Toxicity and Tolerability of 177Lu-DOTA-TATE PRRT with a Modified AdministeredActivity Protocol in NETs of Variable Origin – A Phase 2 RegistryStudy
Bibliographic record
Abstract
BACKGROUND: Peptide receptor radionuclide therapy (PRRT) has been recently approved for advanced, metastatic, or progressive neuroendocrine tumors (NETs). OBJECTIVE: This study reports the adverse events (AEs) observed with patient-tailored administered activity. METHODS: Fifty-two PRRT naive patients were treated with 177Lu-DOTATATE. The administered activity ranges between 2.78 and 5.55 GBq/cycle using the patient's unique characteristics (age, symptoms, blood work, and biomarkers). RESULTS: The protocol was well tolerated with the overwhelming majority of participants being forty- six (88%), completing all 4 induction therapy cycles. The median cumulative administered activity was 19.6 GBq (ranged 3.8-22.3 GBq). A total of 42/52 (81%) reported at least one symptom, and 43/52 (83%) had evidence of biochemical abnormality at enrollment that would meet grade 1 or 2 criteria for AEs. These symptoms only slightly increase with treatment to 50/52 (96%) and 51/52 (98%), respectively. The most common symptoms were mild fatigue (62%), shortness of breath (50%), nausea (44%), abdominal pain (38%), and musculoskeletal pain (37%). The most common biomarker abnormalities were mild anemia (81%), reduced estimated glomerular filtration rate (eGFR) (58%), increased alkaline phosphatase (ALP) (50%), and leukopenia (37%). Of critical importance, no 177Lu-DOTATATE related grade 3 or 4 AEs were observed. CONCLUSION: Tailoring the administered activity of 177Lu-DOTATATE to the individual patient with a variety of NETs is both safe and well-tolerated. No patient developed severe grade 3 or 4 AEs. Most patients exhibit symptoms or biochemical abnormality before treatment and this only slightly worsens following induction therapy.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".