| Autor: |
Aksoy, Yagiz A, Xu, Bin, Viswanathan, Kartik, Ahadi, Mahsa S, Al Ghuzlan, Abir, Alzumaili, Bayan, Bani, Mohamed‐Amine, Barletta, Justine A, Chau, Nicole, Chou, Angela, Clarkson, Adele, Clifton‐Bligh, Roderick J, De Leo, Antonio, Dogan, Snjezana, Ganly, Ian, Ghossein, Ronald, Gild, Matti L, Glover, Anthony R, Hadoux, Julien, Lamartina, Livia |
| Předmět: |
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| Zdroj: |
Histopathology; May2024, Vol. 84 Issue 6, p947-959, 13p |
| Abstrakt: |
Aims: Recently, there have been attempts to improve prognostication and therefore better guide treatment for patients with medullary thyroid carcinoma (MTC). In 2022, the International MTC Grading System (IMTCGS) was developed and validated using a multi‐institutional cohort of 327 patients. The aim of the current study was to build upon the findings of the IMTCGS to develop and validate a prognostic nomogram to predict recurrence‐free survival (RFS) in MTC. Methods and Results: Data from 300 patients with MTC from five centres across the USA, Europe, and Australia were used to develop a prognostic nomogram that included the following variables: age, sex, AJCC stage, tumour size, mitotic count, necrosis, Ki67 index, lymphovascular invasion, microscopic extrathyroidal extension, and margin status. A process of 10‐fold cross‐validation was used to optimize the model's performance. To assess discrimination and calibration, the area‐under‐the‐curve (AUC) of a receiver operating characteristic (ROC) curve, concordance‐index (C‐index), and dissimilarity index (D‐index) were calculated. Finally, the model was externally validated using a separate cohort of 87 MTC patients. The model demonstrated very strong performance, with an AUC of 0.94, a C‐index of 0.876, and a D‐index of 19.06. When applied to the external validation cohort, the model had an AUC of 0.9. Conclusions: Using well‐established clinicopathological prognostic variables, we developed and externally validated a robust multivariate prediction model for RFS in patients with resected MTC. The model demonstrates excellent predictive capability and may help guide decisions on patient management. The nomogram is freely available online at https://nomograms.shinyapps.io/MTC_ML_DFS/. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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