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Record W4353021284 · doi:10.1093/jjco/hyad018

A comparison of skin grafts versus local flaps for facial skin cancer from the patient perspective: protocol for a feasibility study

2023· article· en· W4353021284 on OpenAlexaff
Oluwatobi R. Olaiya, Patrick Kim, Lucas Gallo, Emily Dunn, Forough Farrokhyar, Matthew McRae, Sophocles H. Voineskos, Mark McRae

Bibliographic record

VenueJapanese Journal of Clinical Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicReconstructive Facial Surgery Techniques
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineSkin cancerProspective cohort studySurgeryMalignancyCohortPopulationCancerCohort studyObservational studyInternal medicine

Abstract

fetched live from OpenAlex

BRIEF ABSTRACT: This is a protocol to assess feasibility of conducting a prospective cohort study comparing local flaps versus skin grafts for surgical excision of skin cancer from the face. INTRODUCTION: Skin cancer is the most common malignancy worldwide and the face is one of the most common locations of occurrence. Surgical excision is the most popular treatment for small lesions of the face. Defects can be reconstructed using local flaps or skin grafts. There is a paucity of literature evaluating outcomes after skin cancer surgery from the patient's perspective using valid measurement tools. The purpose of this study is to assess the feasibility of conducting a prospective observational cohort study. The primary outcomes include recruitment rates, eligibility rate, compliance of intervention and rate of completion of the primary outcome (FACE-Q scales) at 3 months. Secondary outcomes include examining patient characteristic and FACE-Q score differences between local flaps to skin grafts and adverse events. METHODS AND ANALYSIS: This study is a prospective cohort study consisting of an anticipated 30 patients aged ≥18 years. The study population will consist of a consecutive sample of non-melanoma facial skin cancer patients undergoing a skin graft or local flap. Patients will be followed and evaluated with the FACE-Q questionnaire at 2 weeks, 3 months, 6 months and 1 year post-operation. The following criteria will determine success: patients who meet eligibility criteria >70%; recruitment rate >70%; compliance with intervention >90%; rate of completion of full-scale prospective study primary outcome (FACE-Q at 3 months) >80%; retention rate at 6-month follow-up visit >70%. DISCUSSION: The findings of this study will be used to guide the sample size calculation for a future, large-scale prospective study.Trial registration: ClinicalTrials.gov (NCT04842279).

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)0.004
metaresearch head score (Gemma)0.007
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 score0.151
Threshold uncertainty score0.884

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.310
GPT teacher head0.600
Teacher spread0.290 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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