Heterogeneity of reported outcomes in epidermolysis bullosa clinical research:a scoping review as a first step towards outcome harmonization

BACKGROUND: Epidermolysis bullosa (EB) is a rare, genetically and clinically heterogeneous group of skin fragility disorders. No cure is currently available, but many novel and repurposed treatments are upcoming. For adequate evaluation and comparison of clinical studies in EB, well-defined and consistent consensus-endorsed outcomes and outcome measurement instruments are necessary.OBJECTIVES: To identify previously reported outcomes in EB clinical research, group these outcomes by outcome domains and areas and summarize respective outcome measurement instruments.METHODS: A systematic literature search was performed in the databases MEDLINE, Embase, Scopus, Cochrane CENTRAL, CINAHL, PsycINFO and trial registries covering the period between January 1991 and September 2021. Studies were included if they evaluated a treatment in a minimum of three patients with EB. Two reviewers independently performed the study selection and data extraction. All identified outcomes and their respective instruments were mapped onto overarching outcome domains. The outcome domains were stratified according to subgroups of EB type, age group, intervention, decade and phase of clinical trial.RESULTS: The included studies (n = 207) covered a range of study designs and geographical settings. A total of 1280 outcomes were extracted verbatim and inductively mapped onto 80 outcome domains and 14 outcome areas. We found a steady increase in the number of published clinical trials and outcomes reported over the past 30 years. The included studies mainly focused on recessive dystrophic EB (43%). Wound healing was reported most frequently across all studies and referred to as a primary outcome in 31% of trials. Great heterogeneity of reported outcomes was observed within all stratified subgroups. Moreover, a diverse range of outcome measurement instruments (n = 200) was identified.CONCLUSIONS: We show substantial heterogeneity in reported outcomes and outcome measurement instruments in EB clinical research over the past 30 years. This review is the first step towards harmonization of outcomes in EB, which is necessary to expedite the clinical translation of novel treatments for patients with EB.</p

Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma

Abstract Artificial intelligence (AI) systems have been shown to help dermatologists diagnose melanoma more accurately, however they lack transparency, hindering user acceptance. Explainable AI (XAI) methods can help to increase transparency, yet often lack precise, domain-specific explanations. Moreover, the impact of XAI methods on dermatologists’ decisions has not yet been evaluated. Building upon previous research, we introduce an XAI system that provides precise and domain-specific explanations alongside its differential diagnoses of melanomas and nevi. Through a three-phase study, we assess its impact on dermatologists’ diagnostic accuracy, diagnostic confidence, and trust in the XAI-support. Our results show strong alignment between XAI and dermatologist explanations. We also show that dermatologists’ confidence in their diagnoses, and their trust in the support system significantly increase with XAI compared to conventional AI. This study highlights dermatologists’ willingness to adopt such XAI systems, promoting future use in the clinic