Evidence map›Paper›PMID 36869991›Full record

ArticleBreast cancer research and treatment2023

A prediction model for distant metastasis after isolated locoregional recurrence of breast cancer.

Takeshi Murata, Masayuki Yoshida, Sho Shiino, Ayumi Ogawa, Chikashi Watase, Kaishi Satomi, Kenjiro Jimbo, Akiko Maeshima, Eriko Iwamoto, Shin Takayama and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Breast cancer research and treatment, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.4field-weighted citation impact, top 12% of its field
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

8 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Applications of Artificial Intelligence (AI) in Breast Cancer Care Delivery and Education: A Scoping Review.International journal of environmental research and public health · 2026
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  3. Observational
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors at 2 institutions in 1 country.

Takeshi MurataDepartment of Breast Surgery, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan. tamurata@ncc.go.jp.ORCID http://orcid.org/0000-0003-0942-7599
Masayuki YoshidaDepartment of Diagnostic Pathology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
Sho ShiinoDepartment of Breast Surgery, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
Ayumi OgawaDepartment of Breast Surgery, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
Chikashi WataseDepartment of Breast Surgery, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
Kaishi SatomiDepartment of Diagnostic Pathology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
Kenjiro JimboDepartment of Breast Surgery, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
Akiko MaeshimaDepartment of Diagnostic Pathology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
Eriko IwamotoDepartment of Breast Surgery, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
Shin TakayamaDepartment of Breast Surgery, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
Akihiko SutoDepartment of Breast Surgery, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-Ku, Tokyo, 104-0045, Japan.
National Cancer Center Hospital East · JPNational Cancer Centre Japan · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe impact of progesterone receptor (PR) status on the prognosis of breast cancer after isolated locoregional recurrence (ILRR) remains unclear. This study evaluated the impact of clinicopathologic factors, including PR status of ILRR, on distant metastasis (DM) after ILRR.

methodsWe retrospectively identified 306 patients with ILRR diagnosed at the National Cancer Center Hospital between 1993 and 2021 from the database. Cox proportional hazards analysis was performed to examine factors associated with DM after ILRR. We developed a risk prediction model based on the number of detected risk factors and estimated survival curves using the Kaplan-Meier method.

resultsDuring a median follow-up time of 4.7 years after ILRR diagnosis, 86 patients developed DM, and 50 died. Multivariate analysis revealed that seven risk factors were associated with poor distant metastasis-free survival (DMFS): estrogen receptor-positive/PR-negative/human epidermal growth factor receptor 2-negative ILRR, short disease-free interval, recurrence site other than ipsilateral breast, no-resection of ILRR tumor, chemotherapy for the primary tumor, nodal stage in the primary tumor, and no endocrine therapy for ILRR. The predictive model classified patients into 4 groups based on the number of risk factors: low-, intermediate-, high-, and the highest-risk groups with 0 to 1, 2, 3 to 4, and 5 to 7 factors, respectively. This revealed significant variation in DMFS among the groups. A higher number of the risk factors was associated with poorer DMFS.

conclusionOur prediction model, which considered the ILRR receptor status, may contribute to the development of a treatment strategy for ILRR.

Indexed as

Breast NeoplasmsFemaleHumansNeoplasm Recurrence, LocalPrognosisRetrospective StudiesRisk FactorsBreast cancerChest wall recurrenceDistant metastasisIpsilateral breast tumor recurrenceIsolated locoregional recurrenceProgesterone receptor status

Identifiers

PMID36869991
PMCPMC10147732
OpenAlexW4323066881

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LicenceCC BY
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Registered trials

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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.