Latin American Consensus on the Treatment of Head and Neck Cancer
Bibliographic record
Abstract
Head and neck squamous cell carcinoma (HNSCC) is well known as a serious health problem worldwide, especially in low-income countries or those with limited resources, such as most countries in Latin America. International guidelines cannot always be applied to a population from a large region with specific conditions. This study established a Latin American guideline for care of patients with head and neck cancer and presented evidence of HNSCC management considering availability and oncologic benefit. A panel composed of 41 head and neck cancer experts systematically worked according to a modified Delphi process on (1) document compilation of evidence-based answers to different questions contextualized by resource availability and oncologic benefit regarding Latin America (region of limited resources and/or without access to all necessary health care system infrastructure), (2) revision of the answers and the classification of levels of evidence and degrees of recommendations of all recommendations, (3) validation of the consensus through two rounds of online surveys, and (4) manuscript composition. The consensus consists of 12 sections: Head and neck cancer staging, Histopathologic evaluation of head and neck cancer, Head and neck surgery-oral cavity, Clinical oncology-oral cavity, Head and neck surgery-oropharynx, Clinical oncology-oropharynx, Head and neck surgery-larynx, Head and neck surgery-larynx/hypopharynx, Clinical oncology-larynx/hypopharynx, Clinical oncology-recurrent and metastatic head and neck cancer, Head and neck surgery-reconstruction and rehabilitation, and Radiation therapy. The present consensus established 48 recommendations on HNSCC patient care considering the availability of resources and focusing on oncologic benefit. These recommendations could also be used to formulate strategies in other regions like Latin America countries.
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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 | 0.073 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".