A novel predictive model of lymphovascular space invasion in early-stage endometrial cancer.

Autor:	Taşkum İ; Gaziantep City Hospital, Clinic of Obstetrics and Gynecology, Gaziantep, Turkey., Bademkıran MH; Gaziantep University Faculty of Medicine, Department of Obstetrics and Gynecology, Gaziantep, Turkey., Çetin F; Abdulkadir Yüksel State Hospital, Clinic of Obstetrics and Gynecology, Gaziantep, Turkey., Sucu S; Gaziantep University Faculty of Medicine, Department of Obstetrics and Gynecology, Gaziantep, Turkey., Yergin E; Gaziantep City Hospital, Clinic of Obstetrics and Gynecology, Gaziantep, Turkey., Balat Ö; Gaziantep University Faculty of Medicine, Department of Obstetrics and Gynecology, Gaziantep, Turkey., Özkaya H; Abdulkadir Yüksel State Hospital, Clinic of Obstetrics and Gynecology, Gaziantep, Turkey., Uzun E; Gaziantep University Faculty of Medicine, Department of Medical Pathology, Gaziantep, Turkey.
Jazyk:	angličtina
Zdroj:	Turkish journal of obstetrics and gynecology [Turk J Obstet Gynecol] 2024 Mar 04; Vol. 21 (1), pp. 37-42.
DOI:	10.4274/tjod.galenos.2024.92597
Abstrakt:	Objective: To predict lymphovascular space invasion (LVSI) positivity in early-stage (stage 1-2) endometrial cancer (EC) using a predictive model with prognostic factors of EC. Materials and Methods: We included 461 patients who underwent total hysterectomy and bilateral salpingo-oophorectomy with pelvic-paraaortic lymphadenectomy as the primary treatment for presumed early-stage EC at our clinic between 2010 and 2020. Moreover, all surgical specimens were examined histopathologically for the positivity or negativity of LVSI, and the patients were divided into two groups based on these pathologic outcomes. Age, menopausal status, histological type (type 1-2), histological grade (grades 1-2-3), depth of myometrial invasion, and peritoneal cytology results were recorded and analyzed as clinicopathological and demographic characteristics of the patients. The Loess algorithm determined the relationship between the observed and predicted outcomes. The distinction between the algorithms was evaluated by calculating the C-index. Results: LVSI positivity was significantly associated with advanced age, menopause, type 2 EC, advanced histological grade, malignant peritoneal cytology, cervical involvement, and a tumor exceeding 50% of the myometrial depth (p<0.001, respectively). Remarkably, LVSI was most strongly associated with three explanatory variables: 1- More than 50% myometrial invasion [odds ratio (OR): 3.78; 95% confidence interval (CI): 1.80-7.60], 2- Advanced histological grade [OR=1.98 (1.20-3.20) 95% CI], 3- Malignant peritoneal cytology [OR= 3.06 (1.40-6.30) 95% CI]. The penalized maximum likelihood estimation model correctly classified 87% of the included patients (C-index: 0.876). Conclusion: Our predictive model may help predict LVSI based on different prognostic factors. The prognostic factors included in the nomogram were significantly associated with LVSI, particularly myometrial invasion depth of more than 50%, advanced histological grade, and malignant peritoneal cytology. Competing Interests: Conflict of Interest: No conflict of interest was declared by the authors. (Copyright© 2024 The Author. Published by Galenos Publishing House on behalf of Turkish Society of Obstetrics and Gynecology.)
Databáze:	MEDLINE
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