Risk of secondary immune thrombocytopenia following alemtuzumab treatment for multiple sclerosis: a systematic review and meta-analysis
Bibliographic record
Abstract
Object: The purpose of this study was to evaluate the risk of secondary immune thrombocytopenia in multiple sclerosis patients treated with alemtuzumab through a meta-analysis. Methods: We searched databases including PubMed, Web of Science, OVID and EMBASE for studies reporting changes in platelet levels in MS patients treated with alemtuzumab from their inception until May 2023 and performed a meta-analysis. Information and data were screened and extracted by two researchers. The inclusion and exclusion criteria were established according to the PICOS principle. The obtained data were analyzed using the R software meta package and the quality assessment was conducted using Newcastle-Ottawa Scale (NOS). The causes of heterogeneity were analyzed using subgroup analysis and sensitivity analysis. Publication bias was evaluated using funnel plots and Egger test. Results: A total of 15 studies were included, encompassing 1,729 multiple sclerosis patients. Meta-analysis of overall secondary ITP in the included studies yielded a pooled rate of 0.0243. The overall incidence of secondary autoimmune events was 0.2589. In addition, subgroup analysis was applied using study regions and study types. The results showed that the incidence rate of secondary ITP in Europe was about 0.0207, while the incidence of autoimmune events (AEs) was 0.2158. The incidence rate of secondary ITP and AEs in North America was significantly higher than in Europe, being 0.0352 and 0.2622. And the analysis showed that the incidence rates of secondary ITP and AEs in prospective studies were 0.0391 and 0.1771. Retrospective studies had an incidence rate of secondary ITP at 2.16, and an incidence rate of AEs at 0.2743. Conclusion: This study found that there was a certain incidence of Immune thrombocytopenia in multiple sclerosis patients after treatment with alemtuzumab. Alemtuzumab may have some interference with platelet levels, and the mechanism may be associated with Treg cells. But due to the absence of a control group in the included literature, we cannot determine the specific impact of Alemtuzumab on platelet levels in patients with MS. Therefore, clinical physicians should perform a comprehensive assessment of the patient's benefit-to-risk ratio before initiating alemtuzumab. Systematic Review Registration: Inplasy website, DOI number is 10.37766/inplasy2024.3.0007.
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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 | 0.016 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.059 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".