Metastatic progression following multimodal therapy for unfavorable-risk prostate cancer
Bibliographic record
Abstract
INTRODUCTION: Identifying the optimal management of unfavorable-risk (Prostate Cancer Risk Stratification [ProCaRS] high intermediate-, high-, and very high-risk categories) non-metastatic prostate cancer is an important public health concern given the large burden of this disease. We compared the rate of metastatic progression-free survival among men diagnosed with unfavorable-risk non-metastatic prostate cancer who were initially treated with radiation therapy or radical prostatectomy. METHODS: Information was obtained from medical records at two academic centers in Canada from 333 men diagnosed with unfavorable-risk non-metastatic prostate cancer between 2007 and 2012. Median followup was 90.4 months. Men were eligible for the study if they received either primary radiation therapy (n=164) or radical prostatectomy (n=169), in addition to various adjuvant and salvage therapies when deemed clinically appropriate. Patients were matched on prognostic covariates using two matching techniques. Multivariable Cox proportional hazards models were used to estimate the hazard ratios (HR) and confidence intervals (CI) for metastatic progression-free survival between groups. RESULTS: After matching, treatment groups were balanced on prognostic variables except for percent core positivity. Hazard ratios from all Cox proportional hazards models (i.e., before and after matching, and with and without multivariable adjustment) showed no difference in the rate of metastatic progression-free survival between groups (adjusted unmatched HR 1.16, 95% CI 0.63, 2.13, p=0.64). CONCLUSIONS: Metastatic progression-free survival did not differ between men diagnosed with unfavorable risk non-metastatic prostate cancer who were treated with either radiation therapy or radical prostatectomy.
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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 | 0.001 | 0.002 |
| 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) | 0.002 | 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".