估计和评估个性化治疗规则在多次归算后的估计和评估
Jenny Shen1, Rebecca A Hubbard1, Kristin A Linn1
1Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Statistics in medicine
|July 27, 2023
概括
本研究介绍了在患者数据不完整的情况下创建个性化治疗规则 (ITR) 的两种方法. 这些框架使用多重归算 (MI),为精准医学研究提供指导,特别是像STEP UP这样的研究.
科学领域:
- 生物统计学 生物统计学
- 精准医学是一门精准的医学.
- 数据科学数据科学数据科学
背景情况:
- 个性化治疗规则 (ITR) 对精准医学至关重要,其目的是根据患者特征优化治疗选择.
- 估计和评估最佳ITR是一个挑战,尤其是在处理缺失数据时,这是临床研究中常见的问题.
- 多重归算 (MI) 被广泛用于缺少的数据,但缺乏在个性化医学中开发ITR的既定框架.
研究的目的:
- 在缺少数据的情况下,提出和评估估计和评估最佳个性化处理规则 (ITR) 的框架.
- 解决在个性化医学和ITR优化背景下应用MI技术的有限指导.
- 为ITR估计和评估提供实用见解,使用现实数据,以STEP UP研究为例.
主要方法:
- 开发和评估了ITR估计和多重归算 (MI) 后评估的两个不同的框架.
- 框架1:将数据分为独立的培训和测试集,分别用于ITR估计和评估.
- 框架2:对最佳ITR的完整数据估计,并使用k-out-of-k启动链置信区间进行性能评估.
主要成果:
- 该研究评估了拟议的ITR框架的性能,使用模拟数据来理解它们在缺失数据条件下的行为.
- 对鼓励身体活动和理解预测因素 (STEP UP) 的社会激励措施研究数据进行了说明性分析.
- 在分析中探索了实际考虑,例如确定MI的最佳归算数量.
结论:
- 开发的框架提供了必要的指导,用于估计和评估最佳ITR在个性化医疗当缺失数据存在时.
- 这项研究强调了在精准医学中处理缺少数据的可靠方法的重要性,以确保可靠的治疗建议.
- 这些发现为研究人员在临床研究中应用ITR提供了实用方法和考虑因素,提高了MI技术的实用性.
相关概念视频
Mechanistic Models: Compartment Models in Individual and Population Analysis
64
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...
64
Multiple Regression
3.0K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
3.0K
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
573
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
On...
573
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
148
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
148
Randomized Experiments
7.0K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
Simple randomization
Simple...
7.0K
Truncation in Survival Analysis
237
Truncation in survival analysis refers to the exclusion of individuals or events from the dataset based on specific criteria related to the time of the event. This exclusion can happen in two primary forms: left truncation and right truncation.
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are...
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are...
237


