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

AI Article Synopsis

  • The study aimed to predict lymphovascular space invasion (LVSI) in early-stage endometrial cancer patients using a special model that looks at different health factors.
  • They analyzed data from 461 patients who had surgery between 2010 and 2020, focusing on factors like age, cancer types, and how deep the cancer has invaded.
  • The results showed that certain factors, such as greater myometrial invasion and higher cancer grade, were strongly linked to LVSI, and their model accurately predicted patient outcomes 87% of the time.

Article Abstract

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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10920972PMC
http://dx.doi.org/10.4274/tjod.galenos.2024.92597DOI Listing

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