Evidence map›Paper›PMID 35090025›Full record

ArticleRadiation research2022

Predictive Radiation Oncology - A New NCI-DOE Scientific Space and Community.

Jeffrey C Buchsbaum, David A Jaffray, Demba Ba, Lynn L Borkon, Christine Chalk, Caroline Chung, Matthew A Coleman, C Norman Coleman, Maximilian Diehn, Kelvin K Droegemeier and 12 more

Abstract read
In one paragraph

Article in Radiation research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
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

22 authors.

Jeffrey C BuchsbaumNational Cancer Institute, Bethesda, Maryland 20892.
David A JaffrayThe University of Texas, MD Anderson Cancer Center, Houston, Texas 77030.
Demba BaHarvard University, Cambridge, Massachusetts 02138.
Lynn L BorkonFrederick National Laboratory for Cancer Research, Frederick, Maryland, 21701.
Christine ChalkU.S. Department of Energy, Boyds, Maryland, 20841.
Caroline ChungThe University of Texas, MD Anderson Cancer Center, Houston, Texas 77030.
Matthew A ColemanLawrence Livermore National Laboratory, Livermore, California 94550.
C Norman ColemanNational Cancer Institute, Bethesda, Maryland 20892.
Maximilian DiehnStanford Medicine, Stanford, California 94305.
Kelvin K DroegemeierUniversity of Oklahoma, Norman, Oklahoma 73072.
Heiko EnderlingH. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida 33612.
Michael G EspeyNational Cancer Institute, Bethesda, Maryland 20892.
Emily J GreenspanNational Cancer Institute, Bethesda, Maryland 20892.
Christopher M HartshornNational Cancer Institute, Bethesda, Maryland 20892.
Thuc HoangU.S. Department of Energy, Washington, DC 20585.
H Timothy HsiaoAmerican Society for Radiation Oncology (ASTRO), Arlington, Virginia 22202.
Cynthia KeppelJefferson Lab, Newport News, Virginia 23606.
Nathan W MooreSandia National Laboratories, Albuquerque, New Mexico 87123.
Fred PriorUniversity of Arkansas for Medical Sciences, Little Rock, Arkansas 72205.
Eric A StahlbergFrederick National Laboratory for Cancer Research, Frederick, Maryland, 21701.
Georgia TourassiOak Ridge National Laboratory, Oak Ridge, Tennessee 37830.
Karen E WillcoxThe University of Texas at Austin, Austin, Texas 78712.

Funding

Intramural NIH HHS Z99 CA999999
6 · The paper itself

Abstract

With a widely attended virtual kickoff event on January 29, 2021, the National Cancer Institute (NCI) and the Department of Energy (DOE) launched a series of 4 interactive, interdisciplinary workshops-and a final concluding "World Café" on March 29, 2021-focused on advancing computational approaches for predictive oncology in the clinical and research domains of radiation oncology. These events reflect 3,870 human hours of virtual engagement with representation from 8 DOE national laboratories and the Frederick National Laboratory for Cancer Research (FNL), 4 research institutes, 5 cancer centers, 17 medical schools and teaching hospitals, 5 companies, 5 federal agencies, 3 research centers, and 27 universities. Here we summarize the workshops by first describing the background for the workshops. Participants identified twelve key questions-and collaborative parallel ideas-as the focus of work going forward to advance the field. These were then used to define short-term and longer-term "Blue Sky" goals. In addition, the group determined key success factors for predictive oncology in the context of radiation oncology, if not the future of all of medicine. These are: cross-discipline collaboration, targeted talent development, development of mechanistic mathematical and computational models and tools, and access to high-quality multiscale data that bridges mechanisms to phenotype. The workshop participants reported feeling energized and highly motivated to pursue next steps together to address the unmet needs in radiation oncology specifically and in cancer research generally and that NCI and DOE project goals align at the convergence of radiation therapy and advanced computing.

Indexed as

Radiation OncologyAcademies and InstitutesHumansNational Cancer Institute (U.S.)United States

Identifiers

PMID35090025
PMCPMC9058979

What OpenQuestion holds

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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.