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Patient-specific forecasting of postradiotherapy prostate-specific antigen kinetics enables early prediction of biochemical relapse
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 recu...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9641236/ https://www.ncbi.nlm.nih.gov/pubmed/36388979 http://dx.doi.org/10.1016/j.isci.2022.105430 |
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author | Lorenzo, Guillermo di Muzio, Nadia Deantoni, Chiara Lucrezia Cozzarini, Cesare Fodor, Andrei Briganti, Alberto Montorsi, Francesco Pérez-García, Víctor M. Gomez, Hector Reali, Alessandro |
author_facet | Lorenzo, Guillermo di Muzio, Nadia Deantoni, Chiara Lucrezia Cozzarini, Cesare Fodor, Andrei Briganti, Alberto Montorsi, Francesco Pérez-García, Víctor M. Gomez, Hector Reali, Alessandro |
author_sort | Lorenzo, Guillermo |
collection | PubMed |
description | 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). |
format | Online Article Text |
id | pubmed-9641236 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-96412362022-11-15 Patient-specific forecasting of postradiotherapy prostate-specific antigen kinetics enables early prediction of biochemical relapse Lorenzo, Guillermo di Muzio, Nadia Deantoni, Chiara Lucrezia Cozzarini, Cesare Fodor, Andrei Briganti, Alberto Montorsi, Francesco Pérez-García, Víctor M. Gomez, Hector Reali, Alessandro iScience Article 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). Elsevier 2022-10-25 /pmc/articles/PMC9641236/ /pubmed/36388979 http://dx.doi.org/10.1016/j.isci.2022.105430 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Lorenzo, Guillermo di Muzio, Nadia Deantoni, Chiara Lucrezia Cozzarini, Cesare Fodor, Andrei Briganti, Alberto Montorsi, Francesco Pérez-García, Víctor M. Gomez, Hector Reali, Alessandro Patient-specific forecasting of postradiotherapy prostate-specific antigen kinetics enables early prediction of biochemical relapse |
title | Patient-specific forecasting of postradiotherapy prostate-specific antigen kinetics enables early prediction of biochemical relapse |
title_full | Patient-specific forecasting of postradiotherapy prostate-specific antigen kinetics enables early prediction of biochemical relapse |
title_fullStr | Patient-specific forecasting of postradiotherapy prostate-specific antigen kinetics enables early prediction of biochemical relapse |
title_full_unstemmed | Patient-specific forecasting of postradiotherapy prostate-specific antigen kinetics enables early prediction of biochemical relapse |
title_short | Patient-specific forecasting of postradiotherapy prostate-specific antigen kinetics enables early prediction of biochemical relapse |
title_sort | patient-specific forecasting of postradiotherapy prostate-specific antigen kinetics enables early prediction of biochemical relapse |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9641236/ https://www.ncbi.nlm.nih.gov/pubmed/36388979 http://dx.doi.org/10.1016/j.isci.2022.105430 |
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