The North American Chronic Immune Thrombocytopenia Registry (NACIR): Demographics and Treatment Responses
Bibliographic record
Abstract
Abstract Abstract 2509 Background: Chronic pediatric immune thrombocytopenia (ITP) has an incidence of 1–2/100,000. Due to its low incidence, large studies in pediatric chronic ITP are difficult. This registry includes patients from 16 sites in the US and Canada and represents one of the largest longitudinal datasets of children/adolescents with chronic ITP. Objective: To describe the North American Chronic ITP Registry (NACIR) study population and evaluate univariate predictors of platelet count response to therapies, including IVIG, anti-D globulin (anti-D), steroids (5–14 day course), and splenectomy. Registry methods and patient characteristics: After local IRB approval, 550 patients with chronic ITP enrolled in the NACIR between January 2004 and June 2010. Eligibility included: ages 6 months-18 years at ITP diagnosis, clinical diagnosis of ITP, and ITP duration >6 months. Primary ITP was defined as isolated thrombocytopenia without associated conditions. Secondary ITP included those patients with immune thrombocytopenia associated with other immune-mediated medical conditions, including Evans Syndrome. Treatment response was defined as a post-treatment platelet count ≥50,000/uL within 7 days of IVIG, 10 days of anti-D, 14 days of steroids, and 30 days of splenectomy. 365 subjects had at least one 6 month follow-up report after enrollment; median duration of follow-up was 2.1 yrs. Demographics of participants include: 46% male; 84% Caucasian, 7% Black, and 7% Asian; and 20% Hispanic. Mean age at diagnosis of acute ITP was 8.7 ± SD 5.2 years. At the time of enrollment in NACIR, subjects had received a median of 2 prior treatments (range 0–7). Results: The median platelet count at diagnosis of acute ITP was 11,000/uL (IQR 6,000–31,000/uL) and at chronic ITP was 35,000/uL (IQR 18,000–66,000/uL). 69 (12.5%) patients had secondary ITP or Evans syndrome. Of those tested, 25.6% (98/359) of patients had a positive ANA (titer > 1:40), and 75/337 (22.3%) had a positive direct anti-globulin test (DAT). 27.5% of patients had an antecedent viral illness. Of the 550 subjects, 2 (0.4%) experienced life-threatening bleeding. Patients were treated as follows: 259 (47.1%) with steroids, 253 (46%) with IVIG, 189 (34.4%) with anti-D, and 64 (11.6%) with splenectomy. Overall responses to therapy included: 69.1% response to steroids, 74.3% response to IVIG, 66.7% response to anti-D, and 85.9% response to splenectomy. Univariate predictors of response to treatments are shown in Table I. Higher platelet count at chronic ITP diagnosis and DAT positive predicted a platelet response to a short course of steroids in univariate analysis. This was confirmed in multivariable analysis of potential confounders, using logistic regression with a backwards elimination procedure. Response to one type of therapy was often strongly associated with a response to a second therapy. Gender, ethnicity, race, older age, and platelets ≥20,000/uL at acute ITP diagnosis were not associated with response to any single therapy. Conclusion: The demographics and laboratory findings of the large, well characterized NACIR population are consistent with other reports of young people with chronic ITP. The novel finding that DAT positivity predicts steroid response, even with multivariable adjustment for confounders, provides evidence that the NACIR is a robust and useful tool for trying to predict response to ITP treatment strategies. Disclosures: Klaassen: Novartis: Research Funding; Cangene: Research Funding. Lambert: Cangene: Membership on an entity's Board of Directors or advisory committees.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".