Visceral fat area and albumin based nutrition-related prognostic index model could better stratify the prognosis of diffuse large B-cell lymphoma in rituximab era

BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease and the existing prognosis systems based on clinical variables are difficult to stratify patients accurately. Nutritional indices play a meaningful role in prognosis of solid tumors, whereas the effect on DLBCL is still equivocal. This retrospective study aimed to develop a novel model based on nutritional indices and other clinical variables to accurately differentiate the prognosis of DLBCL. METHODS: A total of 129 patients pathologically diagnosed with DLBCL in Affiliated Hospital of Xuzhou Medical University from 2014 to 2018 were retrospectively recruited. The total fat area (TFA), visceral fat area (VFA) and subcutaneous fat area (SFA) at the third lumbar vertebra level spine were obtained by computed tomography (CT) to assess the effect of nutritional status on the prognosis of DLBCL. Principal component analysis was used to reduce the dimension of nutritional indices, and continuous variables were evaluated according to X-Tile and Restricted cubic spline. Univariable and multivariable Cox proportional hazard analyses were performed on potential variables. Kaplan-Meier method was utilized to evaluate survival probabilities and the differences between groups were assessed by log-rank test. RESULTS: X-Tile analysis divided VFA and albumin into two and three groups when applying 114.7 cm(2) of VFA, 38.3 and 42.4 g/L of albumin as the optimal cut-off points, respectively. The final scoring model of nutrition-related prognostic index (NPI) comprised four independent prognostic variables. The C-index of the final model was 0.823 [95% CI (0.749~0.897)] by bootstrap resampling. Finally, a maximum score of 6 points was obtained. Compared with IPI, NCCN-IPI and GELTAMO-IPI, NPI showed better accuracy in discerning the prognostic risk of patients. CONCLUSION: VFA and albumin were associated with the prognosis of DLBCL, and the NPI model based on nutritional indices could better stratify the prognosis of DLBCL.