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Related Concept Videos

Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
Biostatistics: Overview01:20

Biostatistics: Overview

Biostatistics plays a crucial role in understanding and analyzing data in healthcare and biology. Biostatisticians conduct experiments, gather evidence, and draw meaningful conclusions using statistical methods and techniques. Different variables form the foundation of biostatistical analysis, allowing researchers to understand and interpret data effectively. These variables are classified into different types, each serving a specific purpose in statistical analysis.
Discrete variables are...
Clinical Trials01:16

Clinical 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...
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

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, controlled...
Kaplan-Meier Approach01:24

Kaplan-Meier Approach

The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
Study Design in Statistics01:15

Study Design in Statistics

A study design is a set of techniques that allow a researcher to collect and analyze data from different variables defined for a specific research problem. Statistics is commonly for effective study design and more robust experiments,
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...

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A Tactile Automated Passive-Finger Stimulator (TAPS)
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Bayesian adaptive clinical trials: a dream for statisticians only?

Sylvie Chevret1

  • 1Biostatistics Department, Saint-Louis Hospital, AP-HP, Paris, France. sylvie.chevret@paris7.jussieu.fr

Statistics in Medicine
|September 10, 2011
PubMed
Summary

Bayesian adaptive designs offer flexibility in clinical trials but are underutilized. This study analyzed global research, finding limited adoption and recommending efforts to promote these methods among statisticians and clinicians.

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Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Bayesian Methodology

Background:

  • Adaptive clinical trial designs accelerate therapeutic evaluation, primarily using frequentist methods.
  • Bayesian methods, known for flexibility, have been proposed for adaptive trials but show limited practical application.
  • Understanding the global scientific output and adoption of Bayesian adaptive designs is crucial.

Purpose of the Study:

  • To map the international scientific production of Bayesian clinical trials.
  • To investigate the development and utilization of Bayesian adaptive methods in clinical research.
  • To identify barriers to adoption and future research directions for Bayesian adaptive designs.

Main Methods:

  • Bibliometric analysis of publications from PubMed and Science Citation Index-Expanded databases.
  • Identification of key research institutions and geographical distribution of authors.
  • Analysis of citation counts to assess the impact and spread of research findings.

Main Results:

  • The majority of publications were biostatistical papers, with significant contributions from US-based researchers, particularly MD Anderson Cancer Center.
  • Research impact varied by topic: clinical articles (32%) and reviews (15%) received more citations than biostatistical articles (3.1%).
  • Limited use of Bayesian adaptive designs in practice was observed, necessitating further investigation into underlying reasons.

Conclusions:

  • Efforts are needed to increase the awareness and adoption of Bayesian adaptive designs in clinical research.
  • Promoting Bayesian approaches among both statisticians and clinicians is essential for wider implementation.
  • Further research should focus on overcoming challenges and enhancing the practical application of these methods.