Prediction of Radiation Esophagitis in Non–Small Cell Lung Cancer Using Clinical Factors, Dosimetric Parameters, and Pretreatment Cytokine Levels

Peter G. Hawkins, Philip S. Boonstra, Stephen T. Hobson, James A. Hayman, Randall K. Ten Haken, Martha M. Matuszak, Paul Stanton, Gregory P. Kalemkerian, Theodore S. Lawrence, Matthew J. Schipper, Feng Ming (Spring) Kong, Shruti Jolly

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

Radiation esophagitis (RE) is a common adverse event associated with radiotherapy for non–small cell lung cancer (NSCLC). While plasma cytokine levels have been correlated with other forms of radiation-induced toxicity, their association with RE has been less well studied. We analyzed data from 126 patients treated on 4 prospective clinical trials. Logistic regression models based on combinations of dosimetric factors [maximum dose to 2 cubic cm (D2cc) and generalized equivalent uniform dose (gEUD)], clinical variables, and pretreatment plasma levels of 30 cytokines were developed. Cross-validated estimates of area under the receiver operating characteristic curve (AUC) and log likelihood were used to assess prediction accuracy. Dose-only models predicted grade 3 RE with AUC values of 0.750 (D2cc) and 0.727 (gEUD). Combining clinical factors with D2cc increased the AUC to 0.779. Incorporating pretreatment cytokine measurements, modeled as direct associations with RE and as potential interactions with the dose-esophagitis association, produced AUC values of 0.758 and 0.773, respectively. D2cc and gEUD correlated with grade 3 RE with odds ratios (ORs) of 1.094/Gy and 1.096/Gy, respectively. Female gender was associated with a higher risk of RE, with ORs of 1.09 and 1.112 in the D2cc and gEUD models, respectively. Older age was associated with decreased risk of RE, with ORs of 0.992/year and 0.991/year in the D2cc and gEUD models, respectively. Combining clinical with dosimetric factors but not pretreatment cytokine levels yielded improved prediction of grade 3 RE compared to prediction by dose alone. Such multifactorial modeling may prove useful in directing radiation treatment planning.

Original languageEnglish (US)
Pages (from-to)102-108
Number of pages7
JournalTranslational Oncology
Volume11
Issue number1
DOIs
StatePublished - Jan 1 2018

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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    Hawkins, P. G., Boonstra, P. S., Hobson, S. T., Hayman, J. A., Ten Haken, R. K., Matuszak, M. M., Stanton, P., Kalemkerian, G. P., Lawrence, T. S., Schipper, M. J., Kong, F. M. S., & Jolly, S. (2018). Prediction of Radiation Esophagitis in Non–Small Cell Lung Cancer Using Clinical Factors, Dosimetric Parameters, and Pretreatment Cytokine Levels. Translational Oncology, 11(1), 102-108. https://doi.org/10.1016/j.tranon.2017.11.005