Diane Uschner

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Bio

Diane Uschner, PhD., is an Assistant Research Professor in the Department of Biostatistics and Bioinformatics at the George Washington University School of Public Health. She joined the GW Biostatistics Center in April 2018 and currently serves as Co-Investigator of the Coordinating Center for the TODAY2 long-term follow-up study of the Treatment Options for T2D in Adolescents and Youth (TODAY) study. She served as a statistician for the C-Peptide Ancillary Study of the DCCT/EDIC (Diabetes Control and Complications Trial/Epidemiology of Interventions and Complications) study. Dr. Uschner has recently developed an interest in antibacterial resistance and infectious diseases, and is serving as a biostatistician in the Antibiotic Resistance Leadership Group (ARLG). She is the PI of the Data Coordinating Center COVID-19 Community Research Partnership, a research program for the serological and syndromic surveillance of COVID-19. She leads the Data Coordinating Center of a NIST funded project to study the impact of infrastructure failures on excess mortality in the aftermath of Hurricane Maria in Puerto Rico.

Prior to joining GW, Dr. Uschner received her Ph.D. in Biostatistics from the RWTH Aachen University, Germany in 2018. Her PhD thesis focused on the choice of randomization procedures to mitigate bias in clinical trials and was funded by the EU FP7-project “Integrated Design and Analysis of Small Population group Trials” (IDeAl). Her research interests are focused on the design of clinical trials, randomization, control of bias, as well as survival analysis, penalized regression, and statistical learning. Dr. Uschner regularly serves as a reviewer for scientific journals, NIH grant reviews, and meeting abstracts.

Expertise

Expertise:

Biostatistics

Epidemiology

Publications

Publications:

Refereed Journals

Y. Wang, W. F. Rosenberger, D. Uschner. (2019) Randomization Tests for Multi-armed Randomized Clinical Trials. Statistics in Medicine. 39(4): 494-509. https://doi.org/10.1002/sim.8418

Y. Jiang, D. Uschner (2019). What romantic comedies can teach us about response adaptive randomization for clinical trials? Chance. 32(4): 18-22. https://doi.org/10.1080/09332480.2019.1695436

Y. Wang, W. F. Rosenberger, D. Uschner. (2019). Randomization-based inference and the choice of randomization procedures. Statistical papers. 60(2) https://doi.org/10.1007/s00362-018-01070-y .

A. Kroh, D. Uschner, T. Lodewick, R. M. Eickhoff, F. T. Ulmer, U. P. Neumann, M. Binnebösel (2019). Impact of body composition on survival and morbidity after liver resection in HCC patients. Hepatobiliary and Pancreatic Diseases International. 85(1) https://doi.org/10.1016/j.hbpd.2018.07.008.

W. F. Rosenberger, D. Uschner, Y. Wang (2018). Rejoinder. Statistics in Medicine. 38(1) https://doi.org/10.1002/sim.7901.

W. F. Rosenberger, D. Uschner, Y. Wang (2018). The fifteenth Armitage Lecture: Randomization: The forgotten component of the randomized clinical trial. Statistics in Medicine. 38(1) https://doi.org/10.1002/sim.7901.

D. Schindler, D. Uschner, R.-D. Hilgers and N. Heussen (2018). randomizeR: Randomization for Clinical Trials. R package version 1.4.

D. Uschner, D. Schindler, R.-D. Hilgers, N. Heussen (2018). randomizeR: An R Package for the Assessment and Implementation of Randomization in Clinical Trials. Journal of Statistical Software. 85(8). http://doi.org/10.18637/jss.v085.i08.

D. Uschner, N. Heussen, R.-D. Hilgers (2018). The Impact of Selection Bias in Randomized Multi-Arm Parallel Group Clinical Trials. PLOS ONE 13(1): e0192065. https://doi.org/10.1371/journal.pone.0192065.

S. Bergrath, M. Müller, R. Rossaint, S. K. Beckers, D. Uschner, M. Czaplik, J. C. Brokmann (2018). Quality outcomes in acute coronary syndromes between telemedically supported paramedics and conventional on-scene physician care - a longitudinal pre-post intervention cohort study. Health Informatics Journal. https://doi.org/10.1177/1460458218775157.

R.-D. Hilgers, D. Uschner, W. F. Rosenberger and N. Heussen (2017). A general framework to assess randomization procedures in the presence of selection and chronological bias. BMC Medical Research Methodology.17:159 https://doi.org/10.1186/s12874-017-0428-z.

R. Gohmann, F. Heckner, D. Uschner, S. D. Reinartz (2017). Body pushers: Low-dose CT, always the best choice? A study of the diagnostic performance of CT scout view. Open Journal of Radiology. 7(2) http://doi.org/10.4236/ojrad.2017.72013.

Chapters in Book

D. Uschner, W. F. Rosenberger. (2019). Bias Control and Precision. In: Principles and Practice of Clinical Trials. Volume 1. Steven Piantadosi, Curtis L. Meinert. Springer (accepted).