The detection of prostate cancer recurrence after external beam radiotherapy relies on the measurement of a sustained rise of serum prostate-specific antigen (PSA). However, this biochemical relapse may take years to occur, thereby delaying the delivery of a secondary treatment to patients with recurring tumors. To address this issue, we propose to use patient-specific forecasts of PSA dynamics to predict biochemical relapse earlier. Our forecasts are based on a mechanistic model of prostate cancer response to external beam radiotherapy, which is fit to patient-specific PSA data collected during standard posttreatment monitoring. Our results show a remarkable performance of our model in recapitulating the observed changes in PSA and yielding short-term predictions over approximately 1 year (cohort median root mean squared error of 0.10-0.47 ng/mL and 0.13 to 1.39 ng/mL, respectively). Additionally, we identify 3 model-based biomarkers that enable accurate identification of biochemical relapse (area under the receiver operating characteristic curve > 0.80) significantly earlier than standard practice (p < 0.01).
iScience. 2022 Oct 25*** epublish ***
Guillermo Lorenzo, Nadia di Muzio, Chiara Lucrezia Deantoni, Cesare Cozzarini, Andrei Fodor, Alberto Briganti, Francesco Montorsi, Víctor M Pérez-García, Hector Gomez, Alessandro Reali
Department of Civil Engineering and Architecture, University of Pavia, via Ferrata 3, 27100 Pavia, Italy., Department of Radiation Oncology, IRCCS San Raffaele Hospital and Scientific Institute, via Olgettina 60, 20132 Milan, Italy., Vita-Salute San Raffaele University, via Olgettina 58, 20132 Milan, Italy., Mathematical Oncology Laboratory, University of Castilla-La Mancha, Edificio Politécnico, Avenida Camilo José Cela 3, 13071 Ciudad Real, Spain., School of Mechanical Engineering, Purdue University, 585 Purdue Mall, West Lafayette, IN 47907, USA.