Challenges in Teledermoscopy Diagnostic Outcome Studies: Scoping Review of Heterogeneous Study Characteristics
Notice bibliographique
Résumé
BACKGROUND: Teledermoscopy has demonstrated benefits such as decreased costs and enhanced access to dermatology care for skin cancer detection. However, the heterogeneity among teledermoscopy studies hinders the systematic reviews' synopsis of diagnostic outcomes, impeding trust and adoption in general practice and limiting overall health care benefits. OBJECTIVE: This study aims to improve understanding and standardization of teledermoscopy diagnostic studies, by identifying and categorizing study characteristics contributing to heterogeneity. Subsequently, the variability and consistency of these characteristics were assessed. METHODS: A review of systematic reviews regarding the diagnostic outcomes of teledermoscopy was performed to discern reported study characteristics contributing to heterogeneity. These characteristics were thematically grouped into 3 domains (population, index test, and reference standard), forming a data extraction framework. A scoping review on teledermoscopy diagnostic outcomes studies was performed, guided by the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. Data pertaining to study characteristics from included studies were extracted and analyzed through descriptive content analysis. Systematic reviews' reference lists validated the scoping review query. RESULTS: The literature search yielded 4 systematic reviews, revealing 15 heterogeneous studies across the population, index test, and reference standard domains. The scoping review identified 49 studies, with 27 overlapping with the systematic reviews. Population characteristics varied, with one-third (16/49, 33%) of studies reporting fewer than 100 samples; most studies (41/49, 84%) reported on the type of lesion, and most (20/49, 41%) teledermoscopy consultations took place in secondary care. One-fifth (11/49, 22%) did not describe inclusion or exclusion criteria, or the criteria varied highly. Index test characteristics showed differences in clinical expertise, profession, and training in dermatoscopic photography, and 59% (29/49) did not report on 1 or more index test characteristics. Image quality and clinical information reporting likewise varied. Reference standard characteristics involved teledermatologists' assessment, but 16 studies did not report teledermatologists' experience levels. Most studies (26/49, 53%) used histopathology as a gold standard. CONCLUSIONS: The heterogeneity in the population, index tests, and reference standard domains across teledermoscopy diagnostic outcome studies underscores the need for standardized reporting. This hinders the synopsis of teledermoscopy diagnostic outcomes in systematic reviews and limits the integration of research results into practice. Adopting a (tailored) STARD (Standards for Reporting Diagnostic Accuracy Studies) checklist for teledermoscopy diagnostic outcome studies is recommended to enhance the consistency and comparability of outcomes. We suggest performing a Delphi study to gather consensus on the tailored STARD guideline.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| 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 ».