Trends in medications for autoimmune disorders during pregnancy and factors for their discontinuation: a population-based study
Bibliographic record
Abstract
OBJECTIVES: The medications used for autoimmune diseases have significantly evolved in recent years, but there is limited knowledge about how treatment practices changed during pregnancy. This study aimed to describe the temporal trends of immunosuppressants, immunomodulators and biologics use during pregnancy among women with autoimmune diseases, compare their use before, during, and after pregnancy, and identify factors predicting the discontinuation of these medications during pregnancy. METHODS: Using data from the Quebec Pregnancy Cohort (1998-2015), which included women under the RAMQ prescription drug plan for at least 12 months before and after pregnancy, the analysis focused on those with at least one International Classification of Diseases Ninth or Tenth Revision code in the year before pregnancy for inflammatory bowel disease, rheumatoid arthritis, spondylarthropathies, connective tissue diseases, systemic lupus erythematosus, or vasculitis. Exposure to immunosuppressants, immunomodulators and biologics were evaluated before and during the pregnancy. Discontinuation during pregnancy was defined as having no prescriptions filled during pregnancy or overlapping with the first day of gestation (1DG), given that at least one prescription was filled in the year prior to pregnancy. Generalized estimating equations were applied to estimate adjusted odds ratios (aOR) for predicting medication discontinuation during pregnancy. RESULTS: Among 441,570 pregnant women, 3,285 had autoimmune diseases. From 1998 to 2014, the use of immunomodulators increased from 3.7% to 11.9%, immunosuppressants from 4.1% to 13.7%, and biologics from 0% to 15.6%. During pregnancy, compared to before, there was a significant decrease in exposure to immunomodulators (8.6% to 5.4%), immunosuppressants (14.2% to 8.7%), and biologics (5.1% to 4.7%). Factors influencing discontinuation varied by medication type; for immunosuppressants, prior biologics use (aOR = 2.12, 95%CI 1.16-3.85) and the year of pregnancy (aOR = 0.93, 95%CI 0.89-0.98) were key factors, while for biologics, it was only the year of pregnancy (aOR = 0.68, 95%CI 0.54-0.86). CONCLUSIONS: The use of immunomodulators, immunosuppressants, and biologics has increased over time. However, exposure during pregnancy decreased, with recent years showing a lower rate of discontinuation. Understanding the factors influencing medication discontinuation during pregnancy can improve management strategies for women with autoimmune diseases.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".