Evidence map›Paper›PMID 41674967›Full record

ArticleTranslational cancer research2026

Toward individualized prognosis in primary breast diffuse large B-cell lymphoma: incidence trends and a predictive model.

Zhiwei Li, Zhaojun Wang, Jieyu Zhou, Yang Ye

Abstract read
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Article in Translational cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Zhiwei LiDepartment of Thyroid Breast Surgery, Dingli Clinical College of Wenzhou Medical University, The Second Affiliated Hospital of Shanghai University, Wenzhou Central Hospital, Wenzhou, China.
Zhaojun WangDepartment of Thyroid Breast Surgery, Dingli Clinical College of Wenzhou Medical University, The Second Affiliated Hospital of Shanghai University, Wenzhou Central Hospital, Wenzhou, China.
Jieyu ZhouDepartment of Thyroid Breast Surgery, Dingli Clinical College of Wenzhou Medical University, The Second Affiliated Hospital of Shanghai University, Wenzhou Central Hospital, Wenzhou, China.
Yang YeDepartment of Thyroid Breast Surgery, Dingli Clinical College of Wenzhou Medical University, The Second Affiliated Hospital of Shanghai University, Wenzhou Central Hospital, Wenzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Primary breast diffuse large B-cell lymphoma (PB-DLBCL) is a rare malignancy with limited population-level prognostic data. We aimed to characterize incidence trends, estimate dynamic conditional survival (CS), and develop a prognostic model for overall survival (OS) using Surveillance, Epidemiology, and End Results (SEER) data. Methods: We identified 792 patients with PB-DLBCL from the SEER database (2000-2021). Age-adjusted incidence rates were calculated to assess trends over time. 10-year CS probabilities were estimated to evaluate dynamic survival patterns. The cohort was randomly divided into training (n=554) and validation (n=238) sets. Best subset regression (BSR) and stepwise backward Cox regression were applied to identify the most informative prognostic variables, which were incorporated into a CS-nomogram. Model performance was assessed using calibration plots, time-dependent receiver operating characteristic curves, concordance index (C-index), and decision curve analysis (DCA). Results: The age-adjusted incidence of PB-DLBCL remained stable over two decades, with no significant trend [annual percent change (APC) =-0.16%]. CS analysis revealed that patients who survived the first post-diagnosis year had progressively improved long-term survival probabilities (10-year CS: 49% at diagnosis Conclusions: PB-DLBCL showed stable incidence and dynamic improvement in survival among patients who surpassed early post-diagnosis milestones. Age, stage, and chemotherapy were key prognostic determinants. The CS-nomogram provided a practical, individualized tool for dynamic survival prediction and risk stratification, supporting personalized clinical decision-making in this rare lymphoma subtype.

Indexed as

incidenceprediction modelPrimary breast diffuse large B-cell lymphoma (PB-DLBCL)Surveillance, Epidemiology, and End Results (SEER)survival

Identifiers

PMID41674967
PMCPMC12885912

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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.