The Safety and Efficacy of Peptide Receptor Radionuclide Therapy for Gastro-Entero-Pancreatic Neuroendocrine Tumors: A Single Center Experience
Bibliographic record
Abstract
The aim of the present study was to evaluate the safety and efficacy of radionuclide therapy with [177Lu]Lu-DOTA-TATE according to our single center experience at the University of Naples Federico II. For the present analysis, we considered 21 patients with progressive, advanced, well-differentiated G1 and G2 in patients with gastro-entero-pancreatic (GEP) neuroendocrine tumors (NETs) treated with [177Lu]Lu-DOTA-TATE according to the decisions of a multidisciplinary team. All patients underwent four cycles of 7–8 GBq of [177Lu]Lu-DOTA-TATE every 8 weeks. A whole-body scan (WBS) was performed 4, 48, and 168 h after each treatment. The dosimetry towards the organ at risk and target lesions was calculated. For each patient, renal and bone marrow parameters were evaluated before, during, and 3 months after the end of the treatment. Follow-up data were obtained and RECIST criteria were considered as the endpoint. Among 21 patients enrolled (mean age 65 ± 9 years); 17 (81%) were men and the small intestine was the most frequent location of disease (n = 12). A mild albeit significant variation (p < 0.05) in both platelets and white blood cell counts among all time points was observed, despite it disappearing 3 months after the end of the therapy. According to the RECIST criteria, 11 (55%) patients had a partial response to therapy and 8 (40%) had stable disease. Only one (5%) patient had disease progression 4 months after treatment. Our data confirm that [177Lu]Lu-DOTA is safe and effective in controlling the burden disease of G1/G2 GEP-NETs patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".