Modeling Early-Onset Cancer Kinetics Reveals Changes in Underlying Risk and the Impact of Population Screening
A model of early-onset cancer trends that distinguishes true risk from detection effects accurately captures cancer kinetics, trends in cancer progression, and the impact of screening, which could inform cancer prevention strategies. This article is part of a special series: Driving Cancer Discoveries with Computational Research, Data Science, and Machine Learning/AI .
Authors
- Piero Dalerba (ORCID: https://orcid.org/0000-0002-8815-4981)
- Navid Mohammad Mirzaei (ORCID: https://orcid.org/0000-0002-0971-0514)
- Chin Hur (ORCID: https://orcid.org/0000-0002-2819-7576)
- Wan Yang (ORCID: https://orcid.org/0000-0002-7555-9728)
- Mary Beth Terry (ORCID: https://orcid.org/0000-0002-4106-5033)
Institutions
- Georgetown University (US)
- Columbia University Irving Medical Center (US)
- Silent Spring Institute (US)
- Hackensack Meridian Health (US)
- Center for Discovery (US)
- Columbia University (US)
Publication Details
- Journal
- Cancer Research
- Published
- 2025-08-29
- DOI
- https://doi.org/10.1158/0008-5472.can-25-0186
- Citations
- 3
- Primary Topic
- Health, Environment, Cognitive Aging
- Type
- article
- Field-Weighted Citation Impact
- 3.60