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 focuses on predictive modeling, longitudinal data analysis, environmental health, biomarker discovery and medical monitoring, with an emphasis on lung diseases and disorders. My lab designs and analyzes medical monitoring studies and integrates geo‑ and bio‑markers to improve early detection and prediction of rapid disease progression. Notable contributions include identifying pediatric phenotypes of rapid lung disease progression using the U.S. Cystic Fibrosis Registry and developing geo‑ and bio‑marker–informed prediction models.
I have taught introductory statistics and longitudinal data analysis and have developed advanced statistical and epidemiologic courses at the University of Cincinnati. I have nearly 20 years of experience in biostatistics, beginning my career at Cincinnati Children’s in 2007, and I have received recognition for biostatistical contributions to rare lung disease research. My work has been supported by the NIH, Cystic Fibrosis Foundation and The LAM Foundation.
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
Interests
Data management and coordination; functional data analysis; longitudinal data analysis; medical monitoring; prediction
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(7):958-968.
Clinical effectiveness of elexacaftor/tezacaftor/ivacaftor in people with cystic fibrosis in the United States. Annals of the American Thoracic Society. 2026; 23(10):1466-1475.
Real-time prediction of rapid weight change in children with cystic fibrosis who have initiated modulator therapy. Clinical Nutrition ESPEN. 2026; 75:103448.
Predicting Psychiatric Readmission of Children and Adolescents Using Machine Learning. Journal of Child and Adolescent Psychopharmacology. 2026; 36(8):483-492.
Poster: 657Changes in FEV1pp variability following initiation of elexacaftor/tezacaftor/ivacaftor: A registry study. Journal of Cystic Fibrosis. 2026; 25:359-360.
Poster: 679Characterizing spatial variability in CF lung function: A US Midwest cohort study. Journal of Cystic Fibrosis. 2026; 25:372.
Poster: 677PRISM-CF: A prototype dashboard to contextualize polygenic risk scores with environmental and clinical factors in cystic fibrosis. Journal of Cystic Fibrosis. 2026; 25:370-371.
Poster: 187Effects of diesel exhaust particles in an aged mouse model of cystic fibrosis disease. Journal of Cystic Fibrosis. 2026; 25:92-93.
Poster: 639Real world impact of elexacaftor/tezacaftor/ivacaftor (ETI) on long-term lung function trajectory among children ages 6-17 in the United States. Journal of Cystic Fibrosis. 2026; 25:349-350.
Poster: 682A longitudinal retrospective analysis of environmental exposure effects on Th2 inflammatory markers and pulmonary function in people with cystic fibrosis. Journal of Cystic Fibrosis. 2026; 25:374.
From the Blog
Lung Health Varies Widely State-to-State for People with Cystic Fibrosis
Rhonda D. Szczesniak, PhD, Emrah Gecili, PhD2/27/2026
Developing a Framework for Studying Lung Function Decline in Cystic Fibrosis
Rhonda D. Szczesniak, PhD7/1/2023
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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