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Enregistrement W2912674942 · doi:10.1182/blood-2018-99-113206

Health Related Quality of Life and Fatigue in Patients with Pyruvate Kinase Deficiency

2018· article· en· W2912674942 sur OpenAlexaff
Eduard J. van Beers, Kevin H.M. Kuo, D. Holmes Morton, Wilma Barcellini, Stefan Eber, Bertil Glader, Hassan M. Yaish, Satheesh Chonat, Nina Kollmar, Jenny M. Despotovic, Dagmar Pospı́šilová, Christine Knoll, Janet L. Kwiatkowski, Yves Pastore, Alexis A. Thompson, Winfred C. Wang, Marcin W. Włodarski, Peter E. Newburger, Yaddanapudi Ravindranath, Jennifer Rothman, Heng Wang, Suzanne Holzhauer, Vicky R. Breakey, Madeleine Verhovsek, Joachim B. Kunz, Sujit Sheth, Mukta Sharma, Melissa J. Rose, Heather A. Bradeen, Melissa A. McNaull, Kathryn Addonizio, David N. Williams, Rachael F. Grace

Notice bibliographique

RevueBlood · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueErythrocyte Function and Pathophysiology
Établissements canadiensMcMaster UniversityUniversité de MontréalCentre Hospitalier Universitaire Sainte-JustineUniversity Health Network
Organismes subventionnairesnon disponible
Mots-clésMedicineMissense mutationQuality of life (healthcare)AnemiaInternal medicineCompound heterozygosityPediatricsGeneticsMutation

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Pyruvate Kinase (PK) deficiency is the most common enzyme defect of the glycolytic pathway causing hereditary non-spherocytic hemolytic anemia. Patients have a broad phenotypic spectrum, ranging from mild anemia to transfusion dependence, and there is wide variation in transfusion practices and decisions about splenectomy. No prior studies have reported on the use of validated health related quality of life (HRQoL) measures in this population. Aim: To describe patient reported outcomes including general HRQoL and fatigue in adults with PK deficiency and the correlation with clinical and laboratory features. Methods: Patients were enrolled on the PK Deficiency Natural History Study, a prospective 30 site international study. All patients had molecularly confirmed PK deficiency. Adults (n=132), ages ≥18 years, completed the EuroQol-5D (high index equivalent to better QoL), PROMIS Fatigue Short Form 7a (high scores equivalent to higher fatigue), and the Functional Assessment of Cancer Therapy-Anemia (FACT-An, high scores equivalent to less fatigue) surveys at enrollment and annually. Timing of administration was convenience based. Survey data were analyzed according to proprietary scoring guidelines. Tests of association were performed using Fisher's exact test (categorical) and Wilcoxon rank sum test (continuous). Regular transfusions were defined as ≥6 transfusions in 12 months. Genotypes were grouped as two missense mutations (M/M), one missense/one non-missense (M/NM), or two non-missense mutations (NM/NM)); non-missense included deletions or other drastic variants. The minimal important difference (MID) for the FACT-An has been reported as 7 points (Cella et al, J Pain Symptom Manage 2002). P-values <0.05 were considered statistically significant. Results: At enrollment, 128 adults completed the FACT-An with a median total score of 156 (IQR 122-190). Patients receiving regular transfusions reported significantly lower FACT-An scores than those who were not regularly transfused (median 129 vs 156, p=0.004) with significantly lower scores for physical, emotional, and functional well-being and anemia sub-scores (Table). This difference also surpassed the MID. However, non- regularly transfused patients with hemoglobin (Hb) <8 g/dl did not report significantly different scores than those with Hb≥ 8 g/dl (p=0.75). There were also no significant differences in FACT-An scores by splenectomy status or age. The FACT-An score differences were greater than the MID for patients with iron overload (ferritin >1000 ng/dL or chelation), higher number of lifetime transfusions, and two missense mutations. Females reported significantly lower scores than males (median 143 vs. 160, p=0.006) with significantly lower anemia sub-scores (p=0.0009). FACT-An surveys completed at the one year follow-up time point validated these findings. EuroQol-5D scores (n=124) at enrollment were similar to the healthy population (median PK deficiency index score 0.88; healthy population index mean 0.88, Shaw et al, Medical Care 2005). No significant differences were found by Hb level, splenectomy status, transfusion status, or genotype group. The median PROMIS fatigue T score (n=66) was 52.1 (IQR 40.5-63.7). Similar to the FACT-An survey data, PROMIS fatigue scores were significantly worse in patients who were regularly transfused (67.0 vs 52.4, p=0.02). PROMIS fatigue scores were also significantly worse in patients ≥40 years old (p=0.05) and females (p=0.01). Conclusions: Using the FACT-An and PROMIS Fatigue measures, patients with PK deficiency who are regularly transfused report significantly more fatigue and worse HRQoL compared with those who are not transfused. Important differences were also seen by iron status and mutation group using the FACT-An. Patients report similar fatigue levels regardless of Hb level, which suggests that symptoms, rather than Hb value alone, should be factored into clinical decision making. In contrast to anemia related HRQoL scores, overall HRQoL scores using validated generic measures in patients with PK deficiency show no differences compared with the healthy population, suggesting that disease-specific measures may better detect the effects of PK deficiency on HRQoL. Disclosures Van Beers: Agios Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Glader:Agios Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Chonat:Agios Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees. Despotovic:AmGen: Research Funding; Novartis: Research Funding; Sanofi: Consultancy. Kwiatkowski:bluebird bio: Consultancy, Honoraria, Research Funding; Agios Pharmaceuticals: Consultancy, Research Funding; Novartis: Research Funding; Apopharma: Research Funding; Terumo: Research Funding. Thompson:La Jolla Pharmaceutical: Research Funding; Baxalta/Shire: Research Funding; Novartis: Research Funding; Celgene: Research Funding; bluebird bio: Consultancy, Research Funding; Biomarin: Research Funding; Amgen: Research Funding. Newburger:TransCytos LLC: Consultancy; Janssen Research & Development, LLC: Consultancy, Honoraria; X4 Pharmaceutics: Consultancy, Honoraria. Ravindranath:AGIOS: Other: Site Investigator for Pyruvate Kinase Deficiency. Sheth:Terumo Corporation: Research Funding; Novartis: Research Funding; La Jolla Pharmaceutical Company: Research Funding; Celgene Corporation: Consultancy, Research Funding; Bluebird Bio: Consultancy. Grace:Agios Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Agios Pharmaceuticals: Research Funding; Agios Pharmaceuticals: Consultancy.

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 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 enseignants0,006
Score d'incertitude au seuil0,189

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 Opus0,033
Tête enseignante GPT0,289
Écart entre enseignants0,255 · 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.

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
Publié2018
Routes d'admission1
Résumé présentoui

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