Introduction/objective: Oral and oropharyngeal mucositis (OM) represents a multifactorial and complex interplay of 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.

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

Bossi P.;
2018-01-01

Abstract

Introduction/objective: Oral and oropharyngeal mucositis (OM) represents a multifactorial and complex interplay of 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.
2018
Head and neck cancer
Intensity modulated radiation therapy
Nasopharyngeal carcinoma
Oral mucositis
Predictive model
Radiation-induced toxicity
Acute Disease
Adolescent
Adult
Aged
Aged
80 and over
Body Mass Index
Chemoradiotherapy
Female
Humans
Male
Middle Aged
Mouth Mucosa
Multivariate Analysis
Nasopharyngeal Carcinoma
Nasopharyngeal Neoplasms
Organs at Risk
Radiation Injuries
Radiotherapy Dosage
Radiotherapy
Intensity-Modulated
Retrospective Studies
Stomatitis
Time Factors
Young Adult
Models
Biological
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11699/80771
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