European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology · 2025
Nodal status in major salivary gland cancer: External validation of a novel N- classification.
Equivalence TrialСтатьяМногоцентровое исследованиеВалидационное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Lombardi Davide, Tomasoni Michele, Missale Francesco, Smeele Ludwig E, Van Lierde Charlotte, Van Eecke Matthieu, Pellini Raul, Mazzola Francesco, Ravanelli Marco, Farina Davide, Clark Jonathan, Low Tsui-Hui Hubert, Gupta Ruta, Fleming Jason C, Ghazal-Asswad Randa, Locati Laura, Filauro Marta, Peretti Giorgio, Patel Snehal, Gagliardini Laura, Bossi Paolo, Poorten Vincent Vander, Piazza Cesare
Аннотация
BACKGROUND: Nodal status has been considered an important prognosticator when dealing with MSGC. Since current TNM N-categories do not accurately stratify patients, alternative nodal staging systems have been advocated. Our group has previously proposed 3 novel N-classification models according to number of metastatic nodes, largest diameter of metastatic nodes, and a combination of these two parameters.
AIM OF THE STUDY: Through an external validation in a new multicentric cohort, the present study aims to confirm the superiority of the previously proposed models over the 8th TNM and to assess which of the models is the most reliable.
MATERIAL AND METHODS: The 3 novel N-classification systems were applied to the validation dataset. Significance of observed differences between primary and validation datasets was assessed using Fisher, chi-squared, and Mann-Whitney tests. Oncological outcomes were overall survival (OS) and recurrence free survival (RFS). Survival estimates were obtained through Kaplan-Meier method. The significance of observed differences in survival and hazard ratios (HRs) according to the levels of each N-classification system was estimated through log-rank test and Cox proportional hazard model, respectively.
RESULTS: N-classification considering number of metastatic nodes showed the best prognostic stratification, with significant differences among pN0, pN1 (number of NM < 4), and pN2 (number of NM ≥ 4) for both survival outcomes. This model confirmed to be superior to current TNM N-categories.
CONCLUSIONS: In patients with MSGC, overall number of involved lymph nodes is the most important prognostic factor, providing a more accurate risk stratification than that obtained using the current TNM classification.
AIM OF THE STUDY: Through an external validation in a new multicentric cohort, the present study aims to confirm the superiority of the previously proposed models over the 8th TNM and to assess which of the models is the most reliable.
MATERIAL AND METHODS: The 3 novel N-classification systems were applied to the validation dataset. Significance of observed differences between primary and validation datasets was assessed using Fisher, chi-squared, and Mann-Whitney tests. Oncological outcomes were overall survival (OS) and recurrence free survival (RFS). Survival estimates were obtained through Kaplan-Meier method. The significance of observed differences in survival and hazard ratios (HRs) according to the levels of each N-classification system was estimated through log-rank test and Cox proportional hazard model, respectively.
RESULTS: N-classification considering number of metastatic nodes showed the best prognostic stratification, with significant differences among pN0, pN1 (number of NM < 4), and pN2 (number of NM ≥ 4) for both survival outcomes. This model confirmed to be superior to current TNM N-categories.
CONCLUSIONS: In patients with MSGC, overall number of involved lymph nodes is the most important prognostic factor, providing a more accurate risk stratification than that obtained using the current TNM classification.