影响功率的因素 在阶段形试验中,当治疗效果随时间变化时,影响功率的因素
Avi Kenny1,2, Emily C Voldal3, Fan Xia4
1Department of Biostatistics & Bioinformatics, Duke University, Durham, NC, USA. avi.kenny@duke.edu.
Trials
|February 20, 2026
概括
为了保持阶段子集群随机试验 (SW-CRTs) 的实力,研究人员在使用时间变化的治疗效果模型时必须增加样本大小. 调整研究设计可以提高随时间推移估计治疗效果的功率.
科学领域:
- 生物统计学 生物统计学
- 临床试验方法论 临床试验方法论
- 流行病学 流行病学
背景情况:
- 步骤集群随机试验 (SW-CRTs) 传统上使用即时治疗 (IT) 模型,假设治疗效果是恒定的.
- 当治疗效果随着暴露时间的变化而变化时,这种假设是有缺陷的,可能导致误导性结果.
- 时间变化的效应模型,如暴露时间指标 (ETI) 模型,提供灵活性,但可以降低统计能力.
研究的目的:
- 调查影响SW-CRT统计功率的因素.
- 为了比较传统的IT模型和灵活的时间变化的效果模型之间的功率.
- 为优化SW-CRT设计和分析功率提供指导.
主要方法:
- 使用公共电力计算软件进行模拟.
- 基于估计和选择,研究设计和分析模型选择的特征功率.
- 评估了各种SW-CRT设计,包括楼梯变体.
主要成果:
- 从IT切换到ETI模型需要大幅增加样本大小 (1.5-3倍或更多),以保持90%的时间平均治疗效应 (TATE) 功率.
- 对于短期影响,SW-CRT的功率高于长期影响.
- 添加早期时间点或增加基线样本大小可以提高TATE的功率;添加晚期时间点的影响最小.
- 时间趋势的限制性建模对TATE功率的影响很小,但增加了点处理效应 (PTE) 的功率.
- 延迟恒定处理模型可以在存在洗期时比IT模型提供轻微的功率增长.
结论:
- 在SW-CRT中使用时间变化的效果模型实现充足的功率需要更大的样本大小或战略设计修改.
- 了解模型灵活性和功率之间的权衡对于SW-CRT规划至关重要.
- 通过考虑早期时间点和基线样本大小,优化SW-CRT设计是对时间变化治疗效应的可靠估计的关键.
相关概念视频
Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs
266
Body:Bioequivalence experimental study designs play a pivotal role in testing the effectiveness of various treatments. Key among these are the repeated measures, cross-over, carry-over, and Latin square designs. In the repeated measures design, each subject receives all treatments, allowing for temporal comparisons. This type of design is useful in reducing variability but requires careful planning to avoid bias.The cross-over design, an economical method, involves sequential administration of...
266
Factors Affecting Activity Coefficient
1.7K
The extended Debye-Hückel equation indicates that the activity coefficient of an ion in an aqueous solution at 25°C depends on three partially interdependent properties: the ionic strength of the solution, the charge of the ion, and the ion size.
The activity coefficient value for an ion is close to one when the solution has almost zero ionic strength, i.e., when the solution shows close to ideal behavior. As the ionic strength of the solution increases from 0 to 0.1 mol/L, a...
The activity coefficient value for an ion is close to one when the solution has almost zero ionic strength, i.e., when the solution shows close to ideal behavior. As the ionic strength of the solution increases from 0 to 0.1 mol/L, a...
1.7K
Parametric Survival Analysis: Weibull and Exponential Methods
1.1K
Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
1.1K
Factorial Design
14.4K
Factorial Analysis is an experimental design that applies Analysis of Variance (ANOVA) statistical procedures to examine a change in a dependent variable due to more than one independent variable, also known as factors. Changes in worker productivity can be reasoned, for example, to be influenced by salary and other conditions, such as skill level. One way to test this hypothesis is by categorizing salary into three levels (low, moderate, and high) and skills sets into two levels (entry level...
14.4K
Randomized Experiments
9.1K
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...
9.1K
What is an Experiment?
19.2K
An experiment is a planned activity carried out under controlled conditions. The purpose of an experiment is to investigate the relationship between two variables. When one variable causes change in another, we call the first variable the explanatory or independent variable. The affected variable is called the response or dependent variable. In a randomized experiment, the researcher manipulates values of the explanatory variable and measures the resulting changes in the response variable. The...
19.2K


