Panendoscopy for Head and Neck Cancers: Detection of Synchronous Second Primary Cancers, Complications and Cost-Benefit Analysis: A Systematic Review
Bibliographic record
Abstract
IMPORTANCE: In patients with head and neck squamous cell carcinoma (HNSCC), the discovery of a second synchronous primary cancer of the aerodigestive tract (SSPCA) significantly impacts management and prognosis. Recent advances in imaging have increasingly allowed for identifying SSPCA before performing panendoscopy, raising questions about the latter's role. OBJECTIVE: To establish the incidence of SSPCA and panendoscopy's impact on management. Complications and costs associated with panendoscopy were also assessed. DESIGN: Systematic review following the preferred reporting items for systematic reviews and meta-analysis guidelines. SETTING: Operating room panendoscopy. PARTICIPANTS: Identifiable HNSCC undergoing initial staging workup. INTERVENTION: Panendoscopy under general anesthesia for SSPCA detection. MAIN OUTCOME MEASURES: Incidence of SSPCA in HNSCC, change in management caused by panendoscopy, incidence of panendoscopy complications, costs for panendoscopy. RESULTS: 51 studies were included (n = 19,914 patients). SSPCA was present in 6.4% (n = 467/7262) of all panendoscopies. Among patients who had a prior computed tomography (CT) of the neck and chest, a change in management resulting from SSPCA detected through panendoscopy occurred in only 1.1% of cases (n = 3/268), and in 0% of cases for those who had a positron-emission tomography-computed tomography (PET) (n = 0/544). The rate of major complications of panendoscopy was 0.7% (n = 58/8386). Only two recent studies in a private healthcare system reported panendoscopy costs ranging from $3802 USD to $17,296 USD. CONCLUSIONS: The role of panendoscopy in the initial workup of HNSCC should be limited to confirming suspicious findings from initial CT or PET. The incidence of major complications for panendoscopy is low but carries a significant financial burden for patients in the private American healthcare system. More studies are needed to assess the cost-effectiveness of panendoscopies for SSPCA detection in a public healthcare system. RELEVANCE: Confirms the lack of benefit for systematic panendoscopy for SSPCA detection in HNSCC patients when initial workup includes a CT of the neck and chest or PET.
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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 | 0.010 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.016 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".