The Mcmaster ITP Registry: Assessing the Prevalence, Clinical and Laboratory Features of Immune Thrombocytopenia
Bibliographic record
Abstract
Abstract Introduction: Immune thrombocytopenia (ITP) is a common platelet disorder; however, it is a heterogeneous disease and optimal treatment has not been established. Understanding the epidemiology of ITP requires large observational cohort studies and prospective registries with prolonged follow-up. We established the McMaster ITP Registry to study the natural history of ITP and to identify clinical and laboratory features that may distinguish disease subgroups. The objectives of this study were 1) to assess the accuracy of data collection in the McMaster ITP Registry; and 2) to describe the prevalence, clinical features and platelet autoantibody results from a large cohort of ITP patients. Methods: The McMaster ITP Registry enrolls consecutive adult patients with thrombocytopenia (platelet count <150 x109/L) from a tertiary hematology clinic. Patients are prospectively followed every 6 months until discharge or death. Patients are assigned to a diagnostic category based on information from the most recent clinic visit. Baseline and time-varying characteristics are collected including prevalent and incident bleeding events and treatments received. Laboratory tests, including screening for secondary causes, are performed at baseline and all platelet counts measured during follow up are captured. Platelet autoantibody testing for anti-glycoprotein (GP) IIbIIIa and anti-GP IbIX is performed at baseline, 6 and 12 months using the direct antigen capture method. Accuracy of data capture for diagnosis, disease stage of ITP, and lowest platelet count was evaluated for 50 registry patients chosen at random by comparing the data in the registry with data abstracted from patients’ charts by 2 independent assessors. Agreement was calculated using Cohen’s kappa (k). Funding for the registry was provided by Amgen. Results: From January 2010 to February 2014, 465 thrombocytopenic patients were enrolled in the McMaster ITP Registry: 258 (55.5%) had ITP, either primary (n=221) or secondary (n= 37). The remaining 207 patients (44.5%) had non-immune thrombocytopenia associated with pregnancy, myelodysplastic syndrome, liver disease or other causes. Median age at diagnosis of ITP was 41 years [interquartile range (IQR), 32 – 58], 62.8% were female and patients had received a median of 2 (IQR, 0 – 4) treatments at last follow up. 33.3% of patients had splenectomy, 15.4% had received rituximab and 20.5% had received thrombopoietin receptor agonists (either romiplostim or eltrombopag). Platelet antibodies were measured in 197 patients with primary ITP: 109 (55.3%) had either anti-IIbIIIa or anti-IbIX. Accuracy of data collection was excellent for all items checked (k>0.8 for each); yet, to improve the method of capturing diagnosis and disease stage, we removed a category (‘mild thrombocytopenia’), renamed a category (‘liver disease’) and added a category (‘unknown cause’) following this validation exercise. Conclusion: In the setting of a tertiary hematology referral clinic, 55% of patients presenting with thrombocytopenia had ITP. Of patients with primary ITP, 55.3% had anti-platelet autoantibodies. Our classification of patients by diagnosis of thrombocytopenia was simplified after the validation study. The McMaster ITP Registry can help identify clinical and laboratory features of ITP patients to better understand natural history and treatment responses. Disclosures Arnold: GSK: Honoraria, Research Funding; Hoffman-LaRoche: Research Funding; Bristol Myers Squibb: Consultancy; Amgen: Consultancy, Honoraria, Research Funding.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".