Addition of New Androgen Receptor Pathway Inhibitors to Docetaxel and Androgen Deprivation Therapy in Metastatic Hormone-Sensitive Prostate Cancer: A Systematic Review and Metanalysis
Bibliographic record
Abstract
In recent years, significant changes have occurred in metastatic hormone-sensitive prostate cancer (mHSPC) management, where docetaxel and new androgen receptor pathway inhibitors (ARPI) have been shown to improve overall survival (OS) compared to androgen deprivation therapy (ADT). Recent data could once again radically change mHSPC treatment. PEACE-1 and ARASENS trials demonstrated a survival benefit of the addition of ARPI to docetaxel and ADT combination (triplet therapy), compared to docetaxel and ADT. With multiple options to choose from, it is crucial to identify the patients who would benefit most from triplet therapy. In this meta-analysis, we evaluated the activity of the triplet therapy versus docetaxel plus ADT in mHSPC. A systematic review of PubMed/Medline, Embase, and the proceedings of major international meetings was performed. Five RCTs fulfilled the inclusion criteria. PEACE-1 and ARASENS studies reported disease-free survival (DFS) and OS. Post hoc analysis of three other trials evaluated the combination of ARPI, docetaxel and ADT. Globally, 2538 patients were included (1270 triplet therapy; 1268 docetaxel + ADT). Triplet therapy was associated with improved OS (hazard ratio (HR) 0.74; 95% confidence interval (CI), 0.66–0.83, p < 0.00001). A statistically significant benefit was shown in high-volume mHSPC patients (HR 0.76; 95% CI 0.59–0.97, p = 0.03) and in patients with de novo metastatic disease (HR 0.73; 95% CI, 0.64–0.82, p < 0.00001). The addition of ARPI to standard therapy was associated with DFS improvement (HR 0.41; 95% CI, 0.35–0.49, p < 0.00001). This metanalysis shows a significant OS benefit from concomitant administration of ARPI, docetaxel and ADT in high volume and de novo mHSPC.
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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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.038 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".