Nomograms Predictive of Recurrence in Malignant Tumors Treated With Skull Base Surgery: An International Collaborative Study.

Authors

Cristina Valero, Ian Ganly, Lillian A Boe, Snehal G Patel, Helena Levyn, Dauren Adilbay, Alana Eagan, Marc A Cohen, Junting Zheng, Mithat Gonen, Prathamesh Pai, Paolo Castelnuovo, Fang Ju Gao, Cesare Piazza, Piero Nicolai, Ben Panizza, James Bowman, Catherine Barnett, Luiz P Kowalski, Ronaldo N Toledo, Dan M Fliss, John R de Almeida, Ian Witterick, Philippe Herman, Walter Fontanella, Gregorio Sanchez Aniceto, Alvaro Rivero Calle, Sefik Hosal, Serdar Ozer, Subramania Iyer, Richard Harvey, C Rene Leemans, Jan-Jaap Hendrickx, Marcelo Figari, Luis Boccalatte, Ken Ichi Nibu, Peter Clarke, Catherine Rennie, Zhu Yi Ming, Claudio Cernea, Sergio Goncalves, Rodney J Schlosser, Fernando L Dias, Zoukaa Sargi, Shahzada Ahmed, Wojciech Golusinski, Se Heon Kim, Shirley Y Su, Shaan M Raza, Franco DeMonte, Ehab Hanna, Jatin P Shah

Published in

Head & neck. Jul 09, 2026. Epub Jul 09, 2026.

Abstract

This study aimed to develop predictive models for local (LR), regional (RR), and distant recurrence (DR) after skull base surgery for primary malignant tumors.
We analyzed 2179 patients (1995-2015) from an international multicenter database, split into training (n = 1297) and validation (n = 882) cohorts. Cox regression identified predictors of LR, RR, and DR, and nomograms were developed and validated using concordance indexes (C-indexes).
Median age was 56 years; 64% were male. The most common sites included the ethmoid sinus (38%), nasal cavity (25%), and maxillary sinus (20%). Squamous cell carcinoma was the most frequent histology (25%). LR predictors included brain invasion, higher-risk histology, pT3/T4, pN+, positive margins, and adjuvant therapy (protective). RR predictors included high-risk histology, pT3/T4, and pN+. DR predictors mirrored LR except for adjuvant therapy. C-indexes were around 0.7 for all endpoints.
These validated nomograms provide useful tools for recurrence risk stratification and personalized management.

PMID:
42425927
Bibliographic data and abstract were imported from PubMed on 10 Jul 2026.

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