Renal and Salivary Gland Functions after Three Cycles of PSMA-617 Therapy Every Four Weeks in Patients with Metastatic Castration-Resistant Prostate Cancer
Bibliographic record
Abstract
Background: [177Lu]Lu-PSMA-617 radioligand therapy (PSMA-RLT) could affect kidney and salivary gland functions in metastatic castration-resistant prostate cancer (mCRPC) patients. Methods: We retrospectively analyzed clinical, renal, and salivary scintigraphy data and salivary [68Ga]Ga-PSMA-11 ligand PET scan measures such as metabolic volume and SUVmax values of 27 mCRPC men (mean age 71 ± 7 years) before and 4 weeks after receiving three cycles of PSMA-RLT every 4 weeks. Twenty-two patients additionally obtained renal and salivary scintigraphy prior to each cycle. A one-way ANOVA, post-hoc Scheffé test and Cochran’s Q test were applied to assess organ toxicity. Results: In total, 54 PSMA PET scans, 98 kidney, and 98 salivary scintigraphy results were evaluated. There were no significant differences for the ejection fraction, peak time, and residual activity after 5 min for both parotid and submandibular glands prior to each cycle and 4 weeks after the last cycle. Similarly, no significant differences in serum creatinine and renal scintigraphy parameters were observed prior to each cycle and 4 weeks after the last treatment. Despite there being no changes in the metabolic volume of both submandibular glands, SUVmax values dropped significantly (p < 0.05). Conclusion: Results evidenced no alterations in renal function and only minimal impairment of salivary function of mCRPC patients who acquired an intense PSMA-RLT regimen every 4 weeks.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".