Barber Emma L, Rutstein Sarah, Miller William C, Gehrig Paola A
University of North Carolina, Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Chapel Hill, NC, United States.
University of North Carolina, Department of Health Policy and Management, Gillings School of Public Health, Chapel Hill, NC, United States; University of North Carolina, Division of Infectious Diseases, Department of Internal Medicine, Chapel Hill, NC, United States.
Gynecol Oncol. 2015 Dec;139(3):401-6. doi: 10.1016/j.ygyno.2015.09.080. Epub 2015 Oct 23.
Cytoreductive surgery for ovarian cancer has higher rates of postoperative complication than neoadjuvant chemotherapy followed by surgery. If patients at high risk of postoperative complication were identified preoperatively, primary therapy could be tailored. Our objective was to develop a predictive model to estimate the risk of major postoperative complication after primary cytoreductive surgery among elderly ovarian cancer patients.
Patients who underwent primary surgery for ovarian cancer between 2005 and 2013 were identified from the National Surgical Quality Improvement Project. Patients were selected using primary procedure CPT codes. Major complications were defined as grade 3 or higher complications on the validated Claviden-Dindo scale. Using logistic regression, we identified demographic and clinical characteristics predictive of postoperative complication.
We identified 2101 ovarian cancer patients of whom 35.9% were older than 65. Among women older than 65, the rate of major postoperative complication was 16.4%. Complications were directly associated with preoperative laboratory values (serum creatinine, platelets, white blood cell count, hematocrit), ascites, white race, and smoking status, and indirectly associated with albumin. Our predictive model had an area under receiver operating characteristic curve of 0.725. In order to not deny patients necessary surgery, we chose a 50% population rate of postoperative complication which produced model sensitivity of 9.8% and specificity of 98%.
Our predictive model uses easily and routinely obtained objective preoperative factors to estimate the risk of postoperative complication among elderly ovarian cancer patients. This information can be used to assess risk, manage postoperative expectations, and make decisions regarding initial treatment.
卵巢癌细胞减灭术的术后并发症发生率高于新辅助化疗后再行手术。如果术前能识别出术后并发症高危患者,就可以制定个体化的初始治疗方案。我们的目的是建立一个预测模型,以评估老年卵巢癌患者初次细胞减灭术后发生主要术后并发症的风险。
从国家外科质量改进项目中确定2005年至2013年间接受卵巢癌初次手术的患者。使用主要手术CPT编码选择患者。主要并发症定义为经验证的Claviden-Dindo分级为3级或更高的并发症。采用逻辑回归分析,确定预测术后并发症的人口统计学和临床特征。
我们纳入了2101例卵巢癌患者,其中35.9%年龄超过65岁。在65岁以上的女性中,术后主要并发症发生率为16.4%。并发症与术前实验室检查值(血清肌酐、血小板、白细胞计数、血细胞比容)、腹水、白种人和吸烟状况直接相关,与白蛋白间接相关。我们的预测模型的受试者工作特征曲线下面积为0.725。为了不拒绝患者进行必要的手术,我们选择了50%的术后并发症发生率,该模型的敏感性为9.8%,特异性为98%。
我们的预测模型使用易于常规获取的术前客观因素来评估老年卵巢癌患者术后并发症的风险。这些信息可用于评估风险、管理术后预期并做出初始治疗决策。