MétaCan
Menu
← Back to cohort

Novel androgen receptor inhibitors in nonmetastatic castration-resistant prostate cancer: A network meta-analysis.

2020· article· en· W3006735780 on OpenAlexaff
Amanda Hird, Diana Magee, Bimal Bhindi, Xiang Y. Ye, Thenappan Chandrasekar, Hanan Goldberg, Laurence Klotz, Neil Fleshner, Raj Satkunasivam, Zachary Klaassen, Christopher J.D. Wallis

Bibliographic record

VenueJournal of Clinical Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsHealth Sciences CentreMount Sinai HospitalUniversity of CalgaryPrincess Margaret Cancer CentreUniversity Health NetworkUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineEnzalutamideMeta-analysisProstate cancerAndrogen deprivation therapyOncologyInternal medicinePlaceboRandomized controlled trialAdverse effectAndrogen receptorCancer

Abstract

fetched live from OpenAlex

131 Background: Novel non-steroidal anti-androgens (NSAAs) including enzalutamide, apalutamide, and darolutamide with androgen deprivation therapy (ADT) have proven efficacy in men with high-risk non-metastatic castrate resistant prostate cancer (nmCRPC). However, in the absence of direct comparative trials, there is little evidence to guide therapeutic choice. Our objective was to perform a network meta-analysis to compare agents and perform a class-level meta-analysis of NSAAs with androgen deprivation therapy (ADT) versus ADT-alone. Methods: We performed a systematic review of phase III parallel-group RCTs in men ≥18 years of age with nmCRPC using EMBASE and MEDLINE, indexed as of March 8, 2019. Our primary outcome was metastasis free survival (MFS). Secondary outcomes included OS, PSA progression free survival (PFS), and rates of grade 3-4 adverse events (AEs). Three RCTs were identified. We performed a random effects meta-analysis of NSAA versus ADT-alone using the inverse variance technique for meta-analysis for efficacy outcomes and the Mantel-Haenszel method for meta-analysis of dichotomous data for AEs. We then performed a network meta-analysis to compare outcomes between NSAAs using fixed-effect models in a Bayesian framework. We estimated the relative ranking of the different treatments for each outcome. Results: Pooled MFS, PSA-PFS, and OS were significantly greater with NSAA versus placebo (HR:0.32,95%CI:0.25-0.41, HR:0.08,95%CI:0.05-0.13, and HR:0.74,95%CI:0.61-0.90, respectively). Apalutamide and enzalutamide had a 56% and 44% likelihood of maximizing MFS, respectively. There was a 44%, 41%, and 15% likelihood that apalutamide, darolutamide and enzalutamide offered the greatest OS benefit, respectively. There was a 61% chance that darolutamide was preferred with respect to AEs. Conclusions: NSAAs improve survival outcomes in patients with high-risk nmCRPC. Apalutamide and enzalutamide may offer improved oncological outcomes. Darolutamide may result in fewer adverse events. These differences, if confirmed, would be meaningful to patients and practitioners when selecting treatment.

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)0.021
metaresearch head score (Gemma)0.028
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 score0.021
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.028
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0140.058
Bibliometrics0.0060.006
Science and technology studies0.0000.000
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.335
GPT teacher head0.501
Teacher spread0.166 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical Oncology→Same topicProstate Cancer Treatment and Research→French-language works237,207→