Therapeutic bronchoscopy for malignant central airway obstructions caused by non‐bronchogenic cancers: Results from the <scp>EpiGETIF</scp> registry
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Little is known about malignant central airway obstruction (MCAO) complicating the metastatic spread of non-bronchogenic solid cancers (NBC) and their bronchoscopic management. This study aimed to describe the epidemiology of this population and determine prognostic factors before therapeutic bronchoscopy (TB). METHODS: In this multicenter study using the EpiGETIF registry, we analysed patients treated with TB for MCAO caused by NBC between January 2019 and December 2022. RESULTS: From a database of 2389 patients, 436 patients (18%) with MCAO and NBC were identified. After excluding patients with direct local invasion, 214 patients (8.9%) were analysed. The main primaries involved were kidney (17.8%), colon (16.4%), sarcoma (15.4%), thyroid (8.9%) and head and neck (7.9%) cancers. Most patients (63.8%) had already received one or more lines of systemic treatment. Obstructions were purely intrinsic in 58.2%, extrinsic in 11.1% and mixed in 30.8%. Mechanical debulking was used in 73.4% of cases, combined with thermal techniques in 25.6% of cases. Airway stenting was required in 38.4% of patients. Median survival after TB was 11.2 months, influenced by histology (p = 0.002), performance status (p = 0.019), initial hypoxia (HR 1.45 [1.01-2.18]), prior oncologic treatment received (HR 1.82 [1.28-2.56], p < 0.001) and assessment of success at the end of the procedure (HR 0.66 [0.44-0.99], p < 0.001). Complications rate was 8.8%, mostly mild, with no procedure-related mortality. CONCLUSION: TB for MCAO caused by a NBC metastasis provides rapid improvement of symptoms and prolonged survival. Patients should be promptly referred by medical oncologists for bronchoscopic management based on the prognostic factors identified.
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 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 | 0.000 | 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 | 0.001 |
| 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".