Association between treatment planning and delivery factors and disease progression in prostate cancer radiotherapy: Results from the TROG 03.04 RADAR trial. Issue 2 (February 2018)

• Record Type: Journal Article
• Authors: Marcello, Marco; Ebert, Martin; Haworth, Annette; Steigler, Allison; Kennedy, Angel; Joseph, David; Denham, James
• Is Part Of: Radiotherapy and oncology. Volume 126:Issue 2(2018)
• Page Start: 249
• Page End: 256
• Publication Date: 2018-02
• Subjects: Prostate -- Radiotherapy -- Treatment factors -- Progression; Oncology -- Periodicals; Radiotherapy -- Periodicals; Tumors -- Periodicals; Medical Oncology -- Periodicals; Neoplasms -- radiotherapy -- Periodicals; Radiotherapy -- Periodicals; Radiothérapie -- Périodiques; Cancérologie -- Périodiques; Tumeurs -- Périodiques; Electronic journals; 616.9940642
• DOI: 10.1016/j.radonc.2017.10.021
• Languages: English
• ISSNs: 0167-8140

Abstract

Abstract: Background and purpose: To evaluate the impact of treatment planning and delivery factors on treatment outcome as measured by post-treatment disease progression. Materials and methods: Accruing 813 external beam radiotherapy participants during 2003–2007, the RADAR trial collected a comprehensive range of clinical treatment factor data for each participant. Both the Fine and Gray competing risks modelling and the Kaplan–Meier (KM) analysis were undertaken to determine the impact of these factors on local-composite progression (LCP), with 709 participants available for analysis. Results: Participants with treatments involving 7 or more beams experienced significantly higher incidence of LCP, with a sub-hazard ratio (relative to 3-beam participants) of 3.056 (CI: 1.446–6.458, p < 0.0034). Participants treated with a more rigorous dose calculation algorithm also displayed significantly higher incidence of LCP, with a sub-hazard ratio of 1.686 (CI: 1.334–2.132, p < 0.0001). The KM analysis resulted in the same groups showing a higher incidence of LCP, with log-rank test results of p = 0.0005 and p = 0.0008 respectively. Conclusions: The RADAR dataset has enabled a successful secondary analysis in which the impact of technical modifications has been assessed, challenging several established hypotheses. Increasingly precise treatments should be complemented with increasing accuracy to avoid potential geometric miss.