A Revised Version of the TNM Classification Leads to Optimized Predictive Performance in Patients with Adrenocortical Carcinoma.
Journal
Hormone and metabolic research = Hormon- und Stoffwechselforschung = Hormones et metabolisme
ISSN: 1439-4286
Titre abrégé: Horm Metab Res
Pays: Germany
ID NLM: 0177722
Informations de publication
Date de publication:
Apr 2023
Apr 2023
Historique:
medline:
7
4
2023
pubmed:
25
2
2023
entrez:
24
2
2023
Statut:
ppublish
Résumé
The prognostic stratification of the current AJCC/UICC TNM classification for adrenocortical carcinoma (ACC) has been validated in only a few studies. In this study, it was hypothesized that redefining the T category cut-off would result in a significant improvement in estimated stage-related survival. In 935 patients with ACC from the SEER database, optimal cut-off values based on tumor size were first determined to redefine T1 and T2 categories. Cox proportional hazards regression analysis and receiver operating characteristics (ROC) were then used to determine the prognostic value of the revised version. A new cut-off value of 9.5 cm tumor size was established to differentiate between T1 and T2 tumors, leading to a revised TNM classification. As a result, a more homogeneous distribution of patients with ACC across all stages was observed. Notably, the predictive value of the newly proposed TNM classification in the ROC analysis exceeded that of the 7th and 8th editions of the AJCC/UICC classification system. Finally, the prognostic superiority of the revised TNM classification was confirmed in a multivariate Cox proportional hazards regression model. In conclusion, the present study demonstrates that updating the current staging system with revised T1 and T2 categories significantly improves the prediction of cancer-specific survival (CSS) in patients with ACC.
Identifiants
pubmed: 36828028
doi: 10.1055/a-2042-2431
pmc: PMC10076106
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
227-235Informations de copyright
The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).
Déclaration de conflit d'intérêts
The authors declare that they have no conflict of interest.
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