Medullary Thyroid Carcinomas Classified According to the International Medullary Carcinoma Grading System and a Surveillance, Epidemiology, and End Results-Based Metastatic Risk Score: A Correlation With Genetic Profile and Angioinvasion

Torricelli, Federica; Santandrea, Giacomo; Botti, Cecilia; Ragazzi, Moira; Vezzani, Silvia; Frasoldati, Andrea; Ghidini, Angelo; Giordano, Davide; Zanetti, Eleonora; Rossi, Teresa; Nicoli, Davide; Ciarrocchi, Alessia; Piana, Simonetta

doi:10.1016/j.modpat.2023.100244

Cited by 1 publication

(4 citation statements)

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“…Vascular space invasion appears to be a more adverse prognostic factor than lymphatic invasion. For example, Torricelli et al 12 . recently demonstrated that angioinvasion was significantly correlated with metastasis and death in a cohort of 66 patients with MTC.…”

Section: Discussionmentioning

confidence: 99%

“…Vascular space invasion appears to be a more adverse prognostic factor than lymphatic invasion. For example, Torricelli et al 12 recently demonstrated that angioinvasion was significantly correlated with metastasis and death in a cohort of 66 patients with MTC. However, some authorities find it difficult to confidently separate capillary from lymphatic space invasion in thyroid malignancies-summarized previously.…”

Section: Discussionmentioning

confidence: 99%

“…In 2022, the International Medullary Thyroid Carcinoma Grading System (IMTCGS) was developed and validated using a cohort of 327 patients with MTC from five centres across the USA, Europe, and Australia 9 . This two‐tiered grading scheme, which incorporates mitotic count, Ki67 proliferative index, and tumour necrosis, has been shown to be a robust independent prognostic tool for patients with MTC in both the original multi‐institutional cohort, and in multiple subsequent independent validation cohorts 10‐12 …”

Section: Introductionmentioning

confidence: 99%

“…9 This two-tiered grading scheme, which incorporates mitotic count, Ki67 proliferative index, and tumour necrosis, has been shown to be a robust independent prognostic tool for patients with MTC in both the original multi-institutional cohort, and in multiple subsequent independent validation cohorts. [10][11][12] As advances in artificial intelligence and machinelearning techniques continue to revolutionize medical practice, predictive modelling has become a popular technique for developing prognostic nomograms for various types of cancer. Nomograms have significant advantages over traditional prognostic techniques, as they can synthesize large numbers of complex variables in a systematic, unbiased manner.…”

Section: Introductionmentioning

confidence: 99%

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Novel prognostic nomogram for predicting recurrence‐free survival in medullary thyroid carcinoma

Aksoy,

Xu,

Viswanathan

et al. 2024

Histopathology

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AimsRecently, 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 ResultsData 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.ConclusionsUsing 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/.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%