| Autor: |
Dario de Biase, Thais Maloberti, Angelo Gianluca Corradini, Francesca Rosini, Marco Grillini, Martina Ruscelli, Sara Coluccelli, Annalisa Altimari, Elisa Gruppioni, Viviana Sanza, Daniela Turchetti, Andrea Galuppi, Martina Ferioli, Susanna Giunchi, Giulia Dondi, Marco Tesei, Gloria Ravegnini, Francesca Abbati, Daniela Rubino, Claudio Zamagni, Pierandrea De Iaco, Donatella Santini, Claudio Ceccarelli, Anna Myriam Perrone, Giovanni Tallini, Antonio De Leo |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Frontiers in Medicine, Vol 10 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2296-858X |
| DOI: |
10.3389/fmed.2023.1146499 |
| Popis: |
IntroductionThe European Society of Gynecologic Oncology/European Society of Radiation Therapy and Oncology/European Society of Pathology (ESGO/ESTRO/ESP) committee recently proposed a new risk stratification system for endometrial carcinoma (EC) patients that incorporates clinicopathologic and molecular features. The aim of the study is to compare the new ESGO/ESTRO/ESP risk classification system with the previous 2016 recommendations, evaluating the impact of molecular classification and defining a new algorithm for selecting cases for molecular analysis to assign the appropriate risk class.MethodsThe cohort included 211 consecutive EC patients. Immunohistochemistry and next-generation sequencing were used to assign molecular subgroups of EC: POLE mutant (POLE), mismatch repair deficient (MMRd), p53 mutant (p53abn), and no specific molecular profile (NSMP).ResultsImmuno-molecular analysis was successful in all cases, identifying the four molecular subgroups: 7.6% POLE, 32.2% MMRd, 20.9% p53abn, and 39.3% NSMP. The recent 2020 guidelines showed a 32.7% risk group change compared with the previous 2016 classification system: the reassignment is due to POLE mutations, abnormal p53 expression, and a better definition of lymphovascular space invasion. The 2020 system assigns more patients to lower-risk groups (42.2%) than the 2016 recommendation (25.6%). Considering the 2020 risk classification system that includes the difference between “unknown molecular classification” and “known,” the integration of molecular subgroups allowed 6.6% of patients to be recategorized into a different risk class. In addition, the use of the proposed algorithm based on histopathologic parameters would have resulted in a 62.6% reduction in molecular analysis, compared to applying molecular classification to all patients.ConclusionApplication of the new 2020 risk classification integrating clinicopathologic and molecular parameters provided more accurate identification of low-and high-risk patients, potentially allowing a more specific selection of patients for post-operative adjuvant therapy. The proposed histopathologic algorithm significantly decreases the number of tests needed and could be a promising tool for cost reduction without compromising prognostic stratification. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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