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August-2016 Volume 12 Issue 2

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International Journal of Molecular Medicine

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Experimental and Therapeutic Medicine is an international journal devoted to laboratory and clinical medicine.

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Oncology Letters is an international journal devoted to Experimental and Clinical Oncology.

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Article

Validation and optimization of a predictive model for radiation pneumonitis in patients with lung cancer

  • Authors:
    • Charlott Mörth
    • Ioannis Kafantaris
    • Markus Castegren
    • Antonios Valachis
  • View Affiliations / Copyright

    Affiliations: Centre for Clinical Research Sörmland, Uppsala University, SE‑631 88 Eskilstuna, Sweden, Department of Pulmonary Medicine, Mälarsjukhuset, SE‑631 88 Eskilstuna, Sweden
  • Pages: 1144-1148
    |
    Published online on: June 6, 2016
       https://doi.org/10.3892/ol.2016.4678
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Abstract

The aim of the current retrospective study was to validate a predictive model for radiation pneumonitis (STRIPE) in an independent dataset and to investigate whether the addition of other potential risk factors could strengthen the accuracy of the model. Consecutive patients with non‑small cell lung carcinoma (NSCLC; n=71) treated with definitive concurrent chemotherapy and radiotherapy were retrospectively assessed for radiation pneumonitis (RP). The results identified that 16 (23%) patients developed grade ≥2 RP. Furthermore, STRIPE score (intermediate vs. low risk) was independently associated with the development of RP [odds ratio (OR), 3.72; 95% confidence interval (CI), 1.00‑13.89], whereas current smoking status was found to be protective against RP (OR, 0.09; 95% CI, 0.01‑0.78). Similar discriminatory power of the STRIPE score was observed as in the original study. The addition of smoking status strengthened the model's discriminatory ability to predict RP. Thus, the addition of smoking status as a risk factor may strengthen the accuracy of the model for predicting RP in patients with NSCLC.
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Copy and paste a formatted citation
Spandidos Publications style
Mörth C, Kafantaris I, Castegren M and Valachis A: Validation and optimization of a predictive model for radiation pneumonitis in patients with lung cancer. Oncol Lett 12: 1144-1148, 2016.
APA
Mörth, C., Kafantaris, I., Castegren, M., & Valachis, A. (2016). Validation and optimization of a predictive model for radiation pneumonitis in patients with lung cancer. Oncology Letters, 12, 1144-1148. https://doi.org/10.3892/ol.2016.4678
MLA
Mörth, C., Kafantaris, I., Castegren, M., Valachis, A."Validation and optimization of a predictive model for radiation pneumonitis in patients with lung cancer". Oncology Letters 12.2 (2016): 1144-1148.
Chicago
Mörth, C., Kafantaris, I., Castegren, M., Valachis, A."Validation and optimization of a predictive model for radiation pneumonitis in patients with lung cancer". Oncology Letters 12, no. 2 (2016): 1144-1148. https://doi.org/10.3892/ol.2016.4678
Copy and paste a formatted citation
x
Spandidos Publications style
Mörth C, Kafantaris I, Castegren M and Valachis A: Validation and optimization of a predictive model for radiation pneumonitis in patients with lung cancer. Oncol Lett 12: 1144-1148, 2016.
APA
Mörth, C., Kafantaris, I., Castegren, M., & Valachis, A. (2016). Validation and optimization of a predictive model for radiation pneumonitis in patients with lung cancer. Oncology Letters, 12, 1144-1148. https://doi.org/10.3892/ol.2016.4678
MLA
Mörth, C., Kafantaris, I., Castegren, M., Valachis, A."Validation and optimization of a predictive model for radiation pneumonitis in patients with lung cancer". Oncology Letters 12.2 (2016): 1144-1148.
Chicago
Mörth, C., Kafantaris, I., Castegren, M., Valachis, A."Validation and optimization of a predictive model for radiation pneumonitis in patients with lung cancer". Oncology Letters 12, no. 2 (2016): 1144-1148. https://doi.org/10.3892/ol.2016.4678
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