MétaCan
Menu
Retour à la cohorte
Enregistrement W4313402716 · doi:10.1002/jvc2.92

Development of rapid, reliable and novel severity measures for psoriasis and eczema

2022· article· en· W4313402716 sur OpenAlexaff
Wayne Gulliver, O. P. Yadav, Susanne Gulliver, M. Cousens

Notice bibliographique

RevueJEADV Clinical Practice · 2022
Typearticle
Langueen
DomaineImmunology and Microbiology
ThématiquePsoriasis: Treatment and Pathogenesis
Établissements canadiensNewfoundland and Labrador Centre for Applied Health Research
Organismes subventionnairesnon disponible
Mots-clésPsoriasis Area and Severity IndexPsoriasisBody surface areaEczema Area and Severity IndexMedicineDermatologyClinical PracticeSeverity of illnessGestalt psychologyCorrelationAtopic dermatitisPsychologyInternal medicinePhysical therapyMathematics

Résumé

récupéré en direct d'OpenAlex

Physician global assessment (PGA) and body surface area (BSA) have long been used to rapidly assess psoriasis patients' disease severity in both clinical practice and trials. Psoriasis area and severity index (PASI) in patients with psoriasis and the Eczema area and severity index (EASI) in patients with atopic eczema are effective but time-consuming and many dermatologists may not find PASI and EASI feasible while evaluating patients in a clinical setting. Developing rapid and effective tools to assess disease severity and response to treatment is of paramount importance. Historically, researchers have attempted to establish methods for developing a rapid, reliable, and valid physician reported outcome (PRO) for psoriasis or eczema that could be used in clinical practice.1, 2 However, the studies shows variation in the correlation coefficients depending on the severity and duration of the disease. We believe that we have developed such a PRO for both PASI and EASI, namely the G2-PASE (Gulliver-Gestalt-psoriasis area severity estimate) and G2 -EASE (Gulliver-Gestalt-eczema area severity estimate) (see Table 1). We considered both a Gestalt BSA and a PGA with a constant (which is arbitrary and may be corrected in the future) to determine the PRO of G2-PASE or G2-EASE. The correlation between PASI and G2-PASE and EASI and G2-EASE was determined using a sample of 100 patients with G2-PASI and 77 with G2-EASE. The data is then validated using a second random sample of 100 and 77 patients, respectively, for the G2-PASE and G2-EASE. The products of Gestalt PGA and BSA were calculated using the appropriate multiplier for G2-PASE and G2-EASE (see Table 1). Correlation coefficients, Cronbach's alpha reliability tests3 and area under the receiver operating characteristic curve (ROC AUC) were used to ascertain the association between PASI and G2-PASE, as well as between EASI and G2-EASE (see Table 2). In both the first and second samples, there is a strong correlation between PASI and G2-PASE, with correlation coefficients of 0.90 (p value 0.00) and 0.82 (p value 0.00), respectively. Overall, excellent reliability was determined using Cronbach's α (0.91 and 0.89). G2-EASE was calculated in a similar manner utilising gestalt BSA and PGA, with a correlation coefficient of 0.95 (p value 0.000) for the first sample and 0.92 (p value 0.000) for the second sample. Cronbach's α values of 0.97 and 0.95 indicated excellent reliability for G2-EASE. AUC values are determined to be 1 (p = 0.00) for all data sets utilised in the study, indicating that the newly adopted tools are highly reliable. Further statistical analysis with a larger data set can be performed to establish the validity of newly developed PRO's. Our plan is to conduct additional validation of data with larger cohorts to strengthen the scientific foundations for G2-PASE and G2-EASE. Based on preliminary data, we conclude that G2-PASE and G2-EASE are both rapid and reliable clinician-reported outcomes effective of estimating PASI and EASI scores using the product of PGA and gestalt BSA with acceptable constants. W. P. Gulliver: Research idea and development of indices; data collection; research design; manuscript write-up and review; manuscript submission; overall supervision. O. P. Yadav: Data validation; statistical data analysis; manuscript write-up and editing. S. Gulliver: Project administration; manuscript editing; review. M. Cousens: Data compilation; manuscript editing. Funding is not available for this study. W. P. Gulliver: Relationships with commercial interests: Grants/research support: AbbVie, Amgen, Eli Lilly, Novartis, Pfizer. Honoraria for Ad Boards/Invited Talks/Consultation: AbbVie, Actelion, Amgen, Arylide, Bausch Health, Boehringer, Celgene, Cipher, Eli Lilly, Galderma, Janssen, LEO Pharma, Merck, Novartis, PeerVoice, Pfizer, Sanofi-Genzyme, Tribute, UCB, Valeant. Other: Clinical trials (study fees): AbbVie, Asana Biosciences, Astellas, Boerhinger-Ingleheim, Celgene, Corrona/National Psoriasis Foundation, Devonian, Eli Lilly, Galapagos, Galderma, Janssen, LEO Pharma, Novartis, Pfizer, Regeneron, UCB. The remaining authors declare no conflict of interest. Data available on request due to privacy/ethical restrictions. Not applicable. Data available on request due to privacy/ethical restrictions.

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)0,003
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,961
Score d'incertitude au seuil0,528

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,002
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 Opus0,086
Tête enseignante GPT0,351
Écart entre enseignants0,266 · 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'étudeSans objet
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
Publié2022
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueJEADV Clinical PracticeMême sujetPsoriasis: Treatment and PathogenesisTravaux en français237 207