Dosimetry and pharmacokinetics of [177Lu]Lu-satoreotide tetraxetan in patients with progressive neuroendocrine tumours
Bibliographic record
Abstract
Abstract Purpose To evaluate the dosimetry and pharmacokinetics of the novel radiolabelled somatostatin receptor antagonist [177Lu]Lu-satoreotide tetraxetan in patients with advanced neuroendocrine tumours (NETs). Methods This study was part of a phase I/II trial of [177Lu]Lu-satoreotide tetraxetan, administered at a median cumulative activity of 13.0 GBq over three planned cycles (median activity/cycle: 4.5 GBq), in 40 patients with progressive NETs. Organ absorbed doses were monitored at each cycle using patient-specific dosimetry; the cumulative absorbed-dose limits were set at 23.0 Gy for the kidneys and 1.5 Gy for bone marrow. Absorbed dose coefficients (ADCs) were calculated using both patient-specific and model-based dosimetry for some patients. Results In all evaluated organs, maximum [177Lu]Lu-satoreotide tetraxetan uptake was observed at the first imaging timepoint (4 h after injection), followed by an exponential decrease. Kidneys were the main route of elimination, with a cumulative excretion of 57–66% within 48 h following the first treatment cycle. At the first treatment cycle, [177Lu]Lu-satoreotide tetraxetan showed a median terminal blood half-life of 127 h and median ADCs of [177Lu]Lu-satoreotide tetraxetan were 5.0 Gy/GBq in tumours, 0.1 Gy/GBq in the bone marrow, 0.9 Gy/GBq in kidneys, 0.2 Gy/GBq in the liver and 0.8 Gy/GBq in the spleen. Using image-based dosimetry, the bone marrow and kidneys received median cumulative absorbed doses of 1.1 and 10.8 Gy, respectively, after three cycles. Conclusion [177Lu]Lu-satoreotide tetraxetan showed a favourable dosimetry profile, with high and prolonged tumour uptake, supporting its acceptable safety profile and promising efficacy. Trial registration NCT02592707. Registered October 30, 2015.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".