Malignancies in systemic lupus erythematosus
Bibliographic record
Abstract
PURPOSE OF REVIEW: Patients with systemic lupus erythematosus (SLE) have altered incidences of certain malignancies as compared with the general population. This review summarizes the recent literature on risk of malignancy in SLE and proposed mechanisms for these altered susceptibilities. RECENT FINDINGS: Recent studies have confirmed previous data showing an increased risk of hematological, lung, thyroid, liver, cervical and vulvovaginal cancers, while demonstrating a decreased risk of breast and prostate cancer. Lymphomagenesis in SLE has been linked to increased activity of multiple inflammatory cytokines as well as possible viral causes. The decreased rates of hormone-sensitive cancers, such as breast and prostate is speculated to be related to the presence of lupus autoantibodies and downregulation of certain proteins in SLE. This knowledge has been utilized to investigate new therapeutic modalities for these malignancies. SUMMARY: Recent data confirm previously reported altered malignancy rates in SLE. There has been some elucidation of mechanisms underlying cancer development in SLE, although additional work is yet to be done.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".