Cancer screening in patients with systemic lupus erythematosus.
Bibliographic record
Abstract
OBJECTIVE: To examine whether patients with systemic lupus erythematosus (SLE) undergo cancer screening according to established guidelines, to compare their reported screening practices with information from the general population, and to examine potential predictors of screening within our SLE sample. METHODS: We conducted a patient survey of cancer screening practices within the Montreal General Hospital lupus cohort. We compared self-reported frequency of cancer screening to guidelines suggested for the general population, and to figures for cancer screening reported in the general population. We also developed logistic regression models to establish potential predictors of screening for patients with SLE, with cervical cancer screening being the outcome of interest in our primary analyses. RESULTS: Of 48 women aged 50-69, 53% (95% confidence interval, CI: 38-68) had had a mammogram in the past 12 months, compared to 74% (95% CI: 73-75) for similarly aged Quebec women. Of 51 subjects aged 50 and older, only 18% (95% CI: 8-34) reported screening (fecal occult blood check with or without endoscopy) within the recommended time frame, compared to 48% (95% CI: 45-51) for colorectal screening for persons > 50 in the general population. Only 9 of 27 patients with SLE aged less than 30 had Pap tests in the past 12 months (33%, 95% CI: 19-52), compared with a general population rate of 56% (95% CI: 53-59) for similarly aged Quebec women. Our logistic regression model suggested that, among the SLE patients, non-whites, those with lower education, and those with higher disease damage scores were less likely to undergo cervical Pap testing. CONCLUSION: These data suggest that appropriate cancer screening may be overlooked in patients with SLE.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.003 | 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".