Evidence map›Paper›PMID 39069784›Full record

ReviewJournal of breast cancer2024

Palliative Radiotherapy for Symptomatic Primary Tumors in Patients With Locally Advanced Breast Cancer.

Jae Sik Kim, Jee Suk Chang, Kyubo Kim

Abstract readReview
In one paragraph

Review in Journal of breast cancer, 2024. 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

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

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.

Jae Sik KimDepartment of Radiation Oncology, Soonchunhyang University Seoul Hospital, Soonchunhyang University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-0039-8667
Jee Suk ChangDepartment of Radiation Oncology, Yonsei University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0001-7685-3382
Kyubo KimDepartment of Radiation Oncology, Seoul National University Bundang Hospital, Seongnam, Korea.ORCID https://orcid.org/0000-0001-6093-1294

Funding

Soonchunhyang University
6 · The paper itself

Abstract

Breast cancer remains a significant health concern for women, with a significant number of women facing unresectable, symptomatic, and advanced disease that severely affects their quality of life. Palliative radiotherapy (RT) is a well-established modality for managing such cases and alleviating symptoms. Recent advancements in systemic therapies and the resulting increase in long-term survival rates have not only heightened the need for retreatment in certain patients, but have also emphasized the importance of achieving durable local control. Additionally, inconsistencies in RT referral timing and variations in disease severity and extent contribute to diverse RT objectives and expected outcomes. The optimal dose fractionation for RT remains underexplored. Furthermore, a deeper understanding of breast radiobiology, along with the introduction of ultra- and moderately hypofractionated regimens and the widespread adoption of conformal techniques such as intensity-modulated RT, has diversified the approaches in RT dose and target volume. This review aimed to provides a comprehensive summary of the current evidence on the efficacy, outcomes, and toxicity profiles of palliative RT for symptomatic breast cancer. It highlights the need for more optimized regimens and further research to address the evolving treatment landscape and differing expectations of patients and physicians regarding RT.

Indexed as

Breast NeoplasmsPalliative CareRadiotherapyToxicityTreatment Outcome

Identifiers

PMID39069784
PMCPMC11377942

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

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.