This protocol is part of the REPEAT Initiative, a project which samples published research studies conducted using large healthcare data (such as electronic health record or administrative claims) and replicates them by applying the publically reported methods to the same data source as the original authors. The goal is to better understand what information is missing from public reporting that prevents replication of the published results. This project will evaluate how commonly a set of specific design and analysis decisions are or are not reported in publications as well as how lack of clarity in one or more decisions impacts ability to replicate study findings. Our results will inform future policies and guidelines for reporting on healthcare database research. This protocol focuses on one sampled study: "Incidence of type 2 diabetes after bariatric surgery: population-based matched cohort study" by Booth and colleagues. This paper evaluated the effect of stomach surgery for weight loss on development of diabetes in a large population of obese individuals in the United Kingdom (UK) between 2002 and 2014. We will replicate this study based on methods reported in the publication.
This objective of this protocol is to replicate the study: "Incidence of type 2 diabetes after bariatric surgery: population-based matched cohort study" by Booth et al. based on methods reported in the publication and appendices. We have created a checklist of specific study implementation parameters based on a comprehensive catalogue outlined in a consensus paper endorsed by the International Society of Pharmacoepidemiology and the International Society of Pharmacoeconomics and Outcomes research. We will start by reviewing the paper to ascertain which parameters from the catalogue are reported. We will then replicate the study population and analyses based on the study design and implementation parameters extracted during review. The Booth paper compares the development of clinical diabetes in patients who had bariatric surgery before April 30th, 2014 to those who did not have surgery. We will focus on replicating the outcome of development of clinical diabetes over this time period. To assess diabetes onset, a time-to-event framework is used, using a Cox proportional hazards model.
Development of clinical diabetes.
Shirley Wang - Chief Investigator - Harvard University
Elisabetta Patorno - Collaborator - Brigham & Women's Hospital
Jessica Franklin - Collaborator - Brigham & Women's Hospital
Krista Huybrechts - Collaborator - Brigham & Women's Hospital
Sebastian Schneeweiss - Collaborator - Aetion, Inc
Jeremy Rassen - Chief Investigator - Aetion, Inc
Elizabeth Garry - Collaborator - Aetion, Inc