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Network meta-analysis (NMA) comparing the efficacy of enzalutamide versus apalutamide, darolutamide, and bicalutamide for treatment of nonmetastatic (nm) castration-resistant prostate cancer (CRPC).

2021· article· en· W3134153606 on OpenAlexaff
Tomasz M. Beer, Fred Saad, Cora N. Sternberg, Maha Hussain, Arijit Ganguli, Hemant Singh Bhadauria, Mok Oh, Konstantina Skaltsa, Bertrand Tombal

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsEnzalutamideBicalutamideMedicineProstate cancerInternal medicineOncologyPlaceboAndrogen deprivation therapyAndrogen receptorClinical endpointAntiandrogenProstate-specific antigenClinical trialCancerPathology

Abstract

fetched live from OpenAlex

101 Background: Enzalutamide is a potent androgen receptor (AR) inhibitor, targeting multiple steps in AR signaling. In recent years, the EMA and FDA approved enzalutamide for the management of adults with CRPC, irrespective of metastatic status, based on the Phase 3 PROSPER clinical trial results. To provide indirect evidence on the relative efficacy of enzalutamide vs bicalutamide or the second-generation AR antagonists apalutamide and darolutamide for the management of nmCRPC, a NMA was performed using published data from their Phase 3 clinical trials. Methods: NMA enables indirect comparison of ≥3 interventions across a network of studies, identified by systematic literature review and based on a common comparator, to estimate relative effects between interventions. This NMA compared data from PROSPER (enzalutamide vs placebo [PBO]), SPARTAN (apalutamide vs PBO), ARAMIS (darolutamide vs PBO), and STRIVE (enzalutamide vs bicalutamide) studies, following NICE technical support document 2. Four key endpoints (metastasis-free survival [MFS], overall survival [OS], time to prostate-specific antigen progression [TTPP], and time to first use of cytotoxic chemotherapy [TTCH]) were assessed. It was assumed that there was no variation between studies that could influence the size of treatment effect. Fixed-effect models were developed and implemented under a Bayesian framework. Results: MFS, OS, and TTCH outcomes of PROSPER, SPARTAN, and ARAMIS were compared between androgen deprivation treatment alone and in combination with enzalutamide/apalutamide/darolutamide. TTPP of PROSPER, SPARTAN, ARAMIS, and STRIVE was compared between enzalutamide, apalutamide, darolutamide, bicalutamide, and PBO. Enzalutamide showed significant benefit vs PBO for all endpoints measured (median hazard ratio [HR] 0.29, 0.73, 0.54, 0.07 for MFS, OS, TTCH, TTPP respectively, Table), vs darolutamide for MFS HR 0.71, and vs darolutamide HR 0.51 and bicalutamide HR 0.18 for TTPP. OS for enzalutamide vs apalutamide was not statistically different HR 0.94. Conclusions: Enzalutamide showed significant therapeutic benefit; MFS, OS, TTCH, and TTPP were better vs PBO and MFS and/or TTPP were longer compared to darolutamide and bicalutamide. No statistically significant differences were observed between enzalutamide and apalutamide. This NMA may facilitate the development and testing of treatment strategies for nmCRPC. [Table: see text]

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)0.033
metaresearch head score (Gemma)0.054
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: Empirical · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.173

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.054
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0140.066
Bibliometrics0.0070.005
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0030.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.426
GPT teacher head0.525
Teacher spread0.099 · 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
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

Citations5
Published2021
Admission routes1
Has abstractyes

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