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Record W2147218885 · doi:10.1191/0961203304lu1008xx

Breast cancer stage at time of detection in women with systemic lupus erythematosus

2004· article· en· W2147218885 on OpenAlexafffund
Sasha Bernatsky, Ann E. Clarke, Rosalind Ramsey‐Goldman, J.‐F. Boivin, L. Joseph, Raghu Rajan, S Manzi

Bibliographic record

VenueLupus · 2004
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsMcGill UniversityMontreal General Hospital
FundersCanadian Institutes of Health ResearchNational Institutes of HealthFonds de Recherche du Québec - SantéPennsylvania Department of HealthArthritis SocietyLupus CanadaLupus Research AllianceArthritis Foundation
KeywordsMedicineBreast cancerPopulationCancerEpidemiologyInternal medicineCohortStage (stratigraphy)OncologyDiseaseSystemic lupus erythematosus

Abstract

fetched live from OpenAlex

Mounting evidence suggests an increased cancer risk in several autoimmune diseases, including systemic lupus erythematosus (SLE). However, greater scrutiny for cancer in subjects with chronic disease (compared to the general population) might explain this apparent association. If so, one would expect cancers in SLE to be diagnosed at earlier stages than in the general population. This might be particularly evident in cancers where screening is available, such as breast cancer. We linked the University of Pittsburgh lupus cohort with the Pennsylvania Cancer Registry to determine the frequency distribution for stage at diagnosis of invasive breast cancers in the SLE subjects. Data on staging of cancers occurring in the general population of Pennsylvania were obtained from The US Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute. A lower percentage of women with SLE presented with localized breast cancer (nine of the 16, 56.2%) compared to the general population of women (63.5%). Although not definitive, this evidence suggests that cancers in SLE are not necessarily diagnosed at earlier stages than in the general population.

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: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.848
Threshold uncertainty score0.810

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.258
Teacher spread0.247 · 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 designCase report
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

Citations13
Published2004
Admission routes2
Has abstractyes

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