Dr. Krithika Suresh is a research assistant professor in the Department of Biostatistics & Informatics. She received her MMath in Biostatistics from the University of Waterloo in Canada, and her PhD in Biostatistics from the University of Michigan. Krithika works with ACCORDS on the CUAnschutz campus, where she is involved in the design and analysis of health outcomes research studies using pragmatic trials, such as cluster randomized and stepped wedge designs. Her research interests include survival analysis, longitudinal data, joint modeling, and predictive modeling, with applications in cancer research and other health outcomes.
Areas of Expertise
- Joint modeling
- Longitudinal data analysis
- Predictive modeling
- Pragmatic trials design
- Survival analysis
Education, Licensure & Certifications
- PhD, Biostatistics, University of Michigan, 2018
- MMath, Biostatistics, University of Waterloo, 2013
- BMath, University of Waterloo, 2012
- BBA, Wilfrid Laurier University, 2012
Courses
- BIOS 7721: Joint Modeling of Longitudinal and Survival Data
Publications and Presentations
- Dess, R. T., Suresh, K., Zelefsky, M. J., Freedland, S. J., Mahal, B. A., Cooperberg, M. R., ... & Spratt, D. E. (2020). Development and Validation of a Clinical Prognostic Stage Group System for Nonmetastatic Prostate Cancer Using Disease-Specific Mortality Results From the International Staging Collaboration for Cancer of the Prostate. JAMA oncology, 6(12), 1912-1920.
- Suresh, K., Taylor, J. M., & Tsodikov, A. (2019). A Gaussian copula approach for dynamic prediction of survival with a longitudinal biomarker. Biostatistics.
- Feng, M., Suresh, K., Schipper, M. J., Bazzi, L., Ben-Josef, E., Matuszak, M. M., ... & Lawrence, T. S. (2018). Individualized adaptive stereotactic body radiotherapy for liver tumors in patients at high risk for liver damage: a phase 2 clinical trial. JAMA oncology, 4(1), 40-47.
- Suresh, K., Taylor, J. M., Spratt, D. E., Daignault, S., & Tsodikov, A. (2017). Comparison of joint modeling and landmarking for dynamic prediction under an illness‐death model. Biometrical Journal, 59(6), 1277-1300.
- Good, N. M., Suresh, K., Young, G. P., Lockett, T. J., Macrae, F. A., & Taylor, J. M. (2015). A prediction model for colon cancer surveillance data. Statistics in medicine, 34(18), 2662-2675.