Model-Based Selection for Proton Therapy in Breast Cancer: Development of the National Indication Protocol for Proton Therapy and First Clinical Experiences.

AIMS: Proton therapy is a radiation technique that yields less dose in normal tissues than photon therapy. In the Netherlands, proton therapy is reimbursed if the reduced dose to normal tissues is predicted to translate into a prespecified reduction in toxicity, based on nationally approved validated models. The aim of this paper is to present the development of a national indication protocol for proton therapy (NIPP) for model-based selection of breast cancer patients and to report on first clinical experiences. MATERIALS AND METHODS: A national proton therapy working group for breast cancer (PWG-BC) screened the literature for prognostic models able to estimate the individual risk of specific radiation-induced side-effects. After critical appraisal and selection of suitable models, a NIPP for breast cancer was written and subjected to comments by all stakeholders. The approved NIPP was subsequently introduced to select breast cancer patients who would benefit most from proton therapy. RESULTS: The model of Darby et al. (N Engl J Med 2013; 368:987-82) was the only model fulfilling the criteria prespecified by the PWG-BC. The model estimates the relative risk of an acute coronary event (ACE) based on the mean heart dose. The absolute lifetime risk of ACE <80 years was calculated by applying this model to the Dutch absolute incidence of ACE for female and male patients, between 40 and 70 years at breast cancer radiotherapy, with/without cardiovascular risk factors. The NIPP was approved for reimbursement in January 2019. Based on a threshold value of a 2% absolute lower risk on ACE for proton therapy compared with photons, 268 breast cancer patients have been treated in the Netherlands with proton therapy between February 2019 and January 2021. CONCLUSION: The NIPP includes a model that allows the estimation of the absolute risk on ACE <80 years based on mean heart dose. In the first 2 years, 268 breast cancer patients have been treated with proton therapy in The Netherlands.

Effect of breathing motion on robustness of proton therapy plans for left-sided breast cancer patients with indication for locoregional irradiation.

PURPOSE: To investigate the dosimetric impact of breathing motion on robustly optimized proton therapy treatment plans for left-sided breast cancer patients with an indication for locoregional irradiation. MATERIALS AND METHODS: Clinical Target Volumes (CTVs) (left-sided breast, level 1 to 4 axillary lymph nodes, interpectoral and internal mammary lymph node regions) and organs at risk were delineated on 4 D-CTs of ten female patients. After treatment planning to a prescribed dose of 40.05 Gy(RBE) in 15 fractions on the time-averaged CT, the dose was calculated on all ten phases of the breathing cycle. Robustness to setup (5 mm) and range errors (3%) was evaluated for those ten phases. Correlations were evaluated between the phases of the breathing cycle and the D98% of the CTV and the Dmean of the heart. RESULTS: Correlations coefficients were between -0.12 and 0.29. At the most extreme values of the 28 robustness scenarios, the clinical goals were met for all but two patients. The mean heart dose was 0.41 Gy(RBE) with a standard deviation of 0.31 Gy(RBE) of proton therapy plans. CONCLUSION: The effect of breathing motion on the robustness of proton therapy treatment plans for this patient group is minor and not of clinical significance. Based on this patient group, a deep-inspiration breath hold seems to be unnecessary to improve robustness for these patients.

Risk communication in a patient decision aid for radiotherapy in breast cancer: How to deal with uncertainty?

BACKGROUND AND AIM: Patient decision aids for oncological treatment options, provide information on the effect on recurrence rates and/or survival benefit, and on side-effects and/or burden of different treatment options. However, often uncertainty exists around the probability estimates for recurrence/survival and side-effects which is too relevant to be ignored. Evidence is lacking on the best way to communicate these uncertainties. The aim of this study is to develop a method to incorporate uncertainties in a patient decision aid for breast cancer patients to support their decision on radiotherapy. METHODS: Firstly, qualitative interviews were held with patients and health care professionals. Secondly, in the development phase, thinking aloud sessions were organized with four patients and 12 health care professionals, individual and group-wise. RESULTS: Consensus was reached on a pictograph illustrating the whole range of uncertainty for local recurrence risks, in combination with textual explanation that a more exact personalized risk would be given by their own physician. The pictograph consisted of 100 female icons in a 10 x 10 array. Icons with a stepwise gradient color indicated the uncertainty margin. The prevalence and severity of possible side-effects were explained using verbal labels. CONCLUSIONS: We developed a novel way of visualizing uncertainties in recurrence rates in a patient decision aid. The effect of this way of communicating risk uncertainty is currently being tested in the BRASA study (NCT03375801).