Current practice patterns and gaps in guideline-concordant breast cancer survivorship care

Purpose Breast cancer-specific survivorship care guidelines for the more than 3.8 million survivors in the U.S. are available, but implementation in clinical practice remains challenging. We examined current practice patterns and factors associated with guideline-concordant survivorship care among oncologists. Methods A national sample of medical oncologists, recruited using two databases, participated in a survey focused on practice patterns for breast cancer survivorship care. A “survivorship care composite score” was calculated for each respondent based on provision of services recommended in the survivorship guidelines. Descriptive statistics and multivariable linear regression analyses examined associations between physician and practice characteristics and composite scores. Results The survey was completed by 217 medical oncologists, with an overall response rate of 17.9% and eligibility rate of 56.9% for those who responded. Oncologists reported high engagement in evaluation of disease recurrence (78%). Performed less frequently were the provision of survivorship care plans (46%), assessment of psychosocial long-term and late effects (34%), and screening for subsequent cancers (34%). Lack of survivorship care training (p = 0.038) and not routinely informing patients about potential late effects (p = 0.003) were significantly associated with poorer survivorship care composite scores. Conclusions Despite the availability of disease-specific survivorship care guidelines, adherence to their recommendations in clinical practice is suboptimal. Survey results identified key gaps in survivorship care for breast cancer survivors, particularly related to subsequent primary cancers and psychosocial long-term and late effects. Implications for Cancer Survivors Improving the delivery of comprehensive survivorship care for the growing population of breast cancer survivors is a high priority. Disease-specific clinical guidelines for cancer survivorship provide valuable recommendations, but innovative strategies are needed to integrate them into the care of long-term breast cancer survivors.

A patient-specific hybrid phantom for calculating radiation dose and equivalent dose to the whole body

Objective: As cancer survivorship increases, there is growing interest in minimizing the late effects of radiation therapy such as radiogenic second cancer, which may occur anywhere in the body. Assessing the risk of late effects requires knowledge of the dose distribution throughout the whole body, including regions far from the treatment field, beyond the typical anatomical extent of clinical CT scans. Approach: A hybrid phantom was developed which consists of in-field patient CT images extracted from ground truth whole-body CT (WBCT) scans, out-of-field mesh phantoms scaled to basic patient measurements, and a blended transition region. Four of these hybrid phantoms were created, representing male and female patients receiving proton therapy treatment in pelvic and cranial sites. To assess the performance of the hybrid approach, we simulated treatments using the hybrid phantoms, the scaled and unscaled mesh phantoms, and the ground truth whole-body CTs. We calculated absorbed dose and equivalent dose in and outside of the treatment field, with a focus on neutrons induced in the patient by proton therapy. Proton and neutron dose was calculated using a general purpose Monte Carlo code. Main Results: The hybrid phantom provided equal or superior accuracy in calculated organ dose and equivalent dose values relative to those obtained using the mesh phantoms in 78% in all selected organs and calculated dose quantities. Comparatively the default mesh and scaled mesh were equal or superior to the other phantoms in 21% and 28% of cases respectively. Significance: The proposed methodology for hybrid synthesis provides a tool for whole-body organ dose estimation for individual patients without requiring CT scans of their entire body. Such a capability would be useful for personalized assessment of late effects and risk-optimization of treatment plans.