The Mcmaster ITP Registry: Assessing the Prevalence, Clinical and Laboratory Features of Immune Thrombocytopenia
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».