Thrombopoietin Receptor Agonists and Other Second-Line Therapies for Immune Thrombocytopenia: A Narrative Review With a Focus on Drug Access in Canada
Bibliographic record
Abstract
INTRODUCTION: Immune thrombocytopenia (ITP) is an autoimmune disease characterized by low platelet counts and increased risk of bleeding. After corticosteroids with or without intravenous immune globulin (first-line treatment), second-line treatment options include rituximab, splenectomy, thrombopoietin receptor agonists (TPO-RAs), and fostamatinib. In Canada, the choice of second-line therapy is influenced by access to medications. The goals of this narrative review are to 1) summarize the evidence for the use of TPO-RAs and other second-line therapies in ITP and 2) highlight differences in public funding criteria for TPO-RAs across provinces and territories in Canada. METHODS: We conducted a literature review of second-line therapies for ITP. We solicited information on public funding programs for TPO-RAs in Canada from health care providers, pharmacists, and provincial ministries of health. RESULTS: Head-to-head trials involving TPO-RAs, rituximab, splenectomy, and fostamatinib are lacking. There is substantial evidence of effect for TPO-RAs in improving platelet count levels, health-related quality of life, bleeding, and fatigue from placebo-controlled trials and observational studies; however, access to TPO-RAs through provincial funding programs in Canada is variable. Splenectomy failure is a prerequisite for the funding of TPO-RAs in Ontario, Manitoba, and Saskatchewan, but not in Alberta or Quebec. Other provinces either do not have access to public funding or funding is provided on a case-by-case basis. DISCUSSION: TPO-RAs are effective second-line therapies for the treatment of ITP; however, access is variable across Canada, which results in health disparities and poor uptake of international treatment guidelines.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".