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
Received 11 December 2020
Accepted for publication 11 February 2021
Published 10 March 2021 Volume 2021:14 Pages 817—828
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 5
Editor who approved publication: Professor Ning Quan
Wang-Zhong Li,1,2,* Xin Hua,3,* Shu-Hui Lv,1,2,* Hu Liang,1,2 Guo-Ying Liu,1,2 Nian Lu,1,2 Wei-Xin Bei,1,2 Wei-Xiong Xia,1,2 Yan-Qun Xiang1,2
1State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, 510060, People’s Republic of China; 2Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, Guangzhou, 510060, People’s Republic of China; 3Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, 510060, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Yan-Qun Xiang; Wei-Xiong Xia
Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, Guangzhou, People’s Republic of China
Email [email protected]; [email protected]
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.
Keywords: metastatic nasopharyngeal carcinoma, nutritional status, cancer-related inflammation, chemotherapy efficacy, survival outcomes
This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License. By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.Download Article [PDF] View Full Text [HTML][Machine readable]