14 research outputs found

    Patient-reported outcomes measures and patient preferences for minimally invasive glaucoma surgical devices.

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    BackgroundMany therapeutic options are available to glaucoma patients. One recent therapeutic option is minimally invasive glaucoma surgical (MIGS) devices. It is unclear how patients view different treatments and which patient-reported outcomes would be most relevant in patients with mild to moderate glaucoma. We developed a questionnaire for patients eligible for MIGS devices and a patient preference study to examine the value patients place on certain outcomes associated with glaucoma and its therapies.ObjectivesTo summarize the progress to date.MethodsQuestionnaire development: We drafted the questionnaire items based on input from one physician and four patient focus groups, and a review of the literature. We tested item clarity with six cognitive interviews. These items were further refined. Patient preference study: We identified important benefit and risk outcomes qualitatively using semi-structured, one-on-one interviews with patients who were eligible for MIGS devices. We then prioritized these outcomes quantitatively using best-worst scaling methods.ResultsQuestionnaire testing: Three concepts were deemed relevant for the questionnaire: functional limitations, symptoms, and psychosocial factors. We will evaluate the reliability and validity of the 52-item draft questionnaire in an upcoming field test. Patient preference study: We identified 13 outcomes that participants perceived as important. Outcomes with the largest relative importance weights were "adequate IOP control" and "drive a car during the day."ConclusionsPatients have the potential to steer clinical research towards outcomes that are important to them. Incorporating patients' perspectives into the MIGS device development and evaluation process may expedite innovation and availability of these devices

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

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    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
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