Validation of the performance of the Decipher biopsy genomic classifier in intermediate-risk prostate cancer on the phase III randomized trial NRG Oncology/RTOG 0126.
Bibliographic record
Abstract
269 Background: The 22-gene Decipher genomic classifier (GC) is a prognostic biomarker that has been validated in phase III trials in high-risk localized, post-prostatectomy, and metastatic and non-metastatic castration-resistant prostate cancer. Herein, we report the first validation of the biopsy GC in intermediate-risk prostate cancer from the phase III randomized trial NRG/RTOG 0126. Methods: After National Cancer Institute approval, biopsy slides were collected from the NRG biobank from RTOG 0126, a phase III randomized trial of men with intermediate-risk prostate cancer randomized to 70.2 Gy versus 79.2 Gy of radiotherapy without the use of concomitant hormone therapy. RNA was extracted from the highest grade tumor foci and processed through a quality control (QC) pipeline prior to generation of the previously locked 22-gene GC model. After GC data was generated it was linked with clinical outcomes to assess prognostic performance. The primary endpoint for this ancillary project was disease progression, defined as biochemical failure, local failure, distant metastasis or prostate cancer-specific mortality, as well as use of salvage therapy. Secondary endpoints included the previous individual endpoints, metastasis-free survival, and overall survival. Independent GC prognostic performance was assessed using cause-specific Cox or competing risk adjusted Fine-Gray multivariable models that included randomization arm and prognostic stratification factors. Death without events were treated as competing risks. Results: A total of 215 patient samples passed QC of the 449 that had suitable cDNA for expression analysis. The median follow-up was 12.8 years (range 2.4-17.7), and 61% had Gleason 3+4, 24% had Gleason 4+3, and the median PSA was 7.2 ng/mL (IQR 5.0-10.2). On multivariable analysis the 22-gene GC (per 0.1 unit) was independently prognostic for disease progression (subdistribution hazard ratio [sHR] 1.13, 95%CI (1.01-1.26), p = 0.03), biochemical failure (sHR 1.23, 95%CI 1.10-1.37, p < 0.001), distant metastasis (sHR 1.28, 95%CI 1.06-1.54, p = 0.01), and PCSM (sHR 1.45, 95%CI 1.20-1.76, p < 0.001). In patients with lower GC scores the 10-year distant metastasis rate difference between the 70.2 Gy and 79.2 Gy was 5%, as compared with 26% for higher GC patients. Conclusions: This study represents the first validation of any biopsy-based gene expression classifier in intermediate-risk prostate cancer. Decipher is independently prognostic and can identify patients that have low rates of metastatic events despite not receiving concurrent hormone therapy, and can be used to help personalize therapy in this setting. Clinical trial information: NCT00033631.
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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 | 0.017 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".