Erasmus Summer Programme
Master Class: Advances in Epidemiologic Analysis [ESP64]
August 8, 2016
Erasmus MC, Querido Lecture Room
In this Master Class timely topics in study design of epidemiologic and clinical studies will be addressed. Four renowned faculty members will address advanced study design issues in a seminar format.
Moderator Prof. Oscar Franco
Monday August 8, 2016
Long shall we live?!
This presentation will address the causes and consequences of the spectacular increase in life expectancy over the past two centuries from an epidemiological viewpoint.
Professor Albert Hofman, MD, PhD
Professor and chair
Department of Epidemiology
Harvard T.H. Chan School of Public Health
Boston, MA, USA
Tuesday August 9, 2016
Bradford Hill’s Advice on Causal Inference, 50 Years Later
In 1965, Sir Austin Bradford Hill posed what many consider to be the central question in nonexperimental epidemiology: “In what circumstances can we pass from this observed association to a verdict of causation? Upon what basis should we proceed to do so?” He produced a list of considerations, which have been cited by many and widely adopted as a list of causal criteria. Where did this list come from? Do they really serve as causal criteria? How might Bradford Hill wish to modify what he wrote in 1965 in light of the intervening 50 years? These questions and others will be the topic for discussion.
Professor Kenneth J. Rothman, DrPH
Distinguished Fellow, Research Triangle Institute
Research Triangle Park, North Carolina, USA
Professor of Epidemiology, Boston University School of Public Health, Boston, Massachusetts, USA
Wednesday August 10, 2016
Controversies in Epidemiology: the curious case of saturated fatty acids in cardiometabolic risk
Current dietary recommendations encourage reducing the intake of total saturated fatty acids (SFAs) to prevent cardiometabolic diseases; however, recent findings have questioned the role of total SFAs. Several recent systematic reviews and meta-analyses, based on prospective observational studies that examined dietary total SFA intake in relationship with subsequent risk of cardiometabolic outcomes (i.e. coronary heart disease, stroke and type-2 diabetes), found no significant overall association. However, in the observational studies of fatty acid biomarkers, where individual SFA subtypes in blood phospholipids were measured, there seems to be a substantial heterogeneity in the risk associations within the total SFA family. For example, in these biomarker studies, specific odd-chain SFAs appear to have an inverse association with cardiometabolic risk, whereas by contrast, even-chain SFAs are associated positively. Additionally, available randomised secondary prevention trials (where total SFA consumption was replaced with omega-6 polyunsaturated fatty acid intake) are generally small, insufficiently prolonged, vary widely in quality and rigor, and report weak inverse or no significant effects on clinical cardiometabolic outcomes. Furthermore, in metabolic ward studies with intermediate outcomes, in overall, supplementing with diet high in SFA content reduced circulating low-density lipoprotein cholesterol concentration importantly, however, also tended to increase circulating high-density lipoprotein cholesterol, triglycerides and lipoprotein(a) levels, and had no significant effect on insulin resistance. In summary, the value of broad grouping of nutrients such as total SFA and their effects on intermediate factors or clinical outcomes may be limited owing to the potential diversity of specific SFA subtypes in terms of their wide-ranging food sources and discrepant clinical consequences. Further research, therefore, is required to reliably clarify: (1) the roles of individual SFA subtypes, in isolation and in combination, on cardiometabolic risk, particularly in free-living general populations; and (2) potential cardiopreventive or cardiopromotive effects of their principal food sources.
Dr. Rajiv Chowdhury MD, MPhil, PhD
University Lecturer in Global Health
Cardiovascular Epidemiology Unit
Department of Public Health and Primary Care
University of Cambridge, UK
Thursday August 11, 2016
Modern challenges in prediction research
In this era of personalized medicine, clinical prediction models become increasingly relevant to inform patients and guide decision-making. Prediction models may combine various markers and clinical characteristics that relate to a diagnostic or prognostic outcome. Recent developments in model development, validation and impact assessment will be presented, illustrated with various medical case studies.
Professor Ewout W. Steyerberg, PhD
Professor of Medical Decision Making
Erasmus MC, Rotterdam, The Netherlands
The Master Classes are open without registration or fee for participants of the Erasmus Summer Programme, the NIHES programmes, employees of the Erasmus MC University Medical Center and public at large.
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