A photo of Rhonda Szczesniak.

Associate Professor, UC Department of PediatricsUC Department of Environmental Health; UC Department of Mathematical Sciences

513-803-0563

Biography & Affiliation

Biography

Dr. Szczesniak's research program in cystic fibrosis computational medicine is emerging through a strong partnership with the Cystic Fibrosis Foundation and support from NIH. She has standing reviewer positions on grant award panels and is a member of the Cystic Fibrosis Foundation Patient Registry/Comparative Effectiveness Research Committee. She currently leads an initiative with an international consortium of MD/PhD researchers and clinicians on identifying the best practices for the analysis of lung function decline. She currently has an award to sponsor another faculty biostatistician for a career in CF comparative effectiveness research with translation of model systems based on the Cystic Fibrosis Foundation Patient Registry. Her published work leading up to this award was featured on the cover and in an editorial from the Annals of the American Thoracic Society. Most recently, her work on phenotypes of rapid cystic fibrosis lung disease was published in the American Journal of Respiratory and Critical Care Medicine and was highlighted in an accompanying editorial.

Clinical Interests

Cystic fibrosis; blood pressure; glycemic control

Research Interests

Functional data analysis; longitudinal data analysis; medical monitoring; prediction

Academic Affiliation

Associate Professor, UC Department of PediatricsUC Department of Environmental Health; UC Department of Mathematical Sciences

Divisions

Biostatistics

Education

PhD: Statistics, University of Kentucky, Lexington, KY, 2007.

MS: Statistics, University of Kentucky, Lexington, KY, 2005.

BS: Mathematics, Radford University, Radford, VA, 2003.

Publications

Dynamic predictive probabilities to monitor rapid cystic fibrosis disease progression. Szczesniak, RD; Su, W; Brokamp, C; Keogh, RH; Pestian, JP; Seid, M; Diggle, PJ; Clancy, JP. Statistics in Medicine. 2020; 39:740-756.

Prospective validation of a machine learning model that uses provider notes to identify candidates for resective epilepsy surgery. Wissel, BD; Greiner, HM; Glauser, TA; Holland-Bouley, KD; Mangano, FT; Santel, D; Faist, R; Zhang, N; Pestian, JP; Szczesniak, RD; et al. Epilepsia. 2020; 61:39-48.

Feasibility and Acceptability of a Telephone-Based Chaplaincy Intervention to Decrease Parental Spiritual Struggle. Betz, J; Szczesniak, R; Lewis, K; Pestian, T; Bennethum, AS; McBride, J; Grossoehme, DH. Journal of Religion and Health. 2019; 58:2065-2085.

Investigation of bias in an epilepsy machine learning algorithm trained on physician notes. Wissel, BD; Greiner, HM; Glauser, TA; Mangano, FT; Santel, D; Pestian, JP; Szczesniak, RD; Dexheimer, JW. Epilepsia. 2019; 60:e93-e98.

Lymphangioleiomyomatosis Mortality in Patients with Tuberous Sclerosis Complex. Zak, S; Mokhallati, N; Su, W; McCormack, FX; Franz, DN; Mays, M; Krueger, DA; Szczesniak, RD; Gupta, N. Annals of the American Thoracic Society. 2019; 16:509-512.

Can't see the wood for the trees: confounders, colliders and causal inference - a statistician's approach. Huang, B; Szczesniak, R. Thorax. 2019; 74:323-325.

Associating antimicrobial susceptibility testing with clinical outcomes in cystic fibrosis: More rigor and less frequency?. Szczesniak, RD; Cogen, JD; Rosenfeld, M. Journal of Cystic Fibrosis. 2019; 18:159-160.

Control of confounding and reporting of results in causal inference studies. Lederer, DJ; Bell, SC; Branson, RD; Chalmers, JD; Marshall, R; Maslove, DM; Ost, DE; Punjabi, NM; Schatz, M; Smyth, AR; et al. Annals of the American Thoracic Society. 2019; 16:22-28.

Dynamic Prediction of Survival in Cystic Fibrosis: A Landmarking Analysis Using UK Patient Registry Data. Keogh, RH; Seaman, SR; Barrett, JK; Taylor-Robinson, D; Szczesniak, R. Epidemiology. 2019; 30:29-37.

Improving Detection of Rapid Cystic Fibrosis Disease Progression-Early Translation of a Predictive Algorithm Into a Point-of-Care Tool. Szczesniak, RD; Brokamp, C; Su, W; Mcphail, GL; Pestian, J; Clancy, JP. IEEE Journal of Translational Engineering in Health and Medicine-JTEHM. 2019; 7:2800108-8.