Statistical Aspects of Clinical Trials

Statistical Aspects of Trial Design

• Basic ideas and issues in statistical design
• Confirmatory vs. exploratory analyses
• Concepts of superiority, equivalence and non-inferiority trials
• Distinction between ‘between patient’ designs and ‘within patient designs’
• Need to maximize the ‘signal’ whilst controlling the ‘noise’
• Statistical analysis process from the design stage to statistical analysis
• Planning, blind review and statistical analysis and reporting

Sampling and Standard Errors

• Interrelation between the sample and the target population
• Purpose of inferential statistics
• Measures of location and of variability
• Normal probability distribution
• Standard error as a measure of the ‘reliability’

Confidence Intervals and Hypothesis Tests

• Confidence interval and its appropriate interpretation
• Framework for hypothesis testing, p-value and its calculation
• Generalization to practical settings
• Definition of null distribution, testing of statistic and significance level
• One-sided and two-sided tests, type I and type II errors
• Introduction of two-sample t-test and paired t-test as examples

Intent-to-Treat and Analysis Sets

• Principle of Intention-to-treat (ITT)
• Relation to the choice of analysis set
• ‘Full Analysis Set’ and ‘Per Protocol Set’ according to ICH
• Practical issues, such as handling of missing values

Adjusted Analyses

• Two-way analysis of variance (ANOVA
• Investigation of treatment mean effects, center effects
• Treatment by center interactions
• Generalizability to more complex situations

Correlation, Regression, ANCOVA

• Correlation
• Linear regression as a technique for studying dependence
• Multiple linear regression
• Analysis of Covariance as a means of comparing groups
• Use and misuse of baseline testing

Analysis of Binary, Categorical and Ordinal Data

• Chi-squared test for binary data
• Generalization to categorical data
• Use of Mantel-Haenszel chi-squared test for ordinal data
• Odds ratio, relative risk, and number needed to treat
• Role of Fisher’s Exact Test

Power, Sample Size, Statistical and Clinical Significance

• Statistical power in relation to calculation of sample siz
• Role of the standard deviation in this calculation
• Re-evaluation of sample size as trial data accumulates
• Link between p-values and confidence intervals
• Limitations of p-values
• Distinction between clinical and statistical significance

Non-Parametric Methods

• Assumptions underlying ‘parametric tests’
• Transformations to recover normality
• Generalization of the t-test to deal with non-constant variance
• Non-parametric between and within-patient tests
• Wilcoxon Rank Sum and the Wilcoxon
• Signed Rank tests
• Advantages / disadvantages of the non-parametric framework

Practical Issues in Multiple Testing

• Problems associated with undertaking large numbers of statistical tests
• Inflation of the type I error rate
• Areas in which such multiple testing arises and offers solutions

Testing for Equivalence or Non-Inferiority

• Testing for superiority
• Testing for equivalence or non-inferiority
• Confidence interval approach to the equivalence / non-inferiority setting
• Choice of equivalence margins
• Problems associated with sensitivity to drug effects

Meta-Analysis

• Purpose and framework of meta-analysis
• General method for combining results in a meta-analysis
• Role of meta-analyses in the regulatory setting

Methods for the Analysis of Survival Type Data

• Difference of time-to-event data
• Kaplan-Meier estimates
• Log-rank test
• Gehan-Wilcoxon test
• Analyses adjusted for the influence of prognostic variables
• Assumption of independent censoring

Crossover Trials

• Problems associated with carryover effects in 2 x 2 crossover trials
• Advice on when to use and when not to use crossover trials
• Methods of analysis