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Noninfectious Uveitis: A Review of Ophthalmic Management and Clinical Pearls

Luke G Qin, Michael T Pierce, Rachel C Robbins

The uvea is a vascular stratum that includes the iris, ciliary body and choroid. Uveitis is defined as inflammation of a part of the uvea or its entirety, but it is also used to describe inflammatory processes of any part of the eye, such as the vitreous or peripheral retina. The clinical taxonomy of uveitis […]

touchREVIEWS in Ophthalmology. 2024;19(1):1–8:Online ahead of journal publication

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Anterior Segment Corneal and External Disorders Ocular Surface Disease
2 mins

Biomarkers In Dry Eye Disease

Michael A Lemp, Benjamin D Sullivan, Leslie A Crews
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Published Online: May 22nd 2012 European Ophthalmic Review, 2012;6(3):157-163 DOI: http://doi.org/10.17925/EOR.2012.06.03.157
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1

Abstract

Overview

Dry eye disease is a multifactorial chronic disorder of the ocular surface that affects up to 100 million people worldwide. During the pathogenesis of dry eye, impaired function of the lacrimal and meibomian glands results in hyposecretion of aqueous tear fluid, coupled with increased evaporation and instability of the tear film, which becomes increasingly hyperosmolar in character at more severe stages of disease. One critical issue in the field is that the commonly used clinical signs and symptoms for the diagnosis or classification of dry eye often do not correlate with one another. This underscores the need to systematically evaluate current tests and highlights the importance of developing new markers of disease progression for use as endpoints in clinical trials of diagnostic devices and potential therapeutics. In this review, we examine the utility and limitations of commonly used signs and symptoms of dry eye disease and comment on newer biomarkers and analytical devices that show promise for future diagnostic and therapeutic use.

Keywords

Dry eye disease, biomarkers, tear film, hyperosmolarity, symptoms, objective, subjective

2

Article

Dry eye disease (DED) is thought to affect upwards of 30–40 million people within the US.1 Officially, the definition and classification of dry eye was updated in 2007 during the Tear Film and Ocular Surface (TFOS) Dry Eye WorkShop (DEWS).2

‘Dry eye is a multifactorial disease of the tears and ocular surface that results in symptoms of discomfort, visual disturbance and tear film instability with potential damage to the ocular surface. It is accompanied by increased osmolarity of the tear film and inflammation of the ocular surface.’

Whether initiated by ageing, androgen deficiency, contact lens wear, refractive surgery or an autoimmune disease,1,3 dysfunctions of the lacrimal and meibomian glands result in hyposecretion and increased evaporation of tear fluid, which promote instability of the tear film.2,4 This leads to significant fluctuations in vision, loss of lubrication, inflammation, an increase in wear (epitheliopathy) and varying levels of neuropathy and corneal sensitisation. Thus, while diagnosis of DED may be thought to be straightforward in more severe examples of disease, determining the severity of the disease – especially at early stages, requires a deeper understanding of the potential aetiologies and clinical presentation of the disease to reconcile both the statistical and subjective aspects of severity.

Biomarkers – surrogates or substitutes for variables of clinical disease – are often used in the assessment of disease states, particularly in clinical trials of therapeutics and diagnostic devices.5

The terms (bio)markers, surrogates, endpoints, outcomes and others ave been used to describe a metric that is either objective or subjective, which accurately reflects the characteristics of disease. In medicine, common examples of this are the use of serum cholesterol or blood pressure for cardiovascular disease,6 or in ophthalmology intraocular pressure for glaucoma.7 A surrogate outcome has been defined as a “laboratory measurement or a physical sign used as a substitute for a clinically meaningful endpoint that measures directly how a patient feels, functions or survives”.8 The value of such a metric lies in how accurately it can capture important aspects of the disease. Such measures are typically used clinically in diagnosis, assessment of disease severity and response to therapy.

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2

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3

Article Information

Disclosure

This study was supported by TearLab Corporation (San Diego, CA). The authors wish to indicate the following financial interests in TearLab Corporation: Consultant (MAL, LAC), Equity (MAL, BDS), Patents (BDS), Employee (BDS).

Correspondence

Michael A Lemp, TearLab Corporation, 7360 Carroll Road Suite 200, San Diego CA, 92121, US. E: malemp@lempdc.com

Received

2012-03-03T00:00:00

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Machine Learning Models for the Diagnosis of Dry Eyes Using Real-World Clinical Data

Tamer N Jarada, Karl Stonecipher, Olivia Perez

Dry eye disease (DED) is a prevalent ocular condition characterized by discomfort, visual disturbances and tear film instability due to insufficient tear production or rapid tear evaporation.1 With an increasing global incidence (i.e. up to 50%) and its significant impact on the quality of life, there is a growing need for accurate and efficient diagnostic methods to […]

European Ophthalmic Review, 2012;6(3):157-163 DOI: http://doi.org/10.17925/EOR.2012.06.03.157
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