Detailed review and analysis of complex radiotherapy clinical trial planning data: evaluation and initial experience with the SWAN software system

Abstract

Aim: Contemporary radiotherapy clinical trials typically require complex three-dimensional (3D) treatment planning. This produces large amounts of data relating technique and dose delivery for correlation with patient outcomes. Assessment of the quality of this information is required to ensure protocol compliance, to quantify the variation in treatments given to patients and to enhance the power of studies to determine correlates of patient outcomes.

Materials and methods: A software system ('SWAN') was developed to facilitate the objective analysis, quality-assurance and review of digital treatment planning data from multi-centre radiotherapy trials. The utility of this system was assessed on the basis of its functionality and our experience of its use in the context of multi-centre clinical trials and trials-support activities.

Results: The SWAN system has been shown to have the functionality required for use in several multi-centre trials, including automated review and archive processes. Approximately 800 treatment plans from over 30 participating institutions have so far been assessed with the system for several treatment planning scenarios. To illustrate this we include a description of the use of the system for a large-recruitment prostate radiotherapy trial being undertaken in Australasia, including examples of how the review process has changed clinical practice.

Conclusion: The successful implementation of SWAN has been demonstrated in a number of clinical trials. The software provides an opportunity for comprehensive review of treatment parameters that could impact on clinical outcomes and trial results. Such quality-assurance (QA) has previously been difficult or impossible to achieve, particularly for a clinical trial involving large numbers of patients. Such reviews have highlighted inconsistencies in clinical practice that have since been addressed through feedback from the review process. The process of data collection and review should be undertaken by dedicated, experienced and skilled staff in order to ensure efficiency.