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A natural history model for planning prostate cancer testing: Calibration and validation using Swedish registry data

Recent prostate cancer screening trials have given conflicting results and it is unclear how to reduce prostate cancer mortality while minimising overdiagnosis and overtreatment. Prostate cancer testing is a partially observable process, and planning for testing requires either extrapolation from ra...

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Autores principales: Karlsson, Andreas, Jauhiainen, Alexandra, Gulati, Roman, Eklund, Martin, Grönberg, Henrik, Etzioni, Ruth, Clements, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6375591/
https://www.ncbi.nlm.nih.gov/pubmed/30763406
http://dx.doi.org/10.1371/journal.pone.0211918
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author Karlsson, Andreas
Jauhiainen, Alexandra
Gulati, Roman
Eklund, Martin
Grönberg, Henrik
Etzioni, Ruth
Clements, Mark
author_facet Karlsson, Andreas
Jauhiainen, Alexandra
Gulati, Roman
Eklund, Martin
Grönberg, Henrik
Etzioni, Ruth
Clements, Mark
author_sort Karlsson, Andreas
collection PubMed
description Recent prostate cancer screening trials have given conflicting results and it is unclear how to reduce prostate cancer mortality while minimising overdiagnosis and overtreatment. Prostate cancer testing is a partially observable process, and planning for testing requires either extrapolation from randomised controlled trials or, more flexibly, modelling of the cancer natural history. An existing US prostate cancer natural history model (Gulati et al, Biostatistics 2010;11:707-719) did not model for differences in survival between Gleason 6 and 7 cancers and predicted too few Gleason 7 cancers for contemporary Sweden. We re-implemented and re-calibrated the US model to Sweden. We extended the model to more finely describe the disease states, their time to biopsy-detectable cancer and prostate cancer survival. We first calibrated the model to the incidence rate ratio observed in the European Randomised Study of Screening for Prostate Cancer (ERSPC) together with age-specific cancer staging observed in the Stockholm PSA (prostate-specific antigen) and Biopsy Register; we then calibrated age-specific survival by disease states under contemporary testing and treatment using the Swedish National Prostate Cancer Register. After calibration, we were able to closely match observed prostate cancer incidence trends in Sweden. Assuming that patients detected at an earlier stage by screening receive a commensurate survival improvement, we find that the calibrated model replicates the observed mortality reduction in a simulation of ERSPC. Using the resulting model, we predicted incidence and mortality following the introduction of regular testing. Compared with a model of the current testing pattern, organised 8 yearly testing for men aged 55–69 years was predicted to reduce prostate cancer incidence by 14% and increase prostate cancer mortality by 2%. The model is open source and suitable for planning for effective prostate cancer screening into the future.
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spelling pubmed-63755912019-03-01 A natural history model for planning prostate cancer testing: Calibration and validation using Swedish registry data Karlsson, Andreas Jauhiainen, Alexandra Gulati, Roman Eklund, Martin Grönberg, Henrik Etzioni, Ruth Clements, Mark PLoS One Research Article Recent prostate cancer screening trials have given conflicting results and it is unclear how to reduce prostate cancer mortality while minimising overdiagnosis and overtreatment. Prostate cancer testing is a partially observable process, and planning for testing requires either extrapolation from randomised controlled trials or, more flexibly, modelling of the cancer natural history. An existing US prostate cancer natural history model (Gulati et al, Biostatistics 2010;11:707-719) did not model for differences in survival between Gleason 6 and 7 cancers and predicted too few Gleason 7 cancers for contemporary Sweden. We re-implemented and re-calibrated the US model to Sweden. We extended the model to more finely describe the disease states, their time to biopsy-detectable cancer and prostate cancer survival. We first calibrated the model to the incidence rate ratio observed in the European Randomised Study of Screening for Prostate Cancer (ERSPC) together with age-specific cancer staging observed in the Stockholm PSA (prostate-specific antigen) and Biopsy Register; we then calibrated age-specific survival by disease states under contemporary testing and treatment using the Swedish National Prostate Cancer Register. After calibration, we were able to closely match observed prostate cancer incidence trends in Sweden. Assuming that patients detected at an earlier stage by screening receive a commensurate survival improvement, we find that the calibrated model replicates the observed mortality reduction in a simulation of ERSPC. Using the resulting model, we predicted incidence and mortality following the introduction of regular testing. Compared with a model of the current testing pattern, organised 8 yearly testing for men aged 55–69 years was predicted to reduce prostate cancer incidence by 14% and increase prostate cancer mortality by 2%. The model is open source and suitable for planning for effective prostate cancer screening into the future. Public Library of Science 2019-02-14 /pmc/articles/PMC6375591/ /pubmed/30763406 http://dx.doi.org/10.1371/journal.pone.0211918 Text en © 2019 Karlsson et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Karlsson, Andreas
Jauhiainen, Alexandra
Gulati, Roman
Eklund, Martin
Grönberg, Henrik
Etzioni, Ruth
Clements, Mark
A natural history model for planning prostate cancer testing: Calibration and validation using Swedish registry data
title A natural history model for planning prostate cancer testing: Calibration and validation using Swedish registry data
title_full A natural history model for planning prostate cancer testing: Calibration and validation using Swedish registry data
title_fullStr A natural history model for planning prostate cancer testing: Calibration and validation using Swedish registry data
title_full_unstemmed A natural history model for planning prostate cancer testing: Calibration and validation using Swedish registry data
title_short A natural history model for planning prostate cancer testing: Calibration and validation using Swedish registry data
title_sort natural history model for planning prostate cancer testing: calibration and validation using swedish registry data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6375591/
https://www.ncbi.nlm.nih.gov/pubmed/30763406
http://dx.doi.org/10.1371/journal.pone.0211918
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