Estimation of the optimal utilisation rates of radical prostatectomy, external beam radiotherapy and brachytherapy in the treatment of prostate cancer by a review of clinical practice guidelines. Issue 1 (January 2016)

• Record Type: Journal Article
• Authors: Thompson, Stephen R.; Delaney, Geoff P.; Jacob, Susannah; Shafiq, Jesmin; Wong, Karen; Hanna, Timothy P.; Gabriel, Gabriel S.; Barton, Michael B.
• Is Part Of: Radiotherapy and oncology. Volume 118:Issue 1(2016:Jan.)
• Page Start: 118
• Page End: 121
• Publication Date: 2016-01
• Subjects: Prostate cancer -- Brachytherapy -- Radiotherapy -- Radical prostatectomy -- Utilisation rate -- Patterns of care; 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.2015.12.023
• Languages: English
• ISSNs: 0167-8140

Abstract

Abstract: Background and purpose: We aimed to construct an evidence-based model of optimal treatment utilisation for prostate cancer, incorporating all local treatment modalities: radical prostatectomy (RP), external beam radiotherapy (EBRT), and brachytherapy (BT); and then to compare this optimal model with actual practice. Materials and methods: Evidence-based guidelines were used to construct a prostate cancer treatment decision-tree. The proportion of patients who fulfilled treatment criteria was drawn from the epidemiological literature. These data were combined to calculate the overall proportion of patients that should optimally have RP, EBRT and/or BT at least once during the course of their disease. The model was peer reviewed and tested by sensitivity analyses and compared with actual practice. Results: Optimal utilisation rates, at some point during the disease course, were: RP, 24% (range 15–30%); EBRT, 58% (range 54–64%); BT, 9.6% (range 6.0–17.9%); and any RT, 60% (range 56–66%). Many patients had indications for more than one of these treatments, and at least one of these treatments was indicated in 76% of patients. The model was sensitive to patient preference estimates. Optimal rates were achievable in some health care jurisdictions. Conclusions: Modelling optimal utilisation of all local treatment options for a particular cancer is possible. These optimal prostate cancer treatment rates can be used as a planning and quality assurance tool, providing an evidence-based benchmark against which can be measured patterns of practice.