Evidence map›Paper›PMID 41114808›Full record

ArticleAnnals of hematology2025

A novel prognostic model based on CA stage for enhanced stratification and survival prediction in patients with Natural killer/T-cell lymphoma.

Jingjing Ge, Zegeng Chen, Qunli Xiong, Huageng Huang, Le Yu, Huawei Weng, Zongyao Huang, Zhao Wang, Ying Tian, He Huang and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Annals of hematology, 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. 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

12 authors.

Jingjing Ge *Department of Medical Oncology, 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, China.
Zegeng Chen *Department of Medical Oncology, 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, China.
Qunli Xiong *Department of Medical Oncology, 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, China.
Huageng HuangDepartment of Medical Oncology, 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, China.
Le YuDepartment of Medical Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, 610041, China.
Huawei WengDepartment of Medical Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, 610041, China.
Zongyao HuangDepartment of Pathology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, 610041, China.
Zhao WangDepartment of Medical Oncology, 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, China.
Ying TianDepartment of Medical Oncology, 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, China.
He HuangDepartment of Medical Oncology, 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, China.
Huangming HongDepartment of Medical Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, 610041, China. honghuangming@scszlyy.org.cn.
Tongyu LinDepartment of Medical Oncology, 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, China. linty@sysucc.org.cn.

Funding

National Natural Science Foundation of China 82300216National Natural Science Foundation of China No.U24A20679, 82470237the Cancer Innovative Research Program of Sun Yat-sen University Cancer Center CIRP-SYSUCC-0022
6 · The paper itself

Abstract

This study aimed to identify key prognostic factors for Natural killer/T-cell lymphoma (NKTCL) in the context of L-asparaginase/pegaspargase-based therapy and to develop a simplified yet accurate prognostic model for risk stratification. Data from 854 NKTCL patients at the Sun Yat-sen University Cancer Center were divided into a training cohort (n = 598) and an internal validation cohort (n = 256). A further 222 patients from Sichuan Cancer Hospital & Institute were used to create an external validation cohort. Least absolute shrinkage and selection operator (LASSO) and Cox regression were used to identify independent risk factors for overall survival (OS). A nomogram (Nomogram-CA) was constructed and evaluated using the consistency index (C-index), calibration curves, time-dependent ROC (tdROC) and decision curve analysis (DCA). Kaplan-Meier survival curves were generated to show the difference in OS between groups. Age, CA stage, B symptoms and hemoglobin (Hb) level were all identified as independent risk factors for OS. Nomogram-CA was constructed based on multivariate analysis results. The DCA curves demonstrated that Nomogram-CA provided more net benefit to patients in the training, internal validation and external validation cohorts. Furthermore, analysis of the Kaplan-Meier survival curve revealed a significantly lower survival rate among patients identified as high-risk by Nomogram-CA when compared to those classified as low-risk (P < 0.05). Nomogram-CA constructed based on independent prognostic factors has better predictive ability compared to the traditional staging system, which can assist clinical doctors in evaluating patient prognosis.

Indexed as

Lymphoma, Extranodal NK-T-CellNomogramsAdolescentAdultAgedAsparaginaseFemaleHumansMaleMiddle AgedNeoplasm StagingPrognosisRetrospective StudiesRisk FactorsSurvival RateYoung AdultAsparaginaseCA stageNatural killer/T-cell lymphomaNomogramPrognosisSurvival

Identifiers

PMID41114808
PMCPMC12672774

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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.