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Record W2793000264 · doi:10.1001/jamaoncol.2017.5808

Radiographic Progression-Free Survival as a Clinically Meaningful End Point in Metastatic Castration-Resistant Prostate Cancer

2018· article· en· W2793000264 on OpenAlexfundno aff
Dana E. Rathkopf, Tomasz M. Beer, Yohann Loriot, Celestia S. Higano, Andrew J. Armstrong, Cora N. Sternberg, Johann S. de Bono, Bertrand Tombal, Teresa Parli, Suman Bhattacharya, De Phung, Andrew Krivoshik, Howard I. Scher, Michael J. Morris

Bibliographic record

VenueJAMA Oncology · 2018
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsnot available
FundersNational Cancer InstituteNational Institutes of HealthActive BiotechAstellas PharmaEisaiIpsenClovis OncologyAdvanced Accelerator ApplicationsEndocyteGilead SciencesGenentechValeant Pharmaceuticals InternationalSanofiGlaxoSmithKlineAmgenPfizerAstraZenecaEli Lilly and CompanyBristol-Myers Squibb
KeywordsMedicineProstate cancerEnzalutamideOncologyInternal medicineProgression-free survivalClinical endpointClinical trialPlaceboDiscontinuationCancerChemotherapyPathology

Abstract

fetched live from OpenAlex

Importance: Drug development for metastatic castration-resistant prostate cancer has been limited by a lack of clinically relevant trial end points short of overall survival (OS). Radiographic progression-free survival (rPFS) as defined by the Prostate Cancer Clinical Trials Working Group 2 (PCWG2) is a candidate end point that represents a clinically meaningful benefit to patients. Objective: To demonstrate the robustness of the PCWG2 definition and to examine the relationship between rPFS and OS. Design, Setting, and Participants: PREVAIL was a phase 3, randomized, double-blind, placebo-controlled multinational study that enrolled 1717 chemotherapy-naive men with metastatic castration-resistant prostate cancer from September 2010 through September 2012. The data were analyzed in November 2016. Interventions: Patients were randomized 1:1 to enzalutamide 160 mg or placebo until confirmed radiographic disease progression or a skeletal-related event and initiation of either cytotoxic chemotherapy or an investigational agent for prostate cancer treatment. Main Outcomes and Measures: Sensitivity analyses (SAs) of investigator-assessed rPFS were performed using the final rPFS data cutoff (May 6, 2012; 439 events; SA1) and the interim OS data cutoff (September 16, 2013; 540 events; SA2). Additional SAs using investigator-assessed rPFS from the final rPFS data cutoff assessed the impact of skeletal-related events (SA3), clinical progression (SA4), a confirmatory scan for soft-tissue disease progression (SA5), and all deaths regardless of time after study drug discontinuation (SA6). Correlations between investigator-assessed rPFS (SA2) and OS were calculated using Spearman ρ and Kendall τ via Clayton copula. Results: In the 1717 men (mean age, 72.0 [range, 43.0-93.0] years in enzalutamide arm and 71.0 [range, 42.0-93.0] years in placebo arm), enzalutamide significantly reduced risk of radiographic progression or death in all SAs, with hazard ratios of 0.22 (SA1; 95% CI, 0.18-0.27), 0.31 (SA2; 95% CI, 0.27-0.35), 0.21 (SA3; 95% CI, 0.18-0.26), 0.21 (SA4; 95% CI, 0.17-0.26), 0.23 (SA5; 95% CI, 0.19-0.30), and 0.23 (SA6; 95% CI, 0.19-0.30) (P < .001 for all). Correlations of rPFS and OS in enzalutamide-treated patients were 0.89 (95% CI, 0.86-0.92) by Spearman ρ and 0.72 (95% CI, 0.68-0.77) by Kendall τ. Conclusions and Relevance: Sensitivity analyses in PREVAIL demonstrated the robustness of the PCWG2 rPFS definition using additional measures of progression. There was concordance between central and investigator review and a positive correlation between rPFS and OS among enzalutamide-treated patients. Trial Registration: clinicaltrials.gov Identifier: NCT01212991.

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)0.053
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.278

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0530.033
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.050
GPT teacher head0.425
Teacher spread0.375 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations57
Published2018
Admission routes1
Has abstractyes

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