Skeletal related events (SREs) in metastatic androgen independent prostate cancer (AIPC) treated with docetaxel-based chemotherapy: Results from ASCENT
Bibliographic record
Abstract
4614 Background: Docetaxel prolongs survival in AIPC patients and zoledronic acid (ZA) reduces the incidence of SREs. The SRE incidence of patients treated with docetaxel-based chemotherapy has not previously been reported. Methods: ASCENT was a randomized clinical trial that compared weekly DN-101 (calcitriol, 45 μg p.o. on day 1) plus docetaxel (36 mg/m2 iv on day 2 for 3 weeks of a 4-week cycle) to placebo plus docetaxel in patients with chemotherapy-naïve metastatic AIPC. ZA use was not restricted. SRE-free survival was described for the entire group and then compared for patients randomly assigned to DN-101 or placebo and stratified by ZA use. Statistical comparisons were conducted using Cochran-Mantel-Haenszel for incidence and log-rank for SRE-free survival. Results: With a median follow-up of 18.3 months, 33% of subjects experienced at least one SRE and the overall median SRE-free survival was 13 (95% CI 10.5–14.3) months. The incidence of SRE by type was: radiation to bone (18.8%), fracture (10%), spinal cord compression (4%), surgery to bone (0.4%). Eighty-five (34%) patients received ZA. The study was not adequately powered to measure the impact of DN-101 or ZA on SRE endpoints. Exploratory analyses showed a trend for an increase in SRE-free survival (HR 0.78, p = 0.13) of DN-101-treated patients. SRE-free survival and incidence for subgroups were examined ( Table ). Conclusions: This is the first report of SRE incidence in a large, prospective study of docetaxel-based therapy. Improved therapies for reducing SREs in AIPC are needed because the risk of SREs remains high despite the use of modern chemotherapy and ZA. [Table: see text] [Table: see text]
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".