The value of the Prognostic Nutritional Index (PNI) in predicting outcomes and guiding the treatment strategy of nasopharyngeal carcinoma (NPC) patients receiving intensity-modulated radiotherapy (IMRT) with or without chemotherapy.
PURPOSE: The purpose of this study was to investigate the significance of the Prognostic Nutritional Index (PNI) in predicting prognoses and guiding treatment choices of nasopharyngeal carcinoma (NPC) patients receiving intensity-modulated radiotherapy (IMRT). METHODS: The 539 patients with newly diagnosed non-metastatic NPC were retrospectively analysed. The PNI was calculated as 10 x serum albumin (g/dL) + 0.005 x total lymphocyte count (per mm(3)). All patients were split randomly into a training set and a testing set. Receiver operating characteristic (ROC) curves were used to identify the cut-off value of PNI and test its prognostic validity. Survival curves were calculated by Kaplan-Meier method, and differences were compared with log-rank test. RESULTS: The median follow-up time was 109.5 months. The 5-year locoregional recurrence-free survival (LRRFS), distant metastasis-free survival (DMFS), disease-specific survival (DSS) and overall survival (OS) of the whole cohort were 90.6, 85.8, 85.3 and 82.7%, respectively. The PNI cut-off value was 52.0 in the training set, which was significant in predicting DMFS, DSS and OS in the testing set. According to the PNI cut-off value, 220 patients of II-IVb stage treated by concurrent chemoradiotherapy (CCRT) were classified into PNI </= 52.0 and >52.0 groups and the 5-year LRRFS, DMFS, DSS, and OS of PNI </= 52.0 group were significantly worse than the PNI > 52.0 group. CONCLUSION: Our results suggest that the PNI is a reliable independent prognostic factor in NPC patients treated with IMRT. For stage II-IVb patients with PNI </= 52.0, CCRT alone does not achieve satisfactory outcomes, and further studies on treatment optimization are needed.
No clinical trial protocols linked to this paper
Clinical trials are automatically linked when NCT numbers are found in the paper's title or abstract.PICO Elements
No PICO elements extracted yet. Click "Extract PICO" to analyze this paper.
Paper Details
MeSH Terms
Associated Data
No associated datasets or code repositories found for this paper.
Related Papers
Related paper suggestions will be available in future updates.