Evidence map›Paper›PMID 34012370›Full record

ArticleBreast care (Basel, Switzerland)2021

Adjuvant Chemotherapy for Low-Clinical-Risk Breast Cancer Defined by Modified Version of Adjuvant! Online: A Propensity Score Matched SEER Analysis.

Jiefeng Huang, Zhiyong Wu, Zechun Zhang, Jie Li, Yunhai Li, Guosheng Ren

Abstract read
In one paragraph

Article in Breast care (Basel, Switzerland), 2021. 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
–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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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

1 citing paper in PubMed.

  1. 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

6 authors.

Jiefeng HuangDepartment of Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Zhiyong WuDiagnosis and Treatment Center of Breast Diseases, Shantou Affiliated Hospital of Sun Yat-Sen University, Shantou, China.
Zechun ZhangDiagnosis and Treatment Center of Breast Diseases, Shantou Affiliated Hospital of Sun Yat-Sen University, Shantou, China.
Jie LiDepartment of Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Yunhai LiDepartment of Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Guosheng RenDepartment of Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe purpose of this research was to investigate whether the modified version of Adjuvant! Online was able to omit chemotherapy (CT) for patients with hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative, and axillary node-negative breast cancer, who are defined as low clinical risk.

methodsFrom 2010 to 2014, HR-positive, HER2-negative, and node-negative breast cancer patients aged 50 years and older were retrieved from the Surveillance, Epidemiology, and End Results (SEER) 18 database. The propensity score matching method was applied between the no-CT and CT groups. Overall survival (OS) was evaluated using Kaplan-Meier analysis and compared across groups using a log-rank test.

resultsA total of 48,857 patients were enrolled. After propensity score matching, the numbers of patients in the no-CT and CT groups were both 3,102. The median follow-up period was 37 months. The 5-year OS rates in the no-CT and CT groups were 92 and 91%, respectively (

conclusionThis retrospective study provides evidence that CT may not be beneficial to patients 50 years of age or older with HR-positive, HER2-negative, axillary node-negative breast cancer and additionally defined as low clinical risk by a modified version of Adjuvant! Online.

Indexed as

Adjuvant chemotherapyAdjuvant! OnlineBreast cancerRisk factorsSEER database

Identifiers

PMID34012370
PMCPMC8114060

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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.