Lung Carcinoids in Adolescents and Young Adults (AYAs): A Still Overlooked Clinical Entity
Bibliographic record
Abstract
), respectively. Although uncommon overall, TCs and ACs represent the most frequent non-hematologic malignancies in the pediatric population. However, significantly less is known about PC in AYAs, a population often overlooked or analyzed within pediatric or adult cohorts. In this critical review, we analyzed existing literature on PCs in the AYA population using a question-and-answer format, emphasizing the substantial gap in current knowledge in this field and the urgent unmet clinical need for future scientific proposals. First, we analyzed epidemiology and the data availability about the association between PCs in AYA patients and genetic syndromes that typically reach the maximal diagnostic incidence within this age group. We then reviewed the available literature about the pathologic characteristics, clinical presentation, and treatment strategies for localized and metastatic disease in PC AYA patients. According to our findings, a significant lack of age-specific evidence and the need for international collaboration and prospective, AYA-focused clinical studies were underscored. Advancing research in this area is essential to improve understanding and develop tailored, evidence-based therapeutic approaches for this peculiar population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".