The Evidence Driven Dosimetric Constraints From Outcome Analysis of H&N Patients’ Data from NRG Oncology RTOG 0522 Trial

Abstract

Clinical trial quality assurance (QA) programs have been shown to be vital in ensuring that inter-institutional differences do not dilute trial results. Most RTOG clinical trials have a radiation therapy quality assurance (RTQA) process that evaluates RT parameters (contour, dose distribution) retrospectively or prospectively. This research is to investigate the impact of radiation treatment clinical trial quality assurance (RTQA) on treatment outcome in a phase III trial for advanced head and neck cancer with development of a predictive model incorporating RTQA parameters. RTQA for RTOG 0522 included initial institution credentialing of RT technologies and individual RT case reviews. The case review processes (include contour and dosimetry evaluations) are performed by radiation oncology and radiation physics co-chairs. RTQA grades (per-protocol, variation acceptable, and deviation unacceptable) are given to contouring of target volume (TV), organ at risk (OAR) and dose-volume coverage of targets as defined in the protocol. The relationship between RTQA parameters and treatment outcome are analyzed with predictive modeling. Logistic regression model is established that includes RTQA parameters, age, T-stage, equivalent dose in fractions of 2 Gy (EQD2), tumor location, and hemoglobin levels. This model is compared to the one without incorporating RTQA parameters. The model prediction accuracy is validated by cross-validation and C-statistical methods. The contour (TV and OAR) quality grades did not correlate with two-year overall survival. The target dose-volume quality grade is slightly related to overall survival (P = 0.094), and the correlation test shows that target dose-volume quality grade is an independent predictive factor. The target contour quality grade (P = 0.019) and target dose-volume quality grade (P = 0.008) are related to local recurrence, while target dose-volume quality grade (P = 0.034) is related to distant metastasis. The model incorporating RTQA parameters shows that the two-year survival ratio is 86.2%, 83.6%, and 80.6% for the three scores of target dose-volume quality of per-protocol, variation acceptable, and deviation unacceptable. The area under the curve (AUC) indicator is 0.737 and 0.733 for the overall survival model with RTQA parameters and without RTQA parameters. The results demonstrate that it is feasible to incorporate RTQA parameters into outcome modeling. This capability is of critical importance for evaluating RTQA methods as related to outcome in head and neck cancer.