Biostatistical Methods for Clinical
Research V
Biostat 226 Winter 2012 (1 unit)
Course Director: Joan Hilton, ScD, MPH
Professor, Division of Biostatistics,
Department of Epidemiology & Biostatistics
| OBJECTIVES |
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This course covers current
issues in the design and analysis of randomized clinical trials (RCTs). It is part of the Biostatistical Methods in Clinical Research
series, continuing on from Biostatistical
Methods IV (Biostat 210), covering additional biostatistical methods
and allowing more in-depth exploration of the topics of Biostatistical
Methods II (Biostat 208) and III
(Biostat 209).
In the health-care setting, randomized controlled trials (RCTs) are experiments
in which investigators randomly assign eligible patients into intervention
groups, and then compare the outcomes of the groups to determine the relative
effect of the intervention. The primary outcome variable in such trials
is typically a measure of ultimate clinical status, such as disease progression.
In this course, we will examine study design and analysis methods that
have been developed to ensure the validity of the results of RCTs.
By the end of the course, students will have a working knowledge of a variety of classical and adaptive study designs for clinical trials, will understand the methods behind interim monitoring of Phase III trials, will be able to design a superiority or noninferiority trial for binary responses, and will understand concepts behind Bayesian designs and analyses.
| PREREQUISITES |
|
Designing Clinical
Research (Epi 202), Biostatistical
Methods I (Biostat 200) or Intro
to Statistical Analysis (Biostat 183), Biostatistical
Methods II (Biostat 208) and III
(Biostat 209). Exceptions to these prerequisites may be made with the
consent of the Course Director, space permitting.
| FACULTY |
|
| FORMAT |
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Lecture Outline:
-
January 3: An Introduction to Clinical Trials
- January 10 & 17: Phase III Outcome Monitoring
- January 24: Phase III Noninferiority Design
- January 31: An adaptive Phase III trial
- February 7: Introduction to Bayesian Methods
Each lecture will be accompanied by homework, assigned on the day of the lecture. Homework assignments are due prior to the following lecture and should be submitted by e-mail to the Course Director.
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GRADING
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Grading: 30% classroom participation; 70% homework assignments.
| ENROLLMENT |
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This course is open to a limited number of individuals outside
of the ATCR and Master's programs. Preference is given to UCSF-affiliated personnel.
We regret that auditing is not permitted. To apply for this course please fill
out and submit the application below. Cost and submission information are in
the application.
Application
(Word doc, 20KB)
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