Evidence map›Paper›PMID 35574329›Full record

ArticleFrontiers in oncology2022

Preoperative Pectoralis Muscle Index Predicts Distant Metastasis-Free Survival in Breast Cancer Patients.

Wen-Juan Huang, Meng-Lin Zhang, Wen Wang, Qing-Chun Jia, Jia-Rui Yuan, Xin Zhang, Shuang Fu, Yu-Xi Liu, Shi-di Miao, Rui-Tao Wang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
2.5field-weighted citation impact, top 10% 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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. Pectoralis major muscle index as an opportunistic predictor of mortality in acute stroke patients treated with intravenous thrombolysis.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
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

10 authors at 3 institutions in 1 country.

Wen-Juan HuangDepartment of Internal Medicine, Harbin Medical University Cancer Hospital, Harbin Medical University, Harbin, China.
Meng-Lin ZhangDepartment of Internal Medicine, Harbin Medical University Cancer Hospital, Harbin Medical University, Harbin, China.
Wen WangDepartment of Internal Medicine, Harbin Medical University Cancer Hospital, Harbin Medical University, Harbin, China.
Qing-Chun JiaDepartment of Internal Medicine, Harbin Medical University Cancer Hospital, Harbin Medical University, Harbin, China.
Jia-Rui YuanDepartment of Internal Medicine, Harbin Medical University Cancer Hospital, Harbin Medical University, Harbin, China.
Xin ZhangDepartment of Internal Medicine, Harbin Medical University Cancer Hospital, Harbin Medical University, Harbin, China.
Shuang FuDepartment of Internal Medicine, Harbin Medical University Cancer Hospital, Harbin Medical University, Harbin, China.
Yu-Xi LiuDepartment of Internal Medicine, Harbin Medical University Cancer Hospital, Harbin Medical University, Harbin, China.
Shi-di MiaoSchool of Computer Science and Technology, Harbin University of Science and Technology, Harbin, China.
Rui-Tao WangDepartment of Internal Medicine, Harbin Medical University Cancer Hospital, Harbin Medical University, Harbin, China.
Third Affiliated Hospital of Harbin Medical University · CNHarbin Medical University · CNHarbin University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Breast cancer is one of the most commonly diagnosed cancers, and the fourth leading cause of cancer deaths in females worldwide. Sarcopenia is related to adverse clinical outcomes in patients with malignancies. Muscle index is a key parameter in evaluating sarcopenia. However, there is no data investigating the association between muscle index and distant metastasis in breast cancer. The aim of this study was to explore whether muscle index can effectively predict distant metastasis and death outcomes in breast cancer patients. Study Design: The clinical data of 493 breast cancer patients at the Harbin Medical University Cancer Hospital between January 2014 and December 2015 were retrospectively analyzed. Quantitative measurements of pectoralis muscle area and skeletal muscle area were performed at the level of the fourth thoracic vertebra (T4) and the eleventh thoracic vertebra (T11) of the chest computed tomography image, respectively. The pectoralis muscle index (PMI) and skeletal muscle index (SMI) were assessed by the normalized muscle area (area/the square of height). Survival analysis was performed using the log-rank test and Cox proportional hazards regression analysis. Result: The patients with metastases had lower PMI at T4 level (PMI/T4) and SMI at T11 level (SMI/T11) compared with the patients without metastases. Moreover, there were significant correlations between PMI/T4 and lymphovascular invasion, Ki67 expression, multifocal disease, and molecular subtype. In addition, multivariate analysis revealed that PMI/T4, not SMI/T11, was an independent prognostic factor for distant metastasis-free survival (DMFS) and overall survival (OS) in breast cancer patients. Conclusions: Low PMI/T4 is associated with worse DMFS and OS in breast cancer patients. Future prospective studies are needed.

Indexed as

breast cancerdistant metastasisoverall survivalprognosisskeletal muscle

Identifiers

PMID35574329
PMCPMC9098931
OpenAlexW4225163143

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.