Taşkum İbrahim, Bademkıran Muhammed Hanifi, Çetin Furkan, Sucu Seyhun, Yergin Erkan, Balat Özcan, Özkaya Halil, Uzun Evren
Gaziantep City Hospital, Clinic of Obstetrics and Gynecology, Gaziantep, Turkey.
Gaziantep University Faculty of Medicine, Department of Obstetrics and Gynecology, Gaziantep, Turkey.
Turk J Obstet Gynecol. 2024 Mar 4;21(1):37-42. doi: 10.4274/tjod.galenos.2024.92597.
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.
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.
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).
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.
使用包含子宫内膜癌（EC）预后因素的预测模型，预测早期（1-2期）子宫内膜癌（EC）的淋巴管间隙浸润（LVSI）阳性情况。
我们纳入了2010年至2020年间在我们诊所接受全子宫切除术、双侧输卵管卵巢切除术及盆腔-腹主动脉旁淋巴结清扫术作为疑似早期EC主要治疗方法的461例患者。此外，对所有手术标本进行组织病理学检查，以确定LVSI的阳性或阴性，并根据这些病理结果将患者分为两组。记录并分析患者的年龄、绝经状态、组织学类型（1-2型）、组织学分级（1-2-3级）、肌层浸润深度和腹腔细胞学检查结果，作为患者的临床病理和人口统计学特征。局部加权回归散点平滑（Loess）算法确定观察结果与预测结果之间的关系。通过计算C指数评估算法之间的差异。
LVSI阳性与高龄、绝经、2型EC、高级别组织学分级、恶性腹腔细胞学检查、宫颈受累以及肿瘤超过肌层深度的50%显著相关（p均<0.001）。值得注意的是，LVSI与三个解释变量的相关性最强：1- 肌层浸润超过50%[比值比（OR）：3.78；95%置信区间（CI）：1.80-7.60]，2- 高级别组织学分级[OR = 1.98（1.20-3.20）95% CI]，3- 恶性腹腔细胞学检查[OR = 3.06（1.40-6.30）95% CI]。惩罚最大似然估计模型正确分类了87%的纳入患者（C指数：0.876）。
我们的预测模型可能有助于基于不同的预后因素预测LVSI。列线图中包含的预后因素与LVSI显著相关，特别是肌层浸润深度超过50%、高级别组织学分级和恶性腹腔细胞学检查。
