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

dc.contributor.authorHawkins, Peter G.
dc.contributor.authorBoonstra, Philip S.
dc.contributor.authorHobson, Stephen T.
dc.contributor.authorHayman, James A.
dc.contributor.authorTen Haken, Randall K.
dc.contributor.authorMatuszak, Martha M.
dc.contributor.authorStanton, Paul
dc.contributor.authorKalemkerian, Gregory P.
dc.contributor.authorLawrence, Theodore S.
dc.contributor.authorSchipper, Matthew J.
dc.contributor.authorKong, Feng-Ming (Spring)
dc.contributor.authorJolly, Shruti
dc.contributor.departmentRadiation Oncology, School of Medicineen_US
dc.date.accessioned2019-01-16T17:13:46Z
dc.date.available2019-01-16T17:13:46Z
dc.date.issued2018-02
dc.description.abstractRadiation 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.en_US
dc.eprint.versionFinal published versionen_US
dc.identifier.citationHawkins, 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. S., … Jolly, S. (2017). 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.en_US
dc.identifier.urihttps://hdl.handle.net/1805/18157
dc.language.isoen_USen_US
dc.publisherElsevieren_US
dc.relation.isversionof10.1016/j.tranon.2017.11.005en_US
dc.relation.journalTranslational oncologyen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/
dc.sourcePMCen_US
dc.subjectRadiation esophagitisen_US
dc.subjectLogistic regression modelsen_US
dc.subjectPretreatment cytokine measurementsen_US
dc.subjectFemalesen_US
dc.subjectDosimetric factorsen_US
dc.subjectOlder ageen_US
dc.subjectMultifactorial modelingen_US
dc.subjectRadiation treatment planningen_US
dc.titlePrediction of Radiation Esophagitis in Non-Small Cell Lung Cancer Using Clinical Factors, Dosimetric Parameters, and Pretreatment Cytokine Levelsen_US
dc.typeArticleen_US
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
main.pdf
Size:
365.76 KB
Format:
Adobe Portable Document Format
Description:
Main article
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.99 KB
Format:
Item-specific license agreed upon to submission
Description: