Related Experiment Video
Updated: Aug 3, 2026
04:53
A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition
Published on: September 20, 2019
Design and analysis of group sequential clinical trials with multiple primary endpoints
Michael R Kosorok1, Shi Yuanjun, David L DeMets
1Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, Wisconsin 53792, USA. kosorok@biostat.wisc.edu
Biometrics
|March 23, 2004
Summary
This study introduces a new method for group sequential clinical trials with multiple primary endpoints. It allows for early stopping when treatment effects are clear, controlling overall error rates for accurate hypothesis conclusions.
Area of Science:
- Clinical Trials Methodology
- Biostatistics
- Pharmacoeconomics
Background:
- Phase III clinical trials often require assessing multiple primary endpoints separately.
- The MERIT-HF study exemplifies this, with endpoints including time to death and time to first hospitalization or death.
- Treatment effects may differ across endpoints, necessitating flexible trial designs.
Purpose of the Study:
- To develop a general methodology for group sequential clinical trials with multiple primary endpoints.
- To enable early study stopping once treatment effects on all endpoints are evident.
- To address challenges in controlling error rates when some endpoints show no treatment effect.
Main Methods:
- Development of a general methodology for group sequential trials with multiple primary endpoints.
- Utilization of a global alpha-spending function to manage the overall Type I error rate.
- Implementation of a multiple decision rule to control error rates for incorrect alternative hypothesis conclusions.
Main Results:
- The proposed methodology provides a framework for group sequential trials with multiple primary endpoints.
- The approach effectively controls the overall Type I error rate.
- Demonstrated efficacy through two simulated examples based on the MERIT-HF study.
Conclusions:
- The developed methodology offers a robust approach for designing and analyzing group sequential clinical trials with multiple primary endpoints.
- This method enhances the ability to make timely and accurate conclusions about treatment efficacy across various outcomes.
- It provides a valuable tool for optimizing clinical trial efficiency and statistical rigor.
Related Concept Videos
01:16Clinical Trials
Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
There are four phases in a clinical trial. A phase one...
01:16Crossover Experiments
Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in different periods. Crossover experiments are generally used in psychology, the pharmaceutical industry, agriculture, and medicine.
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.
01:11Clinical Trials: Overview
Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...
01:20Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs
Bioequivalence experimental study designs are crucial methodologies used in evaluating and comparing the bioavailability of different drug products. These designs are categorized into various types: completely randomized, randomized block, repeated measures, cross and carry-over, and Latin square designs.Completely randomized designs involve randomly allocating treatments to all subjects participating in the experiment. This allocation is achieved by assigning unique random numbers to subjects...
01:15Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs
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...
01:20Comparing the Survival Analysis of Two or More Groups
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and Cox...