Health Utility during the First Two Years of Treatment of Hematological Malignancies
Notice bibliographique
Résumé
Abstract Background There are limited patient reported outcomes for acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS) due to relatively low incidence rates and disease severity. Patient reported outcomes on health utility, a measure of quality of life weighted to the preferences of the general population, are however required for economic evaluation of interventions to diagnose and treat the diseases. This study was designed to report health utility outcomes from patients during their treatment for AML and MDS, for the first time. We sought to use the infrastructure of a multicentre study to report these outcomes in an otherwise inaccessible patient population and enable more accurate economic models. Methods Following institutional research ethics board approval at six recruiting study centres across Canada, the Euroqol five dimensions (EQ5D) health utility instrument and socio-demographic questionnaires were administered by telephone or in person to eligible participants in a national clinical study (NCT01685619). These data were linked to the treatment outcomes and health state transitions of each participant during their treatment of AML or MDS. A longitudinal analysis of treatment effects and cross-sectional regression analyses were undertaken for data collected at four, quarterly time points over the first year following diagnosis, and two semi-annual points over the second year. We defined health utility for specific economic health states and the co-varying impacts from socio-demographic characteristics and treatment-related impacts. Results At least one quality of life questionnaire was returned for 131 (96%) of the eligible patients who participated in the study. Response rates were greater than 60% at each of the scheduled time points. The median overall survival (468 days; 95% CI: 353-660) was reached over the 24 month term of follow-up. The most preferred health states involved greater than 12 months of survival (health utility > 0.78); the least preferred health states were reported for failed treatments and an initial AML diagnosis (health utility < 0.63). There were no significant differences found among utility outcomes that could be related to consolidation modality or remission induction intent. AML patients with 24 months of survival gained 0.037 more quality adjusted life years (QALYs) than MDS patients with equivalent survival time. An ordinary least squares regression model on the cross-sectional data suggests that having an MDS diagnosis was associated with a better short-term health utility while long term outcomes were greater for patients who survived 24 months after being diagnosed with AML (p<0.1). Conclusions This report on health utility outcomes was made possible only by collaboration with health economists and the infrastructure of a multicentre clinical study. The data suggest that survivors following 24 months of treatment for AML gained more QALYs than the survivors of MDS. The findings warrant further investigation due to the suggestion of equivalent health utility between treatments and to further validate the use of the EQ5D instrument in this disease area. Disclosures Savoie: Jazz: Consultancy; Lundbeck: Consultancy; Amgen: Consultancy; BMS: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Pfizer: Consultancy; Celgene: 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 machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».