Hodgkin's lymphoma in systemic lupus erythematosus
Bibliographic record
Abstract
OBJECTIVE: In systemic lupus erythematosus (SLE), there is a well-documented increased risk of non-Hodgkin's lymphoma (NHL), but little is known about the risk of Hodgkin's lymphoma (HL). The purpose of our work was to describe the phenomenon of HL in SLE. METHODS: A multi-site cohort of 9547 SLE subjects was assembled; HL cases were ascertained through cancer registry linkage, and the standardized incidence ratio (SIR) for HL was determined. We also performed a literature search for HL cases in SLE, and compared these with our sample. Finally, we pooled results from our cohort study with two large population-based cohort studies providing SIR estimates for HL in SLE. RESULTS: Five cases of HL occurred in our SLE cohort during the observation interval, for an SIR of 2.4 (95% CI 0.8, 5.5). The literature review documented 13 HL case reports developing in patients with SLE. A pooled analysis combining our data with the other large cohort studies yielded a standardized incidence ratio of 3.16 (95% CI, 1.63-5.51) for HL in SLE. CONCLUSIONS: Data suggest that risk in SLE is increased not only for NHL, but also for other malignancies arising from B-lymphocytes, including HL.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".