Multivariable models of outcomes with [177Lu]Lu-PSMA-617: analysis of the phase 3 VISION trial
Bibliographic record
Abstract
Background [ 177 Lu]Lu-PSMA-617 ( 177 Lu-PSMA-617) prolonged life in patients with metastatic castration-resistant prostate cancer (mCRPC) in VISION (NCT03511664). However, distinguishing between patients likely and unlikely to respond remains a clinical challenge. We present the first multivariable models of outcomes with 177 Lu-PSMA-617 built using data from VISION, a large prospective phase 3 clinical trial powered for overall survival. Methods Adults with progressive post androgen receptor pathway inhibitor and taxane prostate-specific membrane antigen (PSMA)-positive mCRPC received 177 Lu-PSMA-617 plus protocol-permitted standard of care (SoC) or SoC alone. In this post hoc analysis, multivariable Cox proportional hazards models of overall survival (OS) and radiographic progression-free survival (rPFS), and a logistic regression model of prostate-specific antigen response (≥50% decline; PSA50) were constructed and evaluated using C-index or receiver operating characteristic (ROC) analyses with bootstrapping validation. Nomograms were constructed for visualisation. Findings Patients were randomised between June 2018 and October 2019. Data from all 551 patients in the 177 Lu-PSMA-617 arm were analysed in multivariable modelling. The OS nomogram (C-index, 0.73; 95% confidence interval [CI], 0.70–0.76) included whole-body maximum standardised uptake value (SUV max ), time since diagnosis, opioid analgesic use, aspartate aminotransferase, haemoglobin, lymphocyte count, presence of PSMA-positive lesions in lymph nodes, lactate dehydrogenase (LDH), alkaline phosphatase (ALP), and neutrophil count. The rPFS nomogram (C-index, 0.68; 0.65–0.72) included SUV max , time since diagnosis, opioid analgesic use, lymphocyte count, presence of liver metastases by computed tomography, LDH, and ALP. The PSA50 nomogram (area under ROC curve, 0.72; 95% CI, 0.68–0.77) included SUV max , lymphocyte count and ALP. Performances of the OS and rPFS models were maintained when they were reconstructed excluding SUV max . Interpretation These models of outcomes with 177 Lu-PSMA-617 are the first built using prospective phase 3 data. They show that a combination of pretreatment laboratory, clinical, and imaging parameters, reflecting both patient and tumour status, influences outcomes. These models are important for aiding treatment selection, patient management, and clinical trial design. Funding Novartis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".