The association of type and number of high-risk criteria with cancer-specific mortality in prostate cancer patients treated with radical prostatectomy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objectives: This study aimed to test the association between of type and number of D'Amico high-risk criteria (DHRCs) with cancer-specific mortality (CSM) in high-risk prostate cancer patients treated with radical prostatectomy. Materials and methods: In the Surveillance, Epidemiology, and End Results database (2004-2016), we identified 31,281 radical prostatectomy patients with at least 1 DHRC, namely, prostate-specific antigen (PSA) >20 ng/mL (hrPSA), biopsy Gleason Grade Group (hrGGG) score of 4 and 5, or clinical tumor stage ≥T3 (hrcT). Multivariable Cox regression models and competing risks regression models (adjusting for other cause mortality) tested the association between DHRCs and 5-year CSM. Results: Of 31,281 patients, 14,394 (67%) exclusively harbored hrGGG, 3189 (15%) harbored hrPSA, and 1781 (8.2%) harbored hrcT. Only 2132 patients (6.8%) harbored a combination of the 2 DHRCs, and 138 (0.6%) had all 3 DHRCs. Five-year CSM rates ranged from 0.9% to 3.0% when any individual DHRC was present (hrcT, hrPSA, and hrGGG, in that order), 1.6% to 5.9% when 2 DHRCs were present (hrPSA-hrcT, hrcT-hrGGG, and hrPSA-hrGGG, in that order), and 8.1% when all 3 DHRCs were present. Cox regression models and competing risks regression confirmed the independent predictor status of DHRCs for 5-year CSM that was observed in univariable analyses, with hazard ratios from 1.00 to 2.83 for 1 DHRC, 2.35 to 5.88 for combinations of 2 DHRCs, and 7.13 for all 3 DHRCs. Conclusions: Within individual DHRCs, hrcT and hrPSA exhibited weaker effects than hrGGG did. Moreover, a dose-response effect was identified according to the number of DHRCs. Accordingly, the type and number of DHRCs allow further risk stratification within the high-risk subgroup.
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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 it