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Related Concept Videos

Clinical Trials01:16

Clinical Trials

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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...
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Clinical Trials: Overview01:11

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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...
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Trial and Error and Algorithm01:12

Trial and Error and Algorithm

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A problem-solving strategy is a plan of action used to find a solution. Different strategies have distinct action plans. Trial and error involves trying different solutions until one works. For instance, to fix a broken printer, you might check ink levels, ensure the paper tray isn't jammed, and verify the printer's connection to your laptop. This method can be time-consuming but is commonly used. Thomas Edison, for example, used trial and error to find a suitable filament for the light...
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Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
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Outcomes of Glycolysis01:13

Outcomes of Glycolysis

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Nearly all the energy used by cells comes from the bonds that make up complex organic compounds. These organic compounds are broken down into simpler molecules, such as glucose. As a result, cells extract energy from glucose over many chemical reactions—a process called cellular respiration.
Cellular respiration can occur aerobically (with oxygen) or anaerobically (without oxygen). In the presence of oxygen, cellular respiration starts with glycolysis and continues with pyruvate...
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Group Design02:01

Group Design

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The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...
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The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies
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Group-sequential logrank methods for trial designs using bivariate non-competing event-time outcomes.

Tomoyuki Sugimoto1, Toshimitsu Hamasaki2, Scott R Evans3

  • 1Graduate School of Data Science, Shiga University, 1-1-1 Banba, Hikone, Shiga, 522-8522, Japan. tomoyuki-sugimoto@biwako.shiga-u.ac.jp.

Lifetime Data Analysis
|April 14, 2019
PubMed
Summary

This study introduces a group-sequential method for analyzing two correlated event-time outcomes in clinical trials. It provides statistical tools for early stopping decisions, enhancing trial efficiency and sample size calculations.

Keywords:
Bivariate dependenceError-spending methodIndependent censoringLogrank statisticNon-fatal eventsNormal approximation

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Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Survival Analysis

Background:

  • Group-sequential methods are crucial for adaptive clinical trial monitoring.
  • Analyzing multiple correlated event-time outcomes presents unique statistical challenges.
  • Efficient trial design requires robust methods for early stopping decisions.

Purpose of the Study:

  • To develop and present a multivariate (2L-variate) group-sequential weighted logrank test for monitoring two correlated event-time outcomes.
  • To derive the asymptotic distribution and variance-covariance matrix for the 2L-variate weighted logrank statistic.
  • To establish a group-sequential testing procedure for clinical trials evaluating joint effects on two correlated endpoints, enabling early stopping for efficacy.

Main Methods:

  • Derivation of the asymptotic distribution and variance-covariance matrix for the 2L-variate weighted logrank statistic.
  • Formulation of group-sequential testing procedures based on calendar times or information fractions.
  • Application of theoretical results to a practical group-sequential monitoring method for clinical trials.

Main Results:

  • The study provides the theoretical framework for the multivariate group-sequential weighted logrank test.
  • The derived methods allow for the determination of group-sequential testing strategies.
  • The approach facilitates sample size and event number calculations for trials with two correlated event-time outcomes.

Conclusions:

  • The proposed group-sequential method effectively monitors clinical trials with two correlated event-time outcomes.
  • This approach supports early stopping for efficacy, optimizing trial resource allocation.
  • The methodology aids in designing and analyzing trials evaluating joint treatment effects on multiple endpoints.