A phase I/II study of the safety and efficacy of [177Lu]Lu-satoreotide tetraxetan in advanced somatostatin receptor-positive neuroendocrine tumours
Bibliographic record
Abstract
Abstract Purpose We present the results of an open-label, phase I/II study evaluating the safety and efficacy of the novel somatostatin receptor (SSTR) antagonist [177Lu]Lu-satoreotide tetraxetan in 40 patients with previously treated, progressive neuroendocrine tumours (NETs), in which dosimetry was used to guide maximum administered activity. Methods This study was conducted in two parts. Part A consisted of 15 patients who completed three cycles of [177Lu]Lu-satoreotide tetraxetan at a fixed administered activity and peptide amount per cycle (4.5 GBq/300 µg). Part B, which included 25 patients who received one to five cycles of [177Lu]Lu-satoreotide tetraxetan, evaluated different administered activities (4.5 or 6.0 GBq/cycle) and peptide amounts (300, 700, or 1300 μg/cycle), limited to a cumulative absorbed radiation dose of 23 Gy to the kidneys and 1.5 Gy to the bone marrow. Results Median cumulative administered activity of [177Lu]Lu-satoreotide tetraxetan was 13.0 GBq over three cycles (13.1 GBq in part A and 12.9 GBq in part B). Overall, 17 (42.5%) patients experienced grade ≥ 3 treatment‑related adverse events; the most common were lymphopenia, thrombocytopenia, and neutropenia. No grade 3/4 nephrotoxicity was observed. Two patients developed myeloid neoplasms considered treatment related by the investigator. Disease control rate for part A and part B was 94.7% (95% confidence interval [CI]: 82.3–99.4), and overall response rate was 21.1% (95% CI: 9.6–37.3). Conclusion [177Lu]Lu-satoreotide tetraxetan, administered at a median cumulative activity of 13.0 GBq over three cycles, has an acceptable safety profile with a promising clinical response in patients with progressive, SSTR-positive NETs. A 5-year long-term follow-up study is ongoing. Trial registration ClinicalTrials.gov, 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".