Duration of Androgen Suppression with Postoperative Radiotherapy (DADSPORT) for Nonmetastatic Prostate Cancer: A Collaborative Systematic Review and Meta-analysis of Aggregate Data
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: To better understand the role of hormone therapy (HT) with postoperative radiotherapy (RT) for nonmetastatic prostate cancer, the DADSPORT Collaboration planned a systematic review and meta-analysis of aggregate data from randomised controlled trials (RCTs). METHODS: RCTs evaluating HT with postoperative RT in people with nonmetastatic prostate cancer were identified. Methods were prespecified prior to results of recent trials being known (CRD42022325769). The primary outcome was overall survival (OS); metastasis-free survival (MFS) and prostate cancer-specific survival (PCSS) were the secondary outcomes. Summary results, including those by prespecified participant subgroups, were obtained from investigators and combined across trials using a fixed-effect meta-analysis. Sensitivity and network meta-analyses evaluated the consistency of findings. KEY FINDINGS AND LIMITATIONS: Five RCTs (six trial comparisons, 4411 participants; 96% of all eligible) were included in the primary analysis. There was no clear evidence that OS was improved with HT (hazard ratio [HR] = 0.86, 95% confidence interval [CI] = 0.74-1.00, p = 0.057; absolute effect 2% [0-3.5%] at 8 yr) or that effects varied by HT duration (p = 0.6). Any benefit of HT on OS appears to be confined to people with higher pre-RT prostate specific antigen levels (p = 0.07) and CAPRA-S scores (p = 0.09). HT significantly improved MFS (HR = 0.78, 95% CI = 0.69-0.88, p < 0.001) and PCSS (HR = 0.61, 95% CI = 0.47-0.79, p < 0.001), with 4% absolute improvements for both outcomes at 8 yr. CONCLUSION AND CLINICAL IMPLICATIONS: Short- or long-course HT after postoperative RT improves MFS and PCSS. Observed improvements in OS are small and may be limited to people with higher-risk factors.
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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 | 0.037 | 0.070 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.051 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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, 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".