Surgical Care Science, Department of Molecular medicine and Surgery, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
Cancer and Translational Medicine Research Unit, Medical Research Center Oulu, University of Oulu, Oulu University Hospital, Oulu, Finland.
Ann Surg Oncol. 2019 Aug;26(8):2385-2391. doi: 10.1245/s10434-019-07352-5. Epub 2019 Apr 19.
Malnutrition after esophageal cancer surgery is associated with reduced health-related qualify of life. Therefore, a prediction model identifying patients at risk for severe weight loss after surgery was developed.
Data from a Swedish population-based cohort study, including 616 patients undergoing esophageal cancer surgery in 2001-2005, was used. Candidate predictors included risk factors available before and immediately after surgery. Severe weight loss was defined as ≥ 15% loss of body weight between the time of surgery and 6 months postoperatively. The prediction model was developed using multivariable models. The accuracy of the model was measured by the area under the receiver operating characteristics curve (AUC) with bootstrap validation. The model was externally validated in a hospital-based cohort of 91 surgically treated esophageal cancer patients in the United Kingdom in 2011-2016. Each predictor in the final model was assigned a corresponding risk score. The sum of risk scores was equivalent to an estimated probability for severe weight loss.
Among the 351 patients with 6 months follow-up data, 125 (36%) suffered from severe postoperative weight loss. The final prediction model included body mass index at diagnosis, preoperative weight loss, and neoadjuvant therapy. The AUC for the model was 0.78 (95% CI 0.74-0.83). In the validation cohort, the AUC was 0.76. A clinical risk assessment guide was derived from the prediction model.
This prediction model can preoperatively identify individuals with high risk of severe weight loss after esophageal cancer surgery. Intensive nutritional interventions for these patients are recommended.
食管癌手术后营养不良与健康相关生活质量降低有关。因此,开发了一种预测模型,以识别手术后发生严重体重减轻的风险患者。
使用了一项瑞典基于人群的队列研究的数据,该研究纳入了 2001-2005 年间接受食管癌手术的 616 例患者。候选预测因素包括手术前和手术后即刻可用的危险因素。严重体重减轻定义为手术至术后 6 个月之间体重下降≥15%。使用多变量模型开发预测模型。通过自举验证测量模型准确性的接受者操作特征曲线下面积(AUC)。该模型在 2011-2016 年间英国一家医院治疗的 91 例接受手术的食管癌患者的基于医院的队列中进行了外部验证。最终模型中的每个预测因素都被分配了相应的风险评分。风险评分的总和相当于严重体重减轻的估计概率。
在有 6 个月随访数据的 351 例患者中,有 125 例(36%)发生严重术后体重减轻。最终预测模型包括诊断时的体重指数、术前体重减轻和新辅助治疗。该模型的 AUC 为 0.78(95%CI 0.74-0.83)。在验证队列中,AUC 为 0.76。从预测模型中得出了临床风险评估指南。
该预测模型可在术前识别出食管癌手术后严重体重减轻风险较高的个体。建议对这些患者进行强化营养干预。