MétaCan
Menu
Back to cohort
Record W2134920285 · doi:10.1002/jso.23981

A population‐based assessment of melanoma: Does treatment in a regional cancer center make a difference?

2015· article· en· W2134920285 on OpenAlexaffabout
Justin Rivard, Xanthoula Kostaras, Melissa Shea‐Budgell, Laura Chin‐Lenn, May Lynn Quan, J. Gregory McKinnon

Bibliographic record

VenueJournal of Surgical Oncology · 2015
Typearticle
Languageen
FieldMedicine
TopicCutaneous Melanoma Detection and Management
Canadian institutionsUniversity of CalgaryAlberta Cancer FoundationUniversity of Manitoba
Fundersnot available
KeywordsMedicineMelanomaCenter (category theory)CancerPopulationOncologyInternal medicineEnvironmental healthCancer research

Abstract

fetched live from OpenAlex

BACKGROUND: Regionalization of care to specialized centers has improved outcomes for several cancer types. We sought to determine if treatment in a regional cancer center (RCC) impacts guideline adherence and outcomes for patients with melanoma. METHODS: In Alberta, Canada, 561 patients with stage I-IIIC primary melanoma were diagnosed between January 2009 and December 2010. The electronic health record was used to capture demographic and pathologic data. Provincial guidelines for sentinel lymph node biopsy (SLNB) and wide local excision (WLE) are based on recommendations of several pre-existing guidelines including the National Comprehensive Cancer Network. RESULTS: 148 of 561 patients were identified as having been treated at a RCC. Median follow-up was 45 months. Patients treated at the RCC presented with higher stage melanomas. The RCC was more likely to follow guideline recommendations for performing SLNB (81.3% vs. 55.4%, P < 0.0001) but not for the extent of WLE (76.6% vs. 84.1%, P = 0.054). Overall survival was impacted by tumor thickness (HR 1.14, P < 0.0001), ulceration (HR 5.58, P < 0.0001), and mitoses (HR 0.59, P = 0.05). CONCLUSIONS: The RCC more closely followed guidelines for SLNB but not for WLE. Despite patients treated at the RCC presenting with a more advanced stage, overall survival and disease-free survival appear to not be affected by treatment center.

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 score0.457
Threshold uncertainty score0.313

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 studies0.0000.000
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 head0.053
GPT teacher head0.369
Teacher spread0.316 · 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

Citations7
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Surgical OncologySame topicCutaneous Melanoma Detection and ManagementFrench-language works237,207