Evidence map›Paper›PMID 40069218›Full record

ArticleScientific reports2025

TNMpBC-NeoBCSS model: a breast cancer specific survival prediction model for triple-negative metaplastic breast carcinoma patients with neoadjuvant therapy.

Peng Ni, Yu Wang, Xiaorong Bai, Zejian Yang, Tao Wu, Chen Gao, Yuan Cheng, Ligang Niu, Yu Yan, Yuhui Zhou and 10 more

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
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  4. 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

20 authors.

Peng Ni *Department of Breast Surgery, First Affiliated Hospital, Xi'an Jiaotong University, 277 Yanta Western Rd., Xi'an, Xi'an, 710061, Shaanxi Province, China.
Yu Wang *Department of Breast Surgery, First Affiliated Hospital, Xi'an Jiaotong University, 277 Yanta Western Rd., Xi'an, Xi'an, 710061, Shaanxi Province, China.
Xiaorong Bai *Department of Breast Surgery, Gansu Cancer Hospital, Lanzhou, Gansu Province, China.
Zejian YangDepartment of Breast Surgery, First Affiliated Hospital, Xi'an Jiaotong University, 277 Yanta Western Rd., Xi'an, Xi'an, 710061, Shaanxi Province, China.
Tao WuThe Clinical Medical Research Center of Breast and Thyroid Tumor in Xinjiang, Xinjiang Key Laboratory of Oncology, the Affiliated Cancer Hospital of Xinjiang Medical University, Urumqi, 830011, China.
Chen GaoDepartment of Breast Surgery, Gansu Cancer Hospital, Lanzhou, Gansu Province, China.
Yuan ChengDepartment of Breast Surgery, First Affiliated Hospital, Xi'an Jiaotong University, 277 Yanta Western Rd., Xi'an, Xi'an, 710061, Shaanxi Province, China.
Ligang NiuDepartment of Breast Surgery, First Affiliated Hospital, Xi'an Jiaotong University, 277 Yanta Western Rd., Xi'an, Xi'an, 710061, Shaanxi Province, China.
Yu YanDepartment of Breast Surgery, First Affiliated Hospital, Xi'an Jiaotong University, 277 Yanta Western Rd., Xi'an, Xi'an, 710061, Shaanxi Province, China.
Yuhui ZhouDepartment of Breast Surgery, First Affiliated Hospital, Xi'an Jiaotong University, 277 Yanta Western Rd., Xi'an, Xi'an, 710061, Shaanxi Province, China.
Bohui ShiDepartment of Breast Surgery, First Affiliated Hospital, Xi'an Jiaotong University, 277 Yanta Western Rd., Xi'an, Xi'an, 710061, Shaanxi Province, China.
Guanqun GeDepartment of Breast Surgery, First Affiliated Hospital, Xi'an Jiaotong University, 277 Yanta Western Rd., Xi'an, Xi'an, 710061, Shaanxi Province, China.
Yi Long ChengSchool of Chemistry, Engineering Research Center of Energy Storage Materials and Devices, Ministry of Education, Xi'an Jiaotong University, Xi'an, 710049, Shaanxi, China.
Zhishen GeSchool of Chemistry, Engineering Research Center of Energy Storage Materials and Devices, Ministry of Education, Xi'an Jiaotong University, Xi'an, 710049, Shaanxi, China.
Yina JiangDepartment of Pathogenic Biology and Immunology, School of Basic Medical Sciences, Xi'an Jiaotong University Health Science, Xi'an, China.
Ran ZhangThe Clinical Medical Research Center of Breast and Thyroid Tumor in Xinjiang, Xinjiang Key Laboratory of Oncology, the Affiliated Cancer Hospital of Xinjiang Medical University, Urumqi, 830011, China.
Fan LiuDepartment of Breast Surgery, First Affiliated Hospital, Xi'an Jiaotong University, 277 Yanta Western Rd., Xi'an, Xi'an, 710061, Shaanxi Province, China.
Bo WangCenter for Translational Medicine, The First Affiliated Hospital of Xi'an Jiaotong University, 277 Yanta Western Rd, Xi'an, 710061, Shaanxi, China. realwbo@xjtu.edu.cn.
Yu RenDepartment of Breast Surgery, First Affiliated Hospital, Xi'an Jiaotong University, 277 Yanta Western Rd., Xi'an, Xi'an, 710061, Shaanxi Province, China. renyyyyy@126.com.
Can ZhouDepartment of Breast Surgery, First Affiliated Hospital, Xi'an Jiaotong University, 277 Yanta Western Rd., Xi'an, Xi'an, 710061, Shaanxi Province, China. zhoucanz2005@xjtufh.edu.cn.

Funding

Innovation ability support plan of Shaan Xi province 2022PT-24Xi'an Jiaotong University XJTU1AF2021LSL-029
6 · The paper itself

Abstract

The breast cancer specific survival (BCSS) benefits of Neoadjuvant therapy (NeoAT) for triple-negative metaplastic breast cancer (TNMpBC) was uncertain. This study aimed to develop a prediction model for assessing the BCSS for TNMpBC patients with NeoAT. The primary cohort of 1163 patients with TNMpBC, from which a nomogram was established based on the results of a LASSO regression analysis, was derived from multi-centers data in China and the SEER database. This model was further validated by an independent cohort of 155 TNMpBC patients with NeoAT, with discrimination and calibration assessed. Totally 155 (13.3%) TNMpBC patients received NeoAT, with 45 (29.0%) cases demonstrating pathologic complete response (pCR), were enrolled. Subjects acquired pCR had superior BCSS. Four variables significantly associated with BCSS were incorporated in the establishment of model: age at diagnosis, T stage, N stage, and response to NeoAT. This model was well validated, with a C-index of 0.82, and area under the curves of 0.838, 0.866 in training cohort, respectively, for 3- years and 5-years BCSS. Based on the cutoff scores from the TNMpBC-NeoBCSS model and calculated by X-tile analysis, patients in high risk group had a inferior BCSS (HR = 6.77, P < 0.0001) when compared with those in low-risk group. TNMpBC-NeoBCSS model provides a favorable tool for assessing the BCSS for the TNMpBC patients with NeoAT and may help doctors and TNMpBC patients optimally make decision on the necessity of neoadjuvant therapy on the basis of individual BCSS.

Indexed as

Neoadjuvant TherapyTriple Negative Breast NeoplasmsAdultAgedChinaFemaleHumansMiddle AgedNeoplasm StagingNomogramsPrognosisBreast cancer specific survivalNeoadjuvant therapyPathologic complete responseTNMpBC-NeoBCSS modelTriple-negative metaplastic breast cancer

Identifiers

PMID40069218
PMCPMC11897303

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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.