Abstract：
BACKGROUND: The Society of Thoracic Surgeons General Thoracic Surgery Database (STS-GTSD) previously reported short-term risk models for esophagectomy for esophageal cancer. We sought to update existing models using more inclusive contemporary cohorts, with consideration of additional risk factors based on clinical evidence.
METHODS: The study population consisted of adult patients in the STS-GTSD who underwent esophagectomy for esophageal cancer between January 2015 and December 2022. Separate esophagectomy risk models were derived for three primary endpoints: operative mortality, major morbidity, and composite morbidity or mortality. Logistic regression with backward selection was used with predictors retained in models if p<0.10. All derived models were validated using 9-fold cross validation. Model discrimination and calibration were assessed for the overall cohort and specified subgroups.
RESULTS: A total of 18,503 patients from 254 centers underwent esophagectomy for esophageal cancer. Operative mortality, morbidity, and composite morbidity or mortality rates were 3.4%, 30.5% and 30.9%, respectively. Novel predictors of short-term outcomes in the updated models included body surface area and insurance payor type. Overall discrimination was similar or superior to previous GTSD models for operative mortality [C-statistic = 0.72] and for composite morbidity or mortality [C-statistic = 0.62], Model discrimination was comparable across procedure- and demographic-specific sub-cohorts. Model calibration was excellent in all patient sub-groups.
CONCLUSIONS: The newly derived esophagectomy risk models showed similar or superior performance compared to previous models, with broader applicability and clinical face validity. These models provide robust preoperative risk estimation and can be used for shared decision-making, assessment of provider performance, and quality improvement.
METHODS: The study population consisted of adult patients in the STS-GTSD who underwent esophagectomy for esophageal cancer between January 2015 and December 2022. Separate esophagectomy risk models were derived for three primary endpoints: operative mortality, major morbidity, and composite morbidity or mortality. Logistic regression with backward selection was used with predictors retained in models if p<0.10. All derived models were validated using 9-fold cross validation. Model discrimination and calibration were assessed for the overall cohort and specified subgroups.
RESULTS: A total of 18,503 patients from 254 centers underwent esophagectomy for esophageal cancer. Operative mortality, morbidity, and composite morbidity or mortality rates were 3.4%, 30.5% and 30.9%, respectively. Novel predictors of short-term outcomes in the updated models included body surface area and insurance payor type. Overall discrimination was similar or superior to previous GTSD models for operative mortality [C-statistic = 0.72] and for composite morbidity or mortality [C-statistic = 0.62], Model discrimination was comparable across procedure- and demographic-specific sub-cohorts. Model calibration was excellent in all patient sub-groups.
CONCLUSIONS: The newly derived esophagectomy risk models showed similar or superior performance compared to previous models, with broader applicability and clinical face validity. These models provide robust preoperative risk estimation and can be used for shared decision-making, assessment of provider performance, and quality improvement.
摘要：
背景：胸外科医师协会普通胸外科数据库（STS-GTSD）先前报道了食道癌食管切除术的短期风险模型。我们试图使用更具包容性的当代队列更新现有模型，根据临床证据考虑其他危险因素。
方法：研究人群包括2015年1月至2022年12月接受食管癌切除术的STS-GTSD患者。针对三个主要终点，分别推导了食管切除术风险模型：手术死亡率，主要发病率，和复合发病率或死亡率。如果p<0.10，则使用反向选择的逻辑回归与模型中保留的预测因子。所有衍生模型均使用9倍交叉验证进行验证。评估整个队列和指定亚组的模型辨别和校准。
结果：来自254个中心的18,503例食管癌患者接受了食管癌切除术。手术死亡率，发病率，复合发病率或死亡率为3.4%，30.5%和30.9%，分别。更新模型中短期结果的新预测因子包括体表面积和保险付款人类型。对于手术死亡率[C统计量=0.72]和复合发病率或死亡率[C统计量=0.62]，总体区分与以前的GTSD模型相似或优于GTSD模型。模型歧视在程序和人口特定的子队列中具有可比性。模型校准在所有患者亚组中是优异的。
结论：新衍生的食管切除术风险模型与以前的模型相比表现相似或更好，具有更广泛的适用性和临床面部有效性。这些模型提供了稳健的术前风险估计，可用于共享决策，对提供商绩效的评估，和质量改进。
方法：研究人群包括2015年1月至2022年12月接受食管癌切除术的STS-GTSD患者。针对三个主要终点，分别推导了食管切除术风险模型：手术死亡率，主要发病率，和复合发病率或死亡率。如果p<0.10，则使用反向选择的逻辑回归与模型中保留的预测因子。所有衍生模型均使用9倍交叉验证进行验证。评估整个队列和指定亚组的模型辨别和校准。
结果：来自254个中心的18,503例食管癌患者接受了食管癌切除术。手术死亡率，发病率，复合发病率或死亡率为3.4%，30.5%和30.9%，分别。更新模型中短期结果的新预测因子包括体表面积和保险付款人类型。对于手术死亡率[C统计量=0.72]和复合发病率或死亡率[C统计量=0.62]，总体区分与以前的GTSD模型相似或优于GTSD模型。模型歧视在程序和人口特定的子队列中具有可比性。模型校准在所有患者亚组中是优异的。
结论：新衍生的食管切除术风险模型与以前的模型相比表现相似或更好，具有更广泛的适用性和临床面部有效性。这些模型提供了稳健的术前风险估计，可用于共享决策，对提供商绩效的评估，和质量改进。
