Modeling the risk of radiation-induced acute esophagitis for combined Washington University and RTOG trial 93-11 lung cancer patients

Int J Radiat Oncol Biol Phys. 2012 Apr 1;82(5):1674-9. doi: 10.1016/j.ijrobp.2011.02.052. Epub 2011 Jun 14.

Abstract

Purpose: To construct a maximally predictive model of the risk of severe acute esophagitis (AE) for patients who receive definitive radiation therapy (RT) for non-small-cell lung cancer.

Methods and materials: The dataset includes Washington University and RTOG 93-11 clinical trial data (events/patients: 120/374, WUSTL = 101/237, RTOG9311 = 19/137). Statistical model building was performed based on dosimetric and clinical parameters (patient age, sex, weight loss, pretreatment chemotherapy, concurrent chemotherapy, fraction size). A wide range of dose-volume parameters were extracted from dearchived treatment plans, including Dx, Vx, MOHx (mean of hottest x% volume), MOCx (mean of coldest x% volume), and gEUD (generalized equivalent uniform dose) values.

Results: The most significant single parameters for predicting acute esophagitis (RTOG Grade 2 or greater) were MOH85, mean esophagus dose (MED), and V30. A superior-inferior weighted dose-center position was derived but not found to be significant. Fraction size was found to be significant on univariate logistic analysis (Spearman R = 0.421, p < 0.00001) but not multivariate logistic modeling. Cross-validation model building was used to determine that an optimal model size needed only two parameters (MOH85 and concurrent chemotherapy, robustly selected on bootstrap model-rebuilding). Mean esophagus dose (MED) is preferred instead of MOH85, as it gives nearly the same statistical performance and is easier to compute. AE risk is given as a logistic function of (0.0688 MED+1.50 ConChemo-3.13), where MED is in Gy and ConChemo is either 1 (yes) if concurrent chemotherapy was given, or 0 (no). This model correlates to the observed risk of AE with a Spearman coefficient of 0.629 (p < 0.000001).

Conclusions: Multivariate statistical model building with cross-validation suggests that a two-variable logistic model based on mean dose and the use of concurrent chemotherapy robustly predicts acute esophagitis risk in combined-data WUSTL and RTOG 93-11 trial datasets.

Publication types

  • Clinical Trial
  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Aged, 80 and over
  • Analysis of Variance
  • Carcinoma, Non-Small-Cell Lung / drug therapy
  • Carcinoma, Non-Small-Cell Lung / radiotherapy*
  • Cohort Studies
  • Esophagitis / etiology*
  • Esophagus / radiation effects*
  • Female
  • Humans
  • Lung Neoplasms / drug therapy
  • Lung Neoplasms / radiotherapy*
  • Male
  • Middle Aged
  • Models, Biological*
  • Radiation Injuries / complications*
  • Radiotherapy Dosage
  • Risk
  • Sex Factors
  • Tumor Burden
  • Weight Loss