Evidence map›Paper›PMID 41656424›Full record

ArticleEuropean journal of nuclear medicine and molecular imaging2026

Multimodal glyco-lipid-EBVDNA signature prognostic model for individualized risk stratification of locally advanced nasopharyngeal carcinoma.

Jiayu Zhou, Yuchen Hua, Chuanrun Zhang, Qin Liu, Ying Deng, Yuwen Kuang, Jiahuan Lu, Mengwen Wang, Jie Gong, Xiang Guo and 3 more

Abstract read
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In one paragraph

Article in European journal of nuclear medicine and molecular imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

13 authors.

Jiayu Zhou *State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People's Republic of China.
Yuchen Hua *State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People's Republic of China.
Chuanrun Zhang *State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People's Republic of China.
Qin LiuState Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People's Republic of China.
Ying DengState Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People's Republic of China.
Yuwen KuangState Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People's Republic of China.
Jiahuan LuState Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People's Republic of China.
Mengwen WangState Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People's Republic of China.
Jie GongState Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People's Republic of China.
Xiang GuoState Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People's Republic of China.
Xing Lv *State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People's Republic of China.
Zhenchong Yang *State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People's Republic of China.
Weixiong Xia *State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, People's Republic of China. xiawx@sysucc.org.cn.ORCID 0000-0002-2828-5963

Funding

National Natural Science Foundation of China 82572656
6 · The paper itself

Abstract

purposeTo develop and validate a novel risk stratification model for locally advanced nasopharyngeal carcinoma (LA-NPC) based on the "glyco-lipid-viral" axis, addressing the limitations of traditional TNM staging and single-modality biomarkers.

methodsA total of 486 LA-NPC patients were retrospectively enrolled, with a metabolomics subcohort (n = 121) selected. PET/CT-derived glycolytic parameters (MTV, TLG), serum lipid biomarkers, and pretreatment EBV DNA were integrated via recursive partitioning analysis (RPA) to construct the model. Its performance was compared with TNM staging and single-modality markers.

resultsA multimodal model was built via RPA in 121 LA-NPC patients, using Lipsig-Score (lipid metabolite signature score), naso_MTV (PET/CT), and pretreatment EBV DNA. Three risk groups were defined: low-risk (Lipsig-Score < 0.0127 + EBV DNA < 500 copies/mL), intermediate-risk (Lipsig-Score < 0.0127 + EBV DNA ≥ 500 copies/mL, or Lipsig-Score ≥ 0.0127 + naso_MTV < 5.5), and high-risk (Lipsig-Score ≥ 0.0127 + naso_MTV ≥ 5.5). Kaplan–Meier analysis showed significant differences in PFS (log-rank P < 0.0001) and OS (log-rank P < 0.001) among groups, with the model outperforming TNM staging and single-modal markers.

conclusionThe integrated model captures LA-NPC’s multi-dimensional biology, enabling precise risk stratification and providing a reliable basis for individualized treatment.

Indexed as

DNA, ViralHerpesvirus 4, HumanLipidsNasopharyngeal CarcinomaNasopharyngeal NeoplasmsAdultFemaleHumansMaleMiddle AgedNeoplasm StagingPositron Emission Tomography Computed TomographyPrognosisRetrospective StudiesRisk AssessmentDNA, ViralLipidsLipid metabolitesMultimodal modelNasopharyngeal carcinomaPET/CTRecursive partitioning analysis

Identifiers

PMID41656424

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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.