Optimal Duration of Androgen Deprivation Therapy With Definitive Radiotherapy for Localized Prostate Cancer
Bibliographic record
Abstract
Importance: The ideal duration of androgen deprivation therapy (ADT) for treating localized prostate cancer is unknown due to variable adherence and treatment durations tested in clinical trials. Objective: To determine the ideal duration of ADT for patients with prostate cancer treated with radiotherapy. Data Sources: This individual patient data meta-analysis of 13 randomized phase 3 clinical trials evaluated the use of radiotherapy alone or with ADT. It included patients with a median follow-up of 11.3 (IQR, 9.5-14.5) years and ADT duration of 0 to 36 months. Most patients (7392 [72%]) included had National Comprehensive Cancer Network high-risk or very high-risk disease. Study Selection: For this meta-analysis, a systematic literature search from 1980 to 2020 was performed in trial registries (Cochrane Central Register of Controlled Trials and ClinicalTrials.gov), MEDLINE (1966-2020), Embase (1982-2020), Web of Science, and Scopus to identify trials. Data Extraction and Synthesis: Intention-to-treat and as-treated analyses were performed. The number needed to treat to prevent 1 distant metastasis at 10 years was calculated based on prognostic risk group. The analyses were conducted from January 5 to August 15, 2023. Main Outcomes and Measures: The primary end point for this study was overall survival, defined as time to death or last follow-up from randomization. Secondary end points included biochemical recurrence, distant metastasis (DM), prostate cancer-specific mortality, and other-cause mortality. Results: The median (IQR) age among the 10 266 male patients was 70 (65-74) years. Longer durations of ADT were associated with nonlinear improvement in relative benefits of DM, prostate cancer-specific mortality, and overall survival, with reduced estimated benefits beyond 9 to 12 months of ADT based on the end point. There was a near-linear increase in other-cause mortality associated with long-term ADT use (hazard ratio, 1.28; 95% CI, 1.09-1.50; P = .002 for 28 vs 0 months of ADT). The optimal ADT duration based on 10-year DM was 0, 6, 12 months, and undefined for patients with 1 intermediate-risk factor, 2 or more intermediate-risk factors, and National Comprehensive Cancer Network high-risk and very high-risk disease, respectively. Conclusions and Relevance: The results of this meta-analysis suggest that, for men with localized prostate cancer treated with definitive radiotherapy and ADT, there are relative and absolute benefits from increasing durations of ADT that help provide individualized risk estimates.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".