TY - JOUR
T1 - A natural history model for planning prostate cancer testing
T2 - Calibration and validation using Swedish registry data
AU - Karlsson, Andreas
AU - Jauhiainen, Alexandra
AU - Gulati, Roman
AU - Eklund, Martin
AU - Grönberg, Henrik
AU - Etzioni, Ruth
AU - Clements, Mark
N1 - Funding Information:
The Swedish Research Council (MC: 2018-02526, ME: 2015-03292, 2017-00800, HG: 2017-00800), Cancerfonden (MC: CAN 2018/539, ME: CAN 2015/ 649, CAN 2015/1190, CAN 2018/741, HG: CAN 2018/750), the Swedish eScience Research Centre (MC), NordForsk (MC), Prostatacancerförbundet (MC) and National Cancer Institute (RG, RE: U01 CA199338; RG: R50 CA221836). Author AJ is a full time employee and shareholder of AstraZeneca. AstraZeneca provided support in the form of salary for author AJ, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The other funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.
Publisher Copyright:
© 2019 Karlsson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2019/2
Y1 - 2019/2
N2 - 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.
AB - 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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U2 - 10.1371/journal.pone.0211918
DO - 10.1371/journal.pone.0211918
M3 - Article
C2 - 30763406
AN - SCOPUS:85061481204
SN - 1932-6203
VL - 14
JO - PloS one
JF - PloS one
IS - 2
M1 - e0211918
ER -