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Record W2519760394 · doi:10.1136/lupus-2016-000179.101

CE-22 Cancer in systemic lupus erythematosus: results from the slicc inception cohort

2016· article· en· W2519760394 on OpenAlexaff
Sasha Bernatsky, Murray B. Urowitz, John G. Hanly, Ann E. Clarke, Caroline Gordon, Juanita Romero‐Díaz, Graciela S. Alarcón, Sang‐Cheol Bae, Michelle Petri, Joan T. Merrill, Daniel J. Wallace, Paul R. Fortin, Dafna D. Gladman, David Isenberg, Anisur Rahman, Susan Manzi, Ola Nived, Gunnar Sturfelt, Christine Peschken, Jorge Sánchez‐Guerrero, Guillermo Ruiz‐Irastorza, Cynthia Aranow, Ronald van Vollenhoven, Asad Zoma, Kristján Steinsson, Munther A. Khamashta, Ellen M. Ginzler, Anca Askanase, Kenneth Kalunian, Mary Anne Dooley, SSam Lim, Diane L. Kamen, Søren Jacobsen, Manuel Ramos‐Casals, Murat İnanç, Jennifer L. Lee, Rosalind Ramsey‐Goldman

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsUniversity of CalgaryUniversity of TorontoDalhousie UniversityUniversity of ManitobaCentre hospitalier universitaire de QuébecToronto Western HospitalUniversité LavalQueen Elizabeth II Health Sciences CentreMcGill University Health Centre
Fundersnot available
KeywordsMedicineCohortBreast cancerCancerInternal medicineIncidence (geometry)Cervical cancerOncology

Abstract

fetched live from OpenAlex

Background To describe cancer incidence in the largest inception SLE cohort in the world. Materials and methods Patients meeting ACR criteria for new-onset SLE were enrolled across 32 centres. At enrolment and annual assessments, new cancer diagnoses (in the intervening year) were recorded by the examining physician. Confirmation of cancers was done by reviewing medical files including pathology reports. Of 1848 patients enrolled (across 1999–2011), 1676 had at least one follow-up. Patients were followed until death, last visit, or end of study interval for this analysis (August 2015). Results Of 1676 patients followed, the majority (88.7%) were female and 828 (49.4%) were Caucasian (16.5% black, 15.2% Asian, 15.2% Hispanic, 3.7% other). Average age at SLE diagnosis was 34.6 (standard deviation, SD 13.3) years. At baseline, 1085 (64.7%) patients were never-smokers; the remainder were current (n = 248) or ex-smokers (n = 342). Average follow-up from cohort entry was 6.9 (SD 3.6) years. Two patients had cancer (one squamous cell skin and one breast cancer) prior to their SLE diagnosis; these cancers were not included in our analyses. We observed 46 cancers in 46 subjects (with three other subjects reported to have cervical intraepithelial neoplasia, a premalignant condition). At cancer diagnosis, the average age was 51.7 (SD 15.3) years and the average SLE duration was 4.8 (SD 3.1) years. The most common cancer type was breast (n = 9), followed by non-melanoma skin cancer (n = 8, six of which were basal cell), lung (n = 6), prostate (n = 5), four head and neck (tonsillar, tongue, and two oral), cervical (n = 2), thyroid (n = 2), melanoma (n = 2) and one each of Non-Hodgkin lymphoma, leukaemia, multiple myeloma, meduloblastoma brain cancer, renal carcinoma, gastric carcinoid, thymoma, and cutaneous dermatofibrosarcoma. Most of the cancer cases were female (34 cases, 73.9%) and Caucasian (34 cases, 73.9%). Four cancer cases were Hispanic, 4 were black, and 4 were Asian. Twenty of the 46 patients (43.5%) who developed cancers were current (n = 4) or ex-smokers (n = 16); five of the six lung cancers were current (n = 1) or ex-smokers (n = 4). Conclusions Just under 3% of the incident SLE cohort developed a cancer over an average follow-up of 6.9 years. The most common cancers were breast, non-melanoma skin, and lung cancers. The vast majority of lung cancers were smokers, supporting the belief that lung cancer risk in SLE (as in the general population) is largely driven by smoking. Further analyses will determine the standardised incidence rates for these cancers in SLE, versus the general population. Acknowledgements We thank all SLICC investigators and their patients for their invaluable data and dedication to SLE research

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.024
GPT teacher head0.302
Teacher spread0.278 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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