Development of a quality of life questionnaire for patients with pancreatic neuroendocrine tumours (the PANNET module)
Bibliographic record
Abstract
Pancreatic neuroendocrine tumours (panNET) are heterogeneous neoplasms usually characterised by slow growth and secretion of hormones, which often cause symptoms. The effect of these symptoms on quality of life (QoL) has not previously been examined in detail. EORTC (European Organisation for Research and Treatment of Cancer) guidelines were followed in phases 1-3 to produce a potential module of questions usable for trials in panNET, focusing on three common types of panNET. For two less common types, a list of symptoms was constructed. Following an extensive literature search and phase 1a interviews with patients and healthcare workers, a long list of potential issues (169) was obtained. This list was shown to 12 patients from three countries in phase 1b interviews to check that no items were missed. The list was reduced to 57 issues. The list of issues was converted to questions, mainly from existing validated questions within the EORTC item library. The list of questions was then used in a phase 3 international study in eight countries using seven languages. A provisional module of 24 items is presented for use in nonfunctioning panNET, gastrinoma and insulinoma. This module increases knowledge concerning QoL in this condition and may be a useful adjunct in clinical trials. A phase 4 trial is being considered for validation of this questionnaire.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".