Prognostic value of prognostic nutritional index on extranodal natural killer/T‐cell lymphoma patients: A multicenter propensity score matched analysis of 1022 cases in Huaihai Lymphoma Working Group

Author:

Shen Ziyuan1,Zhang Shuo2,Chen Xicheng2,Zhang Qing2,Jiao Yaxue2,Shi Yuye3,Zhang Hao4,Ye Jingjing5,Wang Ling6,Zhu Taigang7,Miao Yuqing8,Wang Liang9,Cai Guoqi1,Sang Wei2ORCID

Affiliation:

1. Department of Epidemiology and Biostatistics School of Public Health Anhui Medical University Hefei Anhui China

2. Department of Hematology Affiliated Hospital of Xuzhou Medical University Xuzhou Jiangsu China

3. Department of Hematology The First People's Hospital of Huaian Huaian Jiangsu China

4. Department of Hematology The Affiliated Hospital of Jining Medical University Jining Shandong China

5. Department of Hematology Qilu Hospital of Shandong University Jinan Shandong China

6. Department of Hematology Taian Central Hospital Taian Shandong China

7. Department of Hematology The General Hospital of Wanbei Coal‐Electric Group Suzhou Anhui China

8. Department of Hematology Yancheng First People's Hospital Yancheng Jiangsu China

9. Department of Hematology Beijing Tongren Hospital Capital Medical University Beijing China

Abstract

AbstractPrognostic nutritional index (PNI), comprised of serum albumin level and lymphocyte count, is associated with the prognosis of several malignant diseases, while the prognostic value of PNI in extranodal natural killer/T cell lymphoma, nasal type (ENKTL) remains unclear. This retrospective multicenter study aimed to investigate the value of PNI in predicting the prognosis of newly diagnosed ENKTL patients by using propensity score matched analysis (PSM). A total of 1022 newly diagnosed ENKTL patients were retrieved from Huaihai Lymphoma Working Group and clinicopathological variables were collected. MaxStat analysis was used to calculate the optimal cut‐off points of PNI and other continuous variables. The median age at diagnosis was 47 years and 69.4% were males, with the 5‐year OS of 71.7%. According to the MaxStat analysis, 41 was the optimal cut‐off point for PNI. The Pseudo R2 before matching was 0.250, and it decreased to less than 0.019 after matching. Confounding factors of the two groups were well balanced after PSM. Multivariable analysis revealed that PNI, Korean Prognostic Index (KPI), eastern cooperative oncology group performance status (ECOG PS), the prognostic index of natural killer lymphoma (PINK) and hemoglobin were independent prognostic factors for ENKTL. The results of subgroup analysis demonstrated that patients with low PNI could predict worse prognosis and re‐stratify patients in ECOG PS ≥ 2, EBER‐positive, the International Prognostic Index (IPI) (HIR + HR), and PINK (HR) groups. PNI combined with IPI, PINK and KPI could improve the prediction efficiency. In conclusion, PNI could accurately stratify the prognosis of ENKTL by PSM analysis and patients with low PNI had poorer prognosis.

Funder

Natural Science Foundation of Jiangsu Province

Publisher

Wiley

Subject

Cancer Research,Oncology,Hematology,General Medicine

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