Beyond intraocular pressure: Optimizing patient-reported outcomes in glaucoma

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Abstract

Glaucoma, an irreversible blinding condition affecting 3–4% adults aged above 40 years worldwide, is set to increase with a rapidly aging global population. Raised intraocular pressure (IOP) is a major risk factor for glaucoma where the treatment paradigm is focused on managing IOP using medications, laser, or surgery regimens. However, notwithstanding IOP and other clinical parameters, patient-reported outcomes, including daily functioning, emotional well-being, symptoms, mobility, and social life, remain the foremost concerns for people being treated for glaucoma. These outcomes are measured using objective patient-centered outcome measures (PCOMs) and subjective patient-reported outcome measures (PROMs). Studies using PCOMs have shown that people with glaucoma have several mobility, navigational and coordination challenges; reading and face recognition deficits; and are slower in adapting to multiple real-world situations when compared to healthy controls. Similarly, studies have consistently demonstrated, using PROMs, that glaucoma substantially and negatively impacts on peoples’ self-reported visual functioning, mobility, independence, emotional well-being, self-image, and confidence in healthcare, compared to healthy individuals, particularly in those with late-stage disease undergoing a heavy treatment regimen. The patient-centred effectiveness of current glaucoma treatment paradigms is equivocal due to a lack of well-designed randomized controlled trials; short post-treatment follow-up periods; an inappropriate selection or availability of PROMs; and/or an insensitivity of currently available PROMs to monitor changes especially in patients with newly diagnosed early-stage glaucoma. We provide a comprehensive, albeit non-systematic, critique of the psychometric properties, limitations, and recent advances of currently available glaucoma-specific PCOMs and PROMs. Finally, we propose that item banking and computerized adaptive testing methods can address the multiple limitations of paper-pencil PROMs; customize their administration; and have the potential to improve healthcare outcomes for people with glaucoma.

Introduction

Glaucoma refers to a related, but somewhat heterogenous, group of optic neuropathies that differ in their causes, risk factors, demographics, symptoms, treatment and diagnosis. The progressive degeneration of retinal ganglion cells in glaucoma results in thinning of the neuroretinal rim and optic disc cupping, a defining characteristic of glaucomatous damage associated with visual field (VF) loss and loss of contrast sensitivity (Fig. 1a and b) (Weinreb and Khaw, 2004). From pathophysiological and treatment standpoints, intraocular pressure (IOP) remains the disease's primary modifiable risk factor, since glaucoma progression can slow significantly if IOP is lowered by 20–50% of its baseline value (Sihota et al., 2018; Wormald, 2003).

Glaucoma can be classified into two broad categories, namely primary open angle glaucoma (POAG) and primary angle-closure glaucoma (PACG), based on the morphology of the anterior chamber angle, located between the peripheral cornea and iris; and containing the Schlemm's canal through which the aqueous humour leaves the eye. As the name implies, the anterior chamber angle is wide open in POAG, and the rise in IOP, if present at all, is a gradual and painless process (Kwon et al., 2009). In contrast, the anterior chamber angle in PACG is either narrowed or completely closed, leading to either asymptomatic chronic PACG, or a rapid increase in IOP with associated notable symptoms, including headaches, eye pain, nausea and blurred vision, termed acute primary angle closure (Nongpiur et al., 2011). Glaucoma can also occur secondary to trauma, medications (e.g. corticosteroids), inflammation (e.g. uveitis), tumours, or other conditions (e.g. pigment dispersion syndrome, exfoliation syndrome).

Glaucoma is the most common cause of irreversible blindness globally, and is set to increase due to a rapidly aging global population (Bourne et al., 2013, 2016, 2018; Stevens et al., 2013; Tham et al., 2014). In 2014, our group synthesized data from 50 population-based studies worldwide to estimate the prevalence of primary glaucoma (open angle and angle-closure) cases (Tham et al., 2014). Using these data, we estimated that approximately 64.3 millions of 2.33 billion individuals (3.5%) aged 40–80 years had glaucoma globally, with POAG cases being approximately six times more common than PACG (3.1% versus 0.5%) (Tham et al., 2014). Those of African ancestry had the highest prevalence of primary glaucoma (6.1%) and POAG (4.2%), whilst PACG prevalence was highest in East Asians (1.1%) (Tham et al., 2014). Importantly, using age and region-adjusted Bayesian models, we projected a 74.0% increase (111.8 million) by the year 2040 (Tham et al., 2014).

