Dr. Frank Harrell gave a talk "Information Allergy" at Distinguished Lecture Series
November 02, 2009
“Information Allergy”
Speaker: Dr. Frank E. Harrell, Jr.
Co-Sponsored by the Center for Health Informatics and Bioinformatics
Distinguished Lecture Series & The NYULMC Clinical and Translational Science Institute
Monday, October 19th – 10:00 – 11:00, Farkas Auditorium
The Center for Health Informatics and Bioinformatics and the Clinical and Translational Science Institute are honored to welcome Dr. Frank E. Harrell, Jr., Professor and Chair of the Department of Biostatistics at Vanderbilt University to our Distinguished Lecture Series.
About the speaker, Professor Frank E. Harrell, Jr. Ph.D.
Dr. Harrell is a Fellow of the American Statistical Association and is the 2008 Mitchell Lecturer for the Department of Statistics, Glasgow University. He is an FDA expert consultant and a member of the NIH Biostatistical Methods and Research Design Study Section. He is the leader of the Design, Biostatistics, and Clinical Research Ethics program for the Vanderbilt NIH CTSA and is the director of the Statistics and Methodology Core for the Vanderbilt Kennedy Center for Research on Human Development. He is the author of the first and third most cited papers (on development of prognostic models) in the 26 year history of Statistics in Medicine and has 188 peer-reviewed publications. His latest areas of emphasis are pharmaceutical safety, flexible Bayesian clinical trial design and Bayesian analysis, and graphical and tabular methods for reporting analyses from clinical trials. Dr Harell founded the Division of Biostatistics and Epidemiology at the University of Virginia School of Medicine in 1996 and the Department of Biostatistics at Vanderbilt University in 2003 which he chairs.
About the lecture: “Information Allergy”
Information allergy is defined as (1) refusing to obtain key information needed to make a sound decision, or (2) ignoring important available information. The latter problem is epidemic in biomedical and epidemiologic research and in clinical practice. Examples include
- ignoring some of the information in confounding variables that would explain away the effect of characteristics such as dietary habits
- ignoring probabilities and “gray zones” in genomics and proteomics research, making arbitrary classifications of patients in such a way that leads to poor validation of gene and protein patterns
- failure to grasp probabilitistic diagnosis and patient-specific costs of incorrect decisions, thus making arbitrary diagnoses and placing the analyst in the role of the bedside decision maker
- classifying patient risk factors and biomarkers into arbitrary “high/low” groups, ignoring the full spectrum of values
- touting the prognostic value of a new biomarker, ignoring basic clinical information that may be even more predictive
- using weak and somewhat arbitrary clinical staging systems resulting from a fear of continuous measurements
- ignoring patient spectrum in estimating the benefit of a treatment
Examples of such problems will be discussed, concluding with an examination of how information–phobic cardiac arrhythmia research contributed to the deaths of thousands of patients.
