Modeling the Risk of Radiation-Induced Acute Esophagitis for Combined Washington University and RTOG Trial 93-11 Lung Cancer Patients
Creators
- 1. Department of Radiation Oncology, Washington University School of Medicine, St Louis, MO (United States)
- 2. Princess Margaret Hospital, Toronto, ON (Canada)
- 3. Department of Radiation Oncology, LDS Hospital, Salt Lake City, UT (United States)
- 4. Department of Radiation Oncology, Phelps County Regional Hospital, Rolla, MO (United States)
- 5. Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY (United States)
Description
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.
Availability note (English)
Available from http://dx.doi.org/10.1016/j.ijrobp.2011.02.052Additional details
Identifiers
- DOI
- 10.1016/j.ijrobp.2011.02.052;
- PII
- S0360-3016(11)00374-9;
Publishing Information
- Journal Title
- International Journal of Radiation Oncology, Biology and Physics
- Journal Volume
- 82
- Journal Issue
- 5
- Journal Page Range
- p. 1674-1679
- ISSN
- 0360-3016
- CODEN
- IOBPD3
INIS
- Country of Publication
- United States
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 44016593
- Subject category
- S62: RADIOLOGY AND NUCLEAR MEDICINE;
- Descriptors DEI
- CHEMOTHERAPY; CLINICAL TRIALS; DATASETS; ESOPHAGUS; HAZARDS; LUNGS; MULTIVARIATE ANALYSIS; NEOPLASMS; PATIENTS; PERFORMANCE; RADIATION DOSES; RADIOTHERAPY; SEX; SIMULATION; STATISTICAL MODELS; VALIDATION
- Descriptors DEC
- BODY; DIGESTIVE SYSTEM; DISEASES; DOCUMENT TYPES; DOSES; MATHEMATICAL MODELS; MATHEMATICS; MEDICINE; NUCLEAR MEDICINE; ORGANS; RADIOLOGY; RESPIRATORY SYSTEM; STATISTICS; TESTING; THERAPY
Optional Information
- Copyright
- Copyright (c) 2012 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.