Modelling second malignancy risks from low dose rate and high dose rate brachytherapy as monotherapy for localised prostate cancer

Abstract

Background and purposeTo estimate the risks of radiation-induced rectal and bladder cancers following low dose rate (LDR) and high dose rate (HDR) brachytherapy as monotherapy for localised prostate cancer and compare to external beam radiotherapy techniques. Materials and methodsLDR and HDR brachytherapy monotherapy plans were generated for three prostate CT datasets. Second cancer risks were assessed using Schneider’s concept of organ equivalent dose. LDR risks were assessed according to a mechanistic model and a bell-shaped model. HDR risks were assessed according to a bell-shaped model. Relative risks and excess absolute risks were estimated and compared to external beam techniques. ResultsExcess absolute risks of second rectal or bladder cancer were low for both LDR (irrespective of the model used for calculation) and HDR techniques. Average excess absolute risks of rectal cancer for LDR brachytherapy according to the mechanistic model were 0.71 per 10,000 person-years (PY) and 0.84 per 10,000 PY respectively, and according to the bell-shaped model, were 0.47 and 0.78 per 10,000 PY respectively. For HDR, the average excess absolute risks for second rectal and bladder cancers were 0.74 and 1.62 per 10,000 PY respectively. The absolute differences between techniques were very low and clinically irrelevant. Compared to external beam prostate radiotherapy techniques, LDR and HDR brachytherapy resulted in the lowest risks of second rectal and bladder cancer. ConclusionsThis study shows both LDR and HDR brachytherapy monotherapy result in low estimated risks of radiation-induced rectal and bladder cancer. LDR resulted in lower bladder cancer risks than HDR, and lower or similar risks of rectal cancer. In absolute terms these differences between techniques were very small. Compared to external beam techniques, second rectal and bladder cancer risks were lowest for brachytherapy.