Symptomatic skeletal events, health-related quality of life and pain in a phase III study of [177Lu]Lu-PSMA-617 in taxane-naive patients with PSMA-positive metastatic castration-resistant prostate cancer: Third interim analysis of PSMAfore
Bibliographic record
Abstract
Ziel/Aim: In PSMAfore (NCT04689828), [ 177 Lu]Lu-PSMA-617 ( 177 Lu-PSMA-617) prolonged rPFS versus androgen receptor pathway inhibitor (ARPI) change in taxane-naive patients with PSMA-positive metastatic castration-resistant prostate cancer (mCRPC). We now present the time to symptomatic skeletal events (SSE) and time to worsening (TTW) in health-related quality of life (HRQoL) and pain at the third interim analysis (data cutoff, 27 Feb 2024). Methodik/Methods: Eligible patients had mCRPC, were candidates for ARPI change after one progression on previous ARPI, and had≥1 PSMA-positive and no exclusionary PSMA-negative metastatic lesions by [ 68 Ga]Ga-PSMA-11 PET/CT. Patients were randomized 1:1 to open-label 177 Lu-PSMA-617 (7.4 GBq q6w; 6 cycles) or ARPI change (abiraterone/enzalutamide). Patients with confirmed radiographic progression on ARPI change could cross over to 177 Lu-PSMA-617. The primary endpoint was rPFS. Other endpoints included time to SSE and TTW in self-reported HRQoL (FACT-P, EQ-5D-5L; secondary) and pain (BPI-SF; exploratory). Ergebnisse/Results: In total, 468 patients (234/arm) were randomized. Median duration of exposure was 8.4 months for 177 Lu-PSMA-617 and 6.5 months for ARPI change. 177 Lu-PSMA-617 prolonged time to SSE (27 [11.5%] vs 63 [26.9%]) and fewer bone fractures were reported versus ARPI change (4 [1.7%] vs 13 [5.6%]). 177 Lu-PSMA-617 prolonged TTW in FACT-P (7,46 [6.08, 8.54]vs 4.27 [3.45, 4.50]), EQ-5D-5L (6,28 [4.70, 7.86] vs 3.88 [3.25, 4.44]) and BPI-SF (5.13 [4.11, 6.14] vs 3.65 [3.05, 4.34]) versus ARPI change. Incidences of grade≥3 adverse events (AEs), serious AEs and AEs leading to discontinuation for 177 Lu-PSMA-617 and ARPI change were 36% and 48%, 20% and 32%, and 5.7% and 5.2%, respectively. Schlussfolgerungen/Conclusion: 177 Lu-PSMA-617 clinically meaningfully and significantly prolonged time to SSE and TTW in self-reported HRQoL and pain versus ARPI change in taxane-naive patients with PSMA-positive mCRPC. The presenter Prof. Matthias Eiber was not part of the original analysis (Original
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".