Long-Term Safety of Ixekizumab Treatment in Patients with Psoriasis, Psoriatic Arthritis, or Axial Spondyloarthritis: a Post Hoc Analysis of Cerebro-Cardiovascular Events.

Introduction: Psoriasis (PsO), psoriatic arthritis (PsA), and axial spondyloarthritis (axSpA) may confer an increased risk for cardiovascular (CV) disease, including major adverse cerebro-cardiovascular events (MACE), deep vein thrombosis (DVT), and pulmonary embolism (PE). Patients with these conditions are often exposed for extended time periods to biologics, such as ixekizumab (IXE). Therefore, understanding the risk of CV events, especially MACE, in patients with PsO, PsA, and axSpA exposed to IXE is important.

The association between obesity and efficacy of psoriasis therapies: An expert consensus panel.

Background: Psoriasis is a chronic inflammatory skin disease often associated with obesity. Psoriasis therapies may be less effective in patients with obese. The purpose of this expert consensus panel is to evaluate the relationship between obesity and efficacy of psoriasis therapies, thereby optimizing patient care.

International Dermatology Outcome Measures (IDEOM): A Report From the 2023 Annual Meeting.

Background: International Dermatology Outcome Measures (IDEOM) is a non-profit organization whose mission is to improve the availability of evidence-based, consensus-driven outcome measures for dermatological diseases. IDEOM facilitates collaboration between stakeholders from various backgrounds, including researchers, patients, physicians, and industry representatives, to develop objective benchmark metrics that enable better treatment and management of dermatologic conditions.

Summary: The 2023 IDEOM Annual Meeting was held June 23-24, 2023.

Development and Validation of Algorithms to Identify Individuals With Cutaneous Lupus From Healthcare Databases.

Background: There are no validated methods to identify individuals with cutaneous lupus erythematosus (CLE) from large databases including claims data and electronic health records, severely limiting the study of the epidemiology of this disease.

Objectives: To develop and validate accurate algorithms to identify individuals with CLE from healthcare records.

Methods: Twelve case-finding algorithms were developed based on the International Classification of Diseases (ICD)-10 diagnosis codes, provider specialty, and medication prescription data.