Multivariable model for predicting acute oral mucositis during combined IMRT and chemotherapy for locally advanced nasopharyngeal cancer patients

Research output: Contribution to journalArticle

Abstract

INTRODUCTION/OBJECTIVE: Oral and oropharyngeal mucositis (OM) represents amultifactorialand complexinterplayof patient-, tumor-, and treatment-related factors. We aimed to build a predictive model for acute OM for locally advanced nasopharyngeal carcinoma (NPC) patients by combining clinical and dosimetric factors.

MATERIALS/METHODS: A series of consecutive NPC patients treated curatively with IMRT/VMAT + chemotherapy at 70 Gy (2-2.12 Gy/fr) was considered. For each patient, clinical- tumor- and treatment-related data were retrospectively collected. oral cavity (OC) and parotid glands (PG, considered as a single organ) were selected as organs-at-risk (OARs). Acute OM was assessed according to CTCAE v4.0 at baseline and weekly during RT. Two endpoints were considered: grade ≥3 and mean grade ≥1.5. DVHs were reduced to Equivalent Uniform Dose (EUD). Dosimetric and clinical/treatment features selected via LASSO were inserted into a multivariable logistic model. Goodness of fit was evaluated through Hosmer-Lemeshow test and calibration plot.

RESULTS: Data were collected for 132 patients. G ≥ 3 and mean G ≥ 1.5 OM were reported in 40 patients (30%). Analyses resulted in a 3-variables model for G ≥ 3 OM, including OC EUD with n = 0.05 (OR = 1.02), PG EUD with n = 1 (OR = 1.06), BMI ≥ 30 (OR = 3.8, for obese patients), and a single variable model for mean G ≥ 1.5 OM, i.e. OC EUD with n = 1 (mean dose) (OR = 1.07). Calibration was good in both cases.

CONCLUSION: OC mean dose was found to impact most on OM duration (mean G ≥ 1.5), while G ≥ 3 OM was associated to a synergic effect between PG mean dose and high dose received by small OC volumes, with BMI acting as a dose-modifying factor.

Original languageEnglish
Pages (from-to)266-272
Number of pages7
JournalOral Oncology
Volume86
DOIs
Publication statusPublished - Nov 2018

    Fingerprint

Cite this