Evidence map›Paper›PMID 37074377›Full record

ArticleAnnals of hematology2023

The prognostic value of controlling nutritional status (CONUT) score-based nomogram on extranodal natural killer/T cell lymphoma patients.

Shuo Zhang, Cai Sun, Xicheng Chen, Dashan Li, Lingling Hu, Meng Zhang, Xudong Zhang, Hao Zhang, Jingjing Ye, Ling Wang and 8 more

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in Annals of hematology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.5field-weighted citation impact, top 18% of its field
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

4 citing papers in PubMed, 6 citations in OpenAlex.

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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 at 9 institutions in 1 country.

Shuo Zhang *Department of Hematology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221006, Jiangsu, China.
Cai Sun *Department of Hematology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221006, Jiangsu, China.
Xicheng Chen *Department of Hematology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221006, Jiangsu, China.
Dashan LiDepartment of Hematology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221006, Jiangsu, China.
Lingling HuDepartment of Hematology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221006, Jiangsu, China.
Meng ZhangDepartment of Hematology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221006, Jiangsu, China.
Xudong ZhangDepartment of Hematology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
Hao ZhangDepartment of Hematology, The Affiliated Hospital of Jining Medical University, Jining, 272000, Shandong, China.
Jingjing YeDepartment of Hematology, Qilu Hospital of Shandong University, Jinan, 250012, Shandong, China.
Ling WangDepartment of Hematology, Tai'an Central Hospital, Tai'an, 271000, Shandong, China.
Tao JiaDepartment of Hematology, The First People's Hospital of Lianyungang, Lianyungang, 222061, Jiangsu, China.
Taigang ZhuDepartment of Hematology, The General Hospital of Wanbei Coal-Electric Group, Suzhou, 234011, Anhui, China.
Yuqing MiaoDepartment of Hematology, Yancheng First People's Hospital, Yancheng, 224001, Jiangsu, China.
Chunling WangDepartment of Hematology, The First People's Hospital of Huai'an, Huai'an, 223300, Jiangsu, China.
Liang WangDepartment of Hematology, Beijing Tongren Hospital, Capital Medical University, Beijing, 100005, China.
Dongmei YanDepartment of Hematology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221006, Jiangsu, China.
Ziyuan ShenDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China.
Wei SangDepartment of Hematology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221006, Jiangsu, China. xyfylbl515@xzhmu.edu.cn.ORCID http://orcid.org/0000-0003-3119-5835
Xuzhou Medical College · CNBeijing Tongren Hospital · CNAffiliated Hospital of Jining Medical University · CNAnhui Medical University · CNFirst Affiliated Hospital of Zhengzhou University · CNHuaian First People’s Hospital · CNNantong University · CNQilu Hospital of Shandong University · CNThe First People’s Hospital of Lianyungang · CN

Funding

Jiangsu Key Research and Development Project of Social Development BE2019638Jiangsu Province's Graduate Scientific Research Innovation Program KYCX21-2685Natural Science Foundation of Jiangsu Province BK20171181Young Medical Talents of Jiangsu Science and Education Health Project QNRC2016791
6 · The paper itself

Abstract

Controlling nutritional status (CONUT) score as an original nutritional assessment tool can be used to assess the prognosis of patients with a variety of malignancies. However, the predictive power of CONUT in extranodal natural killer/T cell lymphoma (ENKTL) patients has never been demonstrated. Our retrospective multicenter study aimed to explore the prognostic value of CONUT in newly diagnosed ENKTL. A total of 1085 newly diagnosed ENKTL patients between 2003 and 2021 were retrospectively retrieved. Cox proportional hazard model was used to explore the prognostic factors of overall survival (OS). The survival rate of ENKTL was evaluated using Kaplan-Meier analysis, and log-rank test was applied to the difference between groups. We investigated the prognostic performance of CONUT, the International Prognostic Index (IPI), the Korean Prognostic Index (KPI), and the Prognostic Index of Natural Killer Cell Lymphoma (PINK) using the receiver operating characteristic (ROC) curve and decision curve analysis (DCA). The median age at diagnosis for the whole cohort was 47 years, and the male to female ratio was 2.2:1. The 5-year OS for all patients was 72.2%. Multivariable analysis showed that CONUT, age, bone marrow involvement, ECOG PS score, and Chinese Southwest Oncology Group and Asia Lymphoma Study Group ENKTL stage were identified as independent predictive factors for OS. Based on multivariable results, a prognostic nomogram was developed. Subgroup analysis demonstrated that patients with severe malnutrition had poorest clinical outcome. In addition, ROC curves and DCA analysis proved that compared with IPI, KPI, and PINK models, the CONUT score-based nomogram showed a better prognostic predictive efficiency of ENKTL. CONUT could effectively stratify the prognosis of ENKTL and the proposed nomogram based on CONUT was an effective prognostic model for prediction.

Indexed as

Lymphoma, Extranodal NK-T-CellNomogramsFemaleHumansKiller Cells, NaturalMaleNutritional StatusPrognosisRetrospective StudiesControlling Nutritional Status scoreExtranodal natural killer/T cell lymphomaNomogramNutritional indicesPrognosis

Identifiers

PMID37074377
OpenAlexW4366352617

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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.