Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

286
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...
286
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

174
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,...
174
Clinical Trials01:16

Clinical Trials

8.3K
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...
8.3K
Clinical Trials: Overview01:11

Clinical Trials: Overview

3.4K
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...
3.4K
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

383
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
383
Hazard Ratio01:12

Hazard Ratio

244
The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial...
244

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Impact of incretin therapies on biochemical and imaging outcomes in metabolic dysfunction-associated steatotic liver disease.

American journal of preventive cardiology·2026
Same author

Association between author specialty and reported outcomes in nonrandomized comparisons of prostatectomy versus radiation.

JNCI cancer spectrum·2026
Same author

Lineage infidelity in FH-deficient RCC with secondary somatic alterations: a case report and implications for diagnosis and treatment.

Therapeutic advances in medical oncology·2026
Same author

TRIPLETE But Incomplete? Accounting for Post-Progression Therapy When Interpreting Overall Survival.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology·2026
Same author

Pan-cancer spatial atlas of tertiary lymphoid structures.

Science (New York, N.Y.)·2026
Same author

Knowledge and Use of Artificial Intelligence Among Oncology Faculty and Trainees at a Comprehensive Cancer Center in 2025.

JCO clinical cancer informatics·2026

Related Experiment Video

Updated: Sep 11, 2025

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment
08:36

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment

Published on: April 19, 2024

697

Bayesian interim analysis and efficiency of phase III randomized trials.

Alexander D Sherry1,2, Pavlos Msaouel3,4, Avital M Miller1

  • 1Department of Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

British Journal of Cancer
|August 11, 2025
PubMed
Summary
This summary is machine-generated.

Bayesian interim analyses enhance phase III oncology trial efficiency by enabling early stopping. This approach reduces patient enrollment and costs without compromising trial interpretation.

More Related Videos

Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure
05:16

Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure

Published on: June 10, 2025

214
A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition
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

10.8K

Related Experiment Videos

Last Updated: Sep 11, 2025

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment
08:36

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment

Published on: April 19, 2024

697
Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure
05:16

Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure

Published on: June 10, 2025

214
A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition
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

10.8K

Area of Science:

  • Clinical Trials
  • Biostatistics
  • Oncology Research

Background:

  • Improving phase III trial efficiency is critical for cost reduction, faster drug approvals, and minimizing patient exposure to unfavorable randomizations.
  • Bayesian early stopping rules offer enhanced efficiency over frequentist methods through flexible priors for efficacy/futility and evaluation of clinically meaningful effect sizes.

Purpose of the Study:

  • To evaluate the efficiency of Bayesian early stopping rules in phase III oncology trials compared to standard frequentist interim analysis.
  • To assess the impact of Bayesian interim analysis on trial interpretation and enrollment numbers.

Main Methods:

  • Reconstruction of individual patient-level data from 184,752 participants across 230 oncology phase III trials using Kaplan-Meier curves.
  • Simulation of accrual dynamics and application of Bayesian early stopping rules.
  • Assessment of agreement between original and Bayesian interim analyses using Bayesian Cohen's kappa.

Main Results:

  • Bayesian interim analysis recommended early closure for 36% of trials (82 out of 230).
  • High sensitivity (96%) for detecting primary endpoint differences and strong agreement in trial interpretation (κ=0.95) were observed.
  • Bayesian interim analysis was associated with reduced patient enrollment.

Conclusions:

  • Bayesian interim analyses demonstrate potential to improve phase III trial efficiency by reducing enrollment needs.
  • This method maintains robust trial interpretation while potentially accelerating the drug development process.