Breast cancer stage at time of detection in women with systemic lupus erythematosus
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".