Advanced Radiation Therapy Technology Use in the Treatment of Bone Metastases in a Public, Salary-Funded, Non-Incentivized Health Care System
Bibliographic record
Abstract
PURPOSE: There is limited evidence to support the routine use of conformal radiotherapy (RT) techniques in the treatment of bone metastases. This study evaluated trends in advanced technique use within the province of British Columbia. MATERIALS AND METHODS: Data on patients who received RT for bone metastases between 2009 and 2016 (with the exception of 2012) at 6 regional cancer centers were reviewed. Descriptive statistics summarized radiation technique patterns. Logistic regression assessed the influence of patient, treatment, and provider variables on receipt of RT technique. RESULTS: A total of 24,215 RT courses were identified; 97% were planned by simple RT and 3% by advanced techniques (3-dimensional conformal radiotherapy, intensity-modulated radiotherapy, and stereotactic body radiotherapy). The use of advanced techniques was significantly higher in recent years compared with in 2009 (odds ratios [ORs], 2.2, 4.2, 4.2, and 6.3, respectively, for the years 2013 to 2016; P < .001). Patients with thyroid, sarcoma, and neuroendocrine malignancies (ORs, 10.3, 5.5, and 5.2, respectively; P < .005) were more likely to be treated with advanced techniques, as were skull, sternum, rib, and pelvic metastases (ORs, 8.0, 5.2, 2.2, and 2.2, respectively; P < .001). Advanced techniques were most commonly used in the setting of re-irradiation (38%). They were associated with slightly higher incompletion rates (3.0% v 1.5%, P < .005) and less use within 30 days of death (6% v 15%, P < .001). CONCLUSION: Within our publicly funded, salary-based provincial health care system, we found that the majority of bone metastases are still being treated by simple RT; however, the use of advanced techniques is increasing, and we identified select patterns in which they are being prescribed. Additional study into clinical benefit is required.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".