Increase in Tumor Control and Normal Tissue Complication Probabilities in Advanced Head-and-Neck Cancer for Dose-Escalated Intensity-Modulated Photon and Proton Therapy

The dose of radiation that locally controls human tumors treated electively or for gross disease is rarely well defined. These doses can be useful in understanding the dose requirements of novel therapies featuring inhomogeneous dosimetry and in an adjuvant setting. The goal of this study was to compute the dose of radiation that locally controls 50% (TCD50) of tumors in human subjects. Logit regression was used with data collected from single institutions or from combinations of local control data accumulated from several institutions treating the same disease. 90 dose response curves were calculated; 62 of macroscopic tumor therapy, 28 of elective therapy with surgery for primary control. The mean and median TCD50 for gross disease were 50.0 and 51.9 Gy, respectively. The mean and median TCD50 for microscopic disease control were 39.3 and 37.9 Gy, respectively. At the TCD50, an additional dose of 1 Gy controlled an additional 2.5% (median) additional patients with macroscopic disease and 4.2% (median) additional patients with microscopic disease. For both macro- and microscopic disease, an increase of 1% of dose at the TCD50 increased control rates approximately 1% (median) or 2-3% (mean). A predominance of dose response curves had shallow slopes accounting for the discrepancy between mean and median values. Doses to control microscopic disease are approximately 12 Gy less than that required to control macroscopic disease, and are about 79% of the dose required to control macroscopic disease. The percentage increase in cures expected for a 1% increase in dose is similar for macroscopic microscopic disease, with a median value of approximately 1%/% and a mean of approximately 2.7%/%.

The purpose of this large multicentre prospective cohort study was to identify which dose volume histogram parameters and pre-treatment factors are most important to predict physician-rated and patient-rated radiation-induced swallowing dysfunction (RISD) in order to develop predictive models for RISD after curative (chemo) radiotherapy ((CH) RT). The study population consisted of 354 consecutive head and neck cancer patients treated with (CH) RT. The primary endpoint was grade 2 or more swallowing dysfunction according to the RTOG/EORTC late radiation morbidity scoring criteria at 6 months after (CH) RT. The secondary endpoints were patient-rated swallowing complaints as assessed with the EORTC QLQ-H&N35 questionnaire. To select the most predictive variables a multivariate logistic regression analysis with bootstrapping was used. At 6 months after (CH) RT the bootstrapping procedure revealed that a model based on the mean dose to the superior pharyngeal constrictor muscle (PCM) and mean dose to the supraglottic larynx was most predictive. For the secondary endpoints different predictive models were found: for problems with swallowing liquids the most predictive factors were the mean dose to the supraglottic larynx and radiation technique (3D-CRT versus IMRT). For problems with swallowing soft food the mean dose to the middle PCM, age (18-65 versus >65 years), tumour site (naso/oropharynx versus other sites) and radiation technique (3D-CRT versus IMRT) were the most predictive factors. For problems with swallowing solid food the most predictive factors were the mean dose to the superior PCM, the mean dose to the supraglottic larynx and age (18-65 versus >65 years). And for choking when swallowing the V60 of the oesophageal inlet muscle and the mean dose to the supraglottic larynx were the most predictive factors. Physician-rated and patient-rated RISD in head and neck cancer patients treated with (CH) RT cannot be predicted with univariate relationships between the dose distribution in a single organ at risk and an endpoint. Separate predictive models are needed for different endpoints and factors other than dose volume histogram parameters are important as well. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.