Investigating Nutrition-Related Complications and Quality of Life in Patients With Gastroenteropancreatic Neuroendocrine Tumors: Protocol for a Mixed-Methods Prospective Study
Bibliographic record
Abstract
BACKGROUND: Gastroenteropancreatic neuroendocrine tumors (GEP NETs) are a heterogeneous group of tumors with distinct effects on the body due to their potential to secrete hormones and peptides. The incidence and prevalence of GEP NETs in Australia are rising. During 2000-2006, the annual incidence was approximately 3.3 per 100,000 population. To date, there has been development of clinical practice and consensus guidelines for NETs covering best practice for diagnosis, treatment, and medical management; however, the supportive care needs and optimal nutritional management of patients affected by NETs remains underresearched, and evidence to guide clinical practice is lacking. While there is emerging research describing the extent of morbidity in different types of GEP NET patients, little is known about the experience of people affected by these tumors and how nutritional status is impacted by either diagnosis or treatment. OBJECTIVE: The objective of this study was to explore nutrition-related complications and quality of life of patients diagnosed with a GEP NET and to generate evidence to inform future research and development of nutrition screening and management practices. METHODS: Patients diagnosed with a GEP NET at two metropolitan recruitment sites will be invited to participate in a 6-month, mixed-methods longitudinal study. Participants recruited to the study will receive usual care and participate in data collection for the study at 4 time points (at recruitment and 2, 4, and 6 months postrecruitment). Study data will include nutritional status, body weight, fat-free mass, and patient-reported outcome measures (dietitian contact, disease-related symptom presence and severity, dietary habits, health-related quality of life, psychological morbidity, and financial impact). At recruitment and 6 months postrecruitment, complete nutrient testing, including relevant plasma vitamin levels, will also be undertaken. A purposive sample of participants will be invited to take part in semistructured interviews to explore the experience of living with a GEP NET and associated nutrition complications. RESULTS: Ethics approval has been obtained, and study recruitment and data collection are underway. CONCLUSIONS: This study will provide the first in-depth, comprehensive description of nutritional issues in patients with GEP NETs. Results will advance the knowledge of nutritional issues faced by patients with GEP NETs and help inform the development of screening tools and clinical practice guidelines. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/11228.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".