Evidence map›Paper›PMID 41715142›Full record

ArticleInfectious agents and cancer2026

Prognostic role of whole blood Epstein‑Barr virus DNA load in angioimmunoblastic T-cell lymphoma.

Yi Zhong, Mengmeng Dong, Fang Yu, Yi Zhao, Lixia Zhu, Fengping Zhou, Wenjun Wu, Yi Li, Fangshu Guan, Linlin Huang and 6 more

Abstract read
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Article in Infectious agents and cancer, 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

What it found

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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

16 authors.

Yi ZhongThe First Affiliated Hospital of Medical School, Zhejiang University, Hangzhou, China.
Mengmeng DongThe First Affiliated Hospital of Medical School, Zhejiang University, Hangzhou, China.
Fang YuThe First Affiliated Hospital of Medical School, Zhejiang University, Hangzhou, China.
Yi ZhaoThe First Affiliated Hospital of Medical School, Zhejiang University, Hangzhou, China.
Lixia ZhuThe First Affiliated Hospital of Medical School, Zhejiang University, Hangzhou, China.
Fengping ZhouSir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Wenjun WuThe First Affiliated Hospital of Medical School, Zhejiang University, Hangzhou, China.
Yi LiThe First Affiliated Hospital of Medical School, Zhejiang University, Hangzhou, China.
Fangshu GuanThe First Affiliated Hospital of Medical School, Zhejiang University, Hangzhou, China.
Linlin HuangThe First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.
Xiujin YeThe First Affiliated Hospital of Medical School, Zhejiang University, Hangzhou, China.
Zhen CaiThe First Affiliated Hospital of Medical School, Zhejiang University, Hangzhou, China.
Jin ZhangSir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Baodong YeThe First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.
Qingming WangThe Second Affiliated Hospital of Nanchang University, Nanchang, China.
Jingsong HeThe First Affiliated Hospital of Medical School, Zhejiang University, Hangzhou, China. hejingsong@zju.edu.cn.

Funding

Key Project of the Zhejiang Higher Education Association's Special Project on "Smart Education and Digital Transformation of Teaching" KT2023416National Natural Science Foundation of China 82270206Natural Science Foundation of Zhejiang Province LZ22H160009
6 · The paper itself

Abstract

objectiveThe prognostic role of Epstein-Barr virus (EBV) DNA in aggressive angioimmunoblastic T-cell lymphoma (AITL) remains unclear. This study aimed to investigate the prognostic significance of whole blood EBV DNA at diagnosis in AITL patients, establish an optimal prognostic cutoff, and develop a novel prognostic index incorporating this viral biomarker.

methodsThis multicenter retrospective study included 323 newly diagnosed AITL patients. The optimal cutoff of EBV DNA was determined using maximally selected rank statistics. Independent prognostic factors identified by multivariate Cox regression were used to construct a novel prognostic index (AITL prognostic index [API]), which was internally validated and compared with existing models.

resultsAt diagnosis, 241 (74.6%) AITL patients were EBV DNA positive, with 143 (44.3%) exceeding the optimal cutoff for EBV DNA load of 6110 copies/mL. EBV DNA > 6110 copies/mL was established as an independent adverse factor for overall survival (HR, 1.553; p =.006), along with age ≥ 60 years, ECOG ≥ 2, platelets < 150 × 109/L, and extranodal sites > 1. Based on these thresholds, API was used to stratify patients into four distinct risk groups with significantly different median OS (p <.001) and demonstrated superior discriminatory power (Harrell’s C-statistic: 0.741; Akaike Information Criterion value: 1829.1) compared to IPI, PIT, PIAI, and AITL score.

conclusionsWhole blood EBV DNA load is a powerful, independent prognostic index in AITL. The novel prognostic index API integrates a quantitative EBV DNA cutoff, providing superior risk stratification over established prognostic models, and guideing clinical decision-making for AITL patients.

Indexed as

Angioimmunoblastic T-cell lymphomaEpstein-Barr virusPrognosisPrognostic model

Identifiers

PMID41715142
PMCPMC13023116

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.