Impact of decipher test on adjuvant and salvage treatments received following radical prostatectomy.
Bibliographic record
Abstract
112 Background: Prostate cancer (PC) patients and providers have tremendous uncertainty as they decide on intervention with adjuvant or salvage radiation therapy (ART, SRT) after radical prostatectomy (RP). We prospectively evaluated the impact of Decipher test, a genomic classifier which predicts metastasis post-RP, on providers’ decision-making for ART and SRT. Methods: 150 men considering ART and 115 men considering SRT from 19 sites across the US were enrolled. Participating providers submitted a management recommendation prior to processing the Decipher test and again after receiving test results. We then followed patients for 12 months to assess actual treatment received and patient reported decisional conflict scale (DCS) and a validated survey on PC-related anxiety. Results: Pre-Decipher, observation was recommended for 89% of adjuvant men and 58% of salvage men. Post-Decipher, 17% of treatment recommendations changed in the adjuvant arm and 30% of recommendations changed in the salvage arm. Among adjuvant men, 78% maintained their recommended management 12 months after Decipher; 76% of salvage men maintained their recommended treatment after Decipher. Among 21 adjuvant men who intensified their treatment (observation to ART or ART to ART plus androgen deprivation therapy), 5 (24%) experienced biochemical recurrence with detectable PSA. In adjuvant men, PC-specific anxiety decreased differently among Decipher risk categories (p-value = 0.045), most notably among Decipher high risk men (9.07 [7.87, 10.26] pre-Decipher, 5.61 [5.35,5.88] 12 months post-Decipher). In salvage men, PC-specific anxiety decreased differently among those whose treatment were concordant (10.28 [8.1,12.47] pre-Decipher, 7.18 [6.82,7.54] 12 months post-Decipher) and those whose treatment were intensified (p-value = 0.01), and decreased differently among low-risk and high-risk Decipher patients (p = 0.04). Conclusions: Use of the Decipher test changed treatment decisions that was consistent with the eventual treatment received in three-fourths of adjuvant and salvage men after RP. Several men that pursued ART experienced PSA progression. PC-specific anxiety decreased in both adjuvant and salvage men. Clinical trial information: NCT02080689.
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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 | 0.009 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".