Research interest

Donna Ankerst performs statistical research in the life sciences, with a focus on clinical risk prediction tools based on multi-center clinical trials, observational studies and electronic health records. She created the most validated and internationally accessed online prostate cancer risk calculator and is currently developing deep learning algorithms for three-dimensional mammograms in collaboration with the TUM Rechts der Isar hospital. She works on models for climate change impacts on forest and health outcomes in Bavaria in cooperation with the TUM School of Life Sciences.


Prostate Biopsy Collaborative Group (PBCG): The PBCG was founded in 2009 to prospectively collect prostate cancer risk factor and biopsy outcome data from multiple international urological centers in order to develop contemporary prostate cancer risk prediction tools. Development of such tools requires novel statistical methods and models for integrating multiple data types from heterogeneous centers, as well as recalibration to accommodate new data and outcomes in response to a continuously evolving prostate cancer clinical landscape. These tools are made publicly available for patient-clinician decision-making, the most recent one can be found here:

Bias correction procedures for external validation: Data from the large North American Selenium and Vitamin E Cancer Prevention Trial (SELECT) and the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO) are used to develop procedures for correcting risk prediction validation procedures for differing eligibility criteria (selection bias) and biopsy protocols (verification bias).

Spatio-temporal prediction error assessment: Visualization and quantification methodology are developed for risk forecasting models that vary in space and time, such as the intertwined processes of infection and death from COVID-19.

Key publications

  • Tolksdorf, Johanna; Kattan, Michael W.; Boorjian, Stephen A.; Freedland, Stephen J.; Saba, Karim; Poyet, Cedric; Guerrios, Lourdes; De Hoedt, Amanda; Liss, Michael A.; Leach, Robin J.; Hernandez, Javier; Vertosick, Emily; Vickers, Andrew J.; Ankerst, Donna P.: Multi-cohort modeling strategies for scalable globally accessible prostate cancer risk tools. BMC Medical Research Methodology 19 (1), 2019 mehr… Volltext ( DOI ) Volltext (mediaTUM)
  • Ankerst, Donna P.; Straubinger, Johanna; Selig, Katharina; Guerrios, Lourdes; De Hoedt, Amanda; Hernandez, Javier; Liss, Michael A.; Leach, Robin J.; Freedland, Stephen J.; Kattan, Michael W.; Nam, Robert; Haese, Alexander; Montorsi, Francesco; Boorjian, Stephen A.; Cooperberg, Matthew R.; Poyet, Cedric; Vertosick, Emily; Vickers, Andrew J.: A Contemporary Prostate Biopsy Risk Calculator Based on Multiple Heterogeneous Cohorts. European Urology 74 (2), 2018, 197-203 mehr… Volltext ( DOI )
  • Strobl, Andreas N.; Vickers, Andrew J.; Van Calster, Ben; Steyerberg, Ewout; Leach, Robin J.; Thompson, Ian M.; Ankerst, Donna P.: Improving patient prostate cancer risk assessment: Moving from static, globally-applied to dynamic, practice-specific risk calculators. Journal of Biomedical Informatics 56, 2015, 87-93 mehr… Volltext ( DOI )
  • Grill, Sonja; Fallah, Mahdi; Leach, Robin J.; Thompson, Ian M.; Hemminki, Kari; Ankerst, Donna P.: A simple-to-use method incorporating genomic markers into prostate cancer risk prediction tools facilitated future validation. Journal of Clinical Epidemiology 68, 2015, 563-573 mehr… Volltext ( DOI )
  • Winter, Susanne; Höfler, Josef; Michel, Alexa K.; Böck, Andreas; Ankerst, Donna P.: Association of tree and plot characteristics with microhabitat formation in European beech and Douglas-fir forests. European Journal of Forest Research 134, 2014, 335-347 mehr… Volltext ( DOI )