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Activity Number: 368 - SPEED: Statistics for Biopharmaceutical Studies
Type: Contributed
Date/Time: Tuesday, July 31, 2018 : 11:35 AM to 12:20 PM
Sponsor: Biopharmaceutical Section
Abstract #332671
Title: Method for Evaluating Longitudinal Follow-Up Frequency: Application to Dementia Research
Author(s): Leah Suttner* and Sharon X Xie
Companies: University of Pennsylvania and University of Pennsylvania
Keywords: Design; Interval-censoring; Parkinson's disease; Survival analysis

Current practice of longitudinal follow-up frequency in outpatient clinical research is mainly based on experience, tradition, and availability of resources. Previous methods for designing follow-up times require parametric assumptions about the hazards for the event. There is a need to develop robust, easy to implement, quantitative procedures for justifying the appropriateness of follow-up frequency. Therefore, we propose a novel method to evaluate follow-up frequency by assessing the impact of ignoring interval-censoring in longitudinal studies. Specifically, we evaluate the bias in estimating hazard ratios using Cox models under various follow-up schedules. Our simulation-based procedure applies the schedules to generated data resembling the survival curve of historical data. Using this method, we evaluate the current follow-up of Parkinson's disease patients at the University of Pennsylvania Morris K. Udall Parkinson's Disease Research Center; however, the method can be applied to any research area with sufficient historical data for appropriate data generation. To allow clinical investigators to implement this method, we provide a Shiny web application.

Authors who are presenting talks have a * after their name.

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