Patterns of Biologics Utilization and Discontinuation Before and During Pregnancy in Women With Autoimmune Diseases: A Population‐Based Cohort Study
Bibliographic record
Abstract
OBJECTIVE: To characterize patterns of biologics use and discontinuation before and during pregnancy in women with autoimmune diseases in British Columbia, Canada. METHODS: Women with ≥1 autoimmune diseases, as identified by International Classification of Diseases Ninth/Tenth Revision codes, who had pregnancies ending in deliveries between January 1, 2002, and December 31, 2012, and had ≥1 prescription for a biologic drug 1 year before pregnancy or during pregnancy, were included. Secular trends, patterns of biologics use, and risk of biologics discontinuation before and during pregnancy were examined. Associations between drug discontinuations and various factors were investigated using multilevel logistic regression models, fitted with binomial generalized estimating equations. RESULTS: Of 6,218 women (8,431 pregnancies) with autoimmune diseases, 131 women (144 pregnancies) were exposed to a biologic before or during pregnancy. The use of biologics in this cohort increased from 0% in 2002 to 5.7% by 2012 (P < 0.001). Within the first trimester of pregnancy, 31% of women (34/110) discontinued their biologic treatment, and 38% (30/79) discontinued use in the second trimester, while 98% of those receiving treatment in the second trimester (50/51) continued treatment in the third trimester. Women with rheumatoid arthritis had three times higher odds (odds ratio 3.40 [95% confidence interval 1.33-8.71]) of discontinuing biologics during pregnancy, compared to those with inflammatory bowel disease. CONCLUSION: Given the increased use of biologics and high odds of discontinuation during pregnancy in certain populations, more research is needed to improve our understanding of the risks and benefits of biologics for fetal and maternal health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".