Multivariable normal-tissue complication modeling of acute esophageal toxicity in advanced stage non-small cell lung cancer patients treated with intensity-modulated (chemo-)radiotherapy

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

Abstract

Background and purpose The majority of normal-tissue complication probability (NTCP) models for acute esophageal toxicity (AET) in advanced stage non-small cell lung cancer (AS-NSCLC) patients treated with (chemo-)radiotherapy are based on three-dimensional conformal radiotherapy (3D-CRT). Due to distinct dosimetric characteristics of intensity-modulated radiation therapy (IMRT), 3D-CRT based models need revision. We established a multivariable NTCP model for AET in 149 AS-NSCLC patients undergoing IMRT. Materials and methods An established model selection procedure was used to develop an NTCP model for Grade ≥2 AET (53 patients) including clinical and esophageal dose-volume histogram parameters. Results The NTCP model predicted an increased risk of Grade ≥2 AET in case of: concurrent chemoradiotherapy (CCR) [adjusted odds ratio (OR) 14.08, 95% confidence interval (CI) 4.70-42.19; p < 0.001], increasing mean esophageal dose [Dmean; OR 1.12 per Gy increase, 95% CI 1.06-1.19; p < 0.001], female patients (OR 3.33, 95% CI 1.36-8.17; p = 0.008), and ≥cT3 (OR 2.7, 95% CI 1.12-6.50; p = 0.026). The AUC was 0.82 and the model showed good calibration. Conclusions A multivariable NTCP model including CCR, Dmean, clinical tumor stage and gender predicts Grade ≥2 AET after IMRT for AS-NSCLC. Prior to clinical introduction, the model needs validation in an independent patient cohort.

Details

OriginalspracheEnglisch
Seiten (von - bis)49-54
Seitenumfang6
FachzeitschriftRadiotherapy and oncology
Jahrgang117
Ausgabenummer1
PublikationsstatusVeröffentlicht - Okt. 2015
Peer-Review-StatusJa

Externe IDs

PubMed 26341608

Schlagworte

Ziele für nachhaltige Entwicklung

Schlagwörter

  • Esophagitis, Intensity-modulated radiation therapy, Non-small cell lung cancer, Predictive models