Prognosis Stratification Tools in Early-Stage Endometrial Cancer: Could We Improve Their Accuracy?

• Published in: Cancers Vol. 14; no. 4; p. 912
• Main Authors: Ramon-Patino, Jorge Luis, Ruz-Caracuel, Ignacio, Heredia-Soto, Victoria, Garcia de la Calle, Luis Eduardo, Zagidullin, Bulat, Wang, Yinyin, Berjon, Alberto, Lopez-Janeiro, Alvaro, Miguel, Maria, Escudero, Javier, Gallego, Alejandro, Castelo, Beatriz, Yebenes, Laura, Hernandez, Alicia, Feliu, Jaime, Pelaez-García, Alberto, Tang, Jing, Hardisson, David, Mendiola, Marta, Redondo, Andres
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 12.02.2022; MDPI
• Subjects: Accuracy; Biomarkers; Cancer; Classification; Endometrial cancer; Endometrium; Gynecology; Malignancy; Medical prognosis; Mutation; Oncology; Prognosis; Statistical analysis; Surgery; Tumors; Values; United States > US; endometrial cancer; risk assessment; CTNNB1; prognosis; biomarkers
• ISSN: 2072-6694; 2072-6694
• DOI: 10.3390/cancers14040912

There are three prognostic stratification tools used for endometrial cancer: ESMO-ESGO-ESTRO 2016, ProMisE, and ESGO-ESTRO-ESP 2020. However, these methods are not sufficiently accurate to address prognosis. The aim of this study was to investigate whether the integration of molecular classification and other biomarkers could be used to improve the prognosis stratification in early-stage endometrial cancer. Relapse-free and overall survival of each classifier were analyzed, and the c-index was employed to assess accuracy. Other biomarkers were explored to improve the precision of risk classifiers. We analyzed 293 patients. A comparison between the three classifiers showed an improved accuracy in ESGO-ESTRO-ESP 2020 when RFS was evaluated (c-index = 0.78), although we did not find broad differences between intermediate prognostic groups. Prognosis of these patients was better stratified with the incorporation of status to the 2020 classifier (c-index 0.81), with statistically significant and clinically relevant differences in 5-year RFS: 93.9% for low risk, 79.1% for intermediate merged group/ wild type, and 42.7% for high risk (including patients with mutation). The incorporation of molecular classification in risk stratification resulted in better discriminatory capability, which could be improved even further with the addition of mutational evaluation.