The role of androgen deprivation therapy prior to radical prostatectomy in high-risk prostate cancer: a systematic review
Bibliographic record
Abstract
INTRODUCTION: Patients with high-risk prostate cancer (HRPCa) are prone to have worse pathological features, resulting in early biochemical recurrence after radical prostatectomy (RP). There is an urgent need to develop novel treatment strategies for this group of patients to optimize their outcomes. The purpose of this study is to perform a systematic review of the role of neoadjuvant hormonal therapy (NHT) followed by RP in HRPCa patients. EVIDENCE ACQUISITION: We performed a systematic review of the following databases, MEDLINE (PubMed), EMBASE, Cochrane Library, and clinical Trial.gov; between January 2007 and August 2023, following the PRISMA guidelines. EVIDENCE SYNTHESIS: After screening and deduplication, we included ten studies from an initial pool of 1275. The risk of bias was low in observational studies but ranged from moderate to low in controlled trials. Five studies utilized traditional androgen deprivation treatments (ADT), revealing favorable pathological outcomes but inconsistency in evaluating oncological results. Additionally, four studies focused on RP combined with androgen receptor pathway inhibitors (ARPIs) in the NHT setting, all showing primarily positive pathological outcome, with no clear evidence of an oncological benefit. Limited long-term follow-up data and a shortage of randomized controlled trials were evident among all the studies included in this review, regardless of the type of hormonal treatment used. CONCLUSIONS: Different hormonal treatments, including traditional ADT and ARPIs, yield positive pathology outcomes. Oncological evidence remains limited, echoing older findings predating ARPIs. Definitive conclusions require longer follow-ups and precise patient selection. Currently, insufficient evidence support ARPIs' superiority over conventional therapy before RP.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.010 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".