O025 The epidemiology of gastroenteropancreatic neuroendocrine tumours (GEP-NETS) in the north-east of England and a systematic review of literature
Bibliographic record
Abstract
Abstract Introduction Gastroenteropancreatic neuroendocrine tumours (GEP-NETs) are rare, indolent malignancies with unknown aetiology and an increasing incidence was observed globally. With limited research on GEP-NET epidemiology, the reasons behind incidence disparities between countries remain unclear. Whether this increase was a true phenomenon or was confounded by factors including diagnostics advancement and classification evolution needs further enquiry. The aims are to evaluate all available literature on GEP-NET incidence rates (IR), and to determine GEP-NET incidence in the North-East and the association between survival and age, gender, grade, stage, and socioeconomic status (SES). Methods Systematic review of relevant literature using MEDLINE, Embase, Scopus and Web of Science. Quality of methodology was assessed using the Newcastle-Ottawa Scale. (2) 140 GEP-NET patients from 1996 to 2019 were identified. Crude IR, age-standardised IR and overall survival (OS) were determined. Outcome parameters were identified from Cox-proportional Hazard analysis. Results GEP-NET global incidence increased in the last decades, whereas Asia and various European countries reported no significant changes. Ethnic and gender differences were observed. (2) Over 23 years, IR increased by 40.5% per annum (0.08–5.94/1,000,000). 5- and 10-year OS were 71.0% and 28.9% respectively. SES had non-significant associations with the covariates. Age >70 yrs (HR=5.48 [2.20–13.66], p<0.001) and middle SES (HR=2.23 [1.05–3.75], p=0.038) were independent predictors for worse prognosis. Conclusion GEP-NETs continue to rise despite differences in reporting methods across the literatures and underlying factors not being captured in this population-based study. A prospective NET registry is necessary to elucidate accurate GEP-NET epidemiology in the UK. Take-home message GEP-NET incidence rates are evidently increasing both in the North-East and globally; yet, the reasons behind such increase remain unclear. This highlights the establishment of a prospective neuroendocrine tumour (NET) registry is imperative in the North-East or in the UK so that all GEPNETs can be captured and detect subtle incidence changes over time.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".