A Scoring System Based on Nutritional and Inflammatory Parameters to Predict the Efficacy of First-Line Chemotherapy and Survival Outcomes for De Novo Metastatic Nasopharyngeal Carcinoma.

Abstract

PURPOSE:

We aimed to develop a simple scoring system based on baseline inflammatory and nutritional parameters to predict the efficacy of first-line chemotherapy and survival outcomes for de novo metastatic nasopharyngeal carcinoma (mNPC).

PATIENTS AND METHODS:

We retrospectively collected ten candidate inflammatory and nutritional parameters from de novo mNPC patients who received platinum-based first-line chemotherapy treatment. We examined the effects of these ten candidate variables on progression-free survival (PFS) using the Cox regression model. We built a risk-scoring system based on the regression coefficients associated with the identified independent prognostic factors. The predictive accuracy of the scoring system was evaluated and independently validated.

RESULTS:

A total of 460 patients were analyzed. Four independent prognostic factors were identified in a training cohort and were used to construct the scoring system, including nutritional risk index, C-reactive protein level, alkaline phosphatase level, and lactate dehydrogenase level. Based on the score obtained from the scoring system, we stratified patients into three prognostic subgroups (low: 0-1 point, intermediate: 2-3 points, and high: 4 points) associated with significantly different disease control rates (94.7% vs. 92.5% vs. 66.0%, respectively) and survival outcomes (3-year PFS: 55.8% vs. 29.1% vs. 11.9%, respectively). The scoring system had a good performance for the prediction of short-term disease control (area under the receiver operating characteristic curve [AUC]: 0.701) and long-term survival outcomes (time-dependent AUC for 5-year PFS: 0.713). The results were internally validated using an independent cohort (AUC for predicting disease control: 0.697; time-dependent AUC for 5-year PFS: 0.713).

CONCLUSION:

We developed and validated a clinically useful risk-scoring system that could predict the efficacy of first-line chemotherapy and survival outcomes in de novo mNPC patients. This system may help clinicians to design personalized treatment strategies.

• Authors: Wang-Zhong Li, Xin Hua, Shu-Hui Lv, Hu Liang, Guo-Ying Liu, Nian Lu, Wei-Xin Bei, Wei-Xiong Xia, Yan-Qun Xiang
• Journal: Journal of inflammation research (J Inflamm Res) Vol. 14 Pg. 817-828 ( 2021) ISSN: 1178-7031 [Print] New Zealand
• PMID: 33732007 (Publication Type: Journal Article)
• Copyright: © 2021 Li et al.