Evidence map›Paper›PMID 34812737›Full record

ArticleEndocrine connections2021

Urinary estrogen metabolites and breast cancer risk in Chinese population.

Xiaomin Li, Ling Fang, Hongjiang Li, Xiaoqin Yang

Open access · goldAbstract read
In one paragraph

Article in Endocrine connections, 2021. 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
0.2field-weighted citation impact, top 37% 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, 4 citations in OpenAlex.

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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

4 authors at 1 institution in 1 country.

Xiaomin LiDepartment of Breast Surgery, West China Hospital, Sichuan University, Chengdu, China.
Ling FangDepartment of Breast Surgery, Cheng Du Shang Jin Nan Fu Hospital, West China Hospital, Sichuan University, Chengdu, China.
Hongjiang LiDepartment of Breast Surgery, West China Hospital, Sichuan University, Chengdu, China.
Xiaoqin YangDepartment of Breast Surgery, West China Hospital, Sichuan University, Chengdu, China.ORCID 0000-0001-8200-3405
Sichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn China, the association between estrogen metabolism and breast cancer risk and the differences in metabolic pattern between breast cancer patients and controls are poorly understood.

methodsA total of 84 patients with invasive breast cancer and 47 controls with benign breast diseases were included in this study. Estrogen metabolites from their morning urine were determined by HPLC-MS/MS and evaluated in both groups, and the predictive value of each estrogen metabolite in the malignant group according to their menstrual status was analyzed.

resultsUrinary concentration of estrogen metabolites 2-hydroxyestrone (2-OHE1), 2-hydroxyestradiol (2-OHE2), 4-hydroxyestradiol (4-OHE2), 4-methoxyestrone (4-MeOE1), and 16α-hydroxyestrone were lower in postmenopausal patients with breast cancer, compared with benign controls. In logistic regression model, breast cancer risk increased with the decline in the levels of 4-OHE2 and 4-MeOE1. In premenopausal patients, a difference in the level of 2-OHE2 was observed between both groups, and 2-OHE2 was found to have predictive value for breast cancer. Additionally, urinary 2-OHE2 level in premenopausal hormone receptor positive (HR+) patients was considerably higher compared with hormone receptor negative patients.

conclusionsWe found that lower urinary levels of 4-OHE2 and 4-MeOE1 had predictive value for breast cancer, and higher 2-OHE1 were associated with HR+ breast cancer in premenopausal women.

Indexed as

breast cancerestrogen metabolismestrogen receptorhormone receptorliquid chromatography tandem mass spectrometry

Identifiers

PMID34812737
PMCPMC8679875
OpenAlexW3215188608

What OpenQuestion holds

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LicenceCC BY-NC
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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.