Statistics is the art and science of summarising data. Statistics play an essential role in all stages of clinical research from design through to analysis and interpretation.
Clinical Trials generate large volumes of data but most of us are looking for the “punch-line”; Did the new treatment work? Were the two groups being compared the same of different? We rely on statistics to help us design the most appropriate trial to answer our questions, to determine the required sample size and to interpret the results. A poorly designed study wastes time, resources and puts patients at unnecessary risk. A solid understanding of statistical principals is important for all team members, not just the team statistician; however for many of us statistics is nearly a foreign language.
This course is aimed at non-statisticians who work in clinical research and provides an introduction to the statistical methods used for the design, conduct and analysis of clinical trials. The course emphasises the application of statistical concepts to clinical research; aiming to demystify the subject and equipping delegates with the knowledge to read, understand, interpret and communicate data & statistics.
This is an introductory course and no significant mathematical knowledge is required.
Delegates should bring a laptop and calculator to the course, if possible. The ICR will endeavour to supply a number of laptops and calculators for delegates to use but cannot guarantee exclusive availability for all attendees.
• Define statistical terminology
• Read the statistical parts of a medical journal paper
• Describe the various types of data and how they are summarised
• Outline the process for statistical analysis of clinical trials
Describing Data
• Types of data, types of endpoints
• How are data described and presented
• Important issues relating to graphs, table, diagrams etc.
• Comparing two groups (means, odds ratios, hazard rates/ratio, Kaplan-Meier)
Significance Testing
• What is being evaluated
• Null and alternative hypothesis
• Types of error - P-values and confidence intervals
• Types of test
Power and Sample Size
• What is power?
• Power and sample size
• Determinants of sample size
• Designing clinical trials from statistical perspective
• Statistical sections of protocols
Statistical Reports
• Populations (ITT, per protocol)
• Safety and efficacy presentation
• Describing and understanding statistical significance