Clinical Variables Associated with PSA Response to Lutetium-177-PSMA ([177Lu]-PSMA-617) Radionuclide Treatment in Men with Metastatic Castration-Resistant Prostate Cancer
Bibliographic record
Abstract
Lutetium-177-PSMA ([177Lu]-PSMA-617), a radiolabeled small molecule, binds with high affinity to prostate-specific membrane antigen (PSMA), enabling targeted radiation therapy to metastatic prostate lesions. Our objective was to retrospectively analyze the activity of [177Lu]-PSMA-617 given off-trial to men with metastatic castration resistant prostate cancer (mCRPC) and identify clinical factors associated with PSA response. Electronic medical records of all men treated with [177Lu]-PSMA-617 were reviewed and analyzed. Overall survival was calculated using the Kaplan–Meier method. The association between potential variables and PSA response was analyzed by univariate analysis, using either logistic regression or χ2/Fisher’s exact test. Multivariable analysis was carried out using logistic regression on all categorical variables with a P-value of <0.1 on univariate analysis. Variables found to be statistically significant were then used to define a categorical score. A total of 52 patients received at least one cycle of [177Lu]-PSMA-617. Clinical benefit was observed in 28 patients (52%). PSA decline ≥20% and ≥50% was observed in 26 (50%) and 18 patients (35%), respectively. Achievement of any PSA decline at first measurement was significantly associated with survival. There was a negative association between the number of previous chemotherapy lines and PSA decline above 20%. Univariate analysis followed by multivariable analysis showed that older age and higher hemoglobin were significantly associated with a PSA decline >20%. A score combining these two parameters was significantly associated with PSA response. In summary, [177Lu]-PSMA-617 is active in the ‘real-life’ setting of heavily pretreated men with mCRPC.
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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 | 0.001 |
| 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".