External Validation of a Predictive Model of Urethral Strictures for Prostate Patients Treated With HDR Brachytherapy Boost
Purpose: For prostate cancer treatment, comparable or superior biochemical control was reported when using External-Beam-Radiotherapy (EBRT) with High-Dose-Rate-Brachytherapy (HDRB)-boost, compared to dose-escalation with EBRT alone. The conformal doses produced by HDRB could allow further beneficia...
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Frontiers Media S.A.
2020-06-01
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Series: | Frontiers in Oncology |
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Online Access: | https://www.frontiersin.org/article/10.3389/fonc.2020.00910/full |
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record_format |
Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Vanessa Panettieri Vanessa Panettieri Tiziana Rancati Eva Onjukka Martin A. Ebert Martin A. Ebert Martin A. Ebert David J. Joseph David J. Joseph David J. Joseph James W. Denham Allison Steigler Jeremy L. Millar Jeremy L. Millar |
spellingShingle |
Vanessa Panettieri Vanessa Panettieri Tiziana Rancati Eva Onjukka Martin A. Ebert Martin A. Ebert Martin A. Ebert David J. Joseph David J. Joseph David J. Joseph James W. Denham Allison Steigler Jeremy L. Millar Jeremy L. Millar External Validation of a Predictive Model of Urethral Strictures for Prostate Patients Treated With HDR Brachytherapy Boost Frontiers in Oncology NTCP HDR brachytherapy urethra predictive modeling prostate cancer |
author_facet |
Vanessa Panettieri Vanessa Panettieri Tiziana Rancati Eva Onjukka Martin A. Ebert Martin A. Ebert Martin A. Ebert David J. Joseph David J. Joseph David J. Joseph James W. Denham Allison Steigler Jeremy L. Millar Jeremy L. Millar |
author_sort |
Vanessa Panettieri |
title |
External Validation of a Predictive Model of Urethral Strictures for Prostate Patients Treated With HDR Brachytherapy Boost |
title_short |
External Validation of a Predictive Model of Urethral Strictures for Prostate Patients Treated With HDR Brachytherapy Boost |
title_full |
External Validation of a Predictive Model of Urethral Strictures for Prostate Patients Treated With HDR Brachytherapy Boost |
title_fullStr |
External Validation of a Predictive Model of Urethral Strictures for Prostate Patients Treated With HDR Brachytherapy Boost |
title_full_unstemmed |
External Validation of a Predictive Model of Urethral Strictures for Prostate Patients Treated With HDR Brachytherapy Boost |
title_sort |
external validation of a predictive model of urethral strictures for prostate patients treated with hdr brachytherapy boost |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Oncology |
issn |
2234-943X |
publishDate |
2020-06-01 |
description |
Purpose: For prostate cancer treatment, comparable or superior biochemical control was reported when using External-Beam-Radiotherapy (EBRT) with High-Dose-Rate-Brachytherapy (HDRB)-boost, compared to dose-escalation with EBRT alone. The conformal doses produced by HDRB could allow further beneficial prostate dose-escalation, but increase in dose is limited by normal tissue toxicity. Previous works showed correlation between urethral dose and incidence of urinary toxicity, but there is a lack of established guidelines on the dose constraints to this organ. This work aimed at fitting a Normal-Tissue-Complication-Probability model to urethral stricture data collected at one institution and validating it with an external cohort, looking at neo-adjuvant androgen deprivation as dose-modifying factor.Materials and Methods: Clinical and dosimetric data of 258 patients, with a toxicity rate of 12.8%, treated at a single institution with a variety of prescription doses, were collected to fit the Lyman–Kutcher–Burman (LKB) model using the maximum likelihood method. Due to the different fractionations, doses were converted into 2 Gy-equivalent doses (α/β = 5 Gy), and urethral stricture was used as an end-point. For validation, an external cohort of 187 patients treated as part of the TROG (Trans Tasman Radiation Oncology Group) 03.04 RADAR trial with a toxicity rate of 8.7%, was used. The goodness of fit was assessed using calibration plots. The effect of neo-adjuvant androgen deprivation (AD) was analyzed separating patients who had received it prior to treatment from those who did not receive it.Results: The obtained LKB parameters were TD50 = 116.7 Gy and m = 0.23; n was fixed to 0.3, based on numerical optimization of the likelihood. The calibration plot showed a good agreement between the observed toxicity and the probability predicted by the model, confirmed by bootstrapping. For the external validation, the calibration plot showed that the observed toxicity obtained with the RADAR patients was well-represented by the fitted LKB model parameters. When patients were stratified by the use of AD TD50 decreased when AD was not present.Conclusions: Lyman–Kutcher–Burman model parameters were fitted to the risk of urethral stricture and externally validated with an independent cohort, to provide guidance on urethral tolerance doses for patients treated with a HDRB boost. For patients that did not receive AD, model fitting provided a lower TD50 suggesting a protective effect on urethra toxicity. |
topic |
NTCP HDR brachytherapy urethra predictive modeling prostate cancer |
url |
https://www.frontiersin.org/article/10.3389/fonc.2020.00910/full |
work_keys_str_mv |
