首页> 外文期刊>Gynecologic Oncology: An International Journal >Prediction of lymph node and distant metastasis in patients with endometrial carcinoma: A new model based on demographics, biochemical factors, and tumor histology
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Prediction of lymph node and distant metastasis in patients with endometrial carcinoma: A new model based on demographics, biochemical factors, and tumor histology

机译:子宫内膜癌患者淋巴结转移和远处转移的预测:基于人口统计学,生化因素和肿瘤组织学的新模型

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Objective To develop a model that might predict the probability of lymph node and distant metastasis (stages IIIC-IV) in endometrial carcinoma. Methods We studied 774 patients with endometrial carcinoma treated in a single institution. Demographic factors, biochemical factors and preoperative tumor characteristics, identified as potential risk factors for advanced carcinoma in unadjusted analyses, were used to create a logistic regression model with lymph node and distant metastasis as the dependent variable. Statistically significant odds ratios in the regression model were rounded to the nearest whole number. These rounded values were the estimated weights for each factor that were summed to generate a score that might predict the probability of stage IIIC-IV carcinoma. Results Biochemical factors and preoperative tumor characteristics predicted lymph node and distant metastasis in the regression model, whereas demographic factors were without effect. The score combining weighted risk factors was: (2 × leukocytosis) + (3 × thrombocytosis) + (7 × elevated CA125) + (4 × high-risk histology). The area under curve (AUC) for this total score was 0.823, with 71.6% sensitivity, 75.2% specificity, 25.9% positive predictive value, and 95.7% negative predictive value, using 6 as cut-point. After excluding stage IV carcinomas from the dataset, the AUC was 0.813 for the total score in predicting nodal involvement (P = 0.82 vs. total score in predicting stage IIIC-IV carcinomas in the complete dataset). Conclusions Based on the high negative predictive value, this prediction model could be applied for identifying patients who may not benefit from lymphadenectomy for endometrial carcinoma staging.
机译:目的建立可预测子宫内膜癌淋巴结和远处转移(IIIC-IV期)可能性的模型。方法我们研究了在单一机构中治疗的774例子宫内膜癌患者。在未经调整的分析中,人口统计学因素,生化因素和术前肿瘤特征被确定为晚期癌症的潜在危险因素,用于建立以淋巴结和远处转移为因变量的逻辑回归模型。回归模型中具有统计意义的优势比四舍五入到最接近的整数。这些四舍五入的值是每个因素的估计权重,这些权重相加后得出可以预测IIIC-IV期癌症可能性的分数。结果在回归模型中,生化因素和术前肿瘤特征可预测淋巴结和远处转移,而人口统计学因素则无影响。加权风险因素的综合得分为:(2×白细胞增多)+(3×血小板增多)+(7×升高的CA125)+(4×高风险组织学)。该总分的曲线下面积(AUC)为0.823,灵敏度为71.6%,特异性为75.2%,阳性预测值为25.9%,阴性预测值为95.7%,以6为切入点。从数据集中排除IV期癌后,预测淋巴结受累的总分的AUC为0.813(相对于完整数据集中预测IIIC-IV期癌的总分,P = 0.82)。结论基于较高的阴性预测价值,该预测模型可用于识别可能因子宫内膜癌分期未从淋巴结清扫术中受益的患者。

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