Evidence map›Paper›PMID 31124293›Full record

ArticleJournal of cellular and molecular medicine2019

An estrogen receptor (ER)-related signature in predicting prognosis of ER-positive breast cancer following endocrine treatment.

Jianing Tang, Qiuxia Cui, Dan Zhang, Xing Liao, Jian Zhu, Gaosong Wu

Abstract readValidation Study
In one paragraph

Article in Journal of cellular and molecular medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–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

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3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

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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

6 authors.

Jianing TangDepartment of Thyroid and Breast Surgery, Zhongnan Hospital of Wuhan University, Wuhan, China.
Qiuxia CuiDepartment of Thyroid and Breast Surgery, Zhongnan Hospital of Wuhan University, Wuhan, China.
Dan ZhangDepartment of Thyroid and Breast Surgery, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China.
Xing LiaoDepartment of Thyroid and Breast Surgery, Zhongnan Hospital of Wuhan University, Wuhan, China.
Jian ZhuDepartment of Thyroid and Breast Surgery, Zhongnan Hospital of Wuhan University, Wuhan, China.ORCID 0000-0003-3596-4339
Gaosong WuDepartment of Thyroid and Breast Surgery, Zhongnan Hospital of Wuhan University, Wuhan, China.ORCID 0000-0001-9296-7080

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quite a few estrogen receptor (ER)-positive breast cancer patients receiving endocrine therapy are at risk of disease recurrence and death. ER-related genes are involved in the progression and chemoresistance of breast cancer. In this study, we identified an ER-related gene signature that can predict the prognosis of ER-positive breast cancer patient receiving endocrine therapy. We collected RNA expression profiling from Gene Expression Omnibus database. An ER-related signature was developed to separate patients into high-risk and low-risk groups. Patients in the low-risk group had significantly better survival than those in the high-risk group. ROC analysis indicated that this signature exhibited good diagnostic efficiency for the 1-, 3- and 5-year disease-relapse events. Moreover, multivariate Cox regression analysis demonstrated that the ER-related signature was an independent risk factor when adjusting for several clinical signatures. The prognostic value of this signature was validated in the validation sets. In addition, a nomogram was built and the calibration plots analysis indicated the good performance of this nomogram. In conclusion, combining with ER status, our results demonstrated that the ER-related prognostic signature is a promising method for predicting the prognosis of ER-positive breast cancer patients receiving endocrine therapy.

Indexed as

Breast NeoplasmsDatabases, GeneticEstrogensFemaleGene Expression Regulation, NeoplasticHumansMiddle AgedNeoplasm Recurrence, LocalPrognosisProportional Hazards ModelsReceptors, EstrogenRegression AnalysisRisk FactorsROC CurveTranscriptomeEstrogensReceptors, Estrogenbreast cancerestrogen receptornomogramprognosis

Identifiers

PMID31124293
PMCPMC6652714

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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.