Cancers primitifs oto-rhino-laryngologiques et cervico-maxillo-faciaux: aspects épidémiologiques et histopathologiques
Bibliographic record
Abstract
INTRODUCTION: Establish the panorama of primitive oto-rhino-laryngology and cervico-maxillofacial tumors diagnosed at a reference center in Togo. METHODS: We conducted a retrospective, descriptive study of cancers diagnosed at the ORL and cervico-maxillofacial surgery department of the CHU Sylvanus Olympio of Lomé. It was conducted over a period of 10 years (1 January 2005 - 31 December 2014). RESULTS: ORL and cervico-maxillofacial tumors account for 0.48% of consultations and 15.3% of all ORL tumors. The average age of patients was 47 years, ranging from 3 months to 86 years. We noted a male predominance; the sex ratio was 1.45. Drinking alcohol and smoking tobacco prevailed in the cancer of the larynx. Upper aerodigestive tract (UAT) tumors accounted for 64,8%, with a prevalence of cancers of the oral cavity (36,2% of UAT), followed by cancers of the oropharynx (18,5% of UAT) and finally by cancers of the larynx (18,1% of UAT). Primary malignant cervical adenopathies accounted for 18%. The rarest lesions were cancers of the ear and of maxillomandibular bone tissue (2.24% each). Histology was dominated by squamous cell carcinoma (61.4%) followed by non-Hodgkin lymphoma (23.2%). CONCLUSION: ORL and cervico-maxillofacial tumors are frequent in Togo and can be diagnosed at any age. The predominant tumor types reported are those of the oral cavity, pharynx and primary malignant cervical adenopathies.
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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".