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Record W2898340726 · doi:10.1093/annonc/mdy284.022

Treatment of metastatic castration-resistant prostate cancer (mCRPC); Survival by type of progression at initiation of treatment

2018· article· en· W2898340726 on OpenAlexaff
Debbie Robbrecht, R.J. van Soest, Ian F. Tannock, Stéphane Oudard, Bertrand Tombal, Mario A. Eisenberger, François Mercier, R. de Wit

Bibliographic record

VenueAnnals of Oncology · 2018
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineProstate cancerDocetaxelInternal medicineHazard ratioRandomizationChemotherapyProportional hazards modelOncologyProgression-free survivalCancerSurgeryRandomized controlled trialConfidence interval

Abstract

fetched live from OpenAlex

Background: The usual sequence of progression events in mCRPC patients treated with new hormonal agents is known: PSA progression, followed by radiological progression and finally pain progression (Ryan, NEJM 2013; Beer, NEJM 2014). Although pain was associated with poor overall survival (OS) in the TAX 327 (Berthold, Clin Cancer Res 2008) and CALGB trials (Halabi, JCO 2008), the influence of type of progression on outcomes is not well documented in phase III trials with chemotherapy. Here, we investigated the impact of type of progression on OS in mCRPC patients receiving docetaxel-based chemotherapy. Methods: Data from the phase III study VENICE evaluating docetaxel 75mg/m2 q3w ± aflibercept (Tannock, Lancet Oncol 2013) was used as a training dataset. At randomization, group 1 (G1) had PSA progression only (n = 231), G2 had radiological progression (± PSA) but no pain (n = 348), and G3 had pain (± PSA, ± radiological) (n = 447). The TAX327 definition for pain was used: Mean present pain intensity ≥ 2 and/or mean analgesic score ≥ 10 within 7 days prior to randomization (Tannock, NEJM 2004). The impact of type of progression on OS was evaluated in a multivariate Cox regression analysis with backward elimination (5% level), stratified for ECOG performance status (0-1 vs 2) and treatment arm. Results: In the VENICE trial median OS was 28.6 months for G1, 26.3 months for G2 and 16.9 months for G3. Hazard ratios [95% CI] for death were 1.14 [0.92-1.41] in G2 and 2.13 [1.75 - 2.59] in G3 compared to G1. In multivariate analysis, pain at randomization was the strongest predictor of poor OS: HR 1.71, 95% CI 1.39-2.11, vs PSA progression only. Other significant prognostic factors included older age, high alkaline phosphatase, short duration of first androgen deprivation therapy, low hemoglobin level and high neutrophil-lymphocyte ratio. Docetaxel led to ≥ 50% decline in PSA in 67.5%, 80.5% and 77% in G1, G2 and G3 respectively. Conclusions: The type of progression at initiation of first-line chemotherapy in mCRPC is prognostic. Patients with pain at initiation of chemotherapy had a median OS of ∼1 year shorter than those having PSA progression only. Validation of these results by an independent dataset (TAX 327) is ongoing. Results will be presented at ESMO. Legal entity responsible for the study: Sanofi. Funding: Sanofi. Disclosure: R.J. van Soest: Honoraria: Astellas, Sanofi, Janssen. I.F. Tannock: Data monitoring reimburse: Janssen, Roche. S. Oudard: Personal fees: Sanofi, Janssen, Astellas. B. Tombal: Advisor, investigator: Sanofi-aventis; Janssen Pharmaceuticals, Inc., Takeda, Astellas, Pharma, Inc., Kyocyt. M. Eisenberger: Consultancy: Sanofi. F. Mercier: Research funding: Sanofi. R. de Wit: Consultant: Sanofi, Merck, Roche; Speaker fees: Merck. All other authors have declared no conflicts of interest.

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)0.003
metaresearch head score (Gemma)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.216
GPT teacher head0.503
Teacher spread0.287 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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