Bagepalli Srinivas Sujatha, Kubakaddi Shruthi Sangamesh, Polisetti Samatha, Amber Shiny, Guruvare Shyamala, Vaman Pai Muralidhar
Department of Obstetrics and Gynecology, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, Karnataka, India.
Int J Womens Health. 2020 Oct 27;12:883-891. doi: 10.2147/IJWH.S268169. eCollection 2020.
Uterine cancer is the second most prevalent cancer of the female genital tract, with 90% of it being of endometrial origin. The aim of this research was to create and validate a risk-scoring model using patients' clinical variables in predicting premalignant and malignant lesions of the uterine endometrium among premenopausal women with abnormal uterine bleeding (AUB).
This is a retrospective cohort study conducted at a tertiary hospital of Southern India for a period of 5 years from July 2014 to August 2019, including women aged ≤55 years who had AUB and underwent endometrial biopsy. The incidence of atypical endometrial hyperplasia (AEH) and endometrial cancer (EC) was determined, and clinical and demographic variables were compared among cases (AEH/EC) and controls (no AEH/EC) using simple logistic regression. A risk-scoring model was derived and validated with a split-sample internal validation method.
A total of 472 premenopausal women presenting with AUB were included in the study. There were 20 women (4.2%) with AEH and eight (1.7%) with EC. We found a statistically significant positive correlation of an anovulatory pattern of bleeding (odds ratio [OR]=3.4; =0.009), age ≥45 years (OR=1.12; =0.01), body mass index (BMI) ≥30 kg/m (OR=2.46; =0.04) and diabetes mellitus (OR=3.00; =0.02) with a higher risk of AEH/EC diagnosis upon histopathological examination of endometrial biopsy specimens of the study population. A risk-scoring model (PAD30) was created using these variables to predict premalignant and malignant endometrial lesions. The best cutoff score derived by the receiver operating characteristics (ROC) curve, of ≥5, had a sensitivity of 85.7% and specificity of 87.6% with an area under the curve (AUC) of 0.84 (95% CI 0.75-0.93; =0.04). With a positive likelihood ratio of 6.91, our prediction model increases the post-test probability of AEH/EC to 30.6% from 6% of the pre-test probability.
The proposed model demonstrated a moderate diagnostic accuracy in predicting premalignant and malignant lesions of the uterine endometrium among symptomatic premenopausal women.
子宫癌是女性生殖道第二常见的癌症，其中90%起源于子宫内膜。本研究的目的是创建并验证一种风险评分模型，该模型利用患者的临床变量来预测绝经前子宫异常出血（AUB）女性子宫内膜的癌前病变和恶性病变。
这是一项在印度南部一家三级医院进行的回顾性队列研究，研究时间为2014年7月至2019年8月，为期5年，纳入年龄≤55岁且有AUB并接受子宫内膜活检的女性。确定非典型子宫内膜增生（AEH）和子宫内膜癌（EC）的发病率，并使用简单逻辑回归比较病例组（AEH/EC）和对照组（无AEH/EC）的临床和人口统计学变量。通过样本分割内部验证方法推导并验证了风险评分模型。
本研究共纳入472例绝经前AUB女性。有20例（4.2%）患有AEH，8例（1.7%）患有EC。我们发现，在对研究人群的子宫内膜活检标本进行组织病理学检查时，无排卵性出血模式（比值比[OR]=3.4；P=0.009）、年龄≥45岁（OR=1.12；P=0.01）、体重指数（BMI）≥30kg/m²（OR=2.46；P=0.04）和糖尿病（OR=3.00；P=0.02）与AEH/EC诊断风险较高存在统计学显著正相关。利用这些变量创建了一个风险评分模型（PAD30）来预测子宫内膜的癌前和恶性病变。通过受试者工作特征（ROC）曲线得出的最佳截断分数≥5，其灵敏度为85.7%，特异度为87.6%曲线下面积（AUC）为0.84（95%CI 0.75 - 0.93；P=0.04）。阳性似然比为6.91，我们的预测模型将AEH/EC的检验后概率从检验前概率的6%提高到30.6%。
所提出的模型在预测有症状的绝经前女性子宫内膜的癌前和恶性病变方面显示出中等诊断准确性。
