Evidence map›Paper›PMID 41964897›Full record

ArticleFuture science OA2026

Nomograms for the prognosis prediction model of early-stage triple-negative breast cancer - based on SEER database.

Yaxue Wang, Fengyan Li

Abstract read
In one paragraph

Article in Future science OA, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Yaxue WangDepartment of Radiation Oncology, Collaborative Innovation Center of Cancer Medicine, State Key Laboratory of Oncology in South China, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China.ORCID 0009-0009-1520-8369
Fengyan LiDepartment of Radiation Oncology, Collaborative Innovation Center of Cancer Medicine, State Key Laboratory of Oncology in South China, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China.ORCID 0009-0001-1319-8912

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsTriple-negative breast cancer (TNBC) is aggressive and unresponsive to hormone therapy, drawing widespread attention to its treatment and prognosis. This study aimed to summarize the prognosis of early-stage TNBC and construct nomograms to accurately predict survival and improve treatment strategies. PATIENTS &

methodsThe modeling group comprised early-stage TNBC patients from the SEER database. Prognostic factors were identified via Cox regression, and nomograms were developed using R software. A validating group with identical screening criteria was assembled from Sun Yat-sen University Cancer Center. Validation involved the Concordance index, Receiver Operating Characteristic curves, and calibration curves.

resultsThe modeling group included 14,389 patients and the validating group 1,146. Age and seven other factors were independent predictors (P < 0.05) and were incorporated into the nomograms. The C-indices for disease-free survival were 0.884 (95% CI: 0.876-0.892) in the modeling group and 0.686 (95% CI: 0.653-0.719) in the validating group. For overall survival, C-indices were 0.873 (95% CI: 0.863-0.883) and 0.741 (95% CI: 0.702-0.780), respectively.

conclusionsThe constructed nomograms demonstrated good predictive performance and may serve as practical tools for risk stratification in early-stage TNBC. However, given the observational nature of the data, the associations between treatment-related factors and survival should be interpreted with caution and warrant confirmation in prospective studies.

Indexed as

nomogramprognostic modelSEER databasesurvival analysisTriple-negative breast cancer

Identifiers

PMID41964897
PMCPMC13078201

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