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Complication Probability Models for Radiation-Induced Heart Valvular Dysfunction: Do Heart-Lung Interactions Play a Role?

PURPOSE: The purpose of this study is to compare different normal tissue complication probability (NTCP) models for predicting heart valve dysfunction (RVD) following thoracic irradiation. METHODS: All patients from our institutional Hodgkin lymphoma survivors database with analyzable datasets were...

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Autores principales: Cella, Laura, Palma, Giuseppe, Deasy, Joseph O., Oh, Jung Hun, Liuzzi, Raffaele, D’Avino, Vittoria, Conson, Manuel, Pugliese, Novella, Picardi, Marco, Salvatore, Marco, Pacelli, Roberto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4216137/
https://www.ncbi.nlm.nih.gov/pubmed/25360627
http://dx.doi.org/10.1371/journal.pone.0111753
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author Cella, Laura
Palma, Giuseppe
Deasy, Joseph O.
Oh, Jung Hun
Liuzzi, Raffaele
D’Avino, Vittoria
Conson, Manuel
Pugliese, Novella
Picardi, Marco
Salvatore, Marco
Pacelli, Roberto
author_facet Cella, Laura
Palma, Giuseppe
Deasy, Joseph O.
Oh, Jung Hun
Liuzzi, Raffaele
D’Avino, Vittoria
Conson, Manuel
Pugliese, Novella
Picardi, Marco
Salvatore, Marco
Pacelli, Roberto
author_sort Cella, Laura
collection PubMed
description PURPOSE: The purpose of this study is to compare different normal tissue complication probability (NTCP) models for predicting heart valve dysfunction (RVD) following thoracic irradiation. METHODS: All patients from our institutional Hodgkin lymphoma survivors database with analyzable datasets were included (n = 90). All patients were treated with three-dimensional conformal radiotherapy with a median total dose of 32 Gy. The cardiac toxicity profile was available for each patient. Heart and lung dose-volume histograms (DVHs) were extracted and both organs were considered for Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) NTCP model fitting using maximum likelihood estimation. Bootstrap refitting was used to test the robustness of the model fit. Model performance was estimated using the area under the receiver operating characteristic curve (AUC). RESULTS: Using only heart-DVHs, parameter estimates were, for the LKB model: D(50) = 32.8 Gy, n = 0.16 and m = 0.67; and for the RS model: D(50) = 32.4 Gy, s = 0.99 and γ = 0.42. AUC values were 0.67 for LKB and 0.66 for RS, respectively. Similar performance was obtained for models using only lung-DVHs (LKB: D(50) = 33.2 Gy, n = 0.01, m = 0.19, AUC = 0.68; RS: D(50) = 24.4 Gy, s = 0.99, γ = 2.12, AUC = 0.66). Bootstrap result showed that the parameter fits for lung-LKB were extremely robust. A combined heart-lung LKB model was also tested and showed a minor improvement (AUC = 0.70). However, the best performance was obtained using the previously determined multivariate regression model including maximum heart dose with increasing risk for larger heart and smaller lung volumes (AUC = 0.82). CONCLUSIONS: The risk of radiation induced valvular disease cannot be modeled using NTCP models only based on heart dose-volume distribution. A predictive model with an improved performance can be obtained but requires the inclusion of heart and lung volume terms, indicating that heart-lung interactions are apparently important for this endpoint.
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spelling pubmed-42161372014-11-05 Complication Probability Models for Radiation-Induced Heart Valvular Dysfunction: Do Heart-Lung Interactions Play a Role? Cella, Laura Palma, Giuseppe Deasy, Joseph O. Oh, Jung Hun Liuzzi, Raffaele D’Avino, Vittoria Conson, Manuel Pugliese, Novella Picardi, Marco Salvatore, Marco Pacelli, Roberto PLoS One Research Article PURPOSE: The purpose of this study is to compare different normal tissue complication probability (NTCP) models for predicting heart valve dysfunction (RVD) following thoracic irradiation. METHODS: All patients from our institutional Hodgkin lymphoma survivors database with analyzable datasets were included (n = 90). All patients were treated with three-dimensional conformal radiotherapy with a median total dose of 32 Gy. The cardiac toxicity profile was available for each patient. Heart and lung dose-volume histograms (DVHs) were extracted and both organs were considered for Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) NTCP model fitting using maximum likelihood estimation. Bootstrap refitting was used to test the robustness of the model fit. Model performance was estimated using the area under the receiver operating characteristic curve (AUC). RESULTS: Using only heart-DVHs, parameter estimates were, for the LKB model: D(50) = 32.8 Gy, n = 0.16 and m = 0.67; and for the RS model: D(50) = 32.4 Gy, s = 0.99 and γ = 0.42. AUC values were 0.67 for LKB and 0.66 for RS, respectively. Similar performance was obtained for models using only lung-DVHs (LKB: D(50) = 33.2 Gy, n = 0.01, m = 0.19, AUC = 0.68; RS: D(50) = 24.4 Gy, s = 0.99, γ = 2.12, AUC = 0.66). Bootstrap result showed that the parameter fits for lung-LKB were extremely robust. A combined heart-lung LKB model was also tested and showed a minor improvement (AUC = 0.70). However, the best performance was obtained using the previously determined multivariate regression model including maximum heart dose with increasing risk for larger heart and smaller lung volumes (AUC = 0.82). CONCLUSIONS: The risk of radiation induced valvular disease cannot be modeled using NTCP models only based on heart dose-volume distribution. A predictive model with an improved performance can be obtained but requires the inclusion of heart and lung volume terms, indicating that heart-lung interactions are apparently important for this endpoint. Public Library of Science 2014-10-31 /pmc/articles/PMC4216137/ /pubmed/25360627 http://dx.doi.org/10.1371/journal.pone.0111753 Text en © 2014 Cella 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Cella, Laura
Palma, Giuseppe
Deasy, Joseph O.
Oh, Jung Hun
Liuzzi, Raffaele
D’Avino, Vittoria
Conson, Manuel
Pugliese, Novella
Picardi, Marco
Salvatore, Marco
Pacelli, Roberto
Complication Probability Models for Radiation-Induced Heart Valvular Dysfunction: Do Heart-Lung Interactions Play a Role?
title Complication Probability Models for Radiation-Induced Heart Valvular Dysfunction: Do Heart-Lung Interactions Play a Role?
title_full Complication Probability Models for Radiation-Induced Heart Valvular Dysfunction: Do Heart-Lung Interactions Play a Role?
title_fullStr Complication Probability Models for Radiation-Induced Heart Valvular Dysfunction: Do Heart-Lung Interactions Play a Role?
title_full_unstemmed Complication Probability Models for Radiation-Induced Heart Valvular Dysfunction: Do Heart-Lung Interactions Play a Role?
title_short Complication Probability Models for Radiation-Induced Heart Valvular Dysfunction: Do Heart-Lung Interactions Play a Role?
title_sort complication probability models for radiation-induced heart valvular dysfunction: do heart-lung interactions play a role?
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4216137/
https://www.ncbi.nlm.nih.gov/pubmed/25360627
http://dx.doi.org/10.1371/journal.pone.0111753
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