Continued Success in Providing Timely Palliative Radiation Therapy at the Rapid Response Radiotherapy Program: A Review of 2008–2012
Bibliographic record
Abstract
OBJECTIVE: We set out to review the Rapid Response Radiotherapy Program (rrrp). METHODS: We retrospectively reviewed a prospective database of patients referred to the rrrp between August 1, 2008, and June 30, 2012, extracting patient demographics, case dispositions, and wait times in days from referral to consultation and from consultation to treatment. RESULTS: Of 2742 patients referred to the rrrp, 1458 (53%) were men, and 1284 (47%) were women. Median age was 64 years. The most prevalent primary cancer sites were lung (33%), breast (21%), and prostate (17%). The most common reasons for referral were bone metastases (53%) and brain metastases (21%). Palliative radiation therapy was given to 1890 patients. The median wait time from referral to consultation was 3 days. Among treated patients, 60% were treated on the day of their consultation, and 33%, within 1-6 days. CONCLUSIONS: The rrrp continues to deliver timely palliative radiation therapy to patients, comparable to earlier reviews. The continued success of the rrrp will remain a model for future rapid-access palliative radiation therapy clinics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".