Comparison and Clinical Implementation of Quality of Life Tools in Patients with Small Bowel Neuroendocrine Tumors Treated with Lu-DOTA-TATE PRRT
Bibliographic record
Abstract
Aim: This study assesses if clinically developed quality of life (QoL) tools are as effective in small bowel neuroendocrine tumors (NETs) as NET-specific research questionnaires. Methods: QoL in patients with small bowel NETs treated with Lu-DOTA-TATE was assessed with The European Organization for Research and Treatment of Cancer (EORTC) QLQ-C30, QLQ-GI.NET21 and Edmonton Symptom Assessment System Revised (ESAS-r) at baseline and after four treatments. Repeated measures ANOVA was performed. Results: Both EORTC and ESAS-r demonstrated maintained overall QoL. EORTC demonstrated statistically and clinically significant improvement in insomnia, diarrhea, gastrointestinal, endocrine symptoms and social function. ESAS-r demonstrated statistically and clinically significant improvement in overall total symptom distress score. Conclusion: ESAS-r is quick and easy to interpret. It is not as sensitive to individual symptoms but does track overall function. EORTC assessment is more complex, but better reflects QoL for NET specific symptoms.
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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 | 0.002 | 0.003 |
| 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) | 0.001 | 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".