The population benefit of evidence-based radiotherapy: 5-Year local control and overall survival benefits
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: To describe the population benefit of radiotherapy in a high-income setting if evidence-based guidelines were routinely followed. METHODS: Australian decision tree models were utilized. Radiotherapy alone (RT) benefit was defined as the absolute proportional benefit of radiotherapy compared with no treatment for radical indications, and of radiotherapy over surgery alone for adjuvant indications. Chemoradiotherapy (CRT) benefit was the absolute incremental benefit of concurrent chemoradiotherapy over RT. Five-year local control (LC) and overall survival (OS) benefits were measured. Citation databases were systematically queried for benefit data. Meta-analysis and sensitivity analysis were performed. FINDINGS: 48% of all cancer patients have indications for radiotherapy, 34% curative and 14% palliative. RT provides 5-year LC benefit in 10.4% of all cancer patients (95% Confidence Interval 9.3, 11.8) and 5-year OS benefit in 2.4% (2.1, 2.7). CRT provides 5-year LC benefit in an additional 0.6% of all cancer patients (0.5, 0.6), and 5-year OS benefit for an additional 0.3% (0.2, 0.4). RT benefit was greatest for head and neck (LC 32%, OS 16%), and cervix (LC 33%, OS 18%). CRT LC benefit was greatest for rectum (6%) and OS for cervix (3%) and brain (3%). Sensitivity analysis confirmed a robust model. INTERPRETATION: Radiotherapy provides significant 5-year LC and OS benefits as part of evidence-based cancer care. CRT provides modest additional benefits.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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