AT vanessapanettieri externalvalidationofapredictivemodelofurethralstricturesforprostatepatientstreatedwithhdrbrachytherapyboost AT vanessapanettieri externalvalidationofapredictivemodelofurethralstricturesforprostatepatientstreatedwithhdrbrachytherapyboost AT tizianarancati externalvalidationofapredictivemodelofurethralstricturesforprostatepatientstreatedwithhdrbrachytherapyboost AT evaonjukka externalvalidationofapredictivemodelofurethralstricturesforprostatepatientstreatedwithhdrbrachytherapyboost AT martinaebert externalvalidationofapredictivemodelofurethralstricturesforprostatepatientstreatedwithhdrbrachytherapyboost AT martinaebert externalvalidationofapredictivemodelofurethralstricturesforprostatepatientstreatedwithhdrbrachytherapyboost AT martinaebert externalvalidationofapredictivemodelofurethralstricturesforprostatepatientstreatedwithhdrbrachytherapyboost AT davidjjoseph externalvalidationofapredictivemodelofurethralstricturesforprostatepatientstreatedwithhdrbrachytherapyboost AT davidjjoseph externalvalidationofapredictivemodelofurethralstricturesforprostatepatientstreatedwithhdrbrachytherapyboost AT davidjjoseph externalvalidationofapredictivemodelofurethralstricturesforprostatepatientstreatedwithhdrbrachytherapyboost AT jameswdenham externalvalidationofapredictivemodelofurethralstricturesforprostatepatientstreatedwithhdrbrachytherapyboost AT allisonsteigler externalvalidationofapredictivemodelofurethralstricturesforprostatepatientstreatedwithhdrbrachytherapyboost AT jeremylmillar externalvalidationofapredictivemodelofurethralstricturesforprostatepatientstreatedwithhdrbrachytherapyboost AT jeremylmillar externalvalidationofapredictivemodelofurethralstricturesforprostatepatientstreatedwithhdrbrachytherapyboost |
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doaj-e1e8f180812843f39d0800c589f5b3e02020-11-25T03:23:08ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2020-06-011010.3389/fonc.2020.00910527027External Validation of a Predictive Model of Urethral Strictures for Prostate Patients Treated With HDR Brachytherapy BoostVanessa Panettieri0Vanessa Panettieri1Tiziana Rancati2Eva Onjukka3Martin A. Ebert4Martin A. Ebert5Martin A. Ebert6David J. Joseph7David J. Joseph8David J. Joseph9James W. Denham10Allison Steigler11Jeremy L. Millar12Jeremy L. Millar13Alfred Health Radiation Oncology, Alfred Hospital, Melbourne, VIC, AustraliaMedical Imaging and Radiation Sciences, Monash University, Clayton, VIC, AustraliaProstate Cancer Program, Scientific Directorate, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, ItalyMedical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, SwedenRadiation Oncology, Sir Charles Gairdner Hospital, Perth, WA, AustraliaSchool of Physics, Mathematics and Computing, University of Western Australia, Perth, WA, Australia5D Clinics, Claremont, WA, Australia5D Clinics, Claremont, WA, AustraliaGenesisCare, Subiaco, WA, AustraliaSchool of Surgery, University of Western Australia, WA, Australia0School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, Australia0School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, AustraliaAlfred Health Radiation Oncology, Alfred Hospital, Melbourne, VIC, Australia1Central Clinical School, Monash University, Melbourne, VIC, AustraliaPurpose: For prostate cancer treatment, comparable or superior biochemical control was reported when using External-Beam-Radiotherapy (EBRT) with High-Dose-Rate-Brachytherapy (HDRB)-boost, compared to dose-escalation with EBRT alone. The conformal doses produced by HDRB could allow further beneficial prostate dose-escalation, but increase in dose is limited by normal tissue toxicity. Previous works showed correlation between urethral dose and incidence of urinary toxicity, but there is a lack of established guidelines on the dose constraints to this organ. This work aimed at fitting a Normal-Tissue-Complication-Probability model to urethral stricture data collected at one institution and validating it with an external cohort, looking at neo-adjuvant androgen deprivation as dose-modifying factor.Materials and Methods: Clinical and dosimetric data of 258 patients, with a toxicity rate of 12.8%, treated at a single institution with a variety of prescription doses, were collected to fit the Lyman–Kutcher–Burman (LKB) model using the maximum likelihood method. Due to the different fractionations, doses were converted into 2 Gy-equivalent doses (α/β = 5 Gy), and urethral stricture was used as an end-point. For validation, an external cohort of 187 patients treated as part of the TROG (Trans Tasman Radiation Oncology Group) 03.04 RADAR trial with a toxicity rate of 8.7%, was used. The goodness of fit was assessed using calibration plots. The effect of neo-adjuvant androgen deprivation (AD) was analyzed separating patients who had received it prior to treatment from those who did not receive it.Results: The obtained LKB parameters were TD50 = 116.7 Gy and m = 0.23; n was fixed to 0.3, based on numerical optimization of the likelihood. The calibration plot showed a good agreement between the observed toxicity and the probability predicted by the model, confirmed by bootstrapping. For the external validation, the calibration plot showed that the observed toxicity obtained with the RADAR patients was well-represented by the fitted LKB model parameters. When patients were stratified by the use of AD TD50 decreased when AD was not present.Conclusions: Lyman–Kutcher–Burman model parameters were fitted to the risk of urethral stricture and externally validated with an independent cohort, to provide guidance on urethral tolerance doses for patients treated with a HDRB boost. For patients that did not receive AD, model fitting provided a lower TD50 suggesting a protective effect on urethra toxicity.https://www.frontiersin.org/article/10.3389/fonc.2020.00910/fullNTCPHDR brachytherapyurethrapredictive modelingprostate cancer |