Evidence map›Paper›PMID 37863013›Full record

ArticleComputer methods and programs in biomedicine2023

ROE (Radiotherapy Outcomes Estimator): An open-source tool for optimizing radiotherapy prescriptions.

Aditi Iyer, Aditya P Apte, Ethan Bendau, Maria Thor, Ishita Chen, Jacob Shin, Abraham Wu, Daniel Gomez, Andreas Rimner, Ellen Yorke and 2 more

Abstract read
In one paragraph

Article in Computer methods and programs in biomedicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

12 authors.

Aditi IyerDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY, United States. Electronic address: iyera@mskcc.org.
Aditya P ApteDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY, United States.
Ethan BendauDepartment of Biomedical Engineering, Columbia University, New York, NY, United States.
Maria ThorDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY, United States.
Ishita ChenDepartment of Radiation Oncology, Tennessee Oncology, Nashville, TN, United States.
Jacob ShinDepartment of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States.
Abraham WuDepartment of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States.
Daniel GomezDepartment of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States.
Andreas RimnerDepartment of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States.
Ellen YorkeDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY, United States.
Joseph O DeasyDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY, United States.
Andrew JacksonDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY, United States.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

BACKGROUND AND

objectivesRadiotherapy prescriptions currently derive from population-wide guidelines established through large clinical trials. We provide an open-source software tool for patient-specific prescription determination using personalized dose-response curves.

methodsWe developed ROE, a plugin to the Computational Environment for Radiotherapy Research to visualize predicted tumor control and normal tissue complication simultaneously, as a function of prescription dose. ROE can be used natively with MATLAB and is additionally made accessible in GNU Octave and Python, eliminating the need for commercial licenses. It provides a curated library of published and validated predictive models and incorporates clinical restrictions on normal tissue outcomes. ROE additionally provides batch-mode tools to evaluate and select among different fractionation schemes and analyze radiotherapy outcomes across patient cohorts.

conclusionROE is an open-source, GPL-copyrighted tool for interactive exploration of the dose-response relationship to aid in radiotherapy planning. We demonstrate its potential clinical relevance in (1) improving patient awareness by quantifying the risks and benefits of a given treatment protocol (2) assessing the potential for dose escalation across patient cohorts and (3) estimating accrual rates of new protocols.

Indexed as

NeoplasmsRadiotherapy Planning, Computer-AssistedHumansPrescriptionsRadiotherapy DosageSoftwareNormal tissue complication probabilityPrescription determinationRadiotherapy analysis softwareRadiotherapy outcome modelingTumor control probability

Identifiers

PMID37863013
PMCPMC10872836

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.