Course "Fundamentals of Statistical Design for Clinical Trials" has been pre-approved by RAPS as eligible for up to 12 credits towards a participant's RAC recertification upon full completion.
Overview:
This 2-day seminar includes an overview of the need for clinical research, types of clinical trial designs, common statistical tests, considerations of sample size, and randomization techniques.
The role of statistics in clinical trials incorporates the tools used to develop a robust study, minimize bias, and assess efficacy of new treatments as relates to efficacy and comparison to competing therapies.
Prior to the use of experimental research, clinicians often used subjective measures and anecdotal evidence of treatment efficacy. Concepts such as variability among individuals and treatments were not considered in early applications.
The application of scientific method, which makes use of the tools statistical theory, allows clinical researchers to set up a robust study design and to make precise and accurate inferences from the information collected in a clinical trial. According to Carter, Scheaffer, and Marks (1986), "Statistics is unique among academic disciplines in that statistical though is needed at every stage of virtually all research investigations including planning the study, selecting the sample, managing the data, and interpreting the results."
The objective of the seminar is to provide information that can be used immediately by personnel involved in the design and analysis of clinical trials. Although the presentation involves use of statistical techniques, presentation of statistical theory will be limited to only what is needed by the attendees to understand and implement trial design and end-point analyses within the statistical framework. However, a basic understanding of basic statistical tests (t-tests, ANOVA, regression) is desired.
Presented examples and training will include the design of a simple randomized trial. A template of a statistical analysis plan will be given to all attendees for use in their practice.
Why you should attend:
Clinical trials are expensive, time consuming, and labor-intensive. Many hands are involved in a successful trial including sponsors, investigators, nurses, data management personnel, legal boards, and regulatory agencies. A set of tools to design a study, collect the information, and analyze the results is required to assure a proper framework for a robust study with minimal bias. Statistics is this tool-set.
While there are similarities in the development and execution of clinical trials, each study presents challenges and differences that require forethought and troubleshooting. A well-informed researcher will enhance the process of conducting and analyzing a clinical trial. Researchers have an ethical obligation to the safety of trial subjects and to the proper practice of medicine. Statistical concepts help to assure proper ethics.
The U.S. Food and Drug Administration (FDA) and other regulatory agencies require the minimization of bias in study design and analysis. In order to minimize bias, particular steps and safeguards, using regulatory guidance, must be put into place to assure validity of a research. Regulatory standards require statistics help to ensure that a study is valid, ethical, reproducible, and transparent. A researcher with a good understanding of the elements of statistical design and analysis will strive to be ethical and objective in order to best benefit the patients he or she serves.
Areas Covered in the Session:
History and reasoning of clinical trials
Scientific method and hypothesis testing
FDA, ICH 9 Guidance/references
Basic clinical trial designs
Study endpoints and statistical tests
Randomization of participants
Sample size considerations
Design a statistical analysis plan
Who Will Benefit:
Trial Sponsors
Principal Investigators
Clinical Investigators
Clinical Research Coordinators
Clinical Research Nurse Coordinators
Clinical Research Associates/Assistants
Clinical Project Managers/Leaders
Study Managers
Regulatory Professionals/Coordinators
Medical Writers who need to interpret statistical reports
Agenda:
Day 1 Schedule
Lecture 1 (90 Mins):
Introduction
Why Clinical Trials?
Phases of a clinical trial
Pre-clinical research
Phase I trials
Phase II trials
Phase III trials
Phase IV trials
Trial organization
Study protocol
Regulatory agencies and issues
Lecture 2 (90 Mins):
Defining the Research Questions
Scientific Method and the statistical framework
Selection of study questions and end-points
Primary question and end-point
Secondary questions and end-points
Safety endpoints and adverse effects
Surrogate outcomes
Composite outcomes
Lecture 3 (90 Mins):
Basic Study Designs
Randomized control studies
Nonrandomized concurrent control studies
Studies with historical controls
Cross-over designs
Withdrawal studies
Factorial Design (Design of Experiments;DOE)
Group allocation designs
Hybrid designs
Equivalency studies
Lecture 4 (90 Mins):
Common Statistical Tests
Descriptive statistics
Comparative tests (t-tests, Analysis of variance (ANOVA)
Models for count data
Regression models
Survival Analysis
Day 2 Schedule
Lecture 1 (90 Mins):
Study Power and Sample Size
Overview of concepts for statistical power analysis
Dichotomous response variables
Continuous response variables
Repeated measurements
Survival/Time to failure outcomes
Equivalency outcomes
Multiple outcomes
Lecture 2 (90 Mins):
Randomization and Blinding
Fixed allocation randomization
Simple randomization
Blocked randomization
Stratified randomization
Adaptive randomization
Baseline adaptive randomization
Response adaptive randomization
Lecture 3 (180 Mins):
AFTERNOON WORKSHOP: Developing a Statistical Analysis Plan
Using FDA guidance as a foundation, learn the steps and criteria needed to develop a statistical analysis plan (SAP).
An SAP template will be given to all attendees.
Speaker
Elaine Eisenbeisz
Owner and Principal Statistician, Omega Statistics
Elaine Eisenbeisz, is a private practice statistician and owner of Omega Statistics, a statistical consulting firm based in Southern California. Elaine has over 30 years of experience in creating data and information solutions for industries ranging from governmental agencies and corporations, to start-up companies and individual researchers.
In addition to her technical expertise, Elaine possesses a talent for conveying statistical concepts and results in a way that people can intuitively understand.
Location: Baltimore, MD Date: August 14th & 15th, 2018 and Time: 9:00 AM to 6:00 PM
Venue: The DoubleTree Baltimore-BWI Airport 890 Elkridge Landing Road - Linthicum, MD 21090
Price:
Price: $1,295.00 (Seminar Fee for One Delegate)
Register for 5 attendees Price: $3,885.00 $6,475.00 You Save: $2,590.00 (40%)*
Register for 10 attendees Price: $7,122.00 $12,950.00 You Save: $5,828.00 (45%)*
Register now and save $200. (Early Bird
Until July 10, Early Bird Price: $1,295.00 From July 11 to August 12, Regular Price: $1,495.00
Sponsorship Program benefits for seminar
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