Skip to main content
Journal cover image

Predicting lung radiotherapy-induced pneumonitis using a model combining parametric Lyman probit with nonparametric decision trees.

Publication ,  Journal Article
Das, SK; Zhou, S; Zhang, J; Yin, F-F; Dewhirst, MW; Marks, LB
Published in: Int J Radiat Oncol Biol Phys
July 15, 2007

PURPOSE: To develop and test a model to predict for lung radiation-induced Grade 2+ pneumonitis. METHODS AND MATERIALS: The model was built from a database of 234 lung cancer patients treated with radiotherapy (RT), of whom 43 were diagnosed with pneumonitis. The model augmented the predictive capability of the parametric dose-based Lyman normal tissue complication probability (LNTCP) metric by combining it with weighted nonparametric decision trees that use dose and nondose inputs. The decision trees were sequentially added to the model using a "boosting" process that enhances the accuracy of prediction. The model's predictive capability was estimated by 10-fold cross-validation. To facilitate dissemination, the cross-validation result was used to extract a simplified approximation to the complicated model architecture created by boosting. Application of the simplified model is demonstrated in two example cases. RESULTS: The area under the model receiver operating characteristics curve for cross-validation was 0.72, a significant improvement over the LNTCP area of 0.63 (p = 0.005). The simplified model used the following variables to output a measure of injury: LNTCP, gender, histologic type, chemotherapy schedule, and treatment schedule. For a given patient RT plan, injury prediction was highest for the combination of pre-RT chemotherapy, once-daily treatment, female gender and lowest for the combination of no pre-RT chemotherapy and nonsquamous cell histologic type. Application of the simplified model to the example cases revealed that injury prediction for a given treatment plan can range from very low to very high, depending on the settings of the nondose variables. CONCLUSIONS: Radiation pneumonitis prediction was significantly enhanced by decision trees that added the influence of nondose factors to the LNTCP formulation.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

Int J Radiat Oncol Biol Phys

DOI

ISSN

0360-3016

Publication Date

July 15, 2007

Volume

68

Issue

4

Start / End Page

1212 / 1221

Location

United States

Related Subject Headings

  • Reproducibility of Results
  • Radiography
  • Radiation Pneumonitis
  • ROC Curve
  • Oncology & Carcinogenesis
  • Middle Aged
  • Male
  • Lung Neoplasms
  • Humans
  • Female
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Das, S. K., Zhou, S., Zhang, J., Yin, F.-F., Dewhirst, M. W., & Marks, L. B. (2007). Predicting lung radiotherapy-induced pneumonitis using a model combining parametric Lyman probit with nonparametric decision trees. Int J Radiat Oncol Biol Phys, 68(4), 1212–1221. https://doi.org/10.1016/j.ijrobp.2007.03.064
Das, Shiva K., Sumin Zhou, Junan Zhang, Fang-Fang Yin, Mark W. Dewhirst, and Lawrence B. Marks. “Predicting lung radiotherapy-induced pneumonitis using a model combining parametric Lyman probit with nonparametric decision trees.Int J Radiat Oncol Biol Phys 68, no. 4 (July 15, 2007): 1212–21. https://doi.org/10.1016/j.ijrobp.2007.03.064.
Das SK, Zhou S, Zhang J, Yin F-F, Dewhirst MW, Marks LB. Predicting lung radiotherapy-induced pneumonitis using a model combining parametric Lyman probit with nonparametric decision trees. Int J Radiat Oncol Biol Phys. 2007 Jul 15;68(4):1212–21.
Das, Shiva K., et al. “Predicting lung radiotherapy-induced pneumonitis using a model combining parametric Lyman probit with nonparametric decision trees.Int J Radiat Oncol Biol Phys, vol. 68, no. 4, July 2007, pp. 1212–21. Pubmed, doi:10.1016/j.ijrobp.2007.03.064.
Das SK, Zhou S, Zhang J, Yin F-F, Dewhirst MW, Marks LB. Predicting lung radiotherapy-induced pneumonitis using a model combining parametric Lyman probit with nonparametric decision trees. Int J Radiat Oncol Biol Phys. 2007 Jul 15;68(4):1212–1221.
Journal cover image

Published In

Int J Radiat Oncol Biol Phys

DOI

ISSN

0360-3016

Publication Date

July 15, 2007

Volume

68

Issue

4

Start / End Page

1212 / 1221

Location

United States

Related Subject Headings

  • Reproducibility of Results
  • Radiography
  • Radiation Pneumonitis
  • ROC Curve
  • Oncology & Carcinogenesis
  • Middle Aged
  • Male
  • Lung Neoplasms
  • Humans
  • Female