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Record W2562953018 · doi:10.3747/co.23.3161

Burden of Illness for Metastatic Melanoma in Canada, 2011–2013

2016· article· en· W2562953018 on OpenAlexafffundvenueabout
D. Scott Ernst, Teresa M. Petrella, Anthony M. Joshua, Ali Hamou, Marroon Thabane, Sophie Vantyghem, Femida Gwadry‐Sridhar

Bibliographic record

VenueCurrent Oncology · 2016
Typearticle
Languageen
FieldMedicine
TopicCutaneous Melanoma Detection and Management
Canadian institutionsNovartis (Canada)Princess Margaret Cancer CentreHealth Sciences CentreWestern UniversitySunnybrook Health Science CentreLondon Health Sciences Centre
FundersNovartis Pharmaceuticals CanadaMelanoma Research AllianceGlaxoSmithKline
KeywordsMedicineEpidemiologyCancer registryMelanomaStage (stratigraphy)Metastatic melanomaDisease registryObservational studyInternal medicineCancerDiseaseRetrospective cohort studyCohortIncidence (geometry)Oncology

Abstract

fetched live from OpenAlex

Background: Detailed epidemiology for patients with advanced metastatic melanoma in Canada is not well characterized. We conducted an analysis of patients with this disease in the province of Ontario, with the aim being to study the presentation, disease characteristics and course, and treatment patterns for malignant melanoma. Methods: In this Canadian observational prospective and retrospective study of patients with malignant melanoma, we used data collected in the Canadian Melanoma Research Network (CMRN) Patient Registry. We identified patients who were seen at 1 of 3 cancer treatment centres between April 2011 and 30 April 2013. Patient data from 2011 and 2012 were collected retrospectively using chart records and existing registry data. Starting January 2013, data were collected prospectively. Variables investigated included age, sex, initial stage, histology, mutation type, time to recurrence, sites of metastases, resectability, and previous therapies. Results: A cohort of 810 patients with melanoma was identified from the cmrn registry. Mean age was 58.7 years, and most patients were men (60% vs. 40%). Factors affecting survival included unresectable or metastatic melanoma, initial stage at diagnosis, presence of brain metastasis, and BRAF mutation status. The proportion of surviving patients decreased with higher initial disease stages. Conclusions: Using registry data, we were able to determine the detailed epidemiology of patients with melanoma in the Canadian province of Ontario, validating the comprehensive and detailed information that can be obtained from registry data.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.936
Threshold uncertainty score0.854

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)0.0010.000

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 head0.057
GPT teacher head0.341
Teacher spread0.284 · 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 designNot applicable
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

Citations19
Published2016
Admission routes4
Has abstractyes

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