Imatinib Mesylate Treatment in Two Patients with Idiopathic Hypereosinophilic Syndrome
Bibliographic record
Abstract
OBJECTIVE: To report 2 clinical cases of hypereosinophilic syndrome (HES) refractory to standard therapy and the variable responses to imatinib mesylate, and to review previously reported cases of imatinib mesylate use in the treatment of hypereosinophilia. case summaries: Two male patients were diagnosed with idiopathic HES complicated with organ involvement. Both were treated with imatinib mesylate after failing to respond to or being unable to tolerate standard therapy. In one patient, treatment with imatinib mesylate 100 mg/day produced resolution of symptoms and peripheral blood cell counts within 6 days. The patient has successfully maintained normal blood cell counts and has been without symptoms for more than one year after starting imatinib mesylate. The other patient failed to respond to imatinib mesylate even at the maximum dose (up to 400 mg/day). DISCUSSION: Imatinib mesylate was considered an appropriate alternative for standard therapy of HES based on the evidence that other treatments used for chronic myelogenous leukemia have also been successful in treating HES. Three small studies have supported this hypothesis. However, not all patients with HES respond to imatinib mesylate therapy. The cases presented here illustrate the marked difference. CONCLUSIONS: Imatinib mesylate has shown some promise in the treatment of HES. However, until the etiology of idiopathic hypereosinophilia and the role of imatinib mesylate in the resolution of this disease are determined, it will continue to be difficult to predict the responsiveness of a patient to imatinib mesylate therapy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".