The objective of this study was to develop a nomogram for refining prognostication for patients with nondisseminated nasopharyngeal cancer (NPC) staged with the proposed 8th edition of the American Joint Committee on Cancer (AJCC)/Union for International Cancer Control (UICC) staging system.Consecutive patients who had been investigated with magnetic resonance imaging, staged with the proposed 8th edition of the AJCC/UICC staging system, and irradiated with intensity-modulated radiotherapy from June 2005 to December 2010 were analyzed. A cohort of 1197 patients treated at Fujian Provincial Cancer Hospital was used as the training set, and the results were validated with 412 patients from Pamela Youde Nethersole Eastern Hospital. Cox regression analyses were performed to identify significant prognostic factors for developing a nomogram to predict overall survival (OS). The discriminative ability was assessed with the concordance index (c-index). A recursive partitioning algorithm was applied to the survival scores of the combined set to categorize the patients into 3 risk groups.A multivariate analysis showed that age, gross primary tumor volume, and lactate dehydrogenase were independent prognostic factors for OS in addition to the stage group. The OS nomogram based on all these factors had a statistically higher bias-corrected c-index than prognostication based on the stage group alone (0.712 vs 0.622, P <.01). These results were consistent for both the training cohort and the validation cohort. Patients with <135 points were categorized as low-risk, patients with 135 to <160 points were categorized as intermediate-risk, and patients with =160 points were categorized as high-risk. Their 5-year OS rates were 92%, 84%, and 58%, respectively.The proposed nomogram could improve prognostication in comparison with the TNM stage group. This could aid in risk stratification for individual NPC patients. Cancer 2016;122:3307-3315. © 2016 American Cancer Society.
View details for DOI 10.1002/cncr.30198
View details for PubMedID 27434142