Scholarlink

Purpose <p>Sinonasal tumors are rare and heterogeneous diseases with a low incidence of neck node metastasis. This study aims to analyze the risk of neck nodes recurrences and to assess patterns and predictors of nodal recurrence in sinonasal malignancies.</p> Methods <p>Retrospective observational cohort study on 574 patients affected by sinonasal malignant tumor who were treated via endoscopic-assisted approaches between January 1998 and December 2023 in our tertiary-care referral University hospital. Nodal recurrence-free survival (N-RFS) was analyzed using Kaplan-Meier curves, with univariate and multivariate Cox regression identifying prognostic factors.</p> Results <p>Nodal involvement at diagnosis was observed in 3.1% (18/574) of patients. During a median follow-up of 62.9 months, nodal recurrence occurred in 6.8% (39/574). Histologies with the highest recurrence included sinonasal neuroendocrine carcinoma (23.5%), sinonasal undifferentiated carcinoma (18.8%), and olfactory neuroblastoma (12.8%). Univariate analysis revealed pT classification (pT &gt; 3), tumor grading (G3/G4), and surgical approach as significant predictors of nodal recurrence. In multivariate analysis, high-grade tumors (HR = 3.109, <i>p</i>&#xa0;= 0.003) and craniofacial/cranio-endoscopic approaches (HR = 2.495, <i>p</i>&#xa0;= 0.023) remained independently associated with worse N-RFS.</p> Conclusions <p>Histotype is the most important factor in determining the incidence and pattern of regional recurrence. Both high tumor grade and more extensive surgical procedures are independent predictors of regional failure. Therefore, long-term follow-up is essential, especially for specific histologies such as olfactory neuroblastoma and sinonasal neuroendocrine carcinoma. Elective neck treatment should be personalized, taking into account the tumor’s histology, grading and overall disease extent to optimize patient outcomes.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Patterns of lymph node recurrence in sinonasal cancers: risk factors and oncological outcomes

  • 期刊论文

  • 发表日期：

    2025年10月24日

查看全文
  • Gianluca Dalfino,
  • Giorgio Sileo,
  • Alessia Lambertoni,
  • Alberto Daniele Arosio,
  • Giulia Monti,
  • Marco Valentini,
  • Mario Turri Zanoni,
  • Maurizio Bignami

摘要

Purpose

Sinonasal tumors are rare and heterogeneous diseases with a low incidence of neck node metastasis. This study aims to analyze the risk of neck nodes recurrences and to assess patterns and predictors of nodal recurrence in sinonasal malignancies.

Methods

Retrospective observational cohort study on 574 patients affected by sinonasal malignant tumor who were treated via endoscopic-assisted approaches between January 1998 and December 2023 in our tertiary-care referral University hospital. Nodal recurrence-free survival (N-RFS) was analyzed using Kaplan-Meier curves, with univariate and multivariate Cox regression identifying prognostic factors.

Results

Nodal involvement at diagnosis was observed in 3.1% (18/574) of patients. During a median follow-up of 62.9 months, nodal recurrence occurred in 6.8% (39/574). Histologies with the highest recurrence included sinonasal neuroendocrine carcinoma (23.5%), sinonasal undifferentiated carcinoma (18.8%), and olfactory neuroblastoma (12.8%). Univariate analysis revealed pT classification (pT > 3), tumor grading (G3/G4), and surgical approach as significant predictors of nodal recurrence. In multivariate analysis, high-grade tumors (HR = 3.109, p = 0.003) and craniofacial/cranio-endoscopic approaches (HR = 2.495, p = 0.023) remained independently associated with worse N-RFS.

Conclusions

Histotype is the most important factor in determining the incidence and pattern of regional recurrence. Both high tumor grade and more extensive surgical procedures are independent predictors of regional failure. Therefore, long-term follow-up is essential, especially for specific histologies such as olfactory neuroblastoma and sinonasal neuroendocrine carcinoma. Elective neck treatment should be personalized, taking into account the tumor’s histology, grading and overall disease extent to optimize patient outcomes.