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Enregistrement W4388418754 · doi:10.2147/ppa.s421871

Patient and Physician Preferences for Acute Myeloid Leukemia Maintenance Treatments Following Hematopoietic Stem Cell Transplantation

2023· article· en· W4388418754 sur OpenAlexaffabout
Lalit Saini, James D. Griffin, Bhavik J. Pandya, Manasee V. Shah, Mo Zhou, Hongbo Yang, Yan Song, Deborah A. Marshall

Notice bibliographique

RevuePatient Preference and Adherence · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensUniversity of CalgaryLondon Health Sciences Centre
Organismes subventionnairesAstellas Pharma
Mots-clésMedicineHematopoietic stem cell transplantationQuality of life (healthcare)TransplantationLogistic regressionMyeloid leukemiaInternal medicineFamily medicineNauseaOncology

Résumé

récupéré en direct d'OpenAlex

Purpose: This study assessed and compared preferences for treatment attributes of maintenance therapies post-hematopoietic stem cell transplantation (HSCT) in patients with acute myeloid leukemia (AML) and in physicians who treat these patients. Patients and Methods: Patients with AML post HSCT and physicians from the United States, United Kingdom, Canada, and Australia (physicians only) completed a web-based discrete choice experiment (DCE). The DCE used inputs identified via a targeted literature review and qualitative interviews to ascertain relevant treatment attributes and associated levels. Six treatment attributes were selected (chance of 2-year relapse-free survival, quality of life [QoL], risk of serious infections, risk of nausea, chance of achieving transfusion independence, and duration of hospitalization annually), each with three or four levels. The experimental design included 36 choice tasks that presented a pair of hypothetical treatment profiles with varying attribute levels; participants chose a preferred treatment for each choice task. Choice tasks were divided into three blocks of 12 tasks each in the patient survey and 4 blocks of 9 tasks each in the physician survey; survey participants were randomly assigned to one of the blocks. Random parameter logit regression models were used to assess the impact of stated attributes on preferences for maintenance treatment post HSCT. Results: Surveys from 84 patients and 149 physicians were assessed. For patients, QoL was the most important attribute, followed by duration of hospitalization and chance of 2-year relapse-free survival. For physicians, chance of 2-year relapse-free survival was the most important attribute, followed by QoL and risk of serious infections. Conclusion: Differences in how patients and physicians valued post-HSCT maintenance treatment attributes were identified. These differences suggest that patient-centered decision-making may help physicians choose maintenance treatments for patients with AML post HSCT that better meet their treatment needs and improve their treatment satisfaction. Plain Language Summary: Patients with acute myeloid leukemia (AML) are often treated with chemotherapy followed by stem cell transplantation (SCT). Following SCT, evidence suggests that some patients may benefit from maintenance therapy. In this study, researchers surveyed patients and physicians who treat patients with AML to understand what maintenance treatment characteristics they most valued following SCT. Characteristics evaluated during the survey were chance of survival without relapse, impact on quality of life, risk of serious infections, risk of nausea, chance of being free of needing blood transfusions, and impact on annual hospital length of stay. For patients, the most important maintenance treatment characteristics were better quality of life and fewer hospital days annually. For physicians, the most important maintenance treatment characteristic was a higher chance of survival without relapse. These results show differences in maintenance treatment preferences between patients and physicians, suggesting that patient-centered decision-making could be useful when selecting a maintenance treatment for AML after SCT that meets patients’ treatment needs and improves their treatment satisfaction. Keywords: acute myeloid leukemia, hematopoietic stem cell transplantation, maintenance treatment, discrete choice experiment, quality of life, treatment preferences

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Autre devis · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,849
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
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)0,0000,000

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 Opus0,038
Tête enseignante GPT0,290
Écart entre enseignants0,252 · 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 tête enseignante, pas un consensus.

Devis d'étudeAutre devis
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

Citations7
Publié2023
Routes d'admission2
Résumé présentoui

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