THUR 196 Pregnancy outcomes in alemtuzumab-treated rrms patients
Bibliographic record
Abstract
Murine studies show no alemtuzumab-related teratogenicity, but no controlled human clinical studies of alemtuzumab in pregnancy exist. In phase 2 (CAMMS223 [ NCT00050778 ]) and phase 3 (CARE-MS I [ NCT00530348 ], CARE-MS II [ NCT00548405 ]) studies, patients received 2 annual alemtuzumab courses. Two extension studies provided longer-term evaluation ( NCT00930553 ; TOPAZ [ NCT02255656 ]). Pregnant/lactating patients were ineligible for further treatment but were followed up for safety. As of 1 April 2017, 248 pregnancies occurred in 156/972 alemtuzumab-treated female patients (mean [SD] age at conception, 32.5 [4.4] years; mean [SD] time from last alemtuzumab dose to conception, 33.5 [22.6] months; 16 within 4 months of dosing), with 218 completed, 14 ongoing, and 16 with unknown outcomes. Of completed pregnancies with known outcomes, 147 (67%) were live births with no congenital abnormalities or birth defects. There were 48 (22%) spontaneous abortions, 22 (10%) elective abortions, and 1 (0.5%) stillbirth. To date, there has been no signal for teratogenicity. Incidence of spontaneous abortions was comparable with treatment-naive MS patients (5%–21%) and the general population (17%–22%). Real-world data are currently collected by the International Lemtrada Pregnancy Exposure Registry, a prospective, non-interventional, observational safety study enrolling patients in ≥19 countries who become pregnant within 4 months of alemtuzumab exposure. Study Support: Sanofi.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".