Endocrine and multiple sclerosis outcomes in patients with autoimmune thyroid events in the alemtuzumab CARE-MS studies
Bibliographic record
Abstract
Background Alemtuzumab is an effective therapy for relapsing multiple sclerosis. Autoimmune thyroid events are a common adverse event. Objective Describe endocrine and multiple sclerosis outcomes over 6 years for alemtuzumab-treated relapsing multiple sclerosis patients in the phase 3 CARE-MS I, II, and extension studies who experienced adverse thyroid events. Methods Endocrine and multiple sclerosis outcomes were evaluated over 6 years. Thyroid event cases, excluding those pre-existing or occurring after Year 6, were adjudicated retrospectively by expert endocrinologists independently of the sponsor and investigators. Results Thyroid events were reported for 378/811 (46.6%) alemtuzumab-treated patients. Following adjudication, endocrinologists reached consensus on 286 cases (75.7%). Of these, 39.5% were adjudicated to Graves’ disease, 2.5% Hashimoto's disease switching to hyperthyroidism, 15.4% Hashimoto's disease, 4.9% Graves’ disease switching to hypothyroidism, 10.1% transient thyroiditis, and 27.6% with uncertain diagnosis; inclusion of anti-thyroid antibody status reduced the number of uncertain diagnoses. Multiple sclerosis outcomes of those with and without thyroid events were similar. Conclusion Adjudicated thyroid events occurring over 6 years for alemtuzumab-treated relapsing multiple sclerosis patients were primarily autoimmune. Thyroid events were considered manageable and did not affect disease course. Thyroid autoimmunity is a common but manageable adverse event in alemtuzumab-treated relapsing multiple sclerosis patients. ClinicalTrials.gov Registration Numbers: CARE-MS I (NCT00530348); CARE-MS II (NCT00548405); CARE-MS Extension (NCT00930553)
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".