Evidence map›Paper›PMID 40336251›Full record

ArticleTechnology in cancer research & treatment

Survival Impact of Postoperative Primary Area Radiotherapy on De Novo Metastatic Breast Cancer: A Retrospective Study.

Pingchuan Li, Lineng Wei, Yinan Ji, Huawei Yang

Erratum issuedAbstract read
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Article in Technology in cancer research & treatment. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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

5 · Who and what money

Authors and funding

4 authors.

Pingchuan LiDepartment of Breast Surgery, Key Laboratory of Breast Cancer Diagnosis and Treatment Research of Guangxi Department of Education, Guangxi Medical University Cancer Hospital, Nanning, China.ORCID 0009-0000-6415-1949
Lineng WeiDepartment of Breast Surgery, Key Laboratory of Breast Cancer Diagnosis and Treatment Research of Guangxi Department of Education, Guangxi Medical University Cancer Hospital, Nanning, China.ORCID 0009-0009-0207-324X
Yinan JiDepartment of Breast Surgery, Key Laboratory of Breast Cancer Diagnosis and Treatment Research of Guangxi Department of Education, Guangxi Medical University Cancer Hospital, Nanning, China.
Huawei YangDepartment of Breast Surgery, Key Laboratory of Breast Cancer Diagnosis and Treatment Research of Guangxi Department of Education, Guangxi Medical University Cancer Hospital, Nanning, China.ORCID 0009-0006-7377-2054

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

IntroductionThe role of radiotherapy (RT) in de novo metastatic breast cancer (dnMBC) patients undergoing surgery remains controversial due to limited evidence. This study aimed to evaluate the impact of postoperative radiotherapy on survival outcomes in this population.Materials and methodsWe retrospectively analyzed 102 dnMBC patients who underwent surgery at a provincial cancer hospital. Patients were grouped based on whether they received postoperative RT. Baseline characteristics were compared using the chi-square test. Kaplan-Meier analysis and Cox proportional hazards models were used to assess the prognostic impact of postoperative radiotherapy on local recurrence-free survival (LRFS), progression-free survival (PFS), and overall survival (OS).ResultsKM survival analysis showed that postoperative RT significantly improved LRFS (HR = 0.3634, 95%CI 0.1552-0.8508,

Indexed as

Breast NeoplasmsAdultAgedCombined Modality TherapyFemaleHumansKaplan-Meier EstimateMastectomyMiddle AgedNeoplasm MetastasisNeoplasm Recurrence, LocalPostoperative PeriodPrognosisRadiotherapy, AdjuvantRetrospective StudiesTreatment Outcomede novo metastatic breast cancerpostoperative radiotherapyprogressionrecurrencesurvival

Identifiers

PMID40336251
PMCPMC12062640

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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.