Changes In Health Status and Quality of Life In Adults with Thalassemia: Year 1 Report of the Thalassemia Longitudinal Cohort Study.
Notice bibliographique
Résumé
Abstract Abstract 1533 Background: Advances in treatment of thalassemia have led to increased life expectancy for patients, making outcomes such as health related quality of life (HRQOL) an important consideration of therapy. However little has been published about the HRQOL of patients living with thalassemia, especially as it may change over time. Our study reports changes in patient-reported HRQOL from baseline to year 1 in the Thalassemia Clinical Research Networks (TCRN) Thalassemia Longitudinal Cohort (TLC) study. Methods: The TCRN is an NIH sponsored network of 16 major thalassemia centers in the US, Canada and London. We report here on the results from 220 patients (approximately 80% of the total cohort) over the age of 14 who completed baseline and year 1 assessments. HRQOL was measured by self-report with the Medical Outcomes Study 36-Item Short Form Health Survey version 2 (SF36v2). We defined a clinically significant change as a difference of at least 2 points on any SF-36 subscale. Results: Overall the patients were 46% male with a mean age of 29 years at baseline (range 14–58). Across the TLC population, mean self-reported HRQOL showed little change over the 1 year study period, with only social functioning showing a significant increase (p=0.04). However in each SF-36 domain over 50% of patients reported a signficant change in scores (an increase or decrease of more than 2 points) (Figure 1). All patients had a significant change on at least one domain, with a mean of 7 domains affected. Overall a small majority of patients (56%) reported that their health in general was “about the same” at year 1 as at baseline; 14% reported it was somewhat worse, 19% somewhat better, and 11% much better. Forty-nine % of patients reported requiring fewer transfusions in year 1, while 34% needed more, and 17% had no change. Most patients (82%) made no change in their chelator, although 8% changed from deferoxamine (DFO) to an oral chelator, fewer than 1% changed from oral to DFO, and 3% each stopped and started chelation. Most patients (61%) reported the same general adherence rate, although taken together there was slightly better reported adherence in year 1. Almost half of patients (47%) reported no change in chelator side effects, although again there was a slight overall decrease in reported side effects across the group. Most patients (92%) reported no new secondary complications in year 1. As expected, increasing age was associated with decreased HRQOL in the following domains: physical function, bodily pain, vitality, social function, mental health, and physical summary scales, although only bodily pain showed a clinically significant change (+2.1 points). Gender, race, change in number of transfusions, and change in chelator were not associated with change in HRQOL, although there was a trend towards improved general health in patients who made any change in chelation. A decrease in reported side effects from chelation was associated with an improvement in physical functioning (+2.8) and the mental summary score (+3.48), while development of a new complication during the one year study period was associated with a decrease in role-emotional (-8.2). Surprisingly an increase in reported adherence was associated with a decrease in social functioning (-5.1), role emotional (-7.7) and the mental summary score (-5.4). Conclusions: As a population, the TLC showed overall stability in clinical status and SF-36 scores over the 1 year study period. However individual patients reported significant changes, both positive and negative, in an average of 7 SF-36 domains. HRQOL appears to be most affected by age, with some association with changes in chelator, secondary complications, side effects and adherance. Further analysis is needed in order to fully understand these associations. Disclosures: Neufeld: Novartis, Inc: Research Funding; Ferrokin, Inc: Research Funding.
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 | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».