Marc D. Ryser, Assistant Professor in Population Health Sciences

Marc D. Ryser conducts research in cancer early detection, with a particular focus on breast cancer overdiagnosis and overtreatment. Using a multi-scale approach, his group generates and analyzes biologic, clinical and population data using a variety of mathematical, statistical and computational tools. Examples of ongoing projects include the evolutionary dynamics of early-stage breast cancer; decision support tools for early-stage breast cancer patients; and estimation of breast cancer overdiagnosis. Dr. Ryser has a keen interest in training the next generation of interdisciplinary researchers and teaches an immersive research seminar for undergraduate students called “Math & Medicine.”

Website: https://sites.duke.edu/marcdryser/

Contact Info:

Office Location:	215 Morris St, Suite 210, Durham, NC 27701
Email Address:
Web Pages:	http://www.math.duke.edu/~ryser/ https://sites.duke.edu/marcdryser/

Teaching (Spring 2023):

• MATH 89S.01, FIRST-YEAR SEMINAR (TOP) Synopsis

  Physics 259, TuTh 08:30 AM-09:45 AM

Education:

Ph.D.	McGill University (Canada)	2011
MS (Physics)	EPFL	2006
BS (Physics)	EPFL	2004

Research Interests:

Please visit my personal site for information about me and my research

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Keywords:

Bone and Bones • Bone Neoplasms • Bone Resorption • Chemotaxis • Computational Biology • Computer Simulation • Fractures, Bone • Gene Expression Profiling • Homeostasis • Meta-Analysis as Topic • Models, Biological • Osteoblasts • Osteoprotegerin • Parathyroid Hormone-Related Protein • RANK Ligand • Solubility • Time Factors

Recent Publications   (More Publications)

1. Fridman, I; Chan, L; Thomas, J; Fish, LJ; Falkovic, M; Brioux, J; Hunter, N; Ryser, DH; Hwang, ES; Pollak, KI; Weinfurt, KP; Ryser, MD, A web-based personalized decision support tool for patients diagnosed with ductal carcinoma in situ: development, content evaluation, and usability testing., Breast Cancer Res Treat, vol. 192 no. 3 (April, 2022), pp. 517-527 [doi]  [abs]
2. Ryser, MD; Lange, J; Inoue, LYT; O'Meara, ES; Gard, C; Miglioretti, DL; Bulliard, J-L; Brouwer, AF; Hwang, ES; Etzioni, RB, Estimation of Breast Cancer Overdiagnosis in a U.S. Breast Screening Cohort., Ann Intern Med, vol. 175 no. 4 (April, 2022), pp. 471-478 [doi]  [abs]
3. Schapiro, D; Yapp, C; Sokolov, A; Reynolds, SM; Chen, Y-A; Sudar, D; Xie, Y; Muhlich, J; Arias-Camison, R; Arena, S; Taylor, AJ; Nikolov, M; Tyler, M; Lin, J-R; Burlingame, EA; Human Tumor Atlas Network, ; Chang, YH; Farhi, SL; Thorsson, V; Venkatamohan, N; Drewes, JL; Pe'er, D; Gutman, DA; Herrmann, MD; Gehlenborg, N; Bankhead, P; Roland, JT; Herndon, JM; Snyder, MP; Angelo, M; Nolan, G; Swedlow, JR; Schultz, N; Merrick, DT; Mazzili, SA; Cerami, E; Rodig, SJ; Santagata, S; Sorger, PK, MITI minimum information guidelines for highly multiplexed tissue images., Nat Methods, vol. 19 no. 3 (March, 2022), pp. 262-267 [doi]
4. Schmitz, RSJM; van den Belt-Dusebout, SW; Cresta, C; Liu, Y-H; Schaapveld, M; Clements, K; Timbres, J; Byng, DT; Ryser, MD; Ren, Y; Lynch, T; Hyslop, T; Menegaz, B; Collyar, D; Hwang, S; Thompson, A; Sawyer, E; Wesseling, J; Lips, EH; Schmidt, MK, Abstract P1-22-02: Subsequent risk of ipsilateral breast events in a multinational DCIS cohort of 48.619 patients: A meta-analysis within the PRECISION consortium, Cancer Research, vol. 82 no. 4_Supplement (February, 2022), American Association for Cancer Research (AACR) [doi]  [abs]
5. Grimm, LJ; Rahbar, H; Abdelmalak, M; Hall, AH; Ryser, MD, Ductal Carcinoma in Situ: State-of-the-Art Review., Radiology, vol. 302 no. 2 (February, 2022), pp. 246-255 [doi]  [abs]

Recent Grant Support

• Dynamic imaging and tissue biomarker models to delineate indolent from aggressive breast calcifications, National Institutes of Health, 2022/09-2027/08.      
• Modeling to Minimize Detection Bias in Cancer Risk Prediction Studies, Fred Hutchinson Cancer Center, 2022/04-2024/08.      
• Molecular and Radiologic Predictors of Invasion in a DCIS Active Surveillance Cohort, Breast Cancer Research Foundation, 2021/10-2023/09.      
• Comparative Modeling for the Prevention and Control of Uterine Cancer, Columbia University, 2021/09-2022/08.      
• The Mathematics of Breast Cancer Overtreatment: Improving Treatment Choice through Effective Communication of Personalized Cancer Risk, National Institutes of Health, 2018/09-2022/08.      
• Modeling to Minimize Detection Bias in Cancer Risk Prediction Studies, Fred Hutchinson Cancer Research Center, 2019/09-2022/03.      
• Molecular and Radiologic Predictors of Invasion in a DCIS Active Surveillance Cohort, Breast Cancer Research Foundation, 2020/10-2021/09.      
• Molecular and Radiologic Predictors of Invasion in a DCIS Active Surveillance Cohort, Breast Cancer Research Foundation, 2019/10-2020/09.      
• Mathematical Analysis of Spatial Cancer Models, National Science Foundation, 1614838, 2016/07-2020/06.