Department of Obstetrics and Gynecology, Shanxi Bethune Hospital (Shanxi Academy of Medical Sciences), Taiyuan, Shanxi, China.
Department of Obstetrics and Gynecology, Shanxi Bethune Hospital (Shanxi Academy of Medical Sciences), Taiyuan, Shanxi, China.
Thromb Res. 2021 Jun;202:52-58. doi: 10.1016/j.thromres.2021.02.035. Epub 2021 Mar 3.
Venous thromboembolism (VTE) is a common post-surgical complication of gynecological malignant tumors that has serious implications on the prognosis and quality-of-life of patients. However, there exists only a few recognized specific evaluation models for the occurrence of VTE after gynecological malignant tumor surgery. We aimed to establish a nomogram model that could predict the probability of post-surgical VTE in patients with gynecological malignancies.
We collected the clinical information of 673 patients who underwent surgery for gynecological malignant tumor in our hospital between January 2014 and May 2020. To reduce bias from confounding factors between groups, a 1:1 ratio propensity score matching (PSM) method was performed; meanwhile, univariate and multivariate analyses were applied to analyze the risk factors of VTE after surgeries. A nomogram prediction model was accordingly established and internally validated.
The predictors contained in the nomogram model included age, D-dimer value, body mass index (BMI), and surgical approach. The C-index of the model was 0.721 (95% confidence interval: 0.644-0.797), with good discrimination and calibration effect. The internally verified C-index value was 0.916. Decision curve analysis confirmed that the nomogram model was clinically useful when the incidence of thrombosis in patients was 10-75%.
Considering the risk factors of VTE after surgery for gynecological malignant tumor, a high-performance nomogram model was established and then validated to provide individual risk assessment and guide treatment decisions.
静脉血栓栓塞症（VTE）是妇科恶性肿瘤术后常见的并发症，对患者的预后和生活质量有严重影响。然而，目前针对妇科恶性肿瘤手术后 VTE 发生的评估模型尚未得到广泛认可。本研究旨在建立一种预测妇科恶性肿瘤患者术后 VTE 发生概率的列线图模型。
我们收集了 2014 年 1 月至 2020 年 5 月期间在我院接受妇科恶性肿瘤手术的 673 例患者的临床资料。为了减少组间混杂因素的偏差，采用 1:1 比例倾向评分匹配（PSM）方法；同时，采用单因素和多因素分析方法分析手术后 VTE 的风险因素。据此建立并内部验证了列线图预测模型。
列线图模型中的预测因子包括年龄、D-二聚体值、体重指数（BMI）和手术方式。模型的 C 指数为 0.721（95%置信区间：0.644-0.797），具有良好的区分度和校准效果。内部验证的 C 指数值为 0.916。决策曲线分析证实，当患者血栓形成率为 10%-75%时，该列线图模型具有临床应用价值。
本研究考虑了妇科恶性肿瘤手术后 VTE 的风险因素，建立并验证了一种高性能的列线图模型，为个体风险评估和治疗决策提供了指导。
