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Enregistrement W2205449481 · doi:10.1182/blood.v124.21.4190.4190

Response to TPO-Receptor Agonists: Role of Immature Platelet Fraction and Anti-GP1b

2014· article· en· W2205449481 sur OpenAlexaff
Alexandra Kruse, Alexa M. Sughroue, Patrick B. Morrissey, Claudia Tchatchouang, Guangheng Zhu, Marina Izak, Heyu Ni, James B. Bussel

Notice bibliographique

RevueBlood · 2014
Typearticle
Langueen
DomaineMedicine
ThématiquePlatelet Disorders and Treatments
Établissements canadiensSt. Michael's Hospital
Organismes subventionnairesnon disponible
Mots-clésPlateletMedicineEltrombopagRomiplostimThrombopoietinInternal medicineImmunologyGastroenterologyImmune thrombocytopeniaBiologyHaematopoiesis

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Thrombocytopenia in Immune Thrombocytopenia (ITP) results from a combination of increased platelet destruction and reduced production, both often secondary to anti-platelet antibodies. Absolute immature platelet fraction (A-IPF) is a measure of young reticulated platelets in peripheral blood, and therefore provides an assessment of platelet production. Decreased platelet production in patients with ITP has been addressed by the recently developed Thrombopoietin Receptor Agonists (TPO-RA), which stimulate megakaryopoiesis and thereby, in responders, increase platelet production to a level which overcomes platelet destruction. The majority of ITP patients will respond to these agents, but which ones will respond is not known. Aims: To explore A) whether baseline A-IPF levels are associated with platelet response to TPO–RA, and B) whether antibodies to platelet glycoproteins 1b or β3 influence the platelet response to TPO-RA. Methods: Platelet counts and A-IPF values were collected from patients treated with TPO-RA (n=91) at Weill Medical College of Cornell University until 2013. All available counts were included, and the median count for each month was determined pre-treatment, and at 1, 2, 3, 4, 5, and 6 months. Patients were divided by whether (n=20) or not (n=71) they often received rescue therapy (i.e. IVIG and/or daily steroids >10mg). The 71 patients who received minimal or no rescue treatment were deemed responders if the average of their six median monthly platelet counts doubled from baseline and was >50x109/L. Based on pretreatment A-IPF, patients were stratified into three cohorts: low (0-25), middle (26-40), and high (41+). Clinical variables such as age, splenectomy status, duration of ITP, and gender were also studied. The 20 “rescue” patients were similarly analyzed. The 84 patients with available sera had their antibody levels measured to GP1b and β3 by Elisa by Dr. Ni. Samples were sent to the lab and analyzed without knowledge of response status or associated A-IPF level. Patients were divided into four categories for analysis of their antiplatelet antibodies: positive for anti-ß3 antibody, positive for anti-GP1b, positive for both, or negative for both. Fisher’s exact, student t-, and chi-square tests were used to analyze differences in response to TPO-RA among patient groups, A-IPF levels, and anti-platelet antibodies. Results: 71 Patients with Minimal Rescue Therapy Fifty-nine of the 71 patients responded to TPO-RA. There was no significant difference in A-IPF values for responders and non-responders (p=0.95; Figure 1). A significant positive correlation was observed between increase in A-IPF over the 6-month period and response rate to TPO-RA (p=0.009). Age, gender, duration of ITP, and splenectomy status neither correlated with response rate, nor trended with A-IPF cohorts. Figure 1 Figure 1. 20 Patients with Rescue Therapy For the 20 patients who often received rescue therapy, low response rates were seen in the low A-IPF cohort and high response rates in the higher A-IPF cohorts. The percent of responders to treatment was higher in patients with chronic ITP than with newly diagnosed and persistent ITP (p= 0.04). Age, gender, and splenectomy status showed no relationship with response to TPO-RA. In comparison with the 71 patient group, the 20 patients presented lower response rates in all groups, with the exception of females. Anti-platelet Antibodies There was a weak correlation between A-IPF and anti-GP1b antibody levels (R=0.225), demonstrating that antibodies to GP1b may have a specific impact on platelet production. Patients who did not have detectable antibody to either GP1b or β3 responded better to TPO-RA than patients who tested positive for both Anti-GP1b and Anti-ß3 (p=0.003). The strongest correlation was observed between level of anti-GP1b and response to TPO-RA (p<0.001; Figure 2). Figure 2 Figure 2. Conclusion: Rather than baseline A-IPF levels or clinical variables, the best predictor of good response to TPO-RA therapy was the absence of anti-GP1b and anti- β3 platelet antibodies, especially anti-GP1b. An explanation for the dominant effect of antibodies to GP1b is that stimulating megakaryopoiesis with TPO-RA would not effect a platelet increase as these antibodies may block proplatelet extension, preventing platelet release into the circulation. This may also explain the effect of anti-GP1b on response to steroids and IVIG. Disclosures Off Label Use: Eltrombopag is a thrombopoietin receptor agonist approved for the treatment of thrombocytopenia in adults with chronic ITP. Use in children and adolescents will be discussed.. Bussel:Amgen: Equity Ownership; GSK: Equity Ownership; Amgen: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding; GSK: Research Funding; Sysmex: 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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,005

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,004
Tête enseignante GPT0,231
Écart entre enseignants0,227 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2014
Routes d'admission1
Résumé présentoui

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