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Source document. This page reproduces the syllabus this course was written to, as published — its semesters, credits and paper numbers are that document’s, not this site’s. The course itself is studied on its own, in any order.

PROGRAMME

Course Title: Statistical Analysis of Clinical Trials

Credits: 3 (Theory) + 1 (Practical)

Hours/Week: 3 (Theory) + 2 (Practical)

Course Outcomes

  1. To acquaint with the need and ethics of clinical trials.
  2. To be aware of drawing the sample size for different population sizes.
  3. To understand dichotomous variables in clinical contexts.
  4. To expertise in performing the designs for various clinical trials.
  5. To perform the analysis and report writing of clinical trial results.

Detailed Structural Units

Unit 1: Introduction to Clinical Trials

Need and ethics of clinical trials, bias and random error in clinical studies, conduct of clinical trials, overview of Phase I–IV trials, multi-center trials. Data management: data definitions, case report forms, database design, data collection systems for good clinical practice.

Unit 2: Determination of Sample Size

For two independent samples of dichotomous response variables, for two independent samples of continuous response variables, and for repeated variables.

Unit 3: Design of Clinical Trials

Parallel vs. cross-over designs, cross-sectional vs. longitudinal designs, objectives and endpoints of clinical trials, design of Phase I trials, design of single-stage and multi-stage Phase II trials, design and monitoring of Phase III trials with sequential stopping, design of bioequivalence trials.

Unit 4: Reporting and Analysis

Analysis of categorical outcomes from Phase I–III trials, analysis of survival data from clinical trials.

Unit 5: Surrogate End Points and Meta-Analysis

Selection and design of trials with surrogate end points, analysis of surrogate end point data. Meta-analysis of clinical trials.

Practical (Credits: 1, 2 hrs/week)

List of Experiments

  1. Determination of Sample Size.
  2. Multiple Logistic Regression with two or three variables.
  3. Analysis of Clinical Trial Data using Crossover Design.
  4. Analysis of Clinical Trial Data using Parallel Design.
  5. Meta-Analysis of Clinical Trials.

Prescribed Textbooks & Reference Literature