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Predicting post-radiation genitourinary hospital admissions in patients with localised prostate cancer

PURPOSE: The risk of treatment-related toxicity is important for patients with localised prostate cancer to consider when deciding between treatment options. We developed a model to predict hospitalisation for radiation-induced genitourinary toxicity based on patient characteristics. METHODS: The pr...

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Autores principales: David, Rowan, Hiwase, Mrunal, Kahokehr, Arman A., Lee, Jason, Watson, David I., Leung, John, O‘Callaghan, Michael E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9712379/
https://www.ncbi.nlm.nih.gov/pubmed/36357601
http://dx.doi.org/10.1007/s00345-022-04212-y
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author David, Rowan
Hiwase, Mrunal
Kahokehr, Arman A.
Lee, Jason
Watson, David I.
Leung, John
O‘Callaghan, Michael E.
author_facet David, Rowan
Hiwase, Mrunal
Kahokehr, Arman A.
Lee, Jason
Watson, David I.
Leung, John
O‘Callaghan, Michael E.
author_sort David, Rowan
collection PubMed
description PURPOSE: The risk of treatment-related toxicity is important for patients with localised prostate cancer to consider when deciding between treatment options. We developed a model to predict hospitalisation for radiation-induced genitourinary toxicity based on patient characteristics. METHODS: The prospective South Australian Prostate Cancer Clinical Outcomes registry was used to identify men with localised prostate cancer who underwent curative intent external beam radiotherapy (EBRT) between 1998 and 2019. Multivariable Cox proportional regression was performed. Model discrimination, calibration, internal validation and utility were assessed using C-statistics and area under ROC, calibration plots, bootstrapping, and decision curve analysis, respectively. RESULTS: There were 3,243 patients treated with EBRT included, of which 644 (20%) patients had a treated-related admission. In multivariable analysis, diabetes (HR 1.35, 95% CI 1.13–1.60, p < 0.001), smoking (HR 1.78, 95% CI 1.40–2.12, p < 0.001), and bladder outlet obstruction (BOO) without transurethral resection of prostate (TURP) (HR 7.49, 95% CI 6.18–9.08 p < 0.001) followed by BOO with TURP (HR 4.96, 95% CI 4.10–5.99 p < 0.001) were strong independent predictors of hospitalisation (censor-adjusted c-statistic = 0.80). The model was well-calibrated (AUC = 0.76). The global proportional hazards were met. In internal validation through bootstrapping, the model was reasonably discriminate at five (AUC 0.75) years after radiotherapy. CONCLUSIONS: This is the first study to develop a predictive model for genitourinary toxicity requiring hospitalisation amongst men with prostate cancer treated with EBRT. Patients with localised prostate cancer and concurrent BOO may benefit from TURP before EBRT. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00345-022-04212-y.
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spelling pubmed-97123792022-12-02 Predicting post-radiation genitourinary hospital admissions in patients with localised prostate cancer David, Rowan Hiwase, Mrunal Kahokehr, Arman A. Lee, Jason Watson, David I. Leung, John O‘Callaghan, Michael E. World J Urol Original Article PURPOSE: The risk of treatment-related toxicity is important for patients with localised prostate cancer to consider when deciding between treatment options. We developed a model to predict hospitalisation for radiation-induced genitourinary toxicity based on patient characteristics. METHODS: The prospective South Australian Prostate Cancer Clinical Outcomes registry was used to identify men with localised prostate cancer who underwent curative intent external beam radiotherapy (EBRT) between 1998 and 2019. Multivariable Cox proportional regression was performed. Model discrimination, calibration, internal validation and utility were assessed using C-statistics and area under ROC, calibration plots, bootstrapping, and decision curve analysis, respectively. RESULTS: There were 3,243 patients treated with EBRT included, of which 644 (20%) patients had a treated-related admission. In multivariable analysis, diabetes (HR 1.35, 95% CI 1.13–1.60, p < 0.001), smoking (HR 1.78, 95% CI 1.40–2.12, p < 0.001), and bladder outlet obstruction (BOO) without transurethral resection of prostate (TURP) (HR 7.49, 95% CI 6.18–9.08 p < 0.001) followed by BOO with TURP (HR 4.96, 95% CI 4.10–5.99 p < 0.001) were strong independent predictors of hospitalisation (censor-adjusted c-statistic = 0.80). The model was well-calibrated (AUC = 0.76). The global proportional hazards were met. In internal validation through bootstrapping, the model was reasonably discriminate at five (AUC 0.75) years after radiotherapy. CONCLUSIONS: This is the first study to develop a predictive model for genitourinary toxicity requiring hospitalisation amongst men with prostate cancer treated with EBRT. Patients with localised prostate cancer and concurrent BOO may benefit from TURP before EBRT. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00345-022-04212-y. Springer Berlin Heidelberg 2022-11-10 2022 /pmc/articles/PMC9712379/ /pubmed/36357601 http://dx.doi.org/10.1007/s00345-022-04212-y Text en © Crown 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
David, Rowan
Hiwase, Mrunal
Kahokehr, Arman A.
Lee, Jason
Watson, David I.
Leung, John
O‘Callaghan, Michael E.
Predicting post-radiation genitourinary hospital admissions in patients with localised prostate cancer
title Predicting post-radiation genitourinary hospital admissions in patients with localised prostate cancer
title_full Predicting post-radiation genitourinary hospital admissions in patients with localised prostate cancer
title_fullStr Predicting post-radiation genitourinary hospital admissions in patients with localised prostate cancer
title_full_unstemmed Predicting post-radiation genitourinary hospital admissions in patients with localised prostate cancer
title_short Predicting post-radiation genitourinary hospital admissions in patients with localised prostate cancer
title_sort predicting post-radiation genitourinary hospital admissions in patients with localised prostate cancer
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9712379/
https://www.ncbi.nlm.nih.gov/pubmed/36357601
http://dx.doi.org/10.1007/s00345-022-04212-y
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