Independent Data Monitoring Committees in Clinical Trials
This course will teach you the statistical display and analysis methods used in monitoring clinical trials for safety, as well as the biases and pitfalls inherent in safety review.
Overview
Complex sample designs such as stratified cluster sampling make it possible to extract maximum information at minimum cost, but they are typically harder to work with than simple random samples. How do you analyze the resulting data – in particular, how do you determine margins of error? This course teaches you how to estimate variances when analyzing survey data from complex samples, and also how to fit linear and logistic regression models to complex sample survey data.
- Introductory, Intermediate
- 4 Weeks
- Expert Instructor
- Tuiton-Back Guarantee
- 100% Online
- TA Support
Learning Outcomes
At the conclusion of this course students will have a basic understanding of the objectives of a Data Monitoring Committee (DMC) and the role of a Data Analysis Center. They will learn how to create and administer a DMC, how to approach meaningful statistical analyses, and how to make data-driven DMC decisions.
- Explain how to set up a data monitoring committee
- Explain how the commmittee conducts business
- Define adverse events
- Describe the statistical analysis goals for DMC’s
- Specify the issues of bias and multiplicity to be alert for
- Describe emerging issues such as biomarkers and causal analysis
Who Should Take This Course
Anyone involved with the design, implementation or analysis of clinical trials.
Our Instructors
Dr. Jay Herson
Course Syllabus
Week 1
Introduction and Organization of a Data Monitoring Program
- Objectives of a Data Monitoring Committee (DMC)
- Differences in DMC’s between the NIH-sponsored trials and industry-sponsored trials
- Issues related to the size of the sponsoring company (Big Pharma, Middle Pharma, Infant Pharma)
- Creation of a DMC
- Selecting members
- Conflicts of interest
- Role of the Data Analysis Center (DAC)
Week 2
Meetings and Clinical Issues
- The DMC Charter
- Types and structure of meetings
- Open and closed sessions
- Adverse event definitions and coding schemes
- Format for meeting agendas
- Impact of multinational trials
Week 3
Statistical Issues, Biases, and Pitfalls
- Goals of statistical analysis for DMC’s
- Useful data displays
- Frequentist, likelihood, and Bayesian analysis methodsIncidence
Rate/patient year
Time-to-event - Incidence
- Rate/patient year
- Time-to-event
- Power
- Multiplicity
- Sources of bias by sponsor
- Investigator
- Granularity bias
- Competing risks
Week 4
DMC Decisions and Emerging Issues
- Types of DMC decisions and the environment in which they are made
- Risk vs. benefit analysis
- Steps taken when a safety issue arises
- Meta-analysis
- Problems particular to Infant Pharma companies
- DMC operations for safety when adaptive designs are employed for efficacy
- Real-time SAE reporting via the internet
- Causal inference
- Biomarkers
- Training of DMC members
- Cost control, DMC audits
- Working with internal safety review committees
- Effect of company mergers and licensing agreements on independent safety review
Prerequisites
Introduction to Statistical Issues in Clinical Trials
- Skill: Introductory, Intermediate
- Credit Options: CEU
Private: Statistics 2 – Inference and Association
- Skill: Introductory, Intermediate
- Credit Options: CEU
Private: Statistics 1 – Probability and Study Design
- Skill: Introductory, Intermediate
- Credit Options: CEU
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Independent Data Monitoring Committees in Clinical Trials
Additional Information
Homework
Homework in this course consists of short answer questions to test concepts.
In addition to assigned readings, this course also has supplemental readings available online.
Course Text
The course text is Data and Safety Monitoring Committees in Clinical Trials, second edition (2016) by Jay Herson, which you can order from CRC Press.
Supplemental Information
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Independent Data Monitoring Committees in Clinical Trials