Fitting NTCP models to bladder doses and acute urinary symptoms during post-prostatectomy radiotherapy Public Deposited

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Creator
  • Pearlstein, Kevin A
    • Affiliation: School of Medicine, Department of Radiation Oncology
  • Dooley, John
    • Affiliation: School of Medicine, Department of Radiation Oncology
  • Wang, Andrew
    • Affiliation: School of Medicine, Department of Radiation Oncology
  • Das, Shiva K
    • Affiliation: School of Medicine, Department of Radiation Oncology
  • Mavroidis, Panayiotis
    • Affiliation: School of Medicine, Department of Radiation Oncology
  • Saripalli, Srinivas
    • Affiliation: School of Medicine, Department of Radiation Oncology
  • Sun, Jasmine
    • Affiliation: School of Medicine, Department of Radiation Oncology
  • Chen, Ronald
    • Affiliation: School of Medicine, Department of Radiation Oncology
Abstract
  • Abstract Background To estimate the radiobiological parameters of three popular normal tissue complication probability (NTCP) models, which describe the dose-response relations of bladder regarding different acute urinary symptoms during post-prostatectomy radiotherapy (RT). To evaluate the goodness-of-fit and the correlation of those models with those symptoms. Methods Ninety-three consecutive patients treated from 2010 to 2015 with post-prostatectomy image-guided intensity modulated radiotherapy (IMRT) were included in this study. Patient-reported urinary symptoms were collected pre-RT and weekly during treatment using the validated Prostate Cancer Symptom Indices (PCSI). The assessed symptoms were flow, dysuria, urgency, incontinence, frequency and nocturia using a Likert scale of 1 to 4 or 5. For this analysis, an increase by ≥2 levels in a symptom at any time during treatment compared to baseline was considered clinically significant. The dose volume histograms of the bladder were calculated. The Lyman-Kutcher-Burman (LKB), Relative Seriality (RS) and Logit NTCP models were used to fit the clinical data. The fitting of the different models was assessed through the area under the receiver operating characteristic curve (AUC), Akaike information criterion (AIC) and Odds Ratio methods. Results For the symptoms of urinary urgency, leakage, frequency and nocturia, the derived LKB model parameters were: 1) D50 = 64.2Gy, m = 0.50, n = 1.0; 2) D50 = 95.0Gy, m = 0.45, n = 0.50; 3) D50 = 83.1Gy, m = 0.56, n = 1.00; and 4) D50 = 85.4Gy, m = 0.60, n = 1.00, respectively. The AUC values for those symptoms were 0.66, 0.58, 0.64 and 0.64, respectively. The differences in AIC between the different models were less than 2 and ranged within 0.1 and 1.3. Conclusions Different dose metrics were correlated with the symptoms of urgency, incontinence, frequency and nocturia. The symptoms of urinary flow and dysuria were poorly associated with dose. The values of the parameters of three NTCP models were determined for bladder regarding four acute urinary symptoms. All the models could fit the clinical data equally well. The NTCP predictions of urgency showed the best correlation with the patient reported outcomes.
Date of publication
Identifier
  • doi:10.1186/s13014-018-0961-x
Resource type
  • Article
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  • In Copyright
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  • The Author(s).
Language
  • English
Bibliographic citation
  • Radiation Oncology. 2018 Feb 02;13(1):17
Publisher
  • BioMed Central
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