A model combining age, equivalent uniform dose and IL-8 may predict radiation esophagitis in patients with non-small cell lung cancer

Shulian Wang, Jeff Campbell, Matthew H. Stenmark, Paul Stanton, Jing Zhao, Martha M. Matuszak, Randall K. Ten Haken, Feng Ming Kong

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Background and purpose: To study whether cytokine markers may improve predictive accuracy of radiation esophagitis (RE) in non-small cell lung cancer (NSCLC) patients. Materials and methods: A total of 129 patients with stage I–III NSCLC treated with radiotherapy (RT) from prospective studies were included. Thirty inflammatory cytokines were measured in platelet-poor plasma samples. Logistic regression was performed to evaluate the risk factors of RE. Stepwise Akaike information criterion (AIC) and likelihood ratio test were used to assess model predictions. Results: Forty-nine of 129 patients (38.0%) developed grade ≥2 RE. Univariate analysis showed that age, stage, concurrent chemotherapy, and eight dosimetric parameters were significantly associated with grade ≥2 RE (p < 0.05). IL-4, IL-5, IL-8, IL-13, IL-15, IL-1α TGFα and eotaxin were also associated with grade ≥2 RE (p < 0.1). Age, esophagus generalized equivalent uniform dose (EUD), and baseline IL-8 were independently associated grade ≥2 RE. The combination of these three factors had significantly higher predictive power than any single factor alone. Addition of IL-8 to toxicity model significantly improves RE predictive accuracy (p = 0.019). Conclusions: Combining baseline level of IL-8, age and esophagus EUD may predict RE more accurately. Refinement of this model with larger sample sizes and validation from multicenter database are warranted.

Original languageEnglish (US)
Pages (from-to)506-510
Number of pages5
JournalRadiotherapy and Oncology
Volume126
Issue number3
DOIs
StatePublished - Mar 2018

Keywords

  • Cytokines
  • Lung neoplasm
  • Non-small cell
  • Radiation esophagitis

ASJC Scopus subject areas

  • Hematology
  • Oncology
  • Radiology Nuclear Medicine and imaging

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