Radiation Oncology (Jun 2023)

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

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

DOI
https://doi.org/10.1186/s13014-023-02272-x
Journal volume & issue
Vol. 18, no. 1
pp. 1 – 10

Abstract

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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.

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