Clinical Epidemiology (EPI 204)
Fall 2022 (3 units)
This is primarily a course about diagnosis and prediction. In public health and clinical practice, diagnostic tests are used to estimate the probability of a prevalent disease, and risk prediction models are used to evaluate the likelihood of an incident outcome. In this course, we will cover:
- performance measures used for diagnostic tests and risk prediction models.
- design and critical appraisal of research studies to evaluate tests and risk models.
- using the results of tests and risk models to inform decision-making.
Although the tests and models discussed are clinical and the decisions are often treatment decisions, the principles apply to any problem of prediction and decision-making under uncertainty.
Objectives
The specific objectives of this course are to provide a basic understanding of:
- sensitivity, specificity, prior and posterior probability.
- likelihood ratios, ROC curves,
- inter-observer agreement, reliability, and measurement error.
- calibration plots, net benefit calculations, decision curves.
- multivariable risk models (both their development and evaluation).
- special issues related to the evaluation of screening tests and programs.
- quantifying treatment benefits and harms using the results of randomized trials and observational studies.
Prerequisites
Designing Clinical Research (EPI 202). Exceptions may be made with the consent of the Course Director, space permitting. The course draws heavily upon clinical examples and may be more challenging for students without any clinical background. However, learning how to use clinical information to diagnose disease or predict outcomes and guide treatment decisions is an excellent way to introduce prediction in general.
Faculty
| Course Director: | Michael Kohn, MD, MPP Professor of Epidemiology & Biostatistics email: [email protected] |
| Course Director Emeritus/Current Co-Director: | Tom Newman, MD, MPH Professor Emeritus, Epidemiology & Biostatistics and Pediatrics Email: [email protected]
|
Format
Each week, new material is introduced via a recorded lecture and recommended readings. After beginning to study the lecture and reading, the class gathers for a large group discussion in which the lecture is briefly reviewed and students have the opportunity to pose questions to course faculty or prompt discussion on any aspect of the material. Homework, in the form of a problem set, is assigned each week. The goal of the homework is to reinforce the main points brought forth in lecture as well as to cover more detailed nuances found in the readings. The problem sets are discussed in detail with course faculty in the small group discussion sections at the end of each weekly cycle.
Large Group Discussion
Content:
Brief formal review of lecture followed by question-and-answer. Recorded lecture should be viewed prior to this session. The video can played at 0.5 to 2.0x speed.
Time: Tuesdays, 8:45 to 10:15 AM, beginning September 20
Small Group Discussion
Content:
Overview and discussion of lectures, and review of homework assignments. A detailed answer key will be available online shortly after each session. Time: Thursdays, 1:15 to 2:45 PM, beginning September 15 (One section will be held on Thursday evenings over Zoom. Details forthcoming.)
Drop-in Help
Content:
Course faculty are available to address questions on course content
Time: Wednesdays, 1:00 to 2:30 PM, beginning September 21.
All course materials and handouts will be posted on the course's online syllabus.
Materials
Evidence-Based Diagnosis by T. Newman and M. Kohn with illustrations by Martina Steurer. Cambridge University Press. 2nd Edition. 2010. UCSF-affiliated students can download a free .pdf through the UCSF Library. (If that link does not work, the easiest way to find it in the UCSF Library Catalog is by searching for “Newman Kohn evidence.” For some reason searching on the title does not work well. Then, you need to go from there to the Cambridge University Press site to download. Or just buy the book, it’s worth it!)
Optional Some of our material can also be found (in abbreviated form) in Designing Clinical Research, by Browner & Newman et al. Chapter 12 is particularly useful and is partly based on this course.
Stata
The statistical software package Stata (Stata Corporation, College Station, TX) is used throughout the TICR Program and is required for this course; version 16 or higher is acceptable. A six-month student license for Stata/BE is the least expensive option that will be suitable to complete all course assignments. For students intending to enroll in courses over 1-2 years, an annual or perpetual license are better long-term options. If your research requires working with more variables, you also may wish to consider Stata/SE. We recommend that you have a personal copy of Stata and bring it on a laptop for all course sessions. Stata may be purchased at a discount for UCSF faculty/staff and at a slightly greater discount for official UCSF Students. You must use your ucsf.edu email address to receive the discount. If you do not purchase your own copy of Stata, UCSF faculty/staff/students may request access to Stata through the UCSF Research Analysis Environment.
Grading
Grading is based equally on homework (including the problem-writing assignment, which counts as one homework) and a take-home final exam. Students will turn in 9 problem sets, a problem-writing assignment, and a final exam. The problem sets are due at the beginning of each Thursday small group session. Except for the first Thursday (9/15), the small-group session will be devoted to reviewing the problem set that students have just turned in. On the first Thursday, we will play the "Kappa Game". You should watch the first lecture, read Chapters 1 and 5 of the textbook, and do Problem Set 0 (not to be turned in) prior to the small group session on 9/15.
Students not in full-year TICR Programs who satisfactorily pass all course requirements will, upon request, receive a Certificate of Course Completion.
To Enroll
ATCR and MAS students use the Student Portal
Students taking individual courses:
Course Fees
How to pay (please read before applying)
Fall Course Schedule
Apply by September 12, 2022 for Fall quarter
Only one application needs to be completed for all courses desired during the quarter.