Low to intermediate grade lung neuroendocrine tumours. A single centre real world experience
Bibliographic record
Abstract
INTRODUCTION: Lung neuroendocrine tumours (LNETs) are a rare heterogenous group of tumours whose incidence has been increasing. We investigated the diagnosis, treatment, and survival patterns of patients with low to intermediate grade LNETs. METHODS: A retrospective chart review of patients with low to intermediate grade LNETs, treated at a Canadian tertiary-level cancer centre was performed. RESULTS: We identified 59 patients. Most were G1or G2 and well or moderately differentiated. Forty-seven patients presented with local or locally advanced disease, of which 57.4 % received curative intent surgery. The rest were treated with definitive radiation, radical chemoradiation with platinum and etoposide, palliative chemotherapy with doxorubicin, or supportive care. The five-year overall survival (OS) for those treated surgically was 83 % versus 44 % in the non-surgical group. Metastatic disease was seen in 24/59 patients, with a five-year OS in patients with stage IV disease of 39 %. Of those with advanced or unresectable disease (n = 32), 21 received palliative systemic treatment with up to three lines of therapy. First-line treatment was most commonly chemotherapy with platinum/etoposide combination or somatostatin analogue therapy. Second-line treatment involved chemotherapy or targeted everolimus. PRRT was used once as a first-line and once as second-line therapy. Third-line included lanreotide or chemotherapy with capecitabine/temozolomide combination. CONCLUSION: Overall, patients with surgically resectable disease had a good five-year OS. However, inoperable or more advanced disease was associated with a poorer OS. Despite many treatment options, the sequence of treatments is poorly established. This highlights the need for further development and dissemination of evidence-based guidelines for LNET patients.
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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 | 0.000 |
| 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 | 0.001 |
| 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".