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Statistical Thinking for Clinical Trials (STCT)

Course No.:

STCT

Course Title:

Statistical Thinking for Clinical Trials

Hours Total:

150 h

Credit Points:

5 ECTS

Course Type: Pflicht

Course Availability: WS, SS

Course Duration: 1 Semester

Admission Requirements:

None

Course Coordinator / Instructor:

See current list of tutors in the Learning Management System

References to Other Modules:

Please see module description

Course Description:

The course covers key bio-statistical concepts as applied in clinical research. While the course does not aim to train statisticians, students will be equipped with the ability to analyze clinical research from a statistics point of view and to communicate efficiently with biostatisticians.

Course Objectives and Outcome:

On successful completion of this module, students will be able to:

  • understand key elements of statistical trial design
  • understand the concept of sampling and inferential statistics, distinguish between the statistical approaches of estimation, confidence intervals, and testing, and understand the role of p-values and type I and type II errors
  • discuss the role of different analysis sets (ITT, per protocol) and understand issues related to incomplete or missing data
  • distinguish between different types of adjusted analyses including regression, analysis of variance (ANOVA) and analysis of covariance (ANCOVA), and understand the concept of correlation
  • understand basic approaches to the analysis of binary, categorical, and ordinal data
  • recognize the importance of adequate sample size planning and understand the difference between statistical significance and clinical relevance
  • understand statistical challenges related to multiple testing and differentiate between some common approaches to deal with multiplicity
  • recognize the need for and understand specific statistical approaches to:
    • the analysis of equivalence and non-inferiority trials
    • meta-analysis
    • the analysis of survival data

Teaching Methods:

This course is taught in blended format. It consists of 120 h directed, remote learning (via recorded presentations, self-readings, and exercises), followed by 4 days of full-time, face-to-face training in form of lectures, supplemented by class discussions. Class discussions refer to the concepts being introduced and case studies.

Course Content:

1 Statistical Aspects of Trial Design

2 ICH Requirements for Statistical Analyses

3 Basic Statistical Concepts: Estimation, Confidence Intervals, Testing, P-values, T-tests, and Type I and Type II Errors

4 Intent-to-treat and Analysis Sets

5 Multicenter Trials and Analysis of Variance

6 Correlation, Regression, Analysis of Covariance

7 Analysis of Binary, Categorical, and Ordinal Data

8 Power, Sample Size, Statistical Significance, and Clinical Relevance

9 Practical Issues in Multiple Testing

10 Assessing Equivalence or Non-Inferiority

11 Meta-Analysis

12 Methods of Survival Data Analysis

Literature:

• Kay, R. (2014). Statistical thinking for non-statisticians in drug regulation (2nd ed.). Chichester: Wiley.
• Altman, D. G. (1991). Practical statistics for medical research. London: Chapman and Hall.
• Armitage, P., Berry, G., & Matthews, J. N. S. (2002). Statistical methods in medical research (4th ed.). Oxford: Blackwell.
• Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2009). Introduction to meta-analysis. Chichester: Wiley.
• Collett, D. (2003). Modelling survival data in medical research. London: Chapman & Hall.

Prerequisites to Qualify for Assessment:

• Course evaluation

Assessment:

• Exam, 90 minutes

Student Workload (in hours): 150

Lectures: 30
Self-study: 90
Self-testing: 30