PD15-07 IMPACT OF BONE-TARGETED THERAPIES IN PATIENTS WITH CHEMOTHERAPY-NAIVE METASTATIC CASTRATION-RESISTANT PROSTATE CANCER ON ENZALUTAMIDE: A POST HOC ANALYSIS OF PREVAIL
Bibliographic record
Abstract
You have accessJournal of UrologyProstate Cancer: Advanced (including Drug Therapy) I (PD15)1 Apr 2019PD15-07 IMPACT OF BONE-TARGETED THERAPIES IN PATIENTS WITH CHEMOTHERAPY-NAIVE METASTATIC CASTRATION-RESISTANT PROSTATE CANCER ON ENZALUTAMIDE: A POST HOC ANALYSIS OF PREVAIL Fred Saad*, Neal D. Shore, Karim Fizazi, Joyce Steinberg, Janet Kim, Ping Lin, Katharina Modelska, and Tomasz M. Beer Fred Saad*Fred Saad* More articles by this author , Neal D. ShoreNeal D. Shore More articles by this author , Karim FizaziKarim Fizazi More articles by this author , Joyce SteinbergJoyce Steinberg More articles by this author , Janet KimJanet Kim More articles by this author , Ping LinPing Lin More articles by this author , Katharina ModelskaKatharina Modelska More articles by this author , and Tomasz M. BeerTomasz M. Beer More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000555460.30099.9fAboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: Enzalutamide (ENZA) prolongs radiographic progression-free survival (rPFS) and overall survival (OS) in men with chemotherapy-naive metastatic castration-resistant prostate cancer (mCRPC). Men with mCRPC are at high risk of developing bone metastases; skeletal complications of bone metastases contribute to morbidity, pain, and death. In this exploratory post hoc analysis of PREVAIL, we analyzed clinical outcomes associated with bone-targeted therapies (BTT) and ENZA vs. ENZA alone. METHODS: The Phase 3 PREVAIL study (NCT01212991) randomized men with mCRPC 1:1 to ENZA (160 mg) or placebo (PBO) with continued androgen-deprivation therapy. Target population for this post hoc analysis was men with bone metastases at baseline, grouped by pre-study baseline BTT use. Co-primary endpoints were rPFS and OS. Eastern Cooperative Oncology Group performance status (ECOG PS) deterioration was defined as time from randomization to first evidence of ECOG PS deterioration by ≥1 grade. Results are presented as hazard ratio (HR) (95% confidence interval [CI]). RESULTS: Of 1429 men, 410 had pre-study BTT use (ENZA, n=534; ENZA + BTT, n=206; PBO, n=485; PBO + BTT, n=204). The risk of rPFS was similar between ENZA + BTT and ENZA alone (HR [95% CI]=1.05 [0.69, 1.60], p=0.4408), whereas the risk of death was higher in ENZA + BTT vs. ENZA alone (1.44 [1.08, 1.92], p=0.0076) (Table). There was a 31% reduction in the risk of rPFS in PBO + BTT vs. PBO alone (0.69 [0.52, 0.93], p=0.0075), and the risk of death was similar between PBO + BTT and PBO alone (0.90 [0.69, 1.19], p=0.2669). The risk of ECOG PS deterioration was similar between ENZA + BTT and ENZA alone (1.06 [0.84, 1.33], p=0.6367), and between PBO + BTT and PBO alone (0.94 [0.74, 1.20], p=0.3615). CONCLUSIONS: In men from PREVAIL with bone metastases at baseline, pre-study BTT use with ENZA was not associated with improved clinical outcomes vs. ENZA alone. rPFS was improved in men taking PBO + BTT vs. PBO alone. The results of these exploratory analyses suggest that BTTs do not improve outcomes in combination with first-line ENZA in mCRPC. Further analysis of optimal timing and combinations when using BTTs remains relevant. Source of Funding: This study was funded by Astellas Pharma Inc. and Medivation LLC, a Pfizer Company, the co-developers of enzalutamide. Medical writing assistance was provided by Patrick Gonyo, PhD, and editorial assistance was provided by Jane Beck from Complete HealthVizion, funded by the study sponsors. Montreal, QC; Myrtle Beach, SC; Villejuif, France; Northbrook, IL; San Francisco, CA; Portland, OR© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e239-e240 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Fred Saad* More articles by this author Neal D. Shore More articles by this author Karim Fizazi More articles by this author Joyce Steinberg More articles by this author Janet Kim More articles by this author Ping Lin More articles by this author Katharina Modelska More articles by this author Tomasz M. Beer 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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".