commons Consortium to establish a data sharing platform, the Veterans Precision Oncology Data Commons (VPODC). The VPODC makes clinical, genomic, and imaging data from the VA available to the research community at large. In this paper, we detail our motivation for data sharing, describe the VPODC, and outline our collaboration model. By transforming VA data into a national resource for research in precision oncology, the VPODC seeks to foster innovation through collaboration and resource sharing that will ultimately lead to improved care for Veterans with cancer.
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.