Evidence map›Paper›PMID 31054583›Full record

ArticleDiagnostic pathology2019

A nomogram for predicting the HER2 status in female patients with breast cancer in China: a nationwide, multicenter, 10-year epidemiological study.

Huimin Zhang, Peiling Xie, Zhuoying Li, Rong Huang, Weiliang Feng, Yanan Kong, Feng Xu, Lin Zhao, Qingkun Song, Jing Li and 7 more

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in Diagnostic pathology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

17 authors at 6 institutions in 1 country.

Huimin ZhangDepartment of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, 710061, Xi'an, People's Republic of China.
Peiling XieDepartment of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, 710061, Xi'an, People's Republic of China.
Zhuoying LiDepartment of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, 710061, Xi'an, People's Republic of China.
Rong HuangDepartment of Cancer Epidemiology, Cancer Institute & Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China.
Weiliang FengDepartment of Breast Surgery, Zhejiang Cancer Hospital, Hangzhou, People's Republic of China.
Yanan KongDepartment of Breast Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China.
Feng XuDepartment of Breast-thyroid Surgery, Xiangya Second Hospital, Central South University, Changsha, People's Republic of China.
Lin ZhaoDepartment of Breast Surgery, Liaoning Cancer Hospital, Shenyang, People's Republic of China.
Qingkun SongDepartment of Cancer Epidemiology, Cancer Institute & Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China.
Jing LiDepartment of Cancer Epidemiology, Cancer Institute & Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China.
Baoning ZhangCenter of Breast Disease, Cancer Institute & Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China.
Jinhu FanDepartment of Cancer Epidemiology, Cancer Institute & Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China.
Youlin QiaoDepartment of Cancer Epidemiology, Cancer Institute & Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China.
Xiaoming XieDepartment of Breast Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China.
Shan ZhengDepartment of Pathology, Cancer Institute & Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China.
Jianjun HeDepartment of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, 710061, Xi'an, People's Republic of China. chinahjj@163.com.
Ke WangDepartment of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, 710061, Xi'an, People's Republic of China. 979915080@qq.com.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNFirst Affiliated Hospital of Xi'an Jiaotong University · CNSun Yat-sen University Cancer Center · CNCentral South University · CNLiaoning Cancer Hospital & Institute · CNZhejiang Cancer Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe concordance rate of human epidermal growth factor receptor 2 (HER2) status between core needle biopsy (CNB) and subsequent excisional biopsies of the same tumor varies from 81 to 96%, which may cause inappropriate neoadjuvant therapy that impair the potential benefit from HER2 targeted therapy for patients. This study aimed to establish a nomogram to predict the HER2 status pre-operatively as an auxiliary diagnosis to CNB assessment.

methodsAmong 4211 breast cancer patients cataloged in the Nation-wide Multicenter 10-year Retrospective Clinical Epidemiological Study of Breast Cancer in China, 2291 patients with complete relevant information were included in this study, which were further randomized 3:1 and divided into a training set and a validation set. The nomogram was established based on independent predictors of HER2 positivity recognized by logistic regression analysis and further validated internally and externally.

resultsThe multivariate logistic regression analysis showed that T-stage, N-stage, estrogen receptor (ER) status, progesterone receptor (PR) status were independent predictors for HER2 status. The nomogram was thereby constructed by those independent predictors as well as histology type. The areas under the receiver operating characteristic curve (AUC) of the training set and the validation set were 0.636 and 0.681, respectively. The calibration plots demonstrated good fitness of the nomogram for HER2 status prediction. With the optimal cutoff value, the nomogram yielded 80.0% sensitivity, 43.1% specificity in the training set and 81.1% sensitivity, 49.8% specificity in the validation set.

conclusionsThe present nomogram can provide valuable information on HER2 status and combined with standard CNB assessment, clinicians could make more appropriate decision on neoadjuvant therapy of breast cancer.

Indexed as

Biomarkers, TumorBiopsy, Large-Core NeedleBreastBreast NeoplasmsChinaErb-b2 Receptor Tyrosine KinasesFemaleHumansImmunohistochemistryNeoadjuvant TherapyNeoplasm StagingNomogramsRetrospective StudiesRiskROC CurveSensitivity and SpecificityBiomarkers, TumorERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesBreast cancerHER2 statusNomogramPrediction and validation

Identifiers

PMID31054583
PMCPMC6500005
OpenAlexW2947940473

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LicenceCC BY
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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.