The prognostic nutritional index, an independent predictor of overall survival for newly diagnosed follicular lymphoma in China

ObjectiveThe prognostic nutritional index (PNI) is an important prognostic factor for survival outcomes in various hematological malignancies. The current study focused on exploring the predictive value of the PNI in newly diagnosed follicular lymphoma (FL) in China. Materials and methodsThe clinical indicators and follow-up data of 176 patients who received chemotherapy or immunotherapy combined with chemotherapy with FL in our hospital from January 2016 to March 2022 were retrospectively analyzed. Cox proportional hazard model was used for univariate and multivariate analyses. Kaplan-Meier curves were used to calculate survival rates and draw survival curves. The log-rank test was applied to compare differences between groups. ResultsThe optimal cut-off value of PNI was 44.3. All patients were divided into a high PNI group (>44.3) and a low PNI group (<= 44.3). The low PNI group had a low CR rate and a high risk of death, with a tendency toward POD24, and Both OS and PFS were worse than those in the high PNI group. PNI was able to predict OS and PFS in FL patients and was the only independent predictor of OS (P = 0.014 HR 5.024; 95%CI 1.388 similar to 18.178) in multivariate analysis. PNI could re-stratify patients into groups of high FLIPI score, high FLIPI2 score, no POD24, and rituximab combined with chemotherapy. Moreover, integrating PNI into the FLIPI and FLIPI2 models improved the area under the curve (AUC) for more accurate survival prediction and prognosis. ConclusionPNI is a significant prognostic indicator for newly diagnosed FL in China that can early identify patients with poor prognosis and guide clinical treatment decisions.

Automated summary

The study aimed to explore the predictive value of prognostic nutritional index (PNI) in newly diagnosed follicular lymphoma (FL) in China. The results showed that PNI could predict survival outcomes in FL patients and was the only independent predictor of overall survival (OS). Integrating PNI into other models improved the accuracy of survival prediction.