Talks focused on translating recent advances in biostatistics into practice. Biostatistics Continuing Education
At a glance
Opportunity for
  • Continuing education on recent advances in biostatistics
Eligibility
  • All members of the Harvard Catalyst community, but primarily geared toward biostatisticians
Session Dates
  • Varies; see below for details

The Harvard Catalyst Biostatistics Program will present seminars on current applied topics in biostatistics. These will include our monthly journal club and work in progress sessions, seminar series, symposia, and short courses.

Journal Club/Work in Progress

April 2018 Journal Club

April 24, 2018, 1:00pm-2:00pm
Harvard T.H. Chan School of Public Health, Room 2-426

Please join us for this meeting of the Harvard Catalyst Biostatistics Journal Club. The leader of this meeting will be Carter Petty, MA, Senior Biostatistician in Biostatistics and Research Design, Institutional Centers for Clinical and Translational Research, BCH. He will discuss "Marginal modeling of nonnested multilevel data using standard software" by D.L. Miglioretti and P.J. Heagerty in Am J Epidemiol. 2007 Feb 15;165(4):453-63.

Journal Club Reading

Carter Petty, MA
Senior Biostatistician in Biostatistics and Research Design
Institutional Centers for Clinical and Translational Research
Boston Children's Hospital

Registration not required.


May 2018 Journal Club

May 24, 2018, 1:00pm-2:00pm
Harvard T.H. Chan School of Public Health, Room 2-426

Robert Glynn, PhD, ScD
Professor of Medicine, Harvard Medical School, BWH
Professor in the Department of Biostatistics, Harvard T.H. Chan School of Public Health

Registration not required.


June 2018 Journal Club

June 14, 2018, 1:00pm-2:00pm
MGH Biostatistics Center, 50 Staniford Street, Suite 560

David Schoenfeld, PhD
Professor of Medicine, Harvard Medical School, MGH
Professor in the Department of Biostatistics, Harvard T.H. Chan School of Public Health

Registration not required.


Seminar Series

Vetting and Advancing Individualized Medicine: Issues and Strategies

May 17, 2018, 1:00pm - 2:00pm
Harvard T.H. Chan School of Public Health, Room 2-426

Nicholas J. Schork, PhD
TGen and TGen/City of Hope IMPACT Center, Phoenix, AZ, and Duarte, CA
J. Craig Venter Institute (JCVI) and Adjunct Professor of Psychiatry and Family and Preventive Medicine (Division of Biostatistics) at the University of California, San Diego (UCSD), La Jolla, CA

Abstract: There is a lot of attention being given to 'personalized,' 'individualized,' and 'precision' medicine. This is not without some justification, as applications of contemporary technologies such as DNA sequencing, proteomics, induced pluripotent stem cells, imaging protocols, and wireless health monitoring devices have identified nuanced and often unique features of individuals at the genomic, physiologic, environmental and behavioral levels that may impact their risk for disease and treatment response. However, unless it can be shown the individualized medicine approaches and strategies result in better outcomes than an alternative approach to treating disease, its adoption will be in question. Vetting individualized medicine strategies is not trivial, although there are a few emerging strategies. These include aggregated N-of-1 trials, drug matching trials, and developing clinical learning systems. Recent trends in regulatory oversight perspectives may accommodate these and related vetting strategies for a number of reasons. This talk discusses relevant issues in vetting individualized medicine and provides examples, analytical results related to specific study designs, and simulation study results, as well as an eye towards the need to vet and test more futuristic technologies, such as individualized digital therapeutics and therapeutic 'companion' technologies.

Registration not required.


Symposia


Short Courses

Absolute Risk: Methods and Applications in Clinical Management and Public Health

April 23, 2018
8:30am - 5:30pm
Minot Room, Countway Library

This course is an introduction to absolute risk, the probability of developing a specific outcome, over a specified time interval, in the presence of competing causes of mortality. This course will define absolute risk and discusses methodological issues relevant to the development and evaluation of absolute risk models. We will present the cause-specific and cumulative incidence approaches to incorporating covariates, and discuss various study designs and data for model building, including cohort, nested case-control, and case-control data combined with registry data. We will show how to evaluate the performance of risk prediction models and discuss the use of absolute risk in individual counseling for prevention strategies, including interventions that can have adverse effects. We also discuss the potential use of such models for disease prevention in the population, including designing prevention trials, estimating the absolute risk reduction in the population from modifying risk factor distributions, the "high risk" preventive intervention strategy, risk-based disease screening, and resource allocation.

Ruth Pfeiffer, PhD
Senior Investigator/Biostatistics Branch
Division of Cancer Epidemiology and Genetics
National Cancer Institute
Graduate of Technical University of Vienna, Austria (MA in applied mathematics) and University of Maryland, College Park (PhD in mathematical statistics)

Mitchell H. Gail, MD, PhD
Senior Investigator
Division of Cancer Epidemiology and Genetics
National Cancer Institute
Graduate of Harvard Medical School (MD) and
George Washington University (PhD in statistics)

Registration is required. Please email us to register.

Causal Mediation Analysis

May 14, 2018
8:30am - 5:30pm
Location TBD

The workshop will cover some of the recent developments in causal mediation analysis and provide practical tools to implement these techniques. Mediation analysis concerns assessing the mechanisms and pathways by which causal effects operate. The course will cover the traditional methods for mediation in epidemiology and the social sciences. For dichotomous, continuous, and time-to-event outcomes, discussion will be given as to when the standard approaches to mediation analysis are valid. Alternative mediation analysis techniques under the potential outcomes framework for causal inference will be described when the standard approaches do not work. The no-confounding assumptions needed for these techniques will be described. SAS, SPSS, Stata and R macros to implement these techniques will be covered and distributed to course participants. The use and implementation of sensitivity analysis techniques to assess how sensitive conclusions are to violations of assumptions will be covered. Discussion will be given to how such mediation analysis approaches can be extended when interactive and mediating mechanisms are simultaneously present. The methods will be illustrated by various applications to perinatal, genetic, and social epidemiology. Familiarity with linear and logistic regression will be assumed; knowledge of counterfactual notation would be helpful but is not necessary.

Linda Valeri, PhD
Instructor in Psychiatry, Harvard Medical School
Biostatistician, Laboratory for Psychiatric Biostatistics, McLean Hospital

Registration is required. Please email us to register.