Real-world utilisation of brachytherapy boost and patient-reported functional outcomes in men who had external beam radiation therapy for prostate cancer in Australia
Bibliographic record
Abstract
Background and purpose: We aimed to evaluate utilisation of brachytherapy (BT) boost in men who had external beam radiation therapy (EBRT) for prostate cancer, and to compare patient-reported functional outcomes (PRO) following each approach in a population-based setting in Australia. Materials and methods: This is a population-based cohort of men with localised prostate cancer enrolled in the Victorian Prostate Cancer Outcomes Registry, who had EBRT between 2015 and 2020. Primary outcomes were proportion who had BT-boost, and PRO (assessed using the EPIC-26 questionnaires) 12 months post-treatment. Multivariable logistic regressions were used to evaluate factors associated with BT-boost, and linear regressions were used to estimate differences in EPIC-26 domain scores between EBRT alone and EBRT + BT. Results: Of the 1,626 men in the study, 88 (5.4 %) had BT-boost. Factors independently associated with BT-boost were younger age, higher socioeconomic status, and treatment in public institutions. 1,555 men completed EPIC-26 questionnaires. No statistically or clinically significant differences in EPIC-26 urinary, sexual and bowel functional domain scores were observed between men who had EBRT + BT vs EBRT alone, with adjusted mean differences in urinary incontinence, urinary irritative/ obstruction, sexual, and bowel domain of 1.28 (95 %CI = -3.23 to 5.79), -2.87 (95 %CI = -6.46 to 0.73), 0.49 (95 %CI = -4.78 to 5.76), and 2.89 (95 %CI = -0.83 to 6.61) respectively. Conclusion: 1-in-20 men who had EBRT for prostate cancer had BT-boost. This is the first time that PRO following EBRT+/-BT is reported at a population-based level in Australia, with no evidence to suggest worse PRO with addition of BT-boost 12 months post-treatment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".