The Effect of Surgeon Referral and a Radiation Oncologist Productivity-Based Metric on Radiation Therapy Receipt Among Elderly Women With Early Stage Breast Cancer: Analysis From a Tertiary Cancer Network

Purpose Guidelines for early-stage breast cancer allow for radiation therapy (RT) omission after breast conserving surgery among older women, though high utilization of RT persists. This study explored surgeon referral and the effect of a productivity-based bonus metric for radiation oncologists in an academic institution with centralized quality assurance review. Methods and Materials We evaluated patients ≥70 years of age treated with breast conserving surgery for estrogen receptor (ER)+ pT1N0 breast cancer at a single tertiary cancer network between 2015 and 2018. The primary outcomes were radiation oncology referral and RT receipt. Covariables included patient and physician characteristics and treatment decisions before versus after productivity metric implementation. Univariable generalized linear effects models explored associations between these outcomes and covariables. Results Of 703 patients included, 483 (69%) were referred to radiation oncology and 273 (39%) received RT (among those referred, 57% received RT). No difference in RT receipt pre- versus post-productivity metric implementation was observed (P = .57). RT receipt was associated with younger patient age (70-74 years; odds ratio [OR], 2.66; 95% confidence interval [CI], 1.54-4.57) and higher grade (grade 3; OR, 7.75; 95% CI, 3.33-18.07). Initial referral was associated with younger age (70-74; OR, 5.64; 95% CI, 3.37-0.45) and higher performance status (Karnofsky performance status ≥90; OR, 5.34; 95% CI, 2.63-10.83). Conclusions Nonreferral to radiation oncology accounted for half of RT omission but was based on age and Karnofsky performance status, in accordance with guidelines. Lack of radiation oncologist practice change in response to misaligned financial incentives is reassuring, potentially reflecting incentive design and/or centralized quality assurance review. Multi-institutional studies are needed to confirm these findings.