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Purpose: Prior studies have forecasted demand for radiation therapy to grow 10 times faster than the supply between 2010 and 2020. We updated these projections for 2015 to 2025 to determine whether this imbalance persists and to assess the accuracy of prior projections.Methods and Materials: The demand for radiation therapy between 2015 and 2025 was estimated by combining current radiation utilization rates determined by the Surveillance, Epidemiology, and End Results data with population projections provided by the US Census Bureau. The supply of radiation oncologists was forecast by using workforce demographics and full-time equivalent (FTE) status provided by the American Society for Radiation Oncology (ASTRO), current resident class sizes, and expected survival per life tables from the US Centers for Disease Control.Results: Between 2015 and 2025, the annual total number of patients receiving radiation therapy during their initial treatment course is expected to increase by 19%, from 490,000 to 580,000. Assuming a graduating resident class size of 200, the number of FTE physicians is expected to increase by 27%, from 3903 to 4965. In comparison with prior projections, the new projected demand for radiation therapy in 2020 dropped by 24,000 cases (a 4% relative decline). This decrease is attributable to an overall reduction in the use of radiation to treat cancer, from 28% of all newly diagnosed cancers in the prior projections down to 26% for the new projections. By contrast, the new projected supply of radiation oncologists in 2020 increased by 275 FTEs in comparison with the prior projection for 2020 (a 7% relative increase), attributable to rising residency class sizes.Conclusion: The supply of radiation oncologists is expected to grow more quickly than the demand for radiation therapy from 2015 to 2025. Further research is needed to determine whether this is an appropriate correction or will result in excess capacity. [ABSTRACT FROM AUTHOR]

Purpose There exists uncertainty in the prognosis of patients following spinal metastasis treatment. We sought to create a scoring system that stratifies patients based on overall survival. Methods and Materials Patients enrolled in 2 prospective trials investigating stereotactic spine radiation surgery (SSRS) for spinal metastasis with ≥3-year follow-up were analyzed. A multivariate Cox regression model was used to create a survival model. Pretreatment variables included were race, sex, age, performance status, tumor histology, extent of vertebrae involvement, previous therapy at the SSRS site, disease burden, and timing of diagnosis and metastasis. Four survival groups were generated based on the model-derived survival score. Results Median follow-up in the 206 patients included in this analysis was 70 months (range: 37-133 months). Seven variables were selected: female sex (hazard ratio [HR] = 0.7, P =.02), Karnofsky performance score (HR = 0.8 per 10-point increase above 60, P =.007), previous surgery at the SSRS site (HR = 0.7, P =.02), previous radiation at the SSRS site (HR = 1.8, P =.001), the SSRS site as the only site of metastatic disease (HR = 0.5, P =.01), number of organ systems involved outside of bone (HR = 1.4 per involved system, P <.001), and >5 year interval from initial diagnosis to detection of spine metastasis (HR = 0.5, P <.001). The median survival among all patients was 25.5 months and was significantly different among survival groups (in group 1 [excellent prognosis], median survival was not reached; group 2 reached 32.4 months; group 3 reached 22.2 months; and group 4 [poor prognosis] reached 9.1 months; P <.001). Pretreatment symptom burden was significantly higher in the patient group with poor survival than in the group with excellent survival (all metrics, P <.05). Conclusions We developed the prognostic index for spinal metastases (PRISM) model, a new model that identified patient subgroups with poor and excellent prognoses. [ABSTRACT FROM AUTHOR]