Sustained remissions of immune thrombocytopenia associated with the use of thrombopoietin receptor agonists
Bibliographic record
Abstract
BACKGROUND: Thrombopoietin receptor agonists (TRAs) are effective treatments for immune thrombocytopenia (ITP). However, continuous therapy is generally required to maintain platelet (PLT) count responses. STUDY DESIGN AND METHODS: In this case series, we describe ITP patients from our practice who achieved durable responses to the TRAs romiplostim and eltrombopag. Patients were classified as having a definite TRA-induced remission if PLT counts increased above 100 × 10(9) /L after TRA treatment and remained above 100 × 10(9) /L even after the medication was discontinued; or a possible TRA-induced remission if PLT counts increased above 100 × 10(9) /L, remained elevated for at least 3 months after the medication was discontinued, but a subsequent relapse occurred or the effect of other disease-modifying therapies could not be excluded. RESULTS: Of 31 patients with chronic ITP treated with TRAs in our practice, nine patients achieved a PLT count response with either romiplostim (n = 6) or eltrombopag (n = 3) that was maintained even after the medications were discontinued. Three patients met criteria for a definite TRA-induced remission, each after exposure to romiplostim. Patients had ITP for a median of 7.8 years and had failed a median of four prior therapies including eight patients who had a splenectomy. We documented a progressive decline in anti-glycoprotein IIbIIIa PLT autoantibodies in one patient while on treatment. CONCLUSION: Some patients with ITP can achieve sustained PLT count responses after the use of TRAs. This observation raises the possibility that these agents may restore immune tolerance to PLT antigens in some patients and supports the practice of down titrating the dose.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".