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Enregistrement W2980012151 · doi:10.1182/blood-2018-99-114589

Patients' Perspectives on the Definition of Cure in Chronic Myeloid Leukemia: A US Based Survey

2018· article· en· W2980012151 sur OpenAlexaff
Gemlyn George, Ehab Atallah, Michael J. Mauro, Stuart L. Goldberg, Arielle Baim, Jessica Guhl, Alexander Hinman, Jörge E. Cortes, Michael W. Deininger, Brian Druker, Vamsi Kota, Richard A. Larson, Jeffrey H. Lipton, Joseph O. Moore, Vivian G. Oehler, Javier Pinilla Ibarz, Jerald P. Radich, Ellen K. Ritchie, Charles A. Schiffer, Neil P. Shah, Richard T. Silver, Kendra Sweet, James E. Thompson, Martha Wadleigh, Kathryn E. Flynn

Notice bibliographique

RevueBlood · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueChronic Myeloid Leukemia Treatments
Établissements canadiensPrincess Margaret Cancer CentreUniversity Health Network
Organismes subventionnairesnon disponible
Mots-clésMedicineRespondentFamily medicineMyeloid leukemiaDiseaseInternal medicine

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction: The development of tyrosine kinase inhibitors (TKIs) has markedly improved the prognosis of patients (pts) with chronic myeloid leukemia (CML), with the perception by healthcare professionals that this is now a chronic disease to be managed. However, the need for continuous TKI therapy may result in ongoing toxicities, limits on fertility, and financial hardship. The H. Jean Khoury Cure CML consortium (HJKC3) is a collaborative effort of physicians and researchers at 17 academic centers. The HJKC3-001 2017 Patient Survey sought to define pts' expectations for treatment in CML to serve as a guidepost for future research in this area. Methods: Pts with CML were recruited by HJKC3 physicians, CML advocacy groups, and social media. An online survey platform (Qualtrics®) was used to obtain informed consent and administer the questionnaire. The anonymous survey was designed to gauge priorities for research in CML, understand patient definitions of cure, and elicit patient interest in future directions for CML therapy. Patient demographic and health characteristics were also collected. The data were analyzed using descriptive statistics. Results: Of the 458 pts who completed the survey, the median age of respondents was 54 years (range 18-81); 88% of pts identified as non-Hispanic white, 2% as non-Hispanic black, 2% as non-Hispanic Asian, 4% as Hispanic, and 4% other. Patients rated their overall health as poor (4%), fair (18%), good (40%), very good (28%) and excellent (9%). All but one respondent said that more research was needed for CML, with pts indicating their preferences for where they considered the need was greatest (Table 1). Overwhelmingly, 94% of respondents considered cure in CML as not taking any more pills. All but three respondents had received treatment with a TKI, with 26% (n=119) of pts having previously stopped their TKI medication for at least one month. When presented with the possibility of stopping all future treatment for CML with additional treatment, 97% of pts were willing to add another oral medication to their TKI while 89% of pts would accept intravenous treatment in addition to a TKIs. Half of the pts had discussed treatment discontinuation with their physician, with 45% considering this option in an attempt at treatment-free-remission. Of the pts that stopped taking their TKIs for at least one month, 65% did so because of side effects and another 10% because of cost. Conclusion: This survey demonstrates that pts do not consider disease control with life-long oral medication as cure; rather, cure requires the absence of treatment. Overwhelmingly, pts indicated the importance of continuing CML research with an ultimate goal of treatment-free cure. The advent of oral TKIs has been a tremendous success for pts with this disease. Nevertheless, it remains a source of disruption in pts' lives, particularly through side effects and costs. The HJKC3 was initiated with the goal of curing CML. Disclosures Atallah: Novartis: Consultancy; Jazz: Consultancy; Pfizer: Consultancy; BMS: Consultancy; Abbvie: Consultancy. Mauro:Bristol-Myers Squibb: Consultancy; Pfizer: Consultancy; Takeda: Consultancy; Novartis: Consultancy, Research Funding. Goldberg:COTA Inc.: Employment, Equity Ownership. Cortes:Daiichi Sankyo: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Astellas Pharma: Consultancy, Research Funding; Arog: Research Funding. Deininger:Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees; Blueprint: Consultancy. Druker:ARIAD: Research Funding; Third Coast Therapeutics: Membership on an entity's Board of Directors or advisory committees; Patient True Talk: Consultancy; Amgen: Membership on an entity's Board of Directors or advisory committees; MolecularMD: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Novartis Pharmaceuticals: Research Funding; Henry Stewart Talks: Patents & Royalties; Leukemia & Lymphoma Society: Membership on an entity's Board of Directors or advisory committees, Research Funding; McGraw Hill: Patents & Royalties; Aptose Therapeutics: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Cepheid: Consultancy, Membership on an entity's Board of Directors or advisory committees; GRAIL: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Meyers Squibb: Research Funding; Oregon Health & Science University: Patents & Royalties; Gilead Sciences: Consultancy, Membership on an entity's Board of Directors or advisory committees; Monojul: Consultancy; Vivid Biosciences: Membership on an entity's Board of Directors or advisory committees; Blueprint Medicines: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Millipore: Patents & Royalties; Fred Hutchinson Cancer Research Center: Research Funding; Beta Cat: Membership on an entity's Board of Directors or advisory committees; ALLCRON: Consultancy, Membership on an entity's Board of Directors or advisory committees; Aileron Therapeutics: Consultancy; Celgene: Consultancy. Larson:Novartis: Consultancy, Research Funding; Ariad/Takeda: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; BristolMyers Squibb: Consultancy, Research Funding. Lipton:Bristol-Myers Squibb: Consultancy, Research Funding; ARIAD: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding. Ritchie:Incyte: Consultancy, Speakers Bureau; NS Pharma: Research Funding; Bristol-Myers Squibb: Research Funding; Astellas Pharma: Research Funding; ARIAD Pharmaceuticals: Speakers Bureau; Novartis: Consultancy, Other: Travel, Accommodations, Expenses, Research Funding, Speakers Bureau; Pfizer: Consultancy, Research Funding; Celgene: Consultancy, Other: Travel, Accommodations, Expenses, Speakers Bureau. Shah:Bristol-Myers Squibb: Research Funding; ARIAD: Research Funding. Sweet:Celgene: Honoraria, Speakers Bureau; Jazz: Speakers Bureau; Celgene: Honoraria, Speakers Bureau; Agios: Consultancy; Phizer: Consultancy; Astellas: Consultancy; Astellas: Consultancy; Jazz: Speakers Bureau; Phizer: Consultancy; BMS: Honoraria; Novartis: Consultancy, Honoraria, Speakers Bureau; Agios: Consultancy; Novartis: Consultancy, Honoraria, Speakers Bureau; BMS: Honoraria.

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)0,003
score de la tête « metaresearch » (Gemma)0,008
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,008
Score d'incertitude au seuil0,017

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,008
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0000,001
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 Opus0,024
Tête enseignante GPT0,256
Écart entre enseignants0,232 · 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'étudeQualitatif
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
Publié2018
Routes d'admission1
Résumé présentoui

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