Evidence map›Paper›PMID 41860858›Full record

ArticlePloS one2026

A computational method to estimate the relative biological effectiveness and tumor control probability for low-LET proton irradiations.

Chun-Chieh Chan, Kuang-Lung Hsueh, Chung-Yu Lai, Ya-Yun Hsiao

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Chun-Chieh ChanDepartment of Computer Science and Information Engineering, National Formosa University, Yunlin, Taiwan.
Kuang-Lung HsuehProtein Science and Biophysics Department, WuXi Biology, WuXi AppTec, Shanghai, China.
Chung-Yu LaiDepartment of Medical Equipment Development and Application, Hungkuang University, Taichung, Taiwan.
Ya-Yun HsiaoDepartment of Medical Imaging and Radiological Sciences, Chung Shan Medical University, Taichung, Taiwan.ORCID https://orcid.org/0000-0001-7494-8767

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A constant relative biological effectiveness (RBE) value of 1.1 is used for proton therapy (PT) in many clinical treatment plans. However, several studies show that RBE varies with proton energy, linear energy transfer (LET), and oxygen concentration. This study presents a computational method based on the linear quadratic (LQ) and repair-misrepair-fixation (RMF) models to calculate tumor control probability (TCP) under varying oxygen conditions. We analyze the impact of hypoxia on the parameters of the LQ model, focusing on the ratio and RBE. The proposed method allows for TCP calculations across different oxygen concentrations and for various ion therapies, such as proton and carbon ion therapy. Our results show that increasing the LET from 1 to 12 keV/μm enhances TCP from 61% to 98% under aerobic conditions (21% O2), 45% to 98% under moderately hypoxic conditions (2% O2), and from 1% to 48% under severely hypoxic conditions (0.1% O2). These findings are compared with clinical trial data, demonstrating that hypoxia significantly affects TCP for low-LET radiations.

Indexed as

Linear Energy TransferNeoplasmsProton TherapyRelative Biological EffectivenessComputer SimulationHumansModels, BiologicalOxygenProbabilityOxygen

Identifiers

PMID41860858
PMCPMC13004361

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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.