Focal HDR brachytherapy boost to stereotactic radiotherapy (fBTsRT) for prostate cancer: a phase II randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: For patients with a higher burden of localized prostate cancer, radiation dose escalation with brachytherapy boosts have improved cancer control outcomes at the cost of urinary toxicity. We hypothesize that a focal approach to brachytherapy boosts targeting only grossly visualized tumor volumes (GTV) combined with stereotactic radiotherapy will improve quality of life (QoL) outcomes without compromising cancer control. METHODS: 150 patients with intermediate or high-risk prostate cancer will be enrolled and randomized 1:1 in a cohort multiple randomized clinical trial phase 2 design. Patients are eligible if planned for standard-of-care (SOC) high dose rate (HDR) brachytherapy boost to radiotherapy (RT) with GTVs encompassing < 50% of the prostate gland. Those randomly selected will be offered the experimental treatment, consisting of focal HDR brachytherapy boost (fBT) of 13-15 Gy in 1 fraction followed by stereotactic radiotherapy (sRT) 36.25-40 Gy in 5 fractions to the prostate (+/- 25 Gy to the elective pelvis) delivered every other day. The primary endpoint is to determine if fBTsRT is superior to SOC by having fewer patients experience a minimally important decline (MID) in urinary function as measured by EPIC-26 at 1 and 2 years. Secondary endpoints include rates of toxicity measured by Common Terminology Criteria for Adverse Events (CTCAE), and failure-free survival outcomes. DISCUSSION: This study will determine whether a novel approach for the treatment of localized prostate cancer, fBTsRT, improves QoL and merits further evaluation. Trial registration This trial was prospectively registered in ClinicalTrials.gov as NCT04100174 as a companion to registry NCT03378856 on September 24, 2019.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".