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ISCB2014_abstract_book

10 ISCB 2014 Vienna, Austria • Conference Courses Monday25thAugustTuesday26thAugustThursday28thAugustAuthorIndexPostersWednesday27thAugustSunday24thAugust Sunday, 24th August 2014 – Pre-conference Courses - Half-day - Afternoon Conference courses Course 5 Data and Safety Monitoring Board workshop T Jaki1 , L Hampson1 1 Lancaster University, Lancaster, United Kingdom   Data and Safety Monitoring Boards (DSMBs) are a common feature of long‐term clinical studies in serious and life‐threatening conditions. This workshop describes the remit and composition of DSMBs, and how their work relates to other parties involved in the study, such as the sponsor, the study project team, the investigators, the Steering Committee and the data management centre. The importance of pre‐trial preparation by the DSMB is stressed. Consideration is given to the nature and purpose of safety and efficacy data reports presented to the DSMB, and the balance between the timeliness and the accuracy of the data available is discussed. Statistical problems inherent in repeatedly making multiple treatment comparisons are highlighted, and formal stopping guidelines based on repeated safety analyses are presented. The role of the DSMB in trials with pre‐specified interim efficacy analyses will be discussed. The workshop is structured around group discussions in which partici- pants will play the roles of DSMB members and will discuss realistic trial reports of interim safety and efficacy. Course 6 Interaction analysis T VanderWeele1 1 Departments of Epidemiology and Biostatistics at the Harvard School of Public Health, Boston, United States   This workshop will provide a relatively broad introduction to the topic of interaction between exposures. We discuss interaction on both additive and multiplicative scales using risks, and we discuss their relation to sta- tistical models (e.g. linear, log‐linear and logistic models). We discuss and evaluate arguments that have been made for using additive or multiplica- tive scales to assess interaction. We describe inferential procedures for interaction when logistic models are fit to data but when additive and not just multiplicative measures of interaction are desired. We discuss issues of confounding for interaction analyses and how whether control has been made for only one or both of two exposures affects whether interaction estimates can be interpreted as causal interaction between the two exposures or only as effect hetero- geneity. We further discuss conditions under which interaction gives evidence of synergism within the sufficient cause framework, when interaction is robust to unmeasured confounding, interaction for time‐to‐event out- comes, case‐only estimators of interaction, and power and sample size calculations for additive and multiplicative interaction. Illustrations will be given from environmental, genetic, and infectious disease epidemiology. Software code will be provided. Sunday, 24th August 2014 • Pre-conference Courses - Half-day - Afternoon

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