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Record W4313398715 · doi:10.1016/j.ijrobp.2022.12.035

Analysis of a Biopsy-Based Genomic Classifier in High-Risk Prostate Cancer: Meta-Analysis of the NRG Oncology/Radiation Therapy Oncology Group 9202, 9413, and 9902 Phase 3 Randomized Trials

2022· review· en· W4313398715 on OpenAlexaff
Paul L. Nguyen, Huei–Chung Huang, Daniel E. Spratt, Elai Davicioni, Howard M. Sandler, William U. Shipley, Jason A. Efstathiou, Jeffry Simko, Alan Pollack, Adam P. Dicker, Mack Roach, Seth A. Rosenthal, Kenneth L. Zeitzer, Lucas C. Mendez, Alan C. Hartford, William A. Hall, Anand Desai, Rachel Rabinovitch, Christopher A. Peters, Joseph P. Rodgers, Phuoc T. Tran, Felix Y. Feng

Bibliographic record

VenueInternational Journal of Radiation Oncology*Biology*Physics · 2022
Typereview
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsCancer Care OntarioGenome British ColumbiaDecipher Biosciences (Canada)
FundersNational Cancer InstituteNational Institutes of HealthUniversity of MiamiSylvester Comprehensive Cancer Center, University of Miami Health SystemsNRG OncologyPfizerBristol-Myers Squibb
KeywordsMedicineHazard ratioInternal medicineProstate cancerInterquartile rangeOncologyRandomized controlled trialProstatectomyRadiation therapyConfidence intervalConcordanceBiopsyCancer

Abstract

fetched live from OpenAlex

PURPOSE: Decipher is a genomic classifier (GC) prospectively validated postprostatectomy. We validated the performance of the GC in pretreatment biopsy samples within the context of 3 randomized phase 3 high-risk definitive radiation therapy trials. METHODS AND MATERIALS: A prespecified analysis plan (NRG-GU-TS006) was approved to obtain formalin-fixed paraffin-embedded tissue from biopsy specimens from the NRG biobank from patients enrolled in the NRG/Radiation Therapy Oncology Group (RTOG) 9202, 9413, and 9902 phase 3 randomized trials. After central review, the highest-grade tumors were profiled on clinical-grade whole-transcriptome arrays and GC scores were obtained. The primary objective was to validate the independent prognostic ability for the GC for distant metastases (DM), and secondary for prostate cancer-specific mortality (PCSM) and overall survival (OS) with Cox univariable and multivariable analyses. RESULTS: GC scores were obtained on 385 samples, of which 265 passed microarray quality control (69%) and had a median follow-up of 11 years (interquartile range, 9-13). In the pooled cohort, on univariable analysis, the GC was shown to be a prognostic factor for DM (per 0.1 unit; subdistribution hazard ratio [sHR], 1.29; 95% confidence interval [CI], 1.18-1.41; P < .001), PCSM (sHR, 1.28; 95% CI, 1.16-1.41; P < .001), and OS (hazard ratio [HR], 1.16; 95% CI, 1.08-1.22; P < .001). On multivariable analyses, the GC (per 0.1 unit) was independently associated with DM (sHR, 1.22; 95% CI, 1.09-1.36), PCSM (sHR, 1.23; 95% CI, 1.09-1.39), and OS (HR, 1.12; 95% CI, 1.05-1.20) after adjusting for age, Prostate Specific Antigen, Gleason score, cT stage, trial, and randomized treatment arm. GC had similar prognostic ability in patients receiving short-term or long-term androgen-deprivation therapy, but the absolute improvement in outcome varied by GC risk. CONCLUSIONS: This is the first validation of a gene expression biomarker on pretreatment prostate cancer biopsy samples from prospective randomized trials and demonstrates an independent association of GC score with DM, PCSM, and OS. High-risk prostate cancer is a heterogeneous disease state, and GC can improve risk stratification to help personalize shared decision making.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.039
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.039
Threshold uncertainty score0.206

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.032
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.023
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.129
GPT teacher head0.443
Teacher spread0.315 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations51
Published2022
Admission routes1
Has abstractyes

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