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Enregistrement W2983968100 · doi:10.1182/blood-2019-130591

Physicians' and Patients' Perspectives on Treatments in ITP - a Multi-Country Perspective: Results from the ITP World Impact Survey (I-WISh)

2019· article· en· W2983968100 sur OpenAlexaffabout
James B. Bussel, Waleed Ghanima, Yoshiaki Tomiyama, Donald M. Arnold, Drew Provan, Ming Hou, Cristina Santoro, Serge Laborde, Alexandra Kruse, Caroline Kruse, Mervyn Morgan, Barbara Lovrenčič, John Waller, Jens Haenig, Nichola Cooper

Notice bibliographique

RevueBlood · 2019
Typearticle
Langueen
DomaineMedicine
ThématiquePlatelet Disorders and Treatments
Établissements canadiensMcMaster University
Organismes subventionnairesnon disponible
Mots-clésWishPerspective (graphical)MedicineSociologyComputer science

Résumé

récupéré en direct d'OpenAlex

Treatment strategies for immune thrombocytopenia (ITP) aim to achieve a platelet count associated with adequate hemostasis while maximizing patient (pt) quality of life (QoL) and minimizing treatment-emergent toxicities. However, physicians' (MDs) and pts' treatment goals have not been studied and compared. I-WISh is a cross-sectional survey of 1507 ITP pts and 472 MDs across 13 countries studying burden of ITP and pt QoL using a global pt and MD sampling frame; pts were recruited via MDs and pt advocacy groups (PAGs). ITP expert MDs and PAG representatives designed and endorsed the survey. We report treatment goals that MDs and pts perceive as being most important and how these vary among countries and different healthcare systems. Pt-reported use of ITP treatments at time of survey and any prior time are also described. Top-ranked treatment goals for MDs were reduction in spontaneous bleeds (72%), better QoL (64%), and healthy blood counts (51%). The top treatment goals for pts were healthy blood counts (64%), preventing episodes of ITP worsening (44%), and increasing energy levels (41%). More MDs than pts selected reduction in spontaneous bleeds (72% vs 38%) and QoL (64% vs 38%) as top priorities; fewer MDs vs pts selected healthy blood counts (51% vs 64%) and reduction of fatigue (15% vs 41%). MD and pt rankings of their top 3 treatment goals by country are shown in Fig.1 A&B and differences in MD vs pt perceptions in Fig. 1C. The largest differences in the percentage of MDs and pts who ranked reduction in spontaneous bleeds as a top goal were observed in France, India, Canada, UK, and USA; in each country, MDs ranked this treatment goal more often in their top 3 than pts. In contrast, lighter menstrual periods had a < 10% difference between pts and MDs in all but 2/13 countries. In certain countries, responses appeared to be balanced across similar goals, i.e. ~40% difference in ranking of reduction in spontaneous bleeds by MDs vs pts and healthy blood counts by pts vs MDs in the UK. Similarly, an 11% difference in MD vs pt ranking of improved QoL and pt vs MD ranking of increasing energy levels were observed. The largest differences in the percentages of MDs and pts who ranked healthy blood counts in their top 3 goals were observed in UK and Colombia. The largest differences between MDs and pts in their perception of reduction of fatigue as a top 3 goal were in Canada, Egypt, USA, and UK; MDs generally ranked it less important than pts, except in India. Corticosteroids (CSs) were prescribed in 79% of pts for treatment of ITP, with 26% of pts on CSs at time of survey. Countries with the highest CS use at any time were Colombia, France, and USA; Colombia, India, and Egypt had the highest CS use at time of survey. Lowest CS use at any time prior to the survey was reported by pts in Japan, Turkey, and Germany. Thrombopoietin receptor-agonists (TPO-RAs) were prescribed in 27% of pts, with 17% of pts on TPO-RA at time of survey. Countries with highest TPO-RA use at any time were Turkey, UK, Egypt, and USA. At the time of survey, TPO-RAs were most frequently used by pts in Egypt, with the lowest use in Japan. Anti-CD20 was prescribed in 29% of pts, with 5% on anti-CD20 at the time of survey. Countries with highest anti-CD20 use at any time were USA, France, and Canada. At the time of survey, anti-CD20s were most frequently used by pts in India, with no use in Turkey or Egypt. CSs were the most prevalent ITP treatments prior to and at time of survey. While this was to be expected, the high use of steroids in the USA and France compared with other countries was unanticipated. TPO-RAs and anti-CD20 have changed the landscape of second-line ITP therapies, but their utilization varies greatly among countries. Access to advanced/costly therapies is one factor that differs between countries and may influence treatment trends, but others are also important. The I-WISh survey showed that certain specific treatment goals are perceived differently by MDs and pts. Interpretation of the data is limited by the similarity of answer choice (eg, healthy blood counts and absence of spontaneous bleeds; fatigue, a key component of QoL; and QoL), which may have led to differences in responses despite similar understanding. Nonetheless, an overall agreement was generally observed, which may have been facilitated by increased MD and pt access to information through the internet and other sources, eg, medical education activities. Figure 1 Disclosures Bussel: Tranquil: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; argenx: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Kezar Life Sciences: Consultancy, Membership on an entity's Board of Directors or advisory committees; UCB: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; RallyBio: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Physician Education Resource: Speakers Bureau; 3S Bio: Speakers Bureau; Rigel: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Honoraria, Membership on an entity's Board of Directors or advisory committees; Dova Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Momenta Pharmaceuticals: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Regeneron: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Ghanima:Amgen: Consultancy, Honoraria; Bayer: Honoraria, Research Funding; Pfizer/BMS: Research Funding; Novartis: Consultancy, Honoraria, Research Funding. Tomiyama:Chugai: Honoraria; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Kyowa-Kirin: Honoraria. Arnold:Rigel: Consultancy, Research Funding; Novartis: Honoraria, Research Funding; Bristol-Myers Squibb: Research Funding; Principia: Consultancy. Provan:Rigel ONO: Consultancy, Research Funding; ONO Pharmaceutical: Consultancy; Amgen: Consultancy, Honoraria, Research Funding; MedImunne: Consultancy; UCB: Consultancy; Novartis: Consultancy, Honoraria, Research Funding. Santoro:Grifols: Membership on an entity's Board of Directors or advisory committees; Novo Nordisk: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Shire: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; CSL: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Sobi: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Amgen: Speakers Bureau; GSK: Speakers Bureau; Bayer: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Pfizer: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Gilead: Membership on an entity's Board of Directors or advisory committees. Kruse:UCB: Honoraria; Amgen: Research Funding; Argenx: Research Funding; Dova: Research Funding; Novartis: Research Funding; Momenta: Research Funding; Principia: Research Funding; Octapharma: Research Funding; CSL Behring: Research Funding; UCB: Research Funding; Novartis: Consultancy. Waller:Adelphi Real World: Employment; Novartis: Consultancy. Haenig:Novartis: Employment. Cooper:Principia: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Rigel: Consultancy, Membership on an entity's Board of Directors or advisory committees.

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)0,004
score de la tête « metaresearch » (Gemma)0,015
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 enseignants0,008
Score d'incertitude au seuil0,024

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,015
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0010,001
Communication savante0,0020,002
Science ouverte0,0000,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,012
Tête enseignante GPT0,279
Écart entre enseignants0,267 · 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
Publié2019
Routes d'admission2
Résumé présentoui

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