Evidence map›Paper›PMID 38615057›Full record

ArticleScientific reports2024

Prediction of hematologic toxicity in luminal type breast cancer patients receiving neoadjuvant chemotherapy using CT L1 level skeletal muscle index.

Min Chen, Pinxiu Wang, Yanting Li, Zhuanmei Jin, Yu An, Yanan Zhang, Wenzhen Yuan

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact, top 93% 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

2 citing papers in PubMed, 0 citations in OpenAlex.

  1. Article
  2. Review
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

7 authors at 3 institutions in 1 country.

Min Chen *The First Clinical Medical College, Lanzhou University, Lanzhou, 730000, Gansu Province, China.
Pinxiu Wang *Department of Oncology, Shucheng People's Hospital, Lu'an, 231300, China.
Yanting LiThe First Clinical Medical College, Lanzhou University, Lanzhou, 730000, Gansu Province, China.
Zhuanmei JinThe First Clinical Medical College, Lanzhou University, Lanzhou, 730000, Gansu Province, China.
Yu AnThe First Clinical Medical College, Lanzhou University, Lanzhou, 730000, Gansu Province, China.
Yanan ZhangThe First Clinical Medical College, Lanzhou University, Lanzhou, 730000, Gansu Province, China.
Wenzhen YuanThe Department of Oncology, The First Hospital of Lanzhou University, Lanzhou, 730000, Gansu Province, China. yuanwzh@lzu.edu.cn.
Lanzhou University · CNFirst Hospital of Lanzhou University · CNZoucheng People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to explore the correlation between the CT-L1 and L3 body composition parameters and analyze the relationship between L1 body composition and hematologic toxicity in luminal-type breast cancer patients undergoing neoadjuvant chemotherapy. Data from 140 luminal-type breast cancer patients who underwent surgical treatment after neoadjuvant chemotherapy were analyzed retrospectively. Spearman analysis was used to assess the correlation between CT-L1 and CT-L3 body composition parameters pre-neoadjuvant chemotherapy. Additionally, univariate and multivariate logistic regression analyses were performed to identify factors influencing hematologic toxicity. CT-L1 body composition parameters were positively correlated with CT-L3 body composition parameters in 34 patients. Severe hematological toxicity occurred in 46 cases among the patient cohort. A skeletal muscle index (SMI) of < 32.91 cm

Indexed as

Breast NeoplasmsFemaleHumansMuscle, SkeletalNeoadjuvant TherapyRetrospective StudiesTomography, X-Ray Computed

Identifiers

PMID38615057
PMCPMC11016056
OpenAlexW4394783063

What OpenQuestion holds

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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.