Comparing different NTCP models that predict the incidence of radiation pneumonitis. Normal tissue complication probability

Int J Radiat Oncol Biol Phys. 2003 Mar 1;55(3):724-35. doi: 10.1016/s0360-3016(02)03986-x.

Abstract

Purpose: To compare different normal tissue complication probability (NTCP) models to predict the incidence of radiation pneumonitis on the basis of the dose distribution in the lung.

Methods and materials: The data from 382 breast cancer, malignant lymphoma, and inoperable non-small-cell lung cancer patients from two centers were studied. Radiation pneumonitis was scored using the Southwestern Oncology Group criteria. Dose-volume histograms of the lungs were calculated from the dose distributions that were corrected for dose per fraction effects. The dose-volume histogram of each patient was reduced to a single parameter using different local dose-effect relationships. Examples of single parameters were the mean lung dose (MLD) and the volume of lung receiving more than a threshold dose (V(Dth)). The parameters for the different NTCP models were fit to patient data using a maximum likelihood analysis.

Results: The best fit resulted in a linear local dose-effect relationship, with the MLD as the resulting single parameter. The relationship between the MLD and NTCP could be described with a median toxic dose (TD(50)) of 30.8 Gy and a steepness parameter m of 0.37. The best fit for the relationship between the V(Dth) and the NTCP was obtained with a D(th) of 13 Gy. The MLD model was found to be significantly better than the V(Dth) model (p <0.03). However, for 85% of the studied patients, the difference in NTCP calculated with both models was <10%, because of the high correlation between the two parameters. For dose distributions outside the range of the studied dose-volume histograms, the difference in NTCP, using the two models could be >35%. For arbitrary dose distributions, an estimate of the uncertainty in the NTCP could be determined using the probability distribution of the parameter values of the Lyman-Kutcher-Burman model.

Conclusion: The maximum likelihood method revealed that the underlying local dose-effect relation for radiation pneumonitis was linear (the MLD model), rather than a step function (the V(Dth) model). Thus, for the studied patient population, the MLD was the most accurate predictor for the incidence of radiation pneumonitis.

Publication types

  • Comparative Study
  • Multicenter Study
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Breast Neoplasms / radiotherapy
  • Carcinoma, Non-Small-Cell Lung / radiotherapy
  • Female
  • Humans
  • Incidence
  • Likelihood Functions
  • Lung Neoplasms / radiotherapy
  • Lymphoma / radiotherapy
  • Male
  • Models, Biological*
  • Probability
  • Radiation Pneumonitis / epidemiology
  • Radiation Pneumonitis / etiology*
  • Radiotherapy Dosage
  • Severity of Illness Index