带有类效应的网络元分析:实用指南和模型选择算法
Samuel J Perren1, Hugo Pedder2, Nicky J Welton2
1School of Mathematics, University of Bristol, Bristol, UK.
概括
本研究介绍了类效应网络元分析 (NMA) 模型,用于在类内比较多种治疗方法. 它为选择和应用这些先进的NMA模型提供了实用指南和R包实现.
科学领域:
- 生物统计学 生物统计学
- 医疗保健服务研究 医疗服务研究
- 临床流行病学 临床流行病学
背景情况:
- 网络元分析 (NMA) 合成了来自多个随机对照试验的证据.
- 类效应NMA模型将干预分为类,以改善证据综合,特别是在稀疏数据或断开网络的情况下.
- 现有的文献缺乏对类效应NMA模型的全面指南,包括它们的假设,实现和模型选择.
研究的目的:
- 为类效应NMA提供一个全面的建模框架.
- 在类效应NMA中提出模型选择的系统方法.
- 提供实用指南,用于实施类效应NMA使用"多元化"R包.
主要方法:
- 描述了具有随机/固定的治疗效应和可交换/常见类效应的等级NMA模型.
- 测试异质性,一致性和类效应假设的详细方法.
- 提出了模型选择策略,并评估了模型的合适性.
主要成果:
- 为类效应NMA开发了一个建模框架和实践指南.
- 用一个大型的NMA来说明这种方法,该NMA包含了17个类别的41个干预措施,用于治疗社会焦虑.
- 提供了使用"多重管理"R包的实施细节.
结论:
- 类效应NMA模型为跨干预类综合证据提供了一种有价值的方法.
- 拟议的框架和R包有助于应用和选择适当的类效应NMA模型.
- 这项工作解决了文献中的一个关键差距,使得治疗建议的更强大的证据综合成为可能.
相关概念视频
Pharmacokinetic Models: Comparison and Selection Criterion
319
Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
319
Mechanistic Models: Compartment Models in Individual and Population Analysis
235
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
235
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
271
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
271
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches
472
Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
472
Analysis of Population Pharmacokinetic Data
659
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
659
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
228
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
228


