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Record W2898859752 · doi:10.1159/000490706

Regression of Sebaceous Carcinoma of the Eyelid after a Small Incisional Biopsy: Report of Two Cases

2018· article· en· W2898859752 on OpenAlexaff
Seymour Brownstein, Sonul Mehta, Navdeep Nijhawan, Guy Allaire, Tuan Quynh Tram Nguyen, Tina Tang, Kailun Jiang, Solin Saleh, Evan Kalin-Hajdu, Robbin Bruen, James Oestrelcher

Bibliographic record

VenueOcular Oncology and Pathology · 2018
Typearticle
Languageen
FieldMedicine
TopicNonmelanoma Skin Cancer Studies
Canadian institutionsUniversité de MontréalUniversity of TorontoOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineEyelidIncisional biopsyBiopsyPtosisSebaceous carcinomaBasal cell carcinomaMagnetic resonance imagingMerkel cell carcinomaLesionSurgeryCarcinomaRadiologyPathologyBasal cell

Abstract

fetched live from OpenAlex

PURPOSE: To report 2 cases of regression of sebaceous carcinoma of the eyelid after a small incisional biopsy. METHODS: Clinical, imaging, and histopathological findings are presented, with a literature review on regressing ocular tumors. RESULTS: Our first patient was a 79-year-old man who presented with a 10-month history of progressive left upper eyelid ptosis caused by an eyelid tumor with orbital involvement and confirmed on magnetic resonance imaging. Our second patient was a 70-year-old woman who presented with ptosis with a left upper eyelid mass. Both patients underwent a small incisional biopsy of their lesion. The histopathological diagnoses in both cases were consistent with sebaceous carcinoma. Both patients refused exenteration. Follow-up clinical examination and imaging disclosed total regression of the ptosis and of the neoplasm with no sign of recurrence in both patients over a 4-year period for Case 1 and a 7-year period for Case 2. CONCLUSION: Regression following incisional biopsy of basal cell, squamous cell, and Merkel cell carcinoma, including of the eyelid, is well documented. To the best of our knowledge, our 2 cases of sebaceous carcinoma are the first to be reported with total involution clinically and on imaging of the tumor following partial incisional biopsy.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.534

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.027
GPT teacher head0.330
Teacher spread0.304 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2018
Admission routes1
Has abstractyes

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