Evidence map›Paper›PMID 41212625›Full record

ArticleCancer medicine2025

Survival Prediction in Middle-Aged and Elderly Patients With Burkitt Lymphoma: A Comprehensive Nomogram Approach Based on SEER Data.

Xia Cao, Duanzong Zhang, Jichang Gong, Xin Yang, Jiqiong He, Yaqiong Li, Hongjiang Pu

Abstract read
In one paragraph

Article in Cancer medicine, 2025. 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
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Xia CaoDepartment of Hematology, Dazhou Central Hospital, Dazhou, Sichuan, China.ORCID https://orcid.org/0009-0008-5274-2555
Duanzong ZhangDepartment of Hematology, Dazhou Central Hospital, Dazhou, Sichuan, China.
Jichang GongDepartment of Hematology, Dazhou Central Hospital, Dazhou, Sichuan, China.
Xin YangDepartment of Hematology, Dazhou Central Hospital, Dazhou, Sichuan, China.
Jiqiong HeDepartment of Hematology, Dazhou Central Hospital, Dazhou, Sichuan, China.
Yaqiong LiDepartment of Hematology, Dazhou Central Hospital, Dazhou, Sichuan, China.
Hongjiang PuThe Third Affiliated Hospital of Kunming Medical University, Peking University Cancer Hospital Yunnan Hospital, Yunnan Cancer Hospital, Kunming, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBurkitt lymphoma (BL) in middle-aged and elderly populations presents unique prognostic challenges due to distinct biological behaviors and therapeutic vulnerabilities. Current prognostic tools inadequately address age-specific survival determinants in this understudied cohort.

methodsThis study used the Surveillance, Epidemiology, and End Results (SEER) data from patients diagnosed with BL between 2000 and 2020, aged 45 years and older. Through univariate and multivariate Cox regression analyses, we identified independent prognostic factors affecting overall survival (OS) and cancer-specific survival (CSS). Finally, nomograms were constructed, and the models were evaluated across three dimensions.

resultsMultivariate analysis results indicated that factors such as age, race, Ann Arbor stage, and chemotherapy were independently associated with OS, while age, Ann Arbor stage, radiotherapy, chemotherapy, and number of tumor masses were independently associated with CSS. The nomogram model effectively predicted the 1-, 3-, and 5-year probabilities of OS and CSS. The results from receiver operating characteristic curves, calibration curves, and decision curve analysis in the training and validation groups confirmed that the risk prediction nomogram could accurately predict the survival of BL patients.

conclusionThe nomogram model constructed in this study provides a personalized survival prediction tool for BL patients, effectively distinguishing the survival probabilities of different risk groups. This research offers new insights for risk stratification and treatment management of middle-aged and elderly BL patients.

Indexed as

Burkitt LymphomaNomogramsAgedAged, 80 and overAge FactorsFemaleHumansMaleMiddle AgedPrognosisSEER ProgramBurkitt lymphomaelderlynomogramprognostic modelSEER

Identifiers

PMID41212625
PMCPMC12599551

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