Evidence map›Paper›PMID 41091279›Full record

ArticleBreast cancer research and treatment2025

Prognostic significance of baseline skeletal muscle index and its dynamics in patients with metastatic breast cancer undergoing eribulin treatment.

Masatsugu Amitani, Takaaki Oba, Ayaka Kitazawa, Ryoko Iji, Nami Kiyosawa, Shota Katsuyama, Hiroki Morikawa, Tatsunori Chino, Tadafumi Shimizu, Mayu Ono and 2 more

Abstract read
In one paragraph

Article in Breast cancer research and treatment, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

12 authors.

Masatsugu AmitaniDivision of Breast and Endocrine Surgery, Department of Surgery, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, Japan.
Takaaki ObaDivision of Breast and Endocrine Surgery, Department of Surgery, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, Japan. takaoba@shinshu-u.ac.jp.ORCID http://orcid.org/0000-0001-8283-4989
Ayaka KitazawaDivision of Breast and Endocrine Surgery, Department of Surgery, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, Japan.
Ryoko IjiDivision of Breast and Endocrine Surgery, Department of Surgery, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, Japan.
Nami KiyosawaDivision of Breast and Endocrine Surgery, Department of Surgery, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, Japan.
Shota KatsuyamaDivision of Breast and Endocrine Surgery, Department of Surgery, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, Japan.
Hiroki MorikawaDivision of Breast and Endocrine Surgery, Department of Surgery, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, Japan.
Tatsunori ChinoDivision of Breast and Endocrine Surgery, Department of Surgery, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, Japan.
Tadafumi ShimizuDivision of Breast and Endocrine Surgery, Department of Surgery, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, Japan.
Mayu OnoDivision of Breast and Endocrine Surgery, Department of Surgery, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, Japan.
Toshiharu KanaiDivision of Breast and Endocrine Surgery, Department of Surgery, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, Japan.
Ken-Ichi ItoDivision of Breast and Endocrine Surgery, Department of Surgery, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeIn breast cancer, a low skeletal muscle index (SMI) and prognostic nutritional index (PNI) negatively affect patient outcomes. However, the prognostic implications of changes in these values in patients with metastatic breast cancer (MBC) remain unclear. We evaluated the association between baseline levels and changes in SMI and PNI during eribulin treatment and patient outcomes.

methodsWe retrospectively analyzed 67 patients with MBC treated with eribulin. SMI and PNI were assessed at baseline (pre-SMI, and pre-PNI) and at disease progression; changes from baseline were calculated. Patient outcomes were compared according to baseline status and direction of change.

resultsSMI and PNI were not significantly correlated (p = 0.26, R = 0.02). High pre-SMI and high pre-PNI were associated with significantly improved overall survival (OS) (SMI; hazard ratio [HR] = 0.54, p = 0.04, PNI; HR = 0.33, p < 0.001). Patients with SMI gain during eribulin had longer OS than those with stable SMI or loss (HR = 0.48, p = 0.04), whereas PNI increase was not significantly associated with OS (HR = 0.74, p = 0.32).

conclusionBaseline SMI and PNI provide complementary prognostic information in patients with MBC receiving eribulin. Furthermore, on-treatment SMI gain, but not PNI increase, was associated with improved survival. Monitoring and enhancing skeletal muscle mass may improve outcomes, highlighting the importance of integrating supportive care strategies during chemotherapy.

Indexed as

Antineoplastic AgentsBreast NeoplasmsFuransKetonesMuscle, SkeletalAdultAgedFemaleHumansMiddle AgedNeoplasm MetastasisNutrition AssessmentPolyether PolyketidesPrognosisRetrospective StudiesTreatment OutcomeAntineoplastic AgentseribulinFuransKetonesPolyether PolyketidesChange in skeletal muscle indexChemotherapyEribulinMetastatic breast cancerPrognostic nutritional indexSkeletal muscle index

Identifiers

PMID41091279
PMCPMC12583309

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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.