Effectiveness of Thrombopoietin-receptor Agonists in the Treatment of Refractory Immune Thrombocytopenia Associated to Systemic Lupus Erythematosus
Bibliographic record
Abstract
To the Editor: Thrombocytopenia is frequent in patients with systemic lupus erythematosus (SLE), occurring in 7% to 30% of patients. Less than 5% present a platelet count of < 50,000/mm3 and they usually respond to first- or second-line therapy [corticosteroids, immunosuppressive agents, intravenous immunoglobulin (IVIG), rituximab, or splenectomy]. However, a significant number of patients will not respond to these treatments or will relapse afterward1. Romiplostim and eltrombopag are 2 thrombopoietin-receptor agonist drugs that were approved in 2008 by the US Food and Drug Administration (FDA) to treat patients with chronic idiopathic thrombocytopenic purpura who have an insufficient response to conventional therapy2,3,4,5. To date, there are only 4 published cases of patients with SLE and immune thrombocytopenia successfully treated with these agents6,7,8,9 and 1 case in whom this treatment was not effective10. We describe 2 additional cases of patients with SLE and refractory immune thrombocytopenia who responded to thrombopoietin-receptor agonists. A 69-year-old woman was diagnosed with SLE in 1992 because of anemia, thrombocytopenia, positive antinuclear antibody (ANA), anti-dsDNA, anti-Sm antibodies, lupus anticoagulant, and hypocomplementemia. In 1999, a laparoscopic splenectomy was performed because of severe immune thrombocytopenia (< 10,000/mm3) that was refractory to high-dose prednisone and IVIG. She maintained a normal platelet count until March 2013 when she presented with mild epistaxis, ecchymosis, and thrombocytopenia of 22,000/mm3 without … Address correspondence to Dr. G. Espinosa, Servei de Malalties Autoimmunes, Hospital Clínic, Villarroel 170, 08036 Barcelona, Catalonia, Spain. E-mail: gespino{at}clinic.ub.es
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.004 | 0.003 |
| 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".