PD11-03 RESPONSE TO APALUTAMIDE (APA) AMONG PATIENTS (PTS) WITH NONMETASTATIC CASTRATION-RESISTANT PROSTATE CANCER (NMCRPC) FROM SPARTAN BY DECIPHER GENOMIC CLASSIFIER (GC) SCORE
Bibliographic record
Abstract
You have accessJournal of UrologyProstate Cancer: Markers I (PD11)1 Apr 2019PD11-03 RESPONSE TO APALUTAMIDE (APA) AMONG PATIENTS (PTS) WITH NONMETASTATIC CASTRATION-RESISTANT PROSTATE CANCER (NMCRPC) FROM SPARTAN BY DECIPHER GENOMIC CLASSIFIER (GC) SCORE Fred Saad*, Shibu Thomas, Felix Y. Feng, Michael Gormley, Angela Lopez-Gitlitz, Margaret K. Yu, Shinta Cheng, Deborah S. Ricci, Oliver Brendan Rooney, Paul N. Mainwaring, David Olmos, Simon Chowdhury, Boris A. Hadaschik, Nick Fishbane, Elai Davicioni, Yang Liu, Eric J. Small, and Matthew R. Smith Fred Saad*Fred Saad* More articles by this author , Shibu ThomasShibu Thomas More articles by this author , Felix Y. FengFelix Y. Feng More articles by this author , Michael GormleyMichael Gormley More articles by this author , Angela Lopez-GitlitzAngela Lopez-Gitlitz More articles by this author , Margaret K. YuMargaret K. Yu More articles by this author , Shinta ChengShinta Cheng More articles by this author , Deborah S. RicciDeborah S. Ricci More articles by this author , Oliver Brendan RooneyOliver Brendan Rooney More articles by this author , Paul N. MainwaringPaul N. Mainwaring More articles by this author , David OlmosDavid Olmos More articles by this author , Simon ChowdhurySimon Chowdhury More articles by this author , Boris A. HadaschikBoris A. Hadaschik More articles by this author , Nick FishbaneNick Fishbane More articles by this author , Elai DavicioniElai Davicioni More articles by this author , Yang LiuYang Liu More articles by this author , Eric J. SmallEric J. Small More articles by this author , and Matthew R. SmithMatthew R. Smith More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000555359.59547.3eAboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: The DECIPHER prostate test (GenomeDx Biosciences, Inc., San Diego, CA) is a clinical-grade mRNA-based test with a genomic classifier (GC) score that has been independently validated for predicting metastatic disease post radical prostatectomy in men with prostate cancer (Klein EA, et al. Eur Urol. 2013). Pts with high GC scores have significantly higher risk for metastasis than pts with low to average GC scores. APA, a next-generation androgen receptor inhibitor, improved metastasis-free survival (MFS) and other secondary end points in the SPARTAN study of pts with nmCRPC with prostate-specific antigen doubling time ≤ 10 months who were receiving androgen deprivation therapy (ADT). We evaluated the effect of APA on MFS in a subgroup of SPARTAN pts grouped by DECIPHER GC score. METHODS: A high-density Affymetrix GeneChip platform (1.4 million genomic loci) was used to assess gene expression in 233 archived primary tumors from pts enrolled in SPARTAN who had been randomized 2:1 to APA+ADT or ADT alone. Gene expression values of 22 markers were used to generate GC scores (≤ 0.6 [low to average] vs > 0.6 [high]) using prevalidated algorithms. Cox proportional hazard model was used to assess association of GC scores with clinical outcomes. RESULTS: Among 233 pts in SPARTAN, 50% had a high DECIPHER GC score. 78 and 39 in APA+ADT and ADT arms, respectively, had high GC scores; 76 and 40 pts in these arms, respectively, had low to average GC scores. Pts with high GC score, who typically have poor prognosis with standard of care (SoC) treatment, including ADT, had improved MFS when treated with APA+ADT vs ADT alone (hazard ratio [HR], 0.21; p < 0.0001). Pts with low to average GC score also had improved MFS with APA+ADT vs ADT alone (HR, 0.46; p = 0.031). There was no difference in MFS with APA+ADT among pts with high GC scores vs those receiving APA+ADT who had low to average GC scores (HR, 1.11; p = 0.741). Similar correlations between GC scores and second progression-free survival, overall survival, and symptomatic progression were observed. CONCLUSIONS: APA+ADT improved MFS and can overcome the negative prognosis associated with high GC scores. To our knowledge, this is the first report of application of the DECIPHER GC score at diagnosis to predict outcomes and therapeutic response in CRPC and the first SoC treatment to overcome negative prognosis. Source of Funding: Janssen Research & Development Montréal, Canada; Spring House, PA; San Francisco, CA; Spring House, PA; Los Angeles, CA; Raritan, NJ; Spring House, PA; High Wycombe, United Kingdom; Brisbane, Australia; Madrid, Spain; London, United Kingdom; Essen, Germany; San Diego, CA; San Francisco, CA; Boston, MA© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e216-e216 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Fred Saad* More articles by this author Shibu Thomas More articles by this author Felix Y. Feng More articles by this author Michael Gormley More articles by this author Angela Lopez-Gitlitz More articles by this author Margaret K. Yu More articles by this author Shinta Cheng More articles by this author Deborah S. Ricci More articles by this author Oliver Brendan Rooney More articles by this author Paul N. Mainwaring More articles by this author David Olmos More articles by this author Simon Chowdhury More articles by this author Boris A. Hadaschik More articles by this author Nick Fishbane More articles by this author Elai Davicioni More articles by this author Yang Liu More articles by this author Eric J. Small More articles by this author Matthew R. Smith More articles by this author Expand All Advertisement PDF downloadLoading ...
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".