RESUMO
Pemphigus vulgaris (PV) is a rare autoimmune bullous dermatosis (AIBD) characterized by painful blistering of the skin and mucosa caused by autoantibodies that lead to loss of adhesion in the epidermis. Standard therapy for PV is corticosteroids, either alone or in combination with steroid-sparing immunosuppressants or infusions with rituximab. According to the published European guideline, high-dose intravenous immunoglobulin (IVIg) therapy with a dosage of 2 g per kg body weight distributed over 2-5 days every 4 weeks is a promising treatment option, especially for severe or refractory disease. This report describes a 73-year-old female patient with severe and recurrent disease who achieved stabilization with IVIg treatment. However, the patient experienced side effects such as headaches, nausea, and vomiting, which affected daily life. Hence, she was transitioned to a new IVIg preparation with a new manufacturing process, resulting in fewer side effects and an improved quality of life. Further follow-up is necessary to fully evaluate the effectiveness and tolerability of this new IVIg product.
RESUMO
IMPORTANCE: Total body photography for skin cancer screening is a well-established tool allowing documentation and follow-up of the entire skin surface. Artificial intelligence-based systems are increasingly applied for automated lesion detection and diagnosis. DESIGN AND PATIENTS: In this prospective observational international multicentre study experienced dermatologists performed skin cancer screenings and identified clinically relevant melanocytic lesions (CRML, requiring biopsy or observation). Additionally, patients received 2D automated total body mapping (ATBM) with automated lesion detection (ATBM master, Fotofinder Systems GmbH). Primary endpoint was the percentage of CRML detected by the bodyscan software. Secondary endpoints included the percentage of correctly identified "new" and "changed" lesions during follow-up examinations. RESULTS: At baseline, dermatologists identified 1075 CRML in 236 patients and 999 CRML (92.9%) were also detected by the automated software. During follow-up examinations dermatologists identified 334 CRMLs in 55 patients, with 323 (96.7%) also being detected by ATBM with automated lesions detection. Moreover, all new (n = 13) or changed CRML (n = 24) during follow-up were detected by the software. Average time requirements per baseline examination was 14.1 min (95% CI [12.8-15.5]). Subgroup analysis of undetected lesions revealed either technical (e.g. covering by clothing, hair) or lesion-specific reasons (e.g. hypopigmentation, palmoplantar sites). CONCLUSIONS: ATBM with lesion detection software correctly detected the vast majority of CRML and new or changed CRML during follow-up examinations in a favourable amount of time. Our prospective international study underlines that automated lesion detection in TBP images is feasible, which is of relevance for developing AI-based skin cancer screenings.