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Complication probability models for radiation-induced heart valvular dysfunction: do heart-lung interactions play a role?

Cella L, Palma G, Deasy JO, Oh JH, Liuzzi R, D'Avino V, Conson M, Pugliese N, Picardi M, Salvatore M, Pacelli R - PLoS ONE (2014)

Bottom Line: 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).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.

View Article: PubMed Central - PubMed

Affiliation: Institute of Biostructure and Bioimaging, National Council of Research (CNR), Naples, Italy; Department of Advanced Biomedical Sciences, Federico II University School of Medicine, Naples, Italy.

ABSTRACT

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: D50 = 32.8 Gy, n = 0.16 and m = 0.67; and for the RS model: D50 = 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: D50 = 33.2 Gy, n = 0.01, m = 0.19, AUC = 0.68; RS: D50 = 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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Comparison between the actuarial incidence of radiation-related valvular defects (RVD) in the population and the predicted incidence by each NTCP model.a) heart LKB, b) heart RS, c) lung LKB, d) lung RS, e) three-variable logistic model. Patients were binned according to the considered NTCP model with equal number of patients in each bin. Abbreviation- LKB: Lyman-Kutcher-Burman, RS: Relative Seriality, NTCP: Normal Tissue Complication Probability.
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pone-0111753-g005: Comparison between the actuarial incidence of radiation-related valvular defects (RVD) in the population and the predicted incidence by each NTCP model.a) heart LKB, b) heart RS, c) lung LKB, d) lung RS, e) three-variable logistic model. Patients were binned according to the considered NTCP model with equal number of patients in each bin. Abbreviation- LKB: Lyman-Kutcher-Burman, RS: Relative Seriality, NTCP: Normal Tissue Complication Probability.

Mentions: The comparison between the predicted incidence of RVD by each NTCP model and the actuarial incidence in the population is shown in figure 5.


Complication probability models for radiation-induced heart valvular dysfunction: do heart-lung interactions play a role?

Cella L, Palma G, Deasy JO, Oh JH, Liuzzi R, D'Avino V, Conson M, Pugliese N, Picardi M, Salvatore M, Pacelli R - PLoS ONE (2014)

Comparison between the actuarial incidence of radiation-related valvular defects (RVD) in the population and the predicted incidence by each NTCP model.a) heart LKB, b) heart RS, c) lung LKB, d) lung RS, e) three-variable logistic model. Patients were binned according to the considered NTCP model with equal number of patients in each bin. Abbreviation- LKB: Lyman-Kutcher-Burman, RS: Relative Seriality, NTCP: Normal Tissue Complication Probability.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4216137&req=5

pone-0111753-g005: Comparison between the actuarial incidence of radiation-related valvular defects (RVD) in the population and the predicted incidence by each NTCP model.a) heart LKB, b) heart RS, c) lung LKB, d) lung RS, e) three-variable logistic model. Patients were binned according to the considered NTCP model with equal number of patients in each bin. Abbreviation- LKB: Lyman-Kutcher-Burman, RS: Relative Seriality, NTCP: Normal Tissue Complication Probability.
Mentions: The comparison between the predicted incidence of RVD by each NTCP model and the actuarial incidence in the population is shown in figure 5.

Bottom Line: 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).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.

View Article: PubMed Central - PubMed

Affiliation: Institute of Biostructure and Bioimaging, National Council of Research (CNR), Naples, Italy; Department of Advanced Biomedical Sciences, Federico II University School of Medicine, Naples, Italy.

ABSTRACT

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: D50 = 32.8 Gy, n = 0.16 and m = 0.67; and for the RS model: D50 = 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: D50 = 33.2 Gy, n = 0.01, m = 0.19, AUC = 0.68; RS: D50 = 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.

Show MeSH
Related in: MedlinePlus