The Use of Readily Available Longitudinal Data to Predict the Likelihood of Surgery in Crohn Disease.
The Use of Readily Available Longitudinal Data to Predict the Likelihood of Surgery in Crohn Disease.
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DOI：
10.1093/ibd/izab035
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发表时间：
2021-07-27
影响因子：
4.9
通讯作者：
Waljee AK
中科院分区：
文献类型：
--
作者：
Stidham RW;Liu Y;Enchakalody B;Van T;Krishnamurthy V;Su GL;Zhu J;Waljee AK
尽管影像学、内窥镜检查和炎症生物标志物与未来克罗恩病 (CD) 的结果相关，但常见的实验室研究也可能提供预后机会。我们评估了结合常规收集的实验室研究的机器学习模型，以预测患有 CD 的美国退伍军人的手术结果。使用退伍军人健康管理局、退伍军人综合服务网络 (VISN) 10 组 2001 年至 2015 年间检查的患有 CD 的成年人进行分析。使用患者人口统计数据、药物使用情况和纵向实验室值来模拟 1 年内未来的手术结果。具体来说，考虑预测时的数据结合历史实验室数据特征，描述为实验室值的斜率、分布统计、波动和线性趋势，并进行主成分分析变换以降低维度。 Lasso 正则化逻辑回归用于选择特征并构建预测模型，并使用 10 倍交叉验证按接收者操作特征下的面积评估性能。我们纳入了 2809 名独特患者（其中 256 名接受过手术）的 4950 项观察结果用于建模。我们的优化模型在接收器工作特性下实现了 0.78（SD，0.002）的平均面积。抗肿瘤坏死因子的使用与 1 年内较低的手术概率相关，并且是模型中最有影响力的预测因子，而皮质类固醇的使用与较高的手术概率相关。在实验室变量中，高血小板计数、高平均细胞血红蛋白浓度、低白蛋白水平和低血尿素氮值被确定为对未来手术具有较高的影响和关联。使用结合当前和历史数据的机器学习方法可以预测 CD 手术的未来风险。
Although imaging, endoscopy, and inflammatory biomarkers are associated with future Crohn disease (CD) outcomes, common laboratory studies may also provide prognostic opportunities. We evaluated machine learning models incorporating routinely collected laboratory studies to predict surgical outcomes in U.S. Veterans with CD. Adults with CD from a Veterans Health Administration, Veterans Integrated Service Networks (VISN) 10 cohort examined between 2001 and 2015 were used for analysis. Patient demographics, medication use, and longitudinal laboratory values were used to model future surgical outcomes within 1 year. Specifically, data at the time of prediction combined with historical laboratory data characteristics, described as slope, distribution statistics, fluctuation, and linear trend of laboratory values, were considered and principal component analysis transformations were performed to reduce the dimensionality. Lasso regularized logistic regression was used to select features and construct prediction models, with performance assessed by area under the receiver operating characteristic using 10-fold cross-validation. We included 4950 observations from 2809 unique patients, among whom 256 had surgery, for modeling. Our optimized model achieved a mean area under the receiver operating characteristic of 0.78 (SD, 0.002). Anti-tumor necrosis factor use was associated with a lower probability of surgery within 1 year and was the most influential predictor in the model, and corticosteroid use was associated with a higher probability of surgery. Among the laboratory variables, high platelet counts, high mean cell hemoglobin concentrations, low albumin levels, and low blood urea nitrogen values were identified as having an elevated influence and association with future surgery. Using machine learning methods that incorporate current and historical data can predict the future risk of CD surgery.
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影响因子：
4.9
作者：
Waljee AK;Lipson R;Wiitala WL;Zhang Y;Liu B;Zhu J;Wallace B;Govani SM;Stidham RW;Hayward R;Higgins PDR
通讯作者：
Higgins PDR
DOI：
10.1111/j.1467-9868.2011.00771.x
发表时间：
2011-01-01
影响因子：
5.8
作者：
Tibshirani, Robert
通讯作者：
Tibshirani, Robert
影响因子：
29.4
作者：
Schwartz, DA;Loftus, EV;Sandborn, WJ
通讯作者：
Sandborn, WJ
影响因子：
168.9
作者：
Colombel, Jean-Frederic;Panaccione, Remo;D'Haens, Geert
通讯作者：
D'Haens, Geert
影响因子：
3.1
作者：
Takeyama, Hiroshi;Mizushima, Tsunekazu;Mori, Masaki
通讯作者：
Mori, Masaki