中国系统性红斑狼疮患者生存分析模型开发与验证数据表

数据集获取（Figshare）

• 源站标题：DataSheet_1_Development and Verify of Survival Analysis Models for Chinese Patients With Systemic Lupus Erythematosus.pdf
• DOI：10.3389/fimmu.2022.900332.s001
• 发布日期：2022-06-24
• 文件数：1 个
• 文件总体积：2.17 MB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/DataSheet_1_Development_and_Verify_of_Survival_Analysis_Models_for_Chinese_Patients_With_Systemic_Lupus_Erythematosus_pdf/20139101

命令行下载

curl -L -o "DataSheet_1_Development and Verify of Survival Analysis Models for Chinese Patients With Systemic Lupus Erythematosus.pdf" "https://ndownloader.figshare.com/files/36019376"

文件清单

• DataSheet_1_Development and Verify of Survival Analysis Models for Chinese Patients With Systemic Lupus Erythematosus.pdf（2.17 MB）

文件总体积 2.17 MB（源站 API 实测）。

数据说明

BackgroundThe aim of this study is to develop survival analysis models of hospitalized systemic lupus erythematosus (h-SLE) patients in Jiangsu province using data mining techniques to predict patient survival outcomes and survival status.
MethodsIn this study, based on 1999–2009 survival data of 2453 hospitalized SLE (h-SLE) patients in Jiangsu Province, we not only used the Cox proportional hazards model to analyze patients’ survival factors, but also used neural network models to predict survival outcomes. We used semi-supervised learning to label the censored data and introduced cost-sensitivity to achieve data augmentation, addressing category imbalance and pseudo label credibility. In addition, the risk score model was developed by logistic regression.
ResultsThe overall accuracy of the survival outcome prediction model exceeded 0.7, and the sensitivity was close to 0.8, and through the comparative analysis of multiple indicators, our model outperformed traditional classifiers. The developed survival risk assessment model based on logistic regression found that there was a clear threshold, i.e., a survival threshold indicating the survival risk of patients, and cardiopulmonary and neuropsychiatric involvement, abnormal blood urea nitrogen levels and alanine aminotransferase level had the greatest impact on patient survival time. In addition, the study developed a graphical user interface (GUI) integrating survival analysis models to assist physicians in diagnosis and treatment.
ConclusionsThe proposed survival analysis scheme identifies disease-related pathogenic and prognosis factors, and has the potential to improve the effectiveness of clinical interventions.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fimmu.2022.900332.s001（source: https://frontiersin.figshare.com/articles/dataset/DataSheet_1_Development_and_Verify_of_Survival_Analysis_Models_for_Chinese_Patients_With_Systemic_Lupus_Erythematosus_pdf/20139101）。