简单介绍参数时间到事件模型。

IF 1.1 Q4 PHARMACOLOGY & PHARMACY
Translational and Clinical Pharmacology Pub Date : 2021-03-01 Epub Date: 2021-03-25 DOI:10.12793/tcp.2021.29.e7
Hyeong-Seok Lim
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引用次数: 2

摘要

本教程解释参数时间到事件(TTE)模型的基本概念,重点介绍常用的指数模型、威布尔模型和逻辑逻辑模型。TTE数据通常用作药物治疗效果或疾病预后的终点。虽然非参数Kaplan-Meier分析已被广泛应用于TTE数据分析,但参数化建模分析具有易于模拟、评价连续协变量等优点。将加速失效时间模型与比例风险模型一起作为TTE数据的协变量模型。与比例风险模型相比,加速失效时间模型更直观地反映了协变量改变TTE的协变量效应,而比例风险模型中协变量影响风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Brief introduction to parametric time to event model.

Brief introduction to parametric time to event model.

Brief introduction to parametric time to event model.

Brief introduction to parametric time to event model.

This tutorial explains the basic concept of parametric time to event (TTE) models, focusing on commonly used exponential, Weibull, and log-logistic model. TTE data is commonly used as endpoint for treatment effect of a drug or prognosis of diseases. Although non-parametric Kaplan-Meier analysis has been widely used for TTE data analysis, parametric modeling analysis has its own advantages such as ease of simulation, and evaluation of continuous covariate. Accelerated failure time model is introduced as a covariate model for TTE data together with proportional hazard model. Compared to proportional hazard model, accelerated failure time model provides more intuitive results on covariate effect since it states that covariates change TTE whereas in proportional hazard model covariates affect hazard.

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来源期刊
Translational and Clinical Pharmacology
Translational and Clinical Pharmacology Medicine-Pharmacology (medical)
CiteScore
1.60
自引率
11.10%
发文量
17
期刊介绍: Translational and Clinical Pharmacology (Transl Clin Pharmacol, TCP) is the official journal of the Korean Society for Clinical Pharmacology and Therapeutics (KSCPT). TCP is an interdisciplinary journal devoted to the dissemination of knowledge relating to all aspects of translational and clinical pharmacology. The categories for publication include pharmacokinetics (PK) and drug disposition, drug metabolism, pharmacodynamics (PD), clinical trials and design issues, pharmacogenomics and pharmacogenetics, pharmacometrics, pharmacoepidemiology, pharmacovigilence, and human pharmacology. Studies involving animal models, pharmacological characterization, and clinical trials are appropriate for consideration.
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