Prognostic model on overall survival in elderly nasopharyngeal carcinoma patients: a recursive partitioning analysis identifying pre-treatment risk stratification

Author:

Li Ying,Weng Youliang,Huang Zongwei,Pan Yuhui,Cai Sunqin,Ding Qin,Wu Zijie,Chen Xin,Lu Jun,Hu Dan,Qiu Sufang

Abstract

Abstract Background We aimed to evaluate the optimal management for elderly patients with nasopharyngeal carcinoma (NPC) with intensity-modulated radiotherapy (IMRT). Methods A total of 283 elderly patients with NPC diagnosed from 2015 to 2019 were enrolled in the study. Overall survival (OS) was the primary endpoint. Univariate and multivariate Cox regression analyses were preformed to identify potential prognostic factors. The recursive partitioning analysis (RPA) was used for risk stratification. Kaplan-Meier survival curves were applied to evaluate the survival endpoints, and log-rank test was utilized to assess differences between groups. The prognostic index (PI) was constructed to further predict patients’ prognosis displayed by nomogram model. The area under the receiver operating characteristic (ROC) curves (AUC) and the calibration curves were applied to assess the effectiveness of the model. Results Based on RPA-based risk stratification, we demonstrated that elderly NPC patients who were treated with IC followed by RT had similar OS as those with induction chemotherapy (IC) combined with concurrent chemoradiotherapy (CCRT) in the middle- (stage I-III and pre-treatment EBV > 1840 copies/ml) and high-risk groups (stage IVA). IMRT alone may be the optimal treatment option for the low-risk group (stage I-III with pre-treatment EBV ≤ 1840 copies/ml). We established an integrated PI which was indicted with stronger prognostic power than each of the factors alone for elderly NPC patients (The AUC of PI was 0.75, 0.80, and 0.82 for 1-, 3-, 5-year prediction of OS, respectively). Conclusion We present a robust model for clinical stratification which could guide individual therapy for elderly NPC patients.

Funder

Innovative Medicine Subject of Fujian Provincial Health Commission, China

Major Research Projects for Young and Middle-aged Health Researchers of Fujian Province, China

National Natural Science Foundation of China

Joint Funds for the Innovation of Science and Technology,Fujian Province

High-level Talent Training Program of Fujian Cancer Hospital

Science and Technology Pilot Program of Fujian Province, China

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,Oncology

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