Software Application Profile: dynamicLM-a tool for performing dynamic risk prediction using a landmark supermodel for survival data under competing risks.

Software Application Profile: dynamicLM-a tool for performing dynamic risk prediction using a landmark supermodel for survival data under competing risks.
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软件应用程序简介:DynamicLM-使用具有里程碑意义的超级模型对竞争性风险下的生存数据执行动态风险预测的工具。

DOI:
10.1093/ije/dyad122
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发表时间:
2023-12-25
影响因子:
7.7
通讯作者:
Han, Summer S.
Han, Summer S.
中科院分区:
医学1区
文献类型:
--
作者:
Fries, Anya H.;Choi, Eunji;Wu, Julie T.;Lee, Justin H.;Ding, Victoria Y.;Huang, Robert J.;Liang, Su-Ying;Wakelee, Heather A.;Wilkens, Lynne R.;Cheng, Iona;Han, Summer S.

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提供预后的动态评估对于改善个性化医疗至关重要。生存数据的里程碑模型为疾病进展的动态预测提供了一个潜在的强大解决方案。然而,一直缺乏一个总的框架和灵活执行该模式,以纳入各种成果,如竞争性活动。我们提出了一个R包,dynamicLM,一个用户友好的工具的地标模型的动态预测的生存数据下竞争的风险,其中包括各种功能的数据准备,模型开发,预测和评估的预测性能。 dynamicLM是一个R包。该软件包包括以下选项:纳入时变协变量,捕获预测因子的时间依赖性效应,以及为有或无竞争风险的事件发生时间数据拟合特定原因的里程碑模型。用于评估预测性能的工具包括ROC曲线下时间依赖性面积、Brier评分和校准。可在GitHub [https://github.com/thehanlab/dynamicLM]上获取。
Providing a dynamic assessment of prognosis is essential for improved personalized medicine. The landmark model for survival data provides a potentially powerful solution to the dynamic prediction of disease progression. However, a general framework and a flexible implementation of the model that incorporates various outcomes, such as competing events, have been lacking. We present an R package, dynamicLM, a user-friendly tool for the landmark model for the dynamic prediction of survival data under competing risks, which includes various functions for data preparation, model development, prediction and evaluation of predictive performance. dynamicLM as an R package. The package includes options for incorporating time-varying covariates, capturing time-dependent effects of predictors and fitting a cause-specific landmark model for time-to-event data with or without competing risks. Tools for evaluating the prediction performance include time-dependent area under the ROC curve, Brier Score and calibration. Available on GitHub [https://github.com/thehanlab/dynamicLM].
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