In national hospital databases, certain prognostic factors cannot be taken into account. The main objective was to estimate the performance of two models based on two databases: the Epithor clinical database and the French hospital database. For each of the two databases, we randomly sampled a training dataset with 70% of the data and a validation dataset with 30%. The performance of the models was assessed with the Brier score, the area under the receiver operating characteristic (AUC ROC) curve and the calibration of the model. For Epithor and the hospital database, the training dataset included 10,516 patients (with resp. 227 (2.16%) and 283 (2.7%) deaths) and the validation dataset included 4507 patients (with resp. 93 (2%) and 119 (2.64%) deaths). A total of 15 predictors were selected in the models (including FEV1, body mass index, ASA score and TNM stage for Epithor). The Brier score values were similar in the models of the two databases. For validation data, the AUC ROC curve was 0.73 [0.68–0.78] for Epithor and 0.8 [0.76–0.84] for the hospital database. The slope of the calibration plot was less than 1 for the two databases. This work showed that the performance of a model developed from a national hospital database is nearly as good as a performance obtained with Epithor, but it lacks crucial clinical variables such as FEV1, ASA score, or TNM stage.
在国家医院数据库中，某些预后因素无法被纳入考量。本研究的主要目的是基于两个数据库——Epithor临床数据库和法国医院数据库，评估两种模型的预测性能。针对每个数据库，我们随机抽取了70%的数据作为训练集，30%作为验证集。模型性能通过Brier评分、受试者工作特征曲线下面积（AUC ROC）以及模型校准度进行评估。在Epithor和医院数据库中，训练集分别包含10,516例患者（其中死亡病例分别为227例（2.16%）和283例（2.7%）），验证集分别包含4,507例患者（其中死亡病例分别为93例（2%）和119例（2.64%））。模型共筛选出15项预测因子（Epithor模型中包含FEV1、体重指数、ASA评分和TNM分期等指标）。两个数据库模型的Brier评分值相近。在验证数据中，Epithor的AUC ROC曲线为0.73 [0.68–0.78]，医院数据库为0.8 [0.76–0.84]。两个数据库的校准曲线斜率均小于1。本研究表明，基于国家医院数据库开发的模型性能与Epithor数据库所得结果相近，但缺乏FEV1、ASA评分、TNM分期等关键临床变量。
肿瘤(癌症)患者之家