Background and purpose: Natural killer/T-cell lymphoma (NKTCL) is a scarce subtype of malignant lymphoma
and it has heterogeneous clinical manifestation and treatment effect. Currently
no precise risk stratification is used to guide prognosis. This study aimed to evaluate the prognostic impact of pre-treatme
nt peripheral blood absolute monocyte count (AMC) and platelet-lymphocyte ratio (PLR) in patients with primary nasal NKTCL
and provide more precise information for better risk stratification to select appropriate treatment and improve survival. Methods: Clinical data of 132 patients newly diagnosed with primary nasal NKTCL was collected in the Tianjin Medical University Cancer Institute and Hospital from Jan. 2008 to Dec. 2013. The relationship between AMC and PLR in pre-treatment peripheral blood and 5-year overall survival (OS) and progression-free survival (PFS) of patients was analyzed retrospectively. Independent prognostic factors of patients were determined by univariate analysis and Cox regression analysis. Results: Pre-treatment peripheral blood AMC and PLR play important roles in the prognosis stratification of patients with primary nasal NKTCL. The prognosis in patients of AMC0.5×10
9
/L were higher than those of AMC≥0.5×10
9
/L
The prognosis in patients of PLR150 were higher than those of PLR≥150 (P0.05). Based on the four independent risk factors of staging
ECOG scoring
AMC and PLR
we tried to establish a new prognostic model
dividing all patients into three different risk groups and found that the 5-year OS and PFS of three groups had significant statistical differences. Conclusion: Peripheral blood AMC and PLR were significantly correlated with the prognosis of patients with primary nasal NKTCL. The new prognostic patterns based on the four independent risk factors
such as staging
ECOG scoring
AMC and PLR may be more convenient and more economical than IPI (International Prognostic Index
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Related Author
Ying ZHENG
Dazhi XU
Jing YUAN
Changming ZHOU
Miao MO
Zezhou WANG
Jiangli WANG
Jie SHEN
Related Institution
Department of Cancer Prevention, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University
Department of Gastric Surgery, Division 1, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University
Shanghai Engineering Research Center of Artificial Intelligence Technology for Tumor Diseases