检索结果-南通市图书馆

A machine learning model for colorectal liver metastasis post-hepatectomy prognostications

Hepatobiliary Surgery and Nutrition 2023年第4期12卷 495-506,I0007-I0016页

作者： Cynthia Sin Nga Lam Alina Ashok Bharwani Evelyn Hui Yi Chan Vernice Hui Yan Chan Howard Lai Ho Au Margaret Kay Ho Shireen Rashed Bernard Ming Hong Kwong Wentao Fang Ka Wing Ma Chung Mau Lo Tan To Cheung Li Ka Shing Faculty of Medicine The University of Hong KongHong Kong SARChina Department of Surgery Li Ka Shing Faculty of MedicineThe University of Hong KongHong Kong SARChina

Background:Currently,surgical resection is the mainstay for colorectal liver metastases(CRLM)management and the only potentially curative treatment *** tools can support patient selection for surgical resection to maximize therapeutic *** study aimed to develop a survival prediction model using machine learning based on a multicenter patient sample in Hong ***:Patients who underwent hepatectomy for CRLM between 1 January 2009 and 31 December 2018 in four hospitals in Hong Kong were included in the *** analysis was performed using Cox proportional hazards(CPH).A stepwise selection on Cox multivariable models with Least Absolute Shrinkage and Selection Operator(LASSO)regression was applied to a multiply-imputed dataset to build a prediction *** model was validated in the validation set,and its performance was compared with that of Fong Clinical Risk Score(CRS)using concordance ***:A total of 572 patients were included with a median follow-up of 3.6 *** full models for overall survival(OS)and recurrence-free survival(RFS)consist of the same 8 established and novel variables,namely colorectal cancer nodal stage,CRLM neoadjuvant treatment,Charlson Comorbidity Score,pre-hepatectomy bilirubin and carcinoembryonic antigen(CEA)levels,CRLM largest tumor diameter,extrahepatic metastasis detected on positron emission-tomography(PET)-scan as well as KRAS *** CRLM Machine-learning Algorithm Prognostication model(CMAP)demonstrated better ability to predict OS(C-index=0.651),compared with the Fong CRS for 1-year(C-index=0.571)and 5-year OS(C-index=0.574).It also achieved a C-index of 0.651 for ***:We present a promising machine learning algorithm to individualize prognostications for patients following resection of CRLM with good discriminative ability.

关键词： Machine-learning colorectal liver metastasis(CRLM) prognostic model survival analysis hepatectomy outcome

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：