John Lachin is Research Professor of Biostatistics and Bioinformatics at the Biostatistics Center of the George Washington University. Dr. Lachin was the Principal-Investigator of the Data Coordinating Center for the Diabetes Control and Complications Trial (DCCT: 1981-1998), and also its sequel, the study of the Epidemiology of Diabetes Interventions and Complications (EDIC: 1996 - 2022). Effective January 1, 2020 he stepped down from being the Principal Investigator and is now a co-investigator. He also is the PI for the Glycemia Reduction Approaches for Diabetes: A Comparative Effectiveness Study (GRADE: 2012-2022). Both projects all funded by the NIDDK of the NIH. The DCCT/EDIC completed it 37th year of follow-up and study. During the past year we published numerous articles on the long term benefits of intensive diabetes therapy. Numerous additional manuscripts are under development for publication. Grade is entering its 10th year of funding. Recruitment of 5047 participants was completed in 2017, with follow-up to the summer of 2021 and publications in 2022.
Dr. Lachin is a Fellow of the American Statistical Association, the Royal Statistical Society, and the Society for Clinical Trials for which he also served as President.
Dr. Lachin has published 5 books including Biostatistical Methods (Wiley, Second Edition, 2011) and Randomization in Clinical Trials (co-author, Wiley, Second Edition, 2016), over 75 technical papers on biostatistical methods, and over 250 scientific papers related to his collaborative medical research activities. Recent medical papers include the demonstration that the long-term level of glycemia in type 1 diabetes is an important risk factor for cardiovascular disease and that intensive diabetes therapy that improves glucose control reduces the risk of mortality and the need for ocular surgery. Recent methodological publications include the demonstration that the Wei-Lachin multivariate one-directional test for multiple outcomes is superior to the test of a composite outcome, and demonstration of the fallacy of Last Observation Carried Forward (LOCF) analysis.