A Real-World Study of the Incidence and Outcomes of Early-Onset Well-differentiated Neuroendocrine Neoplasms
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to evaluate the incidence and outcomes of adults with early-onset (20 to 34 y) diagnosis of well-differentiated neuroendocrine neoplasms. METHODS: Surveillance, Epidemiology, and End Results (SEER)-18 database was accessed, and patients with well-differentiated lung or digestive tract neuroendocrine neoplasms diagnosed 2000 to 2018 were reviewed. Annual percent changes (APCs) were calculated for the 3 disease subsites (foregut, midgut, and hindgut) stratified by age group. Kaplan-Meier survival estimates/log-rank testing were used to examine differences in overall survival between the 3 age groups. Multivariable Cox regression analyses were used to evaluate factors affecting overall and cancer-specific survivals. RESULTS: Throughout the study period, patients with early-onset disease (20 to 34 y) have experienced the greatest APC (20 to 34 y: 9.7; 35 to 49 y: 5.4; ≥50 y: 4.1). When APCs were stratified by disease subsite, this difference in APCs appears to be driven by midgut tumors (20 to 34 y: 19.2; 35 to 49: 8.4; ≥50 y: 3.8). Using multivariable Cox regression modeling, the following variables were associated with a higher risk of all-cause death (worse overall survival): male sex (hazard ratio [HR] 1.27; 95% confidence interval [CI]: 1.22-1.31), African American race (HR vs. white race: 1.20; 95% CI: 1.15-1.26), nonhindgut primary (HR foregut vs. hindgut primary: 2.02; 95% CI: 1.91-2.13; HR midgut vs. hindgut primary: 2.09; 95% CI: 1.95-2.24), distant disease (HR vs. regional disease: 2.06; 95% CI: 1.96-2.18), no surgery to the primary (HR: 2.34; 95% CI: 2.24-2.46), and older age (HR: 5.80; 95% CI: 4.87-6.91). CONCLUSION: Cases of early-onset well-differentiated neuroendocrine neoplasms have disproportionately increased over the past 2 decades (compared with other age groups), and this appears to have been driven mainly by midgut tumors.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".