The Tyr Phenomenon: A Hypocalcemic Response in High-Volume Treatment Responders to<sup>177</sup>Lu-Prostate-Specific Membrane Antigen Therapy
Bibliographic record
Abstract
177Lu-prostate-specific membrane antigen (PSMA) is an effective treatment for metastatic castration-resistant prostate cancer. Rarer treatment-related adverse events have not yet been described. Methods: We present case reviews of 2 men with a marked hypocalcemic osteosclerotic response to 177Lu-PSMA-I&T therapy. A clinical dataset of 177Lu-PSMA-I&T therapy was evaluated to estimate the incidence and clinical association with hypocalcemia. Results: Forty-one of the 127 men (32%) had a serum calcium drop, and 6 (5%) developed clinical hypocalcemia during 177Lu-PSMA therapy. The baseline total tumor volume was significantly higher in those who developed hypocalcemia (median, 3,249 cm3 [interquartile range, 1,856–3,852] vs. 465 [interquartile range 135–1,172]; P = 0.002). The mean prostate-specific antigen response in those with hypocalcemia was 78% (SD, 24%). Conclusion: Hypocalcemia may occur in response to 177Lu-PSMA-I&T, particularly with both high-volume bone metastases and a significant prostate-specific antigen response, and may be severe, requiring corticosteroids. Further evaluation of 177Lu-PSMA–induced hypocalcemia is required to better understand mechanisms, optimal treatments, and repercussions from any subsequent osteosclerotic response.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".