Clinicopathological features and current treatment outcomes of neuroendocrine thymic tumours
Bibliographic record
Abstract
OBJECTIVES: Neuroendocrine thymic tumours (NETTs) are a distinct subgroup of rare malignancies. An international, multicentre retrospective analysis was used to study the clinicopathological features, current pattern of diagnosis, treatment and outcomes of patients with NETT. METHODS: One hundred and forty-six NETT treated from 1989 to 2016 at 21 centres in China, Europe and North America were retrospectively collected and reclassified according to the World Health Organization histological type and International Thymic Malignancy Interest Group (ITMIG)/International Association for Studies in Lung Cancer (IASLC)/Union for International Cancer Control (UICC) staging. Clinicopathological features, diagnostic and therapeutic approaches and outcomes were investigated. Results in the earlier and latter halves of the study period were also compared. RESULTS: The pretreatment work-up relied exclusively on computed tomography in 85.6% (125/146) of cases. Most patients had advanced disease, with 32.2% (47/146) having lymph node involvement. Higher-grade histological type was associated with more advanced disease (P < 0.05). Induction therapies and surgical procedures were used more often in the latter half of the study. However, the complete resection rate remained unchanged, being 71.5% (98/137) in the whole group. Complete resection was associated with significantly longer 5-year overall survival (77.2% vs 51.2%; P < 0.001) than incomplete or no resection. Significant survival differences were seen with the T, N and M categories of ITMIG/IASLC/UICC staging. Poorly differentiated carcinoma, ITMIG/IASLC/UICC stage IIIa or above and incomplete or no resection were independent risk factors for worse survival. No survival difference was noted between the earlier and the latter halves of the study (58.2% vs 71.9%; P = 0.299). CONCLUSIONS: Current management similar to that for thymomas is unsatisfactory in providing disease control or long-term survival for patients with NETT. Specific diagnostic tools and novel therapeutic agents are needed to improve management outcomes of this disease.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".