MétaCan
Menu
Back to cohort

TheraP: <sup>177</sup>Lu-PSMA-617 (LuPSMA) versus cabazitaxel in metastatic castration-resistant prostate cancer (mCRPC) progressing after docetaxel—Overall survival after median follow-up of 3 years (ANZUP 1603).

2022· article· en· W4286296265 on OpenAlexaff
Michael S. Hofman, Louise Emmett, Shahneen Sandhu, Amir Iravani, Anthony M. Joshua, Jeffrey C. Goh, David A. Pattison, Thean Hsiang Tan, Ian Kirkwood, Roslyn J. Francis, Craig Gedye, Natalie Rutherford, Alison Yan Zhang, Margaret McJannett, Martin R. Stockler, Scott Williams, Andrew Martin, Ian D. Davis

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsCabazitaxelMedicineDocetaxelProstate cancerInternal medicineOncologyClinical endpointHazard ratioProgression-free survivalCancerOverall survivalUrologyNuclear medicineClinical trialConfidence intervalAndrogen deprivation therapy

Abstract

fetched live from OpenAlex

5000 Background: We previously reported that in men with mCRPC progressing after docetaxel randomly assigned LuPSMA vs. cabazitaxel (Lancet 2021), those assigned LuPSMA has significant improvements in PSA response rate (66% vs. 37%), RECIST response rate (49% vs. 24%), progression-free survival (HR 0.63), less G3-4 toxicities (33% vs. 53%) and better patient-reported outcomes. We now report the secondary endpoint of overall survival (OS) with mature follow-up, for trial participants, and also those initially excluded because of low PSMA-expression or discordant disease on imaging with PSMA-PET and FDG-PET. Methods: Eligibility for the TheraP trial required mCRPC progressing after docetaxel, PET imaging with 68 Ga-PSMA-11 that showed high PSMA-expression (at least one site with SUVmax≥20), and 18 F-FDG demonstrating no sites of disease of FDG-positive and PSMA-negative (discordant disease). Participants were randomly assigned treatment with LuPSMA (8.5-6GBq every 6 weeks, maximum 6 cycles) vs cabazitaxel (20mg/m 2 every 3 weeks, maximum 10 cycles). OS was analyzed by intention-to-treat and summarized by restricted mean survival time (RMST) to account for non-proportional hazards. Results: 291 patients were screened from 6 Feb 2018 to 3 Sep 2019: 200 were eligible and randomly assigned LuPSMA (99) or cabazitaxel (101); 80 of 291 (27%) registered after initial eligibility were excluded after PSMA/FDG-PET(51 SUVmax &lt; 20, 29 discordant), with follow-up available in 61 of the 80 (76%). After a median follow-up time of 36 months (data cut-off 31 Dec 2021), death was reported in 70/101 assigned cabazitaxel, 77/99 assigned LuPSMA, and 55/61 excluded after PSMA/FDG-PET. Subsequent treatments among those assigned cabazitaxel included cabazitaxel in 21, and LuPSMA in 20; and among those assigned LuPSMA included additional LuPSMA in 5, and cabazitaxel in 32. Overall survival was similar in those randomly assigned LuPSMA versus cabazitaxel (RMST to 36 months was 19.1 vs. 19.6 months, difference -0.5, 95% CI -3.7 to + 2.7). No additional safety signals were identified with longer follow-up. Among 61 men excluded by imaging with PSMA/FDG-PET before randomisation, RMST to 36 months was 11.0 months (95% CI 9.0 to 13.1), following treatment that included cabazitaxel in 29 (48%) and LuPSMA in 3 (5%). Conclusions: LuPSMA is a suitable option for men with mCRPC progressing after docetaxel, with lower adverse events, higher response rates, improved patient-reported outcomes, and similar OS compared with cabazitaxel. Median survival was considerably shorter for patients excluded on PSMA/FDG-PET due to either low PSMA expression or FDG-discordant disease who would otherwise be eligible for LuPSMA. Clinical trial information: NCT03392428.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.399
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.131
GPT teacher head0.463
Teacher spread0.332 · 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 teacher head, not a consensus.

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

Citations54
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical OncologySame topicProstate Cancer Treatment and ResearchFrench-language works237,207