Clinical Characteristics and Prognosis of Primary Tracheal Cancer: A Single Institution Experience
Bibliographic record
Abstract
Background Primary tracheal cancers (PTCs) are rare and current evidence-based understanding is limited to retrospective reports and national databases. We present single institutional study of a historical cohort of PTC from Canadian provincial cancer registry database. Materials and Methods: After institutional research ethics board approval, all PTC patients diagnosed from 1980 to 2014 were identified through the Canadian provincial cancer registry. Demographic and tumor related factors were evaluated using descriptive statistics. Survival rates were estimated using the Kaplan-Meier method and cox hazard regression analyses were performed to identify predictors of disease-free survival (DFS) and overall survival (OS). Results: A total of 30 patients were included in the study. At presentation, 10 patients (33%) had only local disease, 14 patients (47%) had locoregional disease and the remaining 4 patients (13%) had distant metastasis. The majority of patients underwent primary radiation treatment. The overall survival rate was 30% at 2 years and 16% at 5 years. Patients receiving radical-intent therapy had better 2-year DFS and OS compared to patients managed with palliative radiotherapy and best supportive care (46%, 17% and 0%) (p=<0.001) and (50%, 23% and 0%) (p=<0.001), respectively. Radiotherapy resulted in a better 2-year OS and DFS (32% versus 14%) (p=<0.03) and (32% versus 0%) (p=<0.001), respectively. Conclusion: PTC is an uncommon neoplasm making the study of the disease technically and logistically challenging. Radical radiotherapy alone is curative option in inoperable PTC. Intent of treatment and radiotherapy were associated with superior survival outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".