Evidence map›Paper›PMID 42876653›Full record

ArticleFrontiers in medicine2026

Radiobiological evaluation of hypofractionated vs. conventional VMAT for synchronous bilateral breast cancer: a focus on regional nodal irradiation.

Jiyong Zhang, Danli Hong, Chunyan Deng

Abstract read
In one paragraph

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

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0citing papers in PubMed
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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

3 authors.

Jiyong ZhangDepartment of Radiation Oncology, Guangdong Engineering Research Center of AI-Powered Precision Cancer Diagnostics and Therapeutics (Proposed)/GuangDong Engineering Technology Research Center of AI-Powered Precision Cancer Diagnostics and Therapeutics, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China.
Danli HongDepartment of Endocrinology, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.
Chunyan DengDepartment of Radiation Oncology, Guangdong Engineering Research Center of AI-Powered Precision Cancer Diagnostics and Therapeutics (Proposed)/GuangDong Engineering Technology Research Center of AI-Powered Precision Cancer Diagnostics and Therapeutics, Cancer Hospital of Shantou University Medical College, Shantou, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To compare the radiobiological characteristics of hypofractionated radiotherapy (HFRT) and conventional fractionated radiotherapy (CFRT) delivered with volumetric modulated arc therapy (VMAT) for synchronous bilateral breast cancer (SBBC) requiring regional nodal irradiation (RNI). Methods: Eighteen patients with SBBC receiving bilateral breast/chest wall irradiation and comprehensive nodal coverage were retrospectively included. For each patient, VMAT plans were generated for CFRT (50 Gy in 25 fractions) and HFRT (40.05 Gy in 15 fractions). Dosimetric parameters of the planning target volume (PTV) were evaluated. Radiobiological assessment included equivalent uniform dose (EUD), tumor control probability (TCP), and normal tissue complication probability (NTCP). TCP was calculated using LQ-Poisson and Niemierko models, while NTCP for the lungs, heart, spinal cord, and esophagus was estimated using Lyman Kutcher Burman and Niemierko models. Results: Both regimens achieved excellent target coverage, with mean PTV V Conclusion: For SBBC patients requiring RNI, HFRT-VMAT achieved target coverage comparable to CFRT while reducing excessive high-dose regions and predicted toxicity to major thoracic organs. Despite slightly lower TCP values, overall tumor control remained favorable, supporting HFRT-VMAT as a feasible treatment option for this patient population.

Indexed as

hypofractionated radiotherapynormal tissue complication probabilityregional nodal irradiationsynchronous bilateral breast cancertumor control probabilityvolumetric modulated arc therapy

Identifiers

PMID42876653
PMCPMC13661328

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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.