Statistics In Clinical Trials

Mastering Statistical Design and Analysis for Clinical Trial Validity

What you'll learn

Understand the basic concepts of biostatistics relevant to clinical trials.

Learn the statistical methods used in the design and analysis of clinical trials.

Interpret statistical results correctly to make informed decisions.

Gain insights into the regulatory aspects of statistical analysis in clinical research.

Develop the ability to critically assess the statistical quality of clinical trial reports.

Requirements

Not required

Description

The “Statistics in Clinical Trials” course offers a comprehensive exploration of the statistical methods essential for clinical trial design, analysis, and interpretation, targeting professionals in clinical research who aim to enhance their analytical skills. This course covers foundational statistical principles, from basic descriptive statistics to advanced methods, providing participants with tools to ensure the validity and reliability of trial data. The curriculum spans 20 one-hour topics, blending theoretical understanding with practical applications, allowing participants to develop a robust statistical skill set tailored to clinical research needs.The course begins with an overview of clinical trials and statistical concepts, setting the stage for deeper exploration of study design and the importance of methodological rigor. Early modules introduce key elements of clinical trial design, such as sample size calculation and randomization methods, which are critical for minimizing bias and ensuring trial validity. Participants will also learn about data management processes, including data collection, cleaning, and validation using tools like Case Report Forms (CRFs) and Electronic Data Capture (EDC) systems.Moving into statistical analysis, participants explore descriptive statistics (measures of central tendency and dispersion) to summarize baseline characteristics and create graphical data representations, providing a solid foundation for data interpretation. The course also covers hypothesis testing fundamentals, including null and alternative hypotheses, Type I and Type II errors, and significance levels, ensuring that participants understand the role of statistical testing in clinical decision-making.Building on these basics, the curriculum progresses into advanced topics like t-tests, ANOVA, Chi-square, and Fisher’s Exact tests for comparing means and analyzing categorical data. These methods are essential for assessing differences across patient groups and treatment outcomes. Further modules delve into correlation and regression analysis, including multiple and logistic regression techniques, which allow participants to evaluate relationships between variables and predict treatment effects.The course also addresses specialized topics such as survival analysis, covering Kaplan-Meier estimates, log-rank tests, and Cox proportional hazards models, which are particularly relevant in trials involving time-to-event outcomes. For studies with repeated measurements or longitudinal data, participants learn about mixed-effects models and Generalized Estimating Equations (GEE) to analyze data across multiple time points effectively.Additional topics include non-parametric methods for non-normal data, approaches for managing multiplicity and conducting interim analyses, and the design of equivalence and non-inferiority trials. Advanced methods such as Bayesian analysis and meta-analysis are introduced, offering participants alternative frameworks for trial design and evidence synthesis across studies.The course concludes with practical guidance on reporting clinical trial results according to CONSORT guidelines, ensuring that participants can accurately and transparently present statistical findings. By covering a broad range of topics, this course equips clinical research professionals with the expertise needed to apply statistical methodologies confidently, supporting the design of scientifically rigorous trials that inform regulatory decisions and contribute to advancements in patient care.

Overview

Section 1: Introduction to Clinical Trials and Statistics

Lecture 1 Introduction to Clinical Trials and Statistics

Section 2: Study Design and Planning

Lecture 2 Study Design and Planning

Section 3: Data Collection and Management

Lecture 3 Data Collection and Management

Section 4: Descriptive Statistics in Clinical Trials

Lecture 4 Descriptive Statistics in Clinical Trials

Section 5: Hypothesis Testing Fundamentals

Lecture 5 Hypothesis Testing Fundamentals

Section 6: T-tests and ANOVA

Lecture 6 T-tests and ANOVA

Section 7: Chi-square and Fisher’s Exact Tests

Lecture 7 Chi-square and Fisher’s Exact Tests

Section 8: Correlation and Simple Linear Regression

Lecture 8 Correlation and Simple Linear Regression

Section 9: Multiple Regression and ANCOVA

Lecture 9 Multiple Regression and ANCOVA

Section 10: Logistic Regression

Lecture 10 Logistic Regression

Section 11: Survival Analysis

Lecture 11 Survival Analysis I

Lecture 12 Survival Analysis II

Section 12: Repeated Measures and Longitudinal Data Analysis

Lecture 13 Repeated Measures and Longitudinal Data Analysis

Section 13: Non-parametric Methods

Lecture 14 Non-parametric Methods

Section 14: Multiplicity and Interim Analyses

Lecture 15 Multiplicity and Interim Analyses

Section 15: Equivalence and Non-inferiority Trials

Lecture 16 Equivalence and Non-inferiority Trials

Section 16: Bayesian Methods in Clinical Trials

Lecture 17 Bayesian Methods in Clinical Trials

Section 17: Meta-analysis and Systematic Reviews

Lecture 18 Meta-analysis and Systematic Reviews

Section 18: Reporting Clinical Trial Results

Lecture 19 Reporting Clinical Trial Results

Section 19: Advanced Topics and Current Trends in Clinical Trials

Lecture 20 Advanced Topics and Current Trends in Clinical Trials

Section 20: Exam

Clinical researchers, project managers, and coordinators involved in clinical trials.,Statisticians and data analysts working in the pharmaceutical, biotech, or medical device industries.,Medical professionals interested in understanding the statistical aspects of clinical research.,Students and academics interested in clinical trial methodologies.