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Purpose: To develop a multiple logistic regression model as normal tissue complication probability model by least absolute shrinkage and selection operator (LASSO) technique in breast cancer patients treated with three-dimensional conformal radiation therapy (3D-CRT), we focused on the changes of pulmonary function tests to achieve the optimal predictive parameters for the occurrence of symptomatic radiation pneumonitis (SRP). Materials and methods: Dosimetric and spirometry data of 60 breast cancer patients were analyzed. Pulmonary function tests were done before RT, after completion of RT, 3, and 6 months after RT. Multiple logistic regression model was used to obtain the effective predictive parameters. Forward selection method was applied in NTCP model to determine the effective risk factors from obtained different parameters. Results: Symptomatic radiation pneumonitis was observed in five patients. Significant changes in pulmonary parameters have been observed at six months after RT. The parameters of mean lung dose (MLD), bridge separation (BS), mean irradiated lung volume (ILVmean), and the percentage of the ipsilateral lung volume that received dose of 20 Gy (IV20) introduced as risk factors using the LASSO technique for SRP in a multiple normal tissue complication probability model in breast cancer patients treated with 3D-CRT. The BS, central lung distance (CLD) and ILV in tangential field have obtained as 23.5 (20.9-26.0) cm, 2.4 (1.5-3.3) cm, and 12.4 (10.6-14.3) % of lung volume in radiation field in patients without pulmonary complication, respectively. Conclusion: The results showed that if BS, CLD, and ILV are more than 23 cm, 2 cm, and 12%, respectively, so incidence of SRP in the patients will be considerable. Our multiple NTCP LASSO model for breast cancer patients treated with 3D-CRT showed that in order to have minimum probability of SRP occurrence, parameters of BS, IV20, ILV and especially MLD would be kept in minimum levels. Considering dose-volume histogram, the mean lung dose factor is most important parameter which minimizing it in treatment planning, minimizes the probability of SRP and consequently improves the quality of life in breast cancer patients.
Słowa kluczowe
Rocznik
Tom
Strony
149--156
Opis fizyczny
Bibliogr. 25 poz., rys., tab.
Twórcy
autor
- Student Research Committee, School of Medicine, Kermanshah University of Medical Sciences, Kermanshah, Iran
autor
- Department of Medical Physics, School of Medicine, Kermanshah University of Medical Sciences, Kermanshah, Iran
autor
- Department of Radiation Oncology, Mahdieh Radiotherapy and Oncology Charity Center, Hamedan, Iran
Bibliografia
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- [2] Lind PA, Wennberg B, Gagliardi G, Fornander T. Pulmonary complications following different radiotherapy techniques for breast cancer, and the association to irradiated lung volume and dose. Breast Cancer Res Treat. 2001;68(3):199-210.
- [3] Johansson S, Bjermer L, Franzen L, Henriksson R. Effects of ongoing smoking on the development of radiation-induced pneumonitis in breast cancer and oesophagus cancer patients. Radiother Oncol. 1998;49(1):41-47.
- [4] Fragkandrea I, Kouloulias V, Mavridis P, et al. Radiation induced pneumonitis following whole breast radiotherapy treatment in early breast cancer patients treated with breast conserving surgery: a single institution study. Hippokratia. 2013;17(3):233-238.
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- [6] Wang S, Liao Z, Wei X, et al. Analysis of clinical and dosimetric factors associated with treatment-related pneumonitis (TRP) in patients with non–small-cell lung cancer (NSCLC) treated with concurrent chemotherapy and three-dimensional conformal radiotherapy (3D-CRT). Int J Radiat Oncol Biol Phys. 2006;66(5):1399-1407.
- [7] Xu C-J, van der Schaaf A, Van't Veld AA, et al. Statistical validation of normal tissue complication probability models. Int J Radiat Oncol Biol Phys. 2012;84(1):e123-e129.
- [8] Xu C-J, van der Schaaf A, Schilstra C, et al. Impact of statistical learning methods on the predictive power of multivariate normal tissue complication probability models. Int J Radiat Oncol Biol Phys. 2012;82(4):e677-e584.
- [9] Lee T-F, Chao P-J, Chang L, et al. Developing multivariable normal tissue complication probability model to predict the incidence of symptomatic radiation pneumonitis among breast cancer patients. PloS one. 2015;10(7):e0131736.
- [10] Lee T-F, Liou M-H, Huang Y-J, et al. LASSO NTCP predictors for the incidence of xerostomia in patients with head and neck squamous cell carcinoma and nasopharyngeal carcinoma. Sci Rep. 2014;4:6217.
- [11] Khan FM, Gerbi BJ. Treatment planning in radiation oncology: Wolters Kluwer Health/Lippincott Williams & Wilkins; 2012.
- [12] Hasanabdali M, Khoshgard K, SedighiPashaki A, et al. Prediction of Lung Tissue Damage by Evaluating Clinical and Dosimetric Parameters in Breast Cancer Patients. J Mazandaran Univ Med Sci. 2016;26(142):40-49.
- [13] Sánchez-Nieto B, Goset KC, Caviedes I, et al. Predictive models for pulmonary function changes after radiotherapy for breast cancer and lymphoma. Int J Radiat Oncol Biol Phys. 2012;82(2):e257-e264.
- [14] Claude L, Pérol D, Ginestet C, et al. A prospective study on radiation pneumonitis following conformal radiation therapy in non-small-cell lung cancer: clinical and dosimetric factors analysis. Radiother Oncol. 2004;71(2):175-181.
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- [20] Hernberg M, Virkkunen P, Maasilta P, et al. Pulmonary toxicity after radiotherapy in primary breast cancer patients: results from a randomized chemotherapy study. Int J Radiat Oncol Biol Phys. 2002;52(1):128-136.
- [21] Jaén J, Vázquez G, Alonso E, et al. Changes in pulmonary function after incidental lung irradiation for breast cancer: A prospective study. Int J Radiat Oncol Biol Phys. 2006;65(5):1381-1388.
- [22] Skwarchuk MW, Jackson A, Zelefsky MJ, et al. Late rectal toxicity after conformal radiotherapy of prostate cancer (I): multivariate analysis and dose–response. Int J Radiat Oncol Biol Phys. 2000;47(1):103-113.
- [23] Svolos P, Tsougos I, Kyrgias G, et al. On the use of published radiobiological parameters and the evaluation of NTCP models regarding lung pneumonitis in clinical breast radiotherapy. Australas Phys Eng Sci Med. 2011;34(1):69-81.
- [24] Beetz I, Schilstra C, van Luijk P, et al. External validation of three dimensional conformal radiotherapy based NTCP models for patient-rated xerostomia and sticky saliva among patients treated with intensity modulated radiotherapy. Radiother Oncol. 2012;105(1):94-100.
- [25] Ling TC, Slater JM, Nookala P, et al. Analysis of intensity-modulated radiation therapy (IMRT), proton and 3D conformal radiotherapy (3D-CRT) for reducing perioperative cardiopulmonary complications in esophageal cancer patients. Cancers. 2014;6(4):2356-2368.
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Bibliografia
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bwmeta1.element.baztech-94327f22-2daa-4a24-8d03-c8ac8aa84784
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