Evidence map›Paper›PMID 39934426›Full record

ArticleAnnals of hematology2025

Metabolic parameter of baseline 18 F-FDG PET/CT with PINK models improve the prediction of treatment outcome in extranodal NK/T-cell lymphoma treated with P-GEMOX chemotherapy.

Cheng Huang, Yi Li, Haixia He, Yan Gao, Xu Zhang, Bing Bai, Liqin Ping, Yanxia He, Shoumin Bai, Xiaoxiao Wang and 1 more

Abstract read
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. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Cheng Huang *Department of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Sun Yat-Sen University, Guangzhou, Guangdong, China.ORCID http://orcid.org/0000-0003-1358-6293
Yi Li *Department of Radiation Oncology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.ORCID http://orcid.org/0000-0001-7363-4387
Haixia He *Department of Radiation Oncology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.ORCID http://orcid.org/0000-0003-4614-6892
Yan GaoDepartment of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Sun Yat-Sen University, Guangzhou, Guangdong, China.ORCID http://orcid.org/0000-0002-6829-5955
Xu ZhangDepartment of Nuclear Medicine, Sun Yat-Sen University Cancer Center, Sun Yat-Sen University, Guangzhou, Guangdong, China.ORCID http://orcid.org/0000-0001-8937-9042
Bing BaiDepartment of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Sun Yat-Sen University, Guangzhou, Guangdong, China.ORCID http://orcid.org/0000-0003-3708-7640
Liqin PingDepartment of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Sun Yat-Sen University, Guangzhou, Guangdong, China.ORCID http://orcid.org/0000-0002-2556-7834
Yanxia HeDepartment of Oncology, Chengdu Third People's Hospital, Chengdu, Sichuan, China.ORCID http://orcid.org/0000-0002-6389-6903
Shoumin BaiDepartment of Radiation Oncology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
Xiaoxiao WangDepartment of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Sun Yat-Sen University, Guangzhou, Guangdong, China. wangxx@sysucc.org.cn.ORCID http://orcid.org/0000-0003-0568-263X
Huiqiang HuangDepartment of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Sun Yat-Sen University, Guangzhou, Guangdong, China. huanghqsysucc@163.com.ORCID http://orcid.org/0000-0002-4623-0536

Funding

National Natural Science Foundation of China 82170188
6 · The paper itself

Abstract

The aim of this study was to investigate the prognostic value of baseline PET/CT parameters alone and combined with clinical features in Extranodal Natural killer/T-cell lymphoma (ENKTL) patients treated with P-GEMOX regimen (pegaspargase, gemcitabine and oxaliplatin). A total of 97 patients were retrospectively evaluated. The relationships between baseline PETCT metabolic parameters and survival were tested using Cox regression analysis and receiver operating characteristic(ROC) curve analysis was employed to evaluate the optimal cut-off value of these parameters. Kaplan-Meier curves with log-rank tests were used for survival analysis. At a median follow-up of 49 months, the 3-year PFS and OS were 62.9% and 70.1%. SUVmean, SUVmax, and SUVpeak were related to both PFS and OS in univariate analysis(P < 0.05 for all). Further multivariate analysis including PET/CT parameters and clinical parameters revealed that SUVmean was an independent prognostic factor and seemed to be slightly superior to SUVmax and SUVpeak. The low SUVmean was significantly associated with a better prognosis (3-year OS 85.1% vs.65.0%, P = 0.014; 3-year PFS 76.8% vs.62.1%, P = 0.032). SUVmean was able to further separate patients with a low-risk PINK/PINKE of < 2(n = 85, 79, separately) into two subgroups with significantly different outcomes. Moreover, the metabolic-parameter-contained m-PINK/PINKE model was constructed and showed superior predictive performance in the whole cohort. Conclusions. SUVmean was an independent prognostic factor in patients with ENKTL treated with P-GEMOX chemotherapy. Adding SUVmean to the PINK or PINKE model could improve the predictive value and further distinguish patients with poor outcomes.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsFluorodeoxyglucose F18Lymphoma, Extranodal NK-T-CellPositron Emission Tomography Computed TomographyAdultAgedAsparaginaseDeoxycytidineFemaleFollow-Up StudiesGemcitabineHumansMaleMiddle AgedOrganoplatinum CompoundsOxaliplatinAsparaginaseDeoxycytidineFluorodeoxyglucose F18GemcitabineOrganoplatinum CompoundsOxaliplatinPolyethylene GlycolsRadiopharmaceuticalsExtranodal Natural killer/T-cell lymphomaMetabolic parameterPrognosis

Identifiers

PMID39934426
PMCPMC11971060

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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.