Qu-Xia Zhang1, Lv-Ping Zhuang2, Zhong-Yang Lin3. 1. Fujian Medical University Cancer Hospital, Fujian Cancer Hospital, No. 420 Fu-ma Road, Fuzhou, 350014, China. 473618399@qq.com. 2. Fujian Medical University, Fuzhou, China. 3. Department of Otolaryngology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Abstract
PURPOSE: Previous studies have shown that approximately 10% of nasopharyngeal cancer (NPC) patients die within a year of disease onset, and that age is an independent predictor. However, no predictive model has been developed. We aimed to establish novel prognostic models to predict the 1-year cancer-specific survival (CSS) of young, middle-aged, and older patients with NPC after radiotherapy. METHODS: The data of 2822 NPC patients who underwent radiotherapy between 2004 and 2015 were reviewed from the surveillance, epidemiology, and end results database. We divided them into young, middle-aged, and older people groups according to age (< 44 years, 45-59 years, and ≥ 60 years, respectively). Multivariate analyses were performed, and prognostic models were constructed. RESULTS: Multivariate analyses indicated that age, ethnicity, histological subtype, T, and M stage were independent predictors of 1-year CSS in the older people group. In contrast, ethnicity and age were not found to have predictive value in the young and middle-aged groups, respectively. Accordingly, three prognostic models with excellent predictive values were established for the three groups (C-indices: 0.791 [95% CI 0.722-0.859], 0.763 [95% CI 0.721-0.806] and 0.723 [95% CI 0.683-0.763], respectively). These predictive values are higher than those of the eighth edition American joint committee cancer tumor-node-metastasis (TNM) classification system. CONCLUSION: Three prognostic models for predicting the 1-year CSS of young, middle-aged, and older NPC patients after radiotherapy showed better predictive power than the TNM classification system. These models may guide treatment strategies and clinical decision-making in different cohorts.
PURPOSE: Previous studies have shown that approximately 10% of nasopharyngeal cancer (NPC) patients die within a year of disease onset, and that age is an independent predictor. However, no predictive model has been developed. We aimed to establish novel prognostic models to predict the 1-year cancer-specific survival (CSS) of young, middle-aged, and older patients with NPC after radiotherapy. METHODS: The data of 2822 NPC patients who underwent radiotherapy between 2004 and 2015 were reviewed from the surveillance, epidemiology, and end results database. We divided them into young, middle-aged, and older people groups according to age (< 44 years, 45-59 years, and ≥ 60 years, respectively). Multivariate analyses were performed, and prognostic models were constructed. RESULTS: Multivariate analyses indicated that age, ethnicity, histological subtype, T, and M stage were independent predictors of 1-year CSS in the older people group. In contrast, ethnicity and age were not found to have predictive value in the young and middle-aged groups, respectively. Accordingly, three prognostic models with excellent predictive values were established for the three groups (C-indices: 0.791 [95% CI 0.722-0.859], 0.763 [95% CI 0.721-0.806] and 0.723 [95% CI 0.683-0.763], respectively). These predictive values are higher than those of the eighth edition American joint committee cancer tumor-node-metastasis (TNM) classification system. CONCLUSION: Three prognostic models for predicting the 1-year CSS of young, middle-aged, and older NPC patients after radiotherapy showed better predictive power than the TNM classification system. These models may guide treatment strategies and clinical decision-making in different cohorts.
Entities:
Keywords:
Early mortality; Nasopharyngeal carcinoma; Nomogram; Prognosis; Surveillance, epidemiology, and end results (SEER) database
Authors: Stephen B Keysar; Phuong N Le; Bettina Miller; Brian C Jackson; Justin R Eagles; Cera Nieto; Jihye Kim; Binwu Tang; Magdalena J Glogowska; J Jason Morton; Nuria Padilla-Just; Karina Gomez; Emily Warnock; Julie Reisinger; John J Arcaroli; Wells A Messersmith; Lalage M Wakefield; Dexiang Gao; Aik-Choon Tan; Hilary Serracino; Vasilis Vasiliou; Dennis R Roop; Xiao-Jing Wang; Antonio Jimeno Journal: J Natl Cancer Inst Date: 2016-09-15 Impact factor: 13.506