The occurrence of keratocystic odontogenic tumours in nevoid basal cell carcinoma syndrome
Bibliographic record
Abstract
OBJECTIVES: This retrospective study reviews the occurrence of keratocystic odontogenic tumours (KOTs) in nevoid basal cell carcinoma syndrome (NBCCS) patients seen in the Oral and Maxillofacial Radiology Special Procedures Clinic in the Faculty of Dentistry at the University of Toronto. METHODS: This study examines the number and radiographic features of KOTs identified in 11 NBCCS patients who presented with 43 KOTs between January 1989 and 30 June 2007 on plain film radiographs and CT. RESULTS: Regression analysis revealed a statistically significant (P < 0.01) relationship between the age at first KOT occurrence and the total number of lifetime KOTs (r = -0.78). Of the KOTs identified, 25 developed in the mandible and 18 developed in the maxillae. The majority of these were associated with a change in either the size or shape of the follicular space, and both plain film radiography and CT were equally effective at demonstrating these changes. CT was, however, more effective at demonstrating endosteal scalloping of cortical bone than plain film radiography (P < 0.001) while the opposite was true for showing tooth displacement (P < 0.01). For patients imaged with both plain radiography and CT (29 KOTs), 5 KOTs were detectable only by CT. CONCLUSIONS: Our results suggest that there should be early and frequent monitoring of NBCCS patients for the development of KOTs in youth and adolescence, and that CT imaging should play an important role in these investigations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".