Local treatment for metastatic prostate cancer: A systematic review
Bibliographic record
Abstract
The potential oncological benefit for radical treatment in the setting of oligometastatic prostate cancer has been under investigation and is frequently discussed. We carried out a systematic review of English language articles using the Medline database (January 2000 to May 2017) to identify studies reporting local treatment in men with metastatic prostate cancer at diagnosis. Primary end-points were oncological outcomes, such as cancer-specific and overall mortality. Secondary end-points were non-oncological outcomes, such as complications, operating room time, blood loss or length of hospital stay. Two independent authors reviewed and extracted all search results. Overall, 18 studies reporting on local treatment in metastatic prostate cancer patients were identified (14 original articles, three brief correspondences and one letter to the editor). All of them were retrospective; one partly included prospective data. All studies addressed oncological outcomes, 16 compared local treatment with no-local treatment and 14 adjusted for confounders using multivariable regression models. All but one study concluded a survival benefit for local treatment in the metastatic setting. Due to heterogeneity of available data, a representative meta-analysis could not be carried out. Five studies reported non-oncological outcomes. Although local treatment in metastatic prostate cancer appears to be feasible, its oncological effect remains unclear due to high susceptibility of available studies to significant selection bias.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".