Abstract
A series of distinct histologic lesions precedes the onset of malignancy in many common cancers, yet early detection remains a major challenge. Many patients still experience late (stage IV) diagnoses and thus poor prognosis and limited options for therapeutic intervention. For cancers with known biomarkers of premalignant progression, optimized patient-specific screening protocols would minimize the risk of undetected progression to advanced stage disease. Here, we propose simple, cost-effective mathematical and statistical approaches to forecasting disease progression that could guide the personalization of optimal screening times for high-risk patients.
Footnotes
This work was supported in part by a Moffitt Cancer Center pilot award to the winning team of the 4th Moffitt IMO workshop on Viruses and Cancer. We would like to thank Drs. Alexander R. A. Anderson and Tom Sellers for the organization and support of the workshop. RW is also partially supported by a K05 award.
↵* (e-mail: heiko.enderling{at}moffitt.org).