Derivation and validation of a nutrition-covered prognostic scoring system for extranodal NK/T-cell lymphoma

IntroductionPatients with aggressive lymphomas are at high risk of losing body resources, resulting in malnutrition, immunodeficiency and inferior outcomes. Nutritional status is closely associated with survival, but often neglected in the prognostic assessment. This study aimed to explore the significance of nutritional status in extranodal NK/T-cell lymphoma (ENKTL). MethodsUnivariate and multivariate Cox regression analyses were conducted to examine the significance of nutritional index on overall survival (OS) and progression-free survival (PFS). A nutrition-incorporated score system was constructed based on the multivariate results, and its calibration, discrimination and clinical utility were tested in the training and validation cohort. ResultsMultivariate analysis revealed controlling nutritional status (CONUT) score could independently predict OS (HR 10.247, P=0.001) and PFS (HR 5.587, P=0.001) in addition to prognostic index of natural killer lymphoma plus EBV (PINK-E). Herein, a reformative model, CONUT-PINK-E, was developed and further verified in external validation cohort. CONUT-PINK-E classified patients into three risk grades with significant survival differences (P < 0.001). Compared with the current models, CONUT-PINK-E presented superior discrimination, calibration and clinical benefit. DiscussionIn this study, we firstly verified that CONUT score was efficient to screen prognosis-related malnutrition in ENKTL. Moreover, we developed the first nutritional assessment-covered scoring system, CONUT-PINK-E, which might be a promising tool to provide references for clinical decision-making of ENKTL patients.

Automated summary

In this study, the significance of nutritional status in extranodal NK/T-cell lymphoma (ENKTL) was explored, and a new scoring system (CONUT-PINK-E) was developed to assess patients' nutritional status and prognosis. The results showed that CONUT-PINK-E could independently predict patients' overall survival and progression-free survival, and presented superior discrimination and clinical benefit compared to current models.