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

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

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

124
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,...
124
Actuarial Approach01:20

Actuarial Approach

69
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
69
Hazard Ratio01:12

Hazard Ratio

103
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...
103
Binomial Probability Distribution01:15

Binomial Probability Distribution

10.3K
A binomial distribution is a probability distribution for a procedure with a fixed number of trials, where each trial can have only two outcomes.
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
There are a fixed number of trials. Think of trials as repetitions of an experiment. The letter n denotes the number of trials.
There are only two possible outcomes,...
10.3K
Kaplan-Meier Approach01:24

Kaplan-Meier Approach

115
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,...
115
Odds Ratio01:09

Odds Ratio

115
The odds ratio (OR) is a statistical measure used extensively in epidemiology and research to quantify the strength of association between exposure and outcome across different groups. Unlike relative risk, which compares the probabilities of an event occurring, the odds ratio compares the odds of an event occurring in the exposed group to the odds of it occurring in the unexposed group. The odds, in this context, are calculated as the probability of the event happening divided by the...
115

You might also read

Related Articles

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

Sort by
Same author

Evaluation of the Efficacy of Human Papillomavirus Screening Compared With Cytology Screening in Pregnant Women: Protocol for a Prospective Multicenter Trial.

JMIR research protocols·2026
Same author

Long-term prognostic impact of a novel arterial stiffness index using upper-arm cuff oscillometric inflation.

Journal of hypertension·2026
Same author

A Multicenter Phase II Study on Atezolizumab plus Bevacizumab Combination Therapy in Patients with Unresectable Hepatocellular Carcinoma and Child-Pugh Classification B Cirrhosis: CHALLENGE Trial.

Liver cancer·2026
Same author

Predicting pathological lymph node status in clinical stage I/II tongue cancer.

International journal of clinical oncology·2026
Same author

Impact of tumor location on the efficacy of concurrent chemoradiotherapy for locally advanced non-small cell lung cancer.

British journal of cancer·2026
Same author

A Bayesian Treatment Selection Design for Phase II Randomised Cancer Clinical Trials.

Statistics in medicine·2026

Related Experiment Video

Updated: Jun 17, 2025

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition
00:04

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

Published on: September 20, 2019

10.6K

Bayesian Predictive Probability Based on a Bivariate Index Vector for Single-Arm Phase II Study With Binary Efficacy

Takuya Yoshimoto1,2, Satoru Shinoda2, Kouji Yamamoto2

  • 1Biometrics Department, Chugai Pharmaceutical Co. Ltd, Chuo-ku, Tokyo, Japan.

Pharmaceutical Statistics
|August 14, 2024
PubMed
Summary

This study introduces a new Bayesian monitoring strategy for oncology Phase II trials. The method uses an index vector to improve interim go/no-go decisions for advancing cancer drug candidates.

Keywords:
Bayesian monitoringefficacy and toxicity endpointsindex vectorpredictive probabilitysingle‐arm Phase II study

More Related Videos

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
09:35

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

17.8K
Author Spotlight: Unveiling Prognostic Indicators in Heart Failure - The Role of Phase Angle and Bioelectrical Impedance Analysis
04:05

Author Spotlight: Unveiling Prognostic Indicators in Heart Failure - The Role of Phase Angle and Bioelectrical Impedance Analysis

Published on: June 30, 2023

1.8K

Related Experiment Videos

Last Updated: Jun 17, 2025

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition
00:04

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

Published on: September 20, 2019

10.6K
A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
09:35

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

17.8K
Author Spotlight: Unveiling Prognostic Indicators in Heart Failure - The Role of Phase Angle and Bioelectrical Impedance Analysis
04:05

Author Spotlight: Unveiling Prognostic Indicators in Heart Failure - The Role of Phase Angle and Bioelectrical Impedance Analysis

Published on: June 30, 2023

1.8K

Area of Science:

  • Clinical Trials
  • Oncology
  • Biostatistics

Background:

  • Phase II oncology studies are critical for advancing potential cancer treatments.
  • Traditional Phase II trials focus on efficacy, but drug safety is also vital.
  • Existing Bayesian monitoring strategies assess trial continuation based on predictive probabilities.

Purpose of the Study:

  • To propose a novel index vector for summarizing Phase II trial outcomes.
  • To enhance interim go/no-go decision-making in clinical trial development.
  • To address limitations of existing strategies in capturing multiple trial outcomes.

Main Methods:

  • Development of a simple index vector to define worst and most promising treatment effect scenarios.
  • Utilizing the index vector to measure deviation between these defined scenarios.
  • Conducting simulation studies to evaluate the proposed method's operating characteristics.

Main Results:

  • The proposed index vector effectively summarizes key trial results.
  • Simulation studies confirmed the method's ability to make appropriate interim decisions.
  • The new strategy enhances the assessment of evidence for Phase III trial progression.

Conclusions:

  • The novel index vector provides a valuable tool for Bayesian monitoring in Phase II oncology trials.
  • This approach improves the reliability of go/no-go decisions for cancer drug development.
  • The method offers a more comprehensive summary of trial outcomes compared to existing strategies.