Evidence map›Paper›PMID 37214188›Full record

ArticleCancer management and research2023

The Ratio of Monocyte to Apolipoprotein A1 is an Independent Predictor of Breast Cancer: A Retrospective Study.

Zhongyuan Lin, Changliang Luo, Yulin Yuan

Open access · goldAbstract read
In one paragraph

Article in Cancer management and research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.7field-weighted citation impact, top 25% of its field
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
4 · The record

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5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Zhongyuan Lin *Department of Clinical Laboratory, The People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical Sciences, Nanning, Guangxi Zhuang Autonomous Region, People's Republic of China.
Changliang Luo *Department of Clinical Laboratory, The People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical Sciences, Nanning, Guangxi Zhuang Autonomous Region, People's Republic of China.
Yulin YuanDepartment of Clinical Laboratory, The People's Hospital of Guangxi Zhuang Autonomous Region, Guangxi Academy of Medical Sciences, Nanning, Guangxi Zhuang Autonomous Region, People's Republic of China.
The People's Hospital of Guangxi Zhuang Autonomous Region · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To explore the predictive value of the ratio of monocyte to apolipoprotein A1 (MAR) (a new index related to inflammation and lipid in breast cancer (BC)) and its relationship with clinicopathological staging. Methods: The hematological test results of 394 patients with breast diseases, including 276 cases of BC, 118 cases of benign breast disease (BBD), and 219 healthy volunteers (HV), were retrospectively collected. The clinical value of MAR was analyzed with binary logistic regression. Results: Using statistical software analysis, the results showed that MAR level (P<0.001) was the largest in the BC group, followed by BBD, and the lowest in the HV group, and it was found to be an indicator to distinguish BC from BBD, also an independent risk factor for BC. The increase in MAR level showed that the risk of BC was 3.733 times higher than that of HV (P<0.001). In addition, there was a notable difference in MAR between early, middle and late stages of BC patients (P=0.047), with the highest MAR level in late stage (0.510±0.078) and the lowest MAR level in early stage (0.392±0.011); the MAR level of those with tumor invasion depth of Phase 4 was the highest (0.484±0.072), and that of Phase 1/2 was the lowest (0.379±0.010), with a statistically significant difference (P<0.001). MAR was positively correlated with tumor invasion depth (P<0.001, r=0.210), that's, the size of MAR increased when there was more deeper tumor invasion. Conclusion: MAR is a new indicator for the auxiliary differential diagnosis of benign and malignant breast diseases, and is also an independent risk factor for BC. High-level MAR is closely related to late staging and tumor invasion depth of BC. It can be seen that MAR is a potentially valuable predictor of BC, and this is the first study to explore the clinical value of MAR in BC.

Indexed as

Apolipoprotein A1breast benign diseasebreast cancerMonocytethe ratio of monocyte to apolipoprotein A1

Identifiers

PMID37214188
PMCPMC10198180
OpenAlexW4376615445

What OpenQuestion holds

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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.