709 - Greater levels of itch relief and skin clearance correlate with improved patient outcomes in atopic dermatitis – real-world insights from TARGET-DERM AD
Notice bibliographique
Résumé
Abstract Introduction/Background Atopic dermatitis (AD) patients undergoing treatment may only experience partial improvements in their itch and skin lesions. However, partial improvement may not translate into optimal patient outcomes. There is limited evidence describing the impact of achieving higher efficacy measures in AD. Objectives To assess the independent and combined effects of itch and skin of improvement on patient-reported symptoms and quality-of-life outcomes. Methods The study included adult participants (age ≥18 years) with AD enrolled in TARGET-DERM AD, an observational, longitudinal study of >4,000 participants across 52 academic/community centers in the United States and Canada. Itch severity was assessed by the Patient-Reported Outcome Measurement Information System (PROMIS) Itch-Severity[3] item evaluating “itch at its worst” on a 0–10 numeric rating scale (NRS). A score of 0 or 1 indicated no/minimal itch (NRS-Itch 0/1). Skin severity was assessed by the validated Investigator Global Assessment of AD (vIGA-AD), with 0 or 1 representing clear/almost clear skin (vIGA-AD 0/1). The association of itch and skin severity with scores representing an ideal state in AD symptoms and quality of life outcomes were assessed as follows: patient-reported clear/almost clear disease (Patient-Oriented Eczema Measure [POEM] 0–2), little or no impact of AD on quality of life (Dermatology Life Quality Index [DLQI] 0/1), little or no sleep impact (NRS-Sleep 0/1), and little or no pain (NRS-Pain 0/1). Associations were assessed using descriptive statistics and logistic regression models including main and interaction effects for itch and skin severity. Results Among adult participants (n=1920; mean age 45 years, 59% female; 55% Non-Hispanic White), data was available from participants at enrollment for the outcomes as follows: vIGA-AD (99%, 1,913), NRS-Itch (54%, 1,042), DLQI (50%, 967), POEM (51%, 974), NRS-Sleep (50%, 958), and NRS-Pain (50%, 965). The proportion reporting ideal state scores was highest among those with NRS-Itch 0/1 (52% DLQI 0/1; 54% POEM 0–2; 57% NRS-Sleep 0/1; 83% NRS-Pain 0/1) and clear/almost clear skin (45% DLQI 0/1; 44% POEM 0–2; 45% NRS-Sleep 0/1; 74% NRS-Pain 0/1), with decreasing proportions generally observed at greater itch and skin severity levels. Among patients who had vIGA-AD 0/1, the proportion of participants with an ideal state score for all PROs increases substantially when patients also attain NRS itch 0/1: 69% DLQI 0/1, 78% POEM 0–2, 68% NRS-Sleep 0/1, and 92% NRS-Pain 0/1. The adjusted odds ratio of reporting DLQI 0/1, POEM 0–2, NRS-Sleep 0/1, and NRS-Pain 0/1 was highest among those with both no/minimal itch and clear/almost clear skin (20.0, 41.6, 6.0, and 16.1, respectively), followed by no/minimal itch only (6.1, 6.7, 3.1, and 4.3, respectively), and clear/almost clear skin only (4.4, 5.0, 1.6, and 3.0, respectively). Conclusions Achieving complete or almost complete resolution of itch and skin lesions is associated with greater odds of achieving an ideal state in terms of patient reported symptoms and quality of life (DLQI, POEM, NRS-Sleep, and NRS-Pain) with itch relief exhibiting a slightly higher impact than skin clearance. These results underscore the importance of assessing and documenting both itch severity and skin clearance to support shared decision-making. Moreover, simultaneous resolution of both itch and skin lesions should be considered when setting treatment goals in AD patients.
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 | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».