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.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".