MétaCan
Menu
Back to cohort
Record W4387392916 · doi:10.1002/hed.27539

Clinical outcomes of oral epithelial dysplasia managed by observation versus excision

2023· article· en· W4387392916 on OpenAlexaff
Christopher D. Bernard, Jasper Zhongyuan Zhang, Hagen Klieb, Nick Blanas, Wei Xu, Marco Magalhaes

Bibliographic record

VenueHead & Neck · 2023
Typearticle
Languageen
FieldDentistry
TopicOral Health Pathology and Treatment
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentrePrincess Margaret Cancer CentreUniversity of TorontoUniversity Health NetworkPublic Health Ontario
Fundersnot available
KeywordsMedicineMalignancyMalignant transformationSurgeryEpithelial dysplasiaCancerSurgical excisionDysplasiaPathologyInternal medicine

Abstract

fetched live from OpenAlex

IMPORTANCE: Oral potentially malignant disorders, including oral epithelial dysplasia (OED), are a group of conditions with an increased risk of progression to oral cancer. Clinical management of OED is challenging and usually involves monitoring with repeated incisional biopsies or complete surgical excision. OBJECTIVE: To determine if complete surgical excision of OED impacts malignant transformation or improves survival outcomes in lesions that progress to malignancy. DESIGN: A retrospective review of all patients diagnosed with OED between 2009 and 2016 was completed, and patients were followed until January 2022 for disease course and outcomes. RESULTS: Hundred and fifty-five cases of OED met the inclusion criteria. Among the 61 lesions managed by observation, 15 progressed to cancer. Among the 94 lesions managed by surgical excision, 27 progressed to cancer. The overall malignant transformation rate was 27%, with an annual rate of 6.4%. Surgical excision with or without histologically negative margins did not decrease malignant transformation but was associated with lower oncologic staging at the time of diagnosis and improved survival. CONCLUSIONS AND RELEVANCE: Surgical excision of OED with or without negative margins did not reduce the rate of transformation to oral cancer but resulted in lower oncologic staging at diagnosis, leading to improved patient outcomes. Our results support the implementation of more extensive tissue sampling to improve cancer diagnosis and patient outcomes.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.003

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.

Opus teacher head0.137
GPT teacher head0.437
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueHead & NeckSame topicOral Health Pathology and TreatmentFrench-language works237,207