Head & neck · 2021
Development and validation of an improved classification and risk stratification system for carotid body tumors: Multinational collaborative cohort study.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Mehanna Hisham, Mistry Pankaj, Golusinski Pawel, Di Maio Pasquale, Nankivell Paul, Snider Francesco, Ferrante Angela M R, Montalto Nausica, Nicolai Piero, Marcantoni Alessandra, Grandi Cesare, Zavatta Marco, Grego Franco, Malec Kataryna, Hosal Sefik, Suslu Nilda, Kuscu Oguz, Torrealba Ignacio, Valdes Francisco, Sharma Neil, Ayuk John, Monksfield Peter, Irving Richard, Dunn Janet A, Kay Mark, Borsetto Daniele
Аннотация
BACKGROUND: This study aims to develop and validate a new classification system that better predicts combined risk of neurological and neurovascular complications following CBT surgery, crucial for treatment decision-making.
METHODS: Multinational retrospective cohort study with 199 consecutive cases. A cohort of 132 CBT cases was used to develop the new classification. To undertake external validation, assessment was made between the actual complication rate and predicted risk by the model on an independent cohort (n = 67).
RESULTS: Univariate analyses showed statistically significant associations between developing a complication and the following factors: craniocaudal dimension, volume, Shamblin classification, and Mehanna types. In the multivariate prognostic model, only Mehanna type remained as a significant risk predictor. The risk of developing complications increases with increasing Mehanna type.
CONCLUSIONS: We have developed and then validated a new classification and risk stratification system for CBTs, which demonstrated better prognostic power for the risk of developing neurovascular complications after surgery.
METHODS: Multinational retrospective cohort study with 199 consecutive cases. A cohort of 132 CBT cases was used to develop the new classification. To undertake external validation, assessment was made between the actual complication rate and predicted risk by the model on an independent cohort (n = 67).
RESULTS: Univariate analyses showed statistically significant associations between developing a complication and the following factors: craniocaudal dimension, volume, Shamblin classification, and Mehanna types. In the multivariate prognostic model, only Mehanna type remained as a significant risk predictor. The risk of developing complications increases with increasing Mehanna type.
CONCLUSIONS: We have developed and then validated a new classification and risk stratification system for CBTs, which demonstrated better prognostic power for the risk of developing neurovascular complications after surgery.