Evidence map›Paper›PMID 40963699›Full record

ReviewDose-response : a publication of International Hormesis Society

Efficacy of Radiotherapy FLASH-RT: From Treating Lung Cancer to Preventing Pulmonary Fibrosis.

Tianyu Yang, Zhiming Xu, Wentao Hu, Zhifei Cao, Yongsheng Zhang

Abstract readReview
In one paragraph

Review in Dose-response : a publication of International Hormesis Society. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Microenvironmental remodeling in FLASH radiotherapy.Frontiers in cell and developmental biology · 2026
    Review
  3. 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

5 authors.

Tianyu YangDepartment of Pathology, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Zhiming XuDepartment of Pathology, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Wentao HuState Key Laboratory of Radiation Medicine and Protection, School of Radiation Medicine and Protection, Suzhou Medical College of Soochow University, Suzhou, China.ORCID https://orcid.org/0000-0001-8495-4175
Zhifei CaoDepartment of Pathology, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Yongsheng ZhangDepartment of Pathology, The Second Affiliated Hospital of Soochow University, Suzhou, China.ORCID https://orcid.org/0000-0002-1857-258X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

FLASH radiotherapy (FLASH-RT) is a radiotherapy technique that achieves ultra-high dose rates in a fraction of a second. Based on data from experimental animal models, FLASH-RT appears to protect a number of normal tissues from radiation-induced damage, including the brain, gastrointestinal tract, and lung, while conventional radiotherapy (CONV-RT) causes radiation-induced toxicity in these tissues. In this review, we provide a brief summary of the history of radiation therapy and focus on some of the most recent FLASH-RT papers and findings. It is particularly noteworthy that pulmonary fibrosis represents a common complication of radiotherapy. New evidence indicates that FLASH-RT, unlike traditional radiotherapy methods, might help protect lung cancer patients from developing pulmonary fibrosis caused by radiation. FLASH-RT will advance more quickly than anticipated, although there are still a number of unresolved concerns. FLASH-RT will be a safer and more effective option for lung cancer treatment.

Indexed as

lung cancerpulmonary fibrosisradiotherapyultra-high dose rate radiotherapy

Identifiers

PMID40963699
PMCPMC12437252

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.