Evidence map›Paper›PMID 36874102›Full record

ArticleFrontiers in oncology2023

Characteristics of recurrence, predictors for relapse and prognosis of rapid relapse triple-negative breast cancer.

Shuang-Long Cai, Jing-Jing Liu, Ying-Xue Liu, Shao-Hong Yu, Xu Liu, Xiu-Quan Lin, Hong-Dan Chen, Xuan Fang, Tao Ma, Ya-Qing Li and 6 more

Abstract read
In one paragraph

Article in Frontiers in oncology, 2023. 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

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

14 citing papers in PubMed.

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  11. Multi-omics profile of exceptional long-term survivors of AJCC stage III triple-negative breast cancer.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2025
    Article
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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

16 authors.

Shuang-Long CaiThe Third Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Jing-Jing LiuThe Third Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Ying-Xue LiuThe Third Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Shao-Hong YuCollege of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
Xu LiuThe Third Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Xiu-Quan LinDepartment for Chronic and Noncommunicable Disease Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China.
Hong-Dan ChenFirst Department of Cadre Clinic, Provincial Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China.
Xuan FangThe Third Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Tao MaThe Third Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Ya-Qing LiKey Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Ying LiThe Third Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Chun-Yan LiThe Third Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Sheng ZhangThe Third Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Xiao-Geng ChenDepartment of Oncological Surgery, Provincial Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China.
Xiao-Jing GuoKey Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Jin ZhangThe Third Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Triple-negative breast cancer (TNBC) patients who recur at different times are associated with distinct biological characteristics and prognoses. Research on rapid-relapse TNBC (RR-TNBC) is sparse. In this study, we aimed to describe the characteristics of recurrence, predictors for relapse, and prognosis in rrTNBC patients. Methods: Clinicopathological data of 1584 TNBC patients from 2014 to 2016 were retrospectively reviewed. The characteristics of recurrence were compared between patients with RR-TNBC and slow relapse TNBC(SR-TNBC). All TNBC patients were randomly divided into a training set and a validation set to find predictors for rapid relapse. The multivariate logistic regression model was used to analyze the data of the training set. C-index and brier score analysis for predicting rapid relapse in the validation set was used to evaluate the discrimination and accuracy of the multivariate logistic model. Prognostic measurements were analyzed in all TNBC patients. Results: Compared with SR-TNBC patients, RR-TNBC patients tended to have a higher T staging, N staging, TNM staging, and low expression of stromal tumor-infiltrating lymphocytes (sTILs). The recurring characteristics were prone to appear as distant metastasis at the first relapse. The first metastatic site was apt to visceral metastasis and less likely to have chest wall or regional lymph node metastasis. Six predictors (postmenopausal status, metaplastic breast cancer,≥pT3 staging,≥pN1 staging, sTIL intermediate/high expression, and Her2 [1+]) were used to construct the predictive model of rapid relapse in TNBC patients. The C-index and brier score in the validation set was 0.861 and 0.095, respectively. This suggested that the predictive model had high discrimination and accuracy. The prognostic data for all TNBC patients showed that RR-TNBC patients had the worst prognosis, followed by SR-TNBC patients. Conclusion: RR-TNBC patients were associated with unique biological characteristics and worse outcomes compared to non-RR-TNBC patients.

Indexed as

biological characteristics analysisprognostic analysisrapid relapseslow relapsetriple negative breast cancer

Identifiers

PMID36874102
PMCPMC9978400

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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.