Radiotherapy Facilities, Equipment, and Staffing in Brazil: A Survey by the Brazilian Society of Radiation Oncology
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Bibliographic record
Abstract
Background: The rising incidences in cancer, together with the population aging have increased the demand for radiotherapy (RT) services in Brazil. Currently, Brazil faces a dearth of RT and solutions to provide a more universal care to cancer is a hot topic in this country. Aim: To evaluate the current status of RT department, staffing, and techniques in Brazil for 2017 following the launch of the National Cancer Program and the EXPANDE program. Methods: The Brazilian Society for Radiation Oncology (SBRT), sent detailed, online-based survey to heads of departments of all Brazilian RT centers (public and private), located in the 27 states in 2017. The survey included questions related to personnel, equipment, type of the center, and % of patients treated (private exclusive (≥ 90% of the treatments focused the private system) or public exclusive (≥ 90% of the treatments focused the public system) or mixed). Respondents were asked to provide average data from the last 5 year. For final analysis we grouped the states per region north, northeast (NE), central-west (C), southeast (SE) and south. A descriptive analysis was performed. Results: A total of 142 responses from 212 sent surveys (67% response rate) were received from 23 states. The total number of the departments and median functioning years per federative region was: 7 departments and 8 years in the north; 27 and 13 years in the NE; 7 and 11.5 years in the central; 27 and 17 years in the south; and 72 and 20 years in the SE region, respectively. The rate of radiation oncologist, physicist, nurse and dosimetrist per department was 3.0, 2.0, 1.7, 0.2 (north), 3.2, 2.4, 1.6, 0.7 (NE), 2.5, 1.7, 1.0, 0.3 (central), 3.4, 2.6, 1.6, 0.7 (south) and 3.9, 2.8, 1.6, 0.9 (SE), respectively. High dose rate brachytherapy was offered by 70% of the departments in the north, 55% in the NE, 30% in the central, 40% in the SE and 37% in the south region, respectively. Ninety-five percent of the department had at least one linear accelerator and only 5% had exclusively cobalt machines. The minority of the centers offered intensity modulated RT (36%) and image-guided RT (42%). 3D-conformal was the technique offered by 87% of the departments and 18% of them still treat patients with 2D technique. Overall, 30% of the departments provide services to the public health system exclusively, 1% to the private sector only and 69% of the department to both private and public. Conclusion: Important heterogeneity in the number of departments and professionals involved within RT services among Brazilian regions was found. Most departments were found to be in operation > 10+ years, indicating the need for recent hardware and software update and/or maintenance. 3D-conformal is the most common offered technique and mixed approach (public and private partnership) is the most common model of business in the country.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it