Rhonda D. Szczesniak, PhD
- Member, Division of Biostatistics and Epidemiology
- Professor, UC Department of Pediatrics
- UC Department of Environmental Health; UC Department of Mathematical Sciences
About
Biography
My research interests include predictive modeling, data management / coordination and medical monitoring, lung diseases and disorders, biomarker discovery and longitudinal data analysis. In my research lab, the goals of my team include designing and analyzing medical monitoring investigations as well as incorporating geo- and bio-markers for customized, enhanced prediction / early detection of swift disease progression.
Some of the most notable discoveries made at my lab include identifying pediatric phenotypes of rapid lung disease progression using the U.S. Cystic Fibrosis Registry and the geo- and bio-marker-informed prediction modeling of rapid lung disease progression.
I was led to my research interests by witnessing how certain things change over time and determining why things transform. This is why I pursued statistics in my graduate studies at the University of Kentucky.
As my career progressed, I received a recognition for biostatistical contributions to cystic fibrosis research in the Journal of Cystic Fibrosis in April 2019. I have also held reviewer positions on grant award panels, and I hold a membership in the Cystic Fibrosis Foundation Patient Registry / Comparative Effectiveness Research Committee. My research has been supported by the National Institutes of Health (NIH), the Cystic Fibrosis Foundation and the LAM Foundation.
I have more than 15 years of experience in the biostatistics field, and I first started working at the Cincinnati Children’s Hospital Medical Center in 2007. Lastly, my research work has been published in a multitude of journals, including Statistical Methods in Medical Research, Statistics in Medicine, Journal of Religion and Health, Journal of Cystic Fibrosis, Journal of Diabetes Research, Annals of the American Thoracic Society, Chest, and American Journal of Respiratory and Critical Care Medicine.
PhD: Statistics, University of Kentucky, Lexington, KY, 2007.
MS: Statistics, University of Kentucky, Lexington, KY, 2005.
BS: Mathematics, Radford University, Radford, VA, 2003.
Interests
Cystic fibrosis; blood pressure; glycemic control
Services and Specialties
Pulmonary Medicine
Interests
Functional data analysis; longitudinal data analysis; medical monitoring; prediction
Research Areas
Biostatistics and Epidemiology
Publications
Lung Function Decline in Cystic Fibrosis: Impact of Data Availability and Modeling Strategies on Clinical Interpretations. Annals of the American Thoracic Society. 2023; 20:958-968.
Predicting lung function decline in cystic fibrosis: the impact of initiating ivacaftor therapy. Respiratory Research. 2024; 25:187.
Comparison of Longitudinal Outcomes in Children with Primary Ciliary Dyskinesia and Cystic Fibrosis. Annals of the American Thoracic Society. 2024; 21:1723-1732.
Robust identification of environmental exposures and community characteristics predictive of rapid lung disease progression. Science of the Total Environment. 2024; 950:175348.
Impact of the expanded label for elexacaftor/tezacaftor/ivacaftor in people with cystic fibrosis with no F508del variant in the USA. The European respiratory journal : official journal of the European Society for Clinical Respiratory Physiology. 2024; 64:2401146.
Forced Expiratory Volume in 1 Second Variability Predicts Lung Transplant or Mortality in People with Cystic Fibrosis in the United States. Annals of the American Thoracic Society. 2024; 21:1416-1420.
Secular and modulator-specific drifts in the predictive performance of a rapid lung function decline algorithm: a cystic fibrosis patient registry study. 2024; 2:10.
208 Impact of diesel exhaust particles on cystic fibrosis lung disease. Journal of Cystic Fibrosis. 2024; 23:s114.
Demographic factors associated with within-individual variability of lung function for adults with cystic fibrosis: A UK registry study. Journal of Cystic Fibrosis. 2024; 23:936-942.
HYPER-LOCALIZATION AND PREDICTIVE MODELING OF RAPID CYSTIC FIBROSIS DISEASE PROGRESSION. Annals of Epidemiology. 2024; 97:76.
From the Blog
Inclined to Predict Declines: A Tool for Informing Early Intervention for Cystic Fibrosis Patients
Rhonda D. Szczesniak, PhD, Assem G. Ziady, PhD ...5/17/2021
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