Characterizing Surgical and Radiotherapy Outcomes in Non-metastatic High-Risk Prostate Cancer: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background Identifying the optimal management of high-risk non-metastatic prostate cancer (PCa) is an important public health concern, given the large burden of this disease. We performed a meta-analysis of studies comparing PCa-specific mortality (CSM) among men diagnosed with high-risk non-metastatic PCa who were treated with primary radiotherapy (RT) and radical prostatectomy (RP). Methods Medline and Embase were searched for articles between January 1, 2005, and February 11, 2020. After title and abstract screening, two authors independently reviewed full-text articles for inclusion. Data were abstracted, and a modified version of the Newcastle-Ottawa Scale, involving a comprehensive list of confounding variables, was used to assess the risk of bias. Results Fifteen studies involving 131,392 patients were included. No difference in adjusted CSM in RT relative to RP was shown (hazard ratio, 1.02 [95% confidence interval: 0.84, 1.25]). Increased CSM was found in a subgroup analysis comparing external beam radiation therapy (EBRT) with RP (1.35 [1.10, 1.68]), whereas EBRT combined with brachytherapy (BT) versus RP showed lower CSM (0.68 [0.48, 0.95]). All studies demonstrated a high risk of bias as none fully adjusted for all confounding variables. Conclusion We found no difference in CSM between men diagnosed with non-metastatic high-risk PCa and treated with RP or RT; however, this is likely explained by increased CSM in men treated with EBRT and decreased CSM in men treated with EBRT + BT studies relative to RP. High risk of bias in all studies identifies the need for better data collection and confounding control in the PCa research.
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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 | 0.018 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.040 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".