Impact of prophylaxis on health‐related quality of life of boys with hemophilia: An analysis of pooled data from 9 countries
Notice bibliographique
Résumé
BackgroundProphylaxis reduces the frequency of bleeds in boys with severe hemophilia and is the standard care for their management in resource‐abundant countries. The effect of prophylaxis on Health‐Related Quality of Life (HRQoL) has not been established, because the sample sizes of most studies are too small to explore the relationship of multiple factors that influence HRQoL.MethodsThe aim of this study was to assess the impact of hemophilia severity and treatment regimen on HRQoL and to establish the minimum important difference (MID) using the international level of score distributions. HRQoL data were pooled from 7 studies across 9 countries. HRQoL was measured using the Canadian Hemophilia Outcomes–Kids’ Life Assessment Tool (CHO‐KLAT). A mixed‐effect linear regression analysis was employed to assess the impact of prophylaxis on the CHO‐KLAT score.ResultsData from 401 boys with hemophilia were analyzed (57.6% severe hemophilia and 57.6% receiving prophylaxis). The model revealed that receiving prophylaxis was significantly associated with higher HRQoL (regression coefficient 8.5, 95% confidence interval [CI] 3.9‐13.1). Boys with severe hemophilia had a significantly lower HRQoL as compared to boys with moderate and mild hemophilia whose CHO‐KLAT scores were 7.0 and 6.6 points higher, respectively. There was a significant interaction between treatment and disease severity (P=0.023), indicating prophylaxis has the most significant impact in boys with severe hemophilia. Based on these pooled data, the MID of the CHO‐KLAT was established at 6.5.ConclusionsThis study confirms the positive effect of prophylaxis on HRQoL in boys with hemophilia in a real‐world setting and provides initial benchmarks for interpreting HRQoL scores based on use of the CHO‐KLAT instrument. Prophylaxis reduces the frequency of bleeds in boys with severe hemophilia and is the standard care for their management in resource‐abundant countries. The effect of prophylaxis on Health‐Related Quality of Life (HRQoL) has not been established, because the sample sizes of most studies are too small to explore the relationship of multiple factors that influence HRQoL. The aim of this study was to assess the impact of hemophilia severity and treatment regimen on HRQoL and to establish the minimum important difference (MID) using the international level of score distributions. HRQoL data were pooled from 7 studies across 9 countries. HRQoL was measured using the Canadian Hemophilia Outcomes–Kids’ Life Assessment Tool (CHO‐KLAT). A mixed‐effect linear regression analysis was employed to assess the impact of prophylaxis on the CHO‐KLAT score. Data from 401 boys with hemophilia were analyzed (57.6% severe hemophilia and 57.6% receiving prophylaxis). The model revealed that receiving prophylaxis was significantly associated with higher HRQoL (regression coefficient 8.5, 95% confidence interval [CI] 3.9‐13.1). Boys with severe hemophilia had a significantly lower HRQoL as compared to boys with moderate and mild hemophilia whose CHO‐KLAT scores were 7.0 and 6.6 points higher, respectively. There was a significant interaction between treatment and disease severity (P=0.023), indicating prophylaxis has the most significant impact in boys with severe hemophilia. Based on these pooled data, the MID of the CHO‐KLAT was established at 6.5. This study confirms the positive effect of prophylaxis on HRQoL in boys with hemophilia in a real‐world setting and provides initial benchmarks for interpreting HRQoL scores based on use of the CHO‐KLAT instrument.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».