Evidence map›Paper›PMID 40033269›Full record

ArticleBMC cancer2025

A novel prognostic model utilizing TMTV and SUVmax from

Hua Wang, Demei Feng, Yiwen Mo, Huangming Hong, Yingying Hu, Li Huang, Xiaolei Wei, Yajun Li, Haibin Huang, Runhui Zheng and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC cancer, 2025. 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. Prognostic value of lesion dissemination onQuantitative imaging in medicine and surgery · 2026
    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

18 authors.

Hua Wang *State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, P. R. China. wanghua@sysucc.org.cn.
Demei Feng *State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, P. R. China.
Yiwen Mo *State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, P. R. China.
Huangming Hong *Sichuan Caner Hospital & Institute / Sichuan Cancer Prevention and Control Center / Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, Sichuan, 610041, China.
Yingying HuState Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, P. R. China.
Li HuangThe Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, 646501, China.
Xiaolei WeiDepartment of Hematology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Yajun LiDepartment of Lymphoma & Hematology, Hunan Cancer Hospital, Changsha, Hunan, 410013, China.
Haibin HuangThe Third Affiliated Hospital of Southern Medical University, Guangzhou, Guangdong, 510070, China.
Runhui ZhengDepartment of Hematology, Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou, Guangdong, 510735, China.
Yonghua LiDepartment of Onset, Guangzhou Southern Theater Command General Hospital, Guangzhou, 510010, China.
Hui ZengThe First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, 510632, China.
Robert Peter GaleHaematology Research Centre, Department of Immunology and Inflammation, Imperial College London, London, UK.
Tian YingDepartment of Nuclear Medicine, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou, 510515, China.
Jing GuoThe Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, 646501, China.
Zhenshu XuDepartment of Hematology, Union Hospital, Fujian Medical University, Fujian Institute of Hematology, Fuzhou, Fujian, 350000, China. zhenshuxu@yahoo.com.
Wei FanState Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, P. R. China. fanwei@sysucc.org.cn.
Tongyu LinState Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, P. R. China. tongyulin@hotmail.com.

Funding

National Natural Science Foundation of China 81700148Natural Science Foundation of Guangdong Province 2021A1515010093
6 · The paper itself

Abstract

backgroundSurvival prediction accuracy of fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (

methodsWe analyzed 390 ENKTL patients with comprehensive clinical and survival data. All patients received asparaginase-based chemotherapy with or without radiotherapy, or radiotherapy alone. Metabolic tumor volume (MTV) was calculated using a 41% SUVmax threshold, and TLG was computed as MTV multiplied by the average SUV. Progression-free survival (PFS) and overall survival (OS) were assessed using Kaplan-Meier curves and compared with log-rank tests. Optimal cut-off values were determined using the Youden' index. Cox regression analysis identified significant prognostic factors. A nomogram predicting 1-, 3-, and 5-year survival was developed and validated using the C-index and calibration curves. Statistical significance was set at p < 0.05.

resultsOf the 390 patients, 262 (67.2%) were included in the training set and 128 (32.8%) in the validation set.

conclusionSUVmax, TMTV, and TLG are independent prognostic factors in ENKTL. Our new model, which integrates

Indexed as

Fluorodeoxyglucose F18Lymphoma, Extranodal NK-T-CellPositron Emission Tomography Computed TomographyAdolescentAdultAgedFemaleGlycolysisHumansKaplan-Meier EstimateMaleMiddle AgedNomogramsPrognosisRadiopharmaceuticalsRetrospective StudiesFluorodeoxyglucose F18Radiopharmaceuticals18F-FDG PET/CTExtra-nodal natural killer/T-cell lymphoma(ENKTL)SUVmaxTotal lesion glycolysis (TLG)Total metabolic tumor volume (TMTV)

Identifiers

PMID40033269
PMCPMC11874801

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

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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.