A survey on pulmonary screening practices among otolaryngology-head & neck surgeons across Canada in the post treatment surveillance of head and neck squamous cell carcinoma
Bibliographic record
Abstract
BACKGROUND: Post treatment lung screening for head and neck cancer patients primarily focuses on the distant metastasis and a high rate of second primary can also be expected. The best screening tool and timing for this purpose is controversial. We sought out to assess the current practice and beliefs among Canadian Head and Neck Surgeons. METHODS: After Ethical Board approval, a nationwide survey was conducted through the Canadian Society of Otolaryngology (CSO) among head and neck surgeons regarding their practices for pulmonary screening in HNSCC patients. RESULTS: Our CSO survey among Otolaryngology-head and neck surgeons showed that 26 out of 32 respondents perform routine lung screen, out of which 23 (88%) feel that chest radiography should be preferred. The majority of respondents felt that lung screening could impact beneficially on mortality. For symptomatic patients, low-dose spiral CT was the preferred modality (48%), followed by PET/CT scan (14%) and sputum cytology (14%). In high-risk asymptomatic patients (current smoker, radiation exposure, family history and advanced HNSCC), 31% of respondents performed a CXR. The same percentage performed a low dose CT, while 19% relied on PET scan. A further 19% of respondents did not perform any screening in high-risk patients. Most respondents (77%) had more than 10 years practice since graduation from medical school and came from the provinces of Quebec, Ontario and Alberta. CONCLUSION: Chest radiography remains the preferred modality for lung screening and was believed to be impacting beneficially on lung mortality. The recent literature does not seem to be in agreement with those beliefs. Further studies to establish which modality is best and concurrent nation-wide education are warranted.
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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 | 0.002 |
| Science and technology studies | 0.002 | 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".