High-Tech Parameters for the Evaluation of Signs and Symptoms of Dry Eye Disease: Identification of Clinical Cut-Offs and Agreement with Low-Tech Tests

Paolo Fogagnolo; Pasquale Aragona; Alfonso Strianese; Edoardo Villani; Giuseppe Giannaccare; Vincenzo Orfeo; Valentina Mirisola; Rita Mencucci; Italian Dry Eye Study Group

doi:10.1007/s40123-024-01034-6

High-Tech Parameters for the Evaluation of Signs and Symptoms of Dry Eye Disease: Identification of Clinical Cut-Offs and Agreement with Low-Tech Tests

Ophthalmol Ther. 2024 Nov;13(11):2999-3011. doi: 10.1007/s40123-024-01034-6. Epub 2024 Sep 28.

Authors

Paolo Fogagnolo¹, Pasquale Aragona², Alfonso Strianese³, Edoardo Villani^{4

5}, Giuseppe Giannaccare⁶, Vincenzo Orfeo⁷, Valentina Mirisola⁸, Rita Mencucci⁹; Italian Dry Eye Study Group

Collaborators

Italian Dry Eye Study Group:
Valentino De Ruvo, Silvia Sonego, Chiara Quisisana, Luca Mario Rossetti, Elisa Imelde Postorino, Claudia Azzaro

Affiliations

¹ Health Sciences Department, University of Milan, Milan, Italy. paolo.fogagnolo@unimi.it.
² Section of Ophthalmology, Department of Biochemical Sciences, University of Messina, Messina, Italy.
³ Eye Clinic, ASST Santi Paolo E Carlo, University of Milan, Milan, Italy.
⁴ Department of Clinical Science and Community Health, University of Milan, Milan, Italy.
⁵ Eye Clinic San Giuseppe Hospital, IRCCS Multimedica, Milan, Italy.
⁶ Department of Ophthalmology, University Magna Graecia of Catanzaro, Catanzaro, Italy.
⁷ Unità Operativa di Oculistica Clinica Mediterranea, Naples, Italy.
⁸ Polistudium SRL, Milan, Italy.
⁹ Department of Neurosciences, Psychology, Drug Research, and Child Health, Eye Clinic, University of Florence, AOU Careggi, Florence, Italy.

Abstract

Introduction: High-tech devices for the assessment of dry eye disease (DED) are increasingly available. However, the agreement between high- and low-tech parameters has been poorly explored to date. Trying to fill these gaps, we conducted a post hoc analysis on a recently published retrospective study on patients with DED receiving both low- and high-tech (Keratograph^®) assessments, and treatment with different lubricating eyedrops.

Methods: Six clinical questions were defined by the authors, considering literature gaps and their clinical experience, namely: (1) are NIKBUT-i and T-BUT interchangeable parameters? (2) What was the correlation between low- and high-tech parameters in untreated and treated patients with DED? (3) What was the correlation between signs and symptoms at baseline and during/after treatment? (4) Which parameters were better associated with symptoms? And with symptoms change over time? (5) What was the performance of NIKBUT-i and T-BUT in detecting clinically relevant changes? (6) What was the clinical advantage of adding other high- and low-tech parameters, respectively, to NIKBUT-i and T-BUT?

Results: Low-tech measures were the best descriptors of the Ocular Surface Disease Index (OSDI) at baseline. In contrast, high-tech assessments demonstrate better performance in detecting changes over time. The distribution of NIKBUT-i data was more dispersed than TBUT both at baseline and follow-up. At a fixed specificity of 80%, the sensitivity in detecting clinically relevant ameliorations of symptoms was 42% for NIKBUT-i and 25% for T-BUT. A battery of high-tech tests could detect 90% of clinical amelioration, compared with 45% with low-tech tests (p < 0.001). Correlation between low- and high-tech parameters in both treated and untreated patients is lacking.

Conclusions: Low-tech measures are adequate for diagnostic purposes in DED, whereas high-tech showed better performances at follow-up, particularly when different tests are combined. Overall, poor interchangeability among parameters and agreement with symptoms was reported both with high- and low-tech assessments.

Keywords: Break-up time; Dry eye disease; High-tech imaging; Tear film instability.