Development of multivariate NTCP models for radiation-induced hypothyroidism: a comparative analysis

Radiation Oncology

Roberto Pacelli¹  Marco Salvatore¹  Vittoria D’Avino²  Manuel Conson¹  Raffaele Liuzzi¹  Laura Cella¹ 

[1] Department of Diagnostic Imaging and Radiation Oncology, Federico II University School of Medicine, Naples, Italy;Institute of Biostructures and Bioimaging, National Council of Research (CNR), Naples, Italy

关键词: Bootstrapping;    Hypothyroidism;    Radiotherapy;    NTCP modeling;   

Others  :  1154855
DOI  :  10.1186/1748-717X-7-224

 received in 2012-10-25, accepted in 2012-12-20,  发布年份 2012

【 摘 要 】

Background

Hypothyroidism is a frequent late side effect of radiation therapy of the cervical region. Purpose of this work is to develop multivariate normal tissue complication probability (NTCP) models for radiation-induced hypothyroidism (RHT) and to compare them with already existing NTCP models for RHT.

Methods

Fifty-three patients treated with sequential chemo-radiotherapy for Hodgkin’s lymphoma (HL) were retrospectively reviewed for RHT events. Clinical information along with thyroid gland dose distribution parameters were collected and their correlation to RHT was analyzed by Spearman’s rank correlation coefficient (Rs). Multivariate logistic regression method using resampling methods (bootstrapping) was applied to select model order and parameters for NTCP modeling. Model performance was evaluated through the area under the receiver operating characteristic curve (AUC). Models were tested against external published data on RHT and compared with other published NTCP models.

Results

If we express the thyroid volume exceeding X Gy as a percentage (V_x(%)), a two-variable NTCP model including V₃₀(%) and gender resulted to be the optimal predictive model for RHT (Rs = 0.615, p < 0.001. AUC = 0.87). Conversely, if absolute thyroid volume exceeding X Gy (V_x(cc)) was analyzed, an NTCP model based on 3 variables including V₃₀(cc), thyroid gland volume and gender was selected as the most predictive model (Rs = 0.630, p < 0.001. AUC = 0.85). The three-variable model performs better when tested on an external cohort characterized by large inter-individuals variation in thyroid volumes (AUC = 0.914, 95% CI 0.760–0.984). A comparable performance was found between our model and that proposed in the literature based on thyroid gland mean dose and volume (p = 0.264).

Conclusions

The absolute volume of thyroid gland exceeding 30 Gy in combination with thyroid gland volume and gender provide an NTCP model for RHT with improved prediction capability not only within our patient population but also in an external cohort.

【 授权许可】

   
2012 Cella et al.; licensee BioMed Central Ltd.

【 图 表 】

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