Critical appraisal of the clinical utility of the dexamethasone intravitreal implant (Ozurdex®) for the treatment of macular edema related to branch retinal vein occlusion or central retinal vein occlusion

Macular edema is a common cause of visual loss in patients with retinal vein occlusions. Ozurdex®, a dexamethasone intravitreal implant, has been shown in randomized controlled trials to reduce macular edema and improve visual acuity in patients with either branch retinal vein occlusions or central retinal vein occlusions. It was approved in the United States in 2009. Since then, new therapeutic agents and clinical data have emerged. The purpose of this review is to critically evaluate the clinical utility of Ozurdex® in the current treatment strategy of macular edema related to retinal vein occlusion

Defining a Minimum Set of Standardized Patient-centered Outcome Measures for Macular Degeneration

Purpose To define a minimum set of outcome measures for tracking, comparing, and improving macular degeneration care. Design Recommendations from a working group of international experts in macular degeneration outcomes registry development and patient advocates, facilitated by the International Consortium for Health Outcomes Measurement (ICHOM). Methods Modified Delphi technique, supported by structured teleconferences, followed by online surveys to drive consensus decisions. Potential outcomes were identified through literature review of outcomes collected in existing registries and reported in major clinical trials. Outcomes were refined by the working group and selected based on impact on patients, relationship to good clinical care, and feasibility of measurement in routine clinical practice. Results Standardized measurement of the following outcomes is recommended: visual functioning and quality of life (distance visual acuity, mobility and independence, emotional well-being, reading and accessing information); number of treatments; complications of treatment; and disease control. Proposed data collection sources include administrative data, clinical data during routine clinical visits, and patient-reported sources annually. Recording the following clinical characteristics is recommended to enable risk adjustment: age; sex; ethnicity; smoking status; baseline visual acuity in both eyes; type of macular degeneration; presence of geographic atrophy, subretinal fibrosis, or pigment epithelial detachment; previous macular degeneration treatment; ocular comorbidities. Conclusions The recommended minimum outcomes and pragmatic reporting standards should enable standardized, meaningful assessments and comparisons of macular degeneration treatment outcomes. Adoption could accelerate global improvements in standardized data gathering and reporting of patient-centered outcomes. This can facilitate informed decisions by patients and health care providers, plus allow long-term monitoring of aggregate data, ultimately improving understanding of disease progression and treatment responses

White paper on ophthalmic imaging for choroidal nevus identification and transformation into Melanoma

Purpose: To discuss the evolution of noninvasive diagnostic methods in the identification of choroidal nevus and determination of risk factors for malignant transformation as well as introduce the novel role that artificial intelligence (AI) can play in the diagnostic process. Methods: White paper. Results: Longstanding diagnostic methods to stratify benign choroidal nevus from choroidal melanoma and to further determine the risk for nevus transformation into melanoma have been dependent on recognition of key clinical features by ophthalmic examination. These risk factors have been derived from multiple large cohort research studies over the past several decades and have garnered widespread use throughout the world. More recent publications have applied ocular diagnostic testing (fundus photog-raphy, ultrasound examination, autofluorescence, and optical coherence tomography) to identify risk factors for the malignant transformation of choroidal nevus based on multimodal imaging features. The widespread usage of ophthalmic imaging systems to identify and follow choroidal nevus, in conjunction with the characterization of malignant transformation risk factors via diagnostic imaging, presents a novel path to apply AI. Conclusions: AI applied to existing ophthalmic imaging systems could be used for both identification of choroidal nevus and as a tool to aid in earlier detection of transformation to malignant melanoma. Translational Relevance: Advances in AI models applied to ophthalmic imaging systems have the potential to improve patient care, because earlier detection and treatment of melanoma has been proven to improve long-term clinical outcomes