Predicting Individualized Postoperative Survival for Stage II/III Colon Cancer Using a Mobile Application Derived from the National Cancer Data Base.
Predicting Individualized Postoperative Survival for Stage II/III Colon Cancer Using a Mobile Application Derived from the National Cancer Data Base.
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DOI：
10.1016/j.jamcollsurg.2015.12.019
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发表时间：
2016-03
影响因子：
5.2
通讯作者：
Nurkin S
中科院分区：
文献类型：
--
作者：
Gabriel E;Attwood K;Thirunavukarasu P;Al-Sukhni E;Boland P;Nurkin S
预测计算器估计术后存活率，并辅助辅助治疗的决策过程。本研究的目的是为II/III期结肠癌患者创建一个术后总生存期(OS)计算器。包括影响OS的因素，包括合并症和术后变量。国家癌症数据库查询了2004至2006年间诊断为II/III期结肠癌并接受手术切除的患者。患者被随机分为测试(NT)队列和验证(NV)队列，前者包括80%的数据集，后者包括20%。对NT进行多变量Cox比例风险回归分析，以确定与5年OS相关的因素。这些被用来建立一个预测模型。使用NV队列对性能进行了评估，并将其转换为移动软件。共有129,040名患者接受了手术。在排除了原位癌、非腺癌组织学、一种以上恶性肿瘤、I期或IV期疾病或丢失数据的患者后，34,176名患者被用于开发该计算器。OS的独立预测因素包括患者特定的特征、病理因素和治疗选择，包括手术类型和辅助治疗。术后住院时间和非计划内再住院率也被作为术后并发症的替代指标(术后1天增加，风险比[HR]1.019，95%CI 1.018至1.021，P<；0.001；非计划内再入院与未再入院R1.35，95%CI 1.25至1.45，P<；0.001)。预测的5年OS率和实际的5年OS率在NV队列中进行了比较，5年区域的曲线为0.77。为II/III期结肠癌患者开发了个性化的术后OS计算器应用程序。这个预测模型使用了全国性的数据，最终形成了一个高度综合的、在临床上有用的工具。
Prediction calculators estimate postoperative survival and assist the decision-making process for adjuvant treatment. The objective of this study was to create a postoperative overall survival (OS) calculator for patients with stage II/III colon cancer. Factors that influence OS, including comorbidity and postoperative variables, were included. The National Cancer Data Base was queried for patients with stage II/III colon cancer, diagnosed between 2004 and 2006, who had surgical resection. Patients were randomly divided to a testing (nt) cohort comprising 80% of the dataset and a validation (nv) cohort comprising 20%. Multivariable Cox proportional hazards regression of nt was performed to identify factors associated with 5-year OS. These were used to build a prediction model. The performance was assessed using the nv cohort and translated into mobile software. A total of 129,040 patients had surgery. After exclusion of patients with carcinoma in situ, non-adenocarcinoma histology, more than 1 malignancy, stage I or IV disease, or missing data, 34,176 patients were used in the development of the calculator. Independent predictors of OS included patient-specific characteristics, pathologic factors, and treatment options, including type of surgery and adjuvant therapy. Length of postoperative stay and unplanned readmission rates were also incorporated as surrogates for postoperative complications (1-day increase in postoperative stay, hazard ratio [HR] 1.019, 95% CI 1.018 to 1.021, p < 0.001; unplanned readmission vs no readmission HR 1.35, 95% CI 1.25 to 1.45, p < 0.001). Predicted and actual 5-year OS rates were compared in the nv cohort with 5-year area under the curve of 0.77. An individualized, postoperative OS calculator application was developed for patients with stage II/III colon cancer. This prediction model uses nationwide data, culminating in a highly comprehensive, clinically useful tool.