Contemporary Incidence and Survival of Lung Neuroendocrine Neoplasms
Bibliographic record
Abstract
Importance: While the epidemiology of overall and gastrointestinal neuroendocrine neoplasms (NENs) has been reported, data specific to lung NENs remain scarce. Objective: To examine the incidence, overall survival (OS), and lung cancer-specific death for lung NENs. Design, Setting, and Participants: Population-based retrospective cohort study in Ontario, Canada, of adult patients with incident lung NENs from 2000 to 2020. Data were analyzed from July to December 2024. Main outcomes and measures: Yearly incidence rates of lung NENs. OS examined with Kaplan-Meier curves and Cox regression models. Lung cancer-specific deaths using cumulative incidence function and Fine-Gray models accounting for the competing risk of death from other causes. Results: Among 4479 total patients, the median (IQR) age at diagnosis was 67 (57-74) years, and 2521 (56.3%) were female; 2056 (45.9%) had typical neuroendocrine tumors (NET), 370 (8.3%) atypical NET, 998 (22.3%) large cell neuroendocrine carcinoma (NEC, including small cell and mixed NEC), and 1055 (23.6%) other NEC, as well as 1103 (24.6%) who presented as stage IV. The incidence of lung NENs increased 2.87-fold from 0.87 to 2.50 per 100 000 from 2000 to 2020. This rise in incidence was observed mostly for typical NET (from 0.51 to 1.09) and for stage I (0.68 to 1.18). With a median (IQR) follow-up of 34 (9-87) months, 5- and 10-year OS were 50% (95% CI, 49%-51%) and 40% (95% CI, 39%-41%) overall. Advancing age, lower socioeconomic status, type of lung NEN, and advancing stage were independently associated with inferior OS. Cumulative incidence of lung cancer-specific deaths was 41% (95% CI, 40%-42%) at 5 years and 46% (95% CI, 45%-47%) at 10 years. Advancing age, type of lung NEN, and increasing stage were independently associated with higher hazards of lung cancer-specific deaths. Lung cancer-specific deaths were exceeded by deaths from other causes starting 2 year after diagnosis for typical NET and 3 years after diagnosis for stage I disease. Conclusions and relevance: The incidence of lung NENs has increased over 20 years, mostly associated with stage I disease. Prolonged OS was observed after lung NEN diagnosis. Patients with typical lung NET and stage I disease were more likely to die of causes other than lung cancer after 1 and 3 years, respectively. These data are important to direct efforts in care, research, and patient counseling.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".