Systemic therapies for metastatic hormone‐sensitive prostate cancer: network meta‐analysis
Bibliographic record
Abstract
OBJECTIVES: To perform a systematic review and network meta-analysis to compare the efficacy and safety of currently available treatments for the management of metastatic hormone-sensitive prostate cancer (mHSPC), as there has been a paradigm shift with the use of next-generation androgen receptor inhibitors (ARIs) and docetaxel. METHODS: Multiple databases were searched for articles published before May 2020 according to the Preferred Reporting Items for Systematic Review and Meta-analysis extension statement for network meta-analysis. Studies comparing overall/progression-free survival (OS/PFS) and/or adverse events (AEs) in patients with mHSPC were eligible. RESULTS: Nine studies (N = 9960) were selected, and formal network meta-analyses were conducted. Abiraterone (hazard ratio [HR] 0.83, 95% credible interval [CrI] 0.76-0.90), docetaxel (HR 0.90, 95% CrI 0.82-0.98), and enzalutamide (HR 0.85, 95% CrI 0.73-0.99) were associated with significantly better OS than androgen-deprivation therapy (ADT), and abiraterone emerged as the best option. Abiraterone (HR 0.71, 95% CrI 0.67-0.76), apalutamide (HR 0.73, 95% CrI 0.65-0.81), docetaxel (HR 0.84, 95% CrI 0.78-0.90), and enzalutamide (HR 0.67, 95% CrI 0.63-0.71) were associated with significantly better PFS than ADT, and enzalutamide emerged as the best option. Abiraterone (HR 0.85, 95% CrI 0.78-0.93), apalutamide (HR 0.87, 95% CrI 0.77-0.98), and enzalutamide (HR 0.80, 95% CrI 0.73-0.88) were significantly more effective than docetaxel. Regarding AEs, apalutamide was the likely best option among the three ARIs. In patients with low-volume mHSPC, enzalutamide was the best option in terms of OS and PFS. CONCLUSIONS: All three ARIs are effective therapies for mHSPC; apalutamide was the best tolerated. All three seemed more effective than docetaxel. These findings may facilitate individualised treatment strategies and inform future comparative trials.
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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) | 0.008 | 0.005 |
| 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) | 0.000 | 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".