Early Versus Delayed Androgen Deprivation Therapy for Biochemical Recurrence After Local Curative Treatment in Non-Metastatic Hormone-Sensitive Prostate Cancer: A Systematic Review of the Literature
Bibliographic record
Abstract
BACKGROUND: The ideal timing of androgen deprivation therapy (ADT) for patients with biochemical recurrence (BCR) of prostate cancer (PCa) remains controversial due to its side effects and uncertain impact on survival outcomes. METHODS: We performed a review of the current literature by comprehensively searching the PubMed, Embase, and Cochrane databases to determine the optimal timing of ADT initiation after biochemical recurrence. We selected 26 studies including systematic reviews, randomized controlled trials (RCTs), and retrospective studies, while also reviewing practice guidelines. RESULTS: Not all patients with BCR cancer experience clinical or radiological progression. While early ADT may delay progression, evidence of its effect on PCa-specific mortality remains inconclusive. The PSA thresholds for initiating ADT vary, complicating decision-making. Key predictors of progression include a short PSA doubling time (PSADT), a high Gleason score (GS), and a brief interval to BCR of PCa post-radiotherapy (RT). Combining ADT with androgen receptor pathway inhibitors (ARPIs) has been shown to improve metastasis-free survival in high-risk patients. CONCLUSION: The ideal timing of ADT initiation in BCR PCa remains uncertain. Early ADT can help control the progression, but its effect on PCa-specific mortality is unclear. Stratifying patients by their risk factors, such as their PSADT, GS, and time to BCR can guide individualized treatment. In high-risk patients, delaying ADT should be avoided, while combining ADT with an androgen receptor pathway inhibitor (ARPI) may further improve outcomes.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.008 | 0.009 |
| 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) | 0.004 | 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".