Increasing age is a strong predisposing risk factor for glaucoma, with the prevalence of the disease in black and Hispanic populations increasing from approximately 0.5% and 1%, respectively, in individuals between 40 and 49 years of age, to 11–22% in those aged 80 years and older (Leske et al., 1994; Tielsch et al., 1991; Varma et al., 2004; Wormald et al., 1994). Race is another known risk factor: blacks and Hispanics have increased prevalence of POAG, while PACG is proportionately more prevalent in those of Inuit, Chinese, Asian Indian or South-East Asian origin, compared to Caucasians (Arkell et al., 1987; Quigley and Broman, 2006; Tham et al., 2014; Tielsch et al., 1991; Varma et al., 2004; Wormald et al., 1994). A history of glaucoma in a first-degree relative, e.g. parents and siblings, is also associated with a higher risk (Kong et al., 2011; Tielsch et al., 1994; Wolfs et al., 1998). For instance, having a sibling with POAG increases the likelihood of an individual developing glaucoma by almost fourfold (Tielsch et al., 1994). Other established risk factors for POAG include diabetes (Zhao et al., 2015), obstructive sleep apnoea (Liu et al., 2016), and refractive error (Marcus et al., 2011; Shen et al., 2016).

Studies have consistently demonstrated the high economic burden of glaucoma, both in terms of direct (e.g., financial cost of treatment) and indirect costs (e.g., loss of well-being, assessed in disability-adjusted life years [DALYs], and loss of work productivity) (Lazcano-Gomez et al., 2016; Varma et al., 2011). Wittenborn and Rein estimated, using data between 2003 and 2011, that glaucoma costs the US population US$5.8 billion per annum in direct and indirect costs, excluding DALYs (Wittenborn and Rein, 2013). Moreover, the economic impact of the disease increases as severity worsens (Lee et al., 2006), with the majority of costs related to medication at all severity stages (Traverso et al., 2005). In terms of DALYs, the Global Burden of Disease Study showed that glaucoma had an estimated global DALYs of 943,000 in 2010, which is again driven by individuals with late-stage disease (Boyers et al., 2015). Assuming a monetary value of US$50,000 per DALY (Gordois et al., 2012), glaucoma contributed an additional ~ US$4.7 billion to the global disease burden.

Section snippets

IOP and beyond

IOP lowering remains a common clinical outcome for glaucoma, with studies unequivocally measuring and reporting changes in IOP in relation to treatment and its associated adherence. IOP, of course, is carefully evaluated in glaucoma because of its strong relevance to future disease progression (Kass et al., 2002; Leske et al., 2007; The Advanced Glaucoma Intervention Study (AGIS), 2000). Indeed, major clinical trials continue to incorporate VF progression as a primary endpoint (Garway-Heath et

What are patient-reported outcomes?

Patient-reported outcomes are reports associated with health conditions, that come directly from the patient, without external interpretation (Food and Drug Administration, 2009). They encompass a range of measurable outcomes from the patient's perspective, including the effect of a disease or health condition on generic health and functioning; as well as disease-specific symptoms and aspects of QoL, self-management, coping, and self-efficacy (Basch, 2014). Patient-reported outcomes can be

Critical review of PCOMs and PROMs in glaucoma

In the following sections, we critically review the psychometric properties of glaucoma-specific PCOMs (objective measures) and PROMs (subjective measures). We evaluate Classical Test Theory (CTT) metrics, such as validity (i.e. the degree to which a PROM measures what it purports to measure), reliability (i.e. the degree to which the measurement is free from measurement error), responsiveness (i.e. the ability of a PROM to detect change over time in the construct being measured) and

Future developments

Healthcare is transitioning from volume-based care (i.e. reimbursement based on the volume of healthcare doctors provide, also known as ‘fee-for-service’ care) to value-based care which is based more on quality of care and patient outcomes rather than quantity of care. This has resulted in a global initiative to incorporate systematic collection of high-quality patient-reported data in clinical care (Basch, 2017). However, as previously outlined, paper-pencil questionnaires are often lengthy,

Conclusions

People with moderate to severe levels of VF damage from glaucoma and/or those undergoing complicated treatment regimens may experience a substantial negative impact on multiple domains of QoL. However, more detailed studies including clinical, population-based and longitudinal data are still needed to fully elucidate people's understanding of their condition and its perceived impact, especially in the early stages which are generally asymptomatic (Crabb, 2016; McDonald et al., 2019). The

Author statement

Eva Fenwick - 25%

Ryan Man- 20%

Tin Aung – 10%

Pradeep Ramulu – 20%

Ecosse Lamoureux – 25%

Funding

E.L. and T.A. are supported by the Singapore National Medical Research Council's Clinician Scientist (NMRC-CSA-SI #JRNMRR140601) and Singapore Translational Research Investigator Awards (NMRC/STAR/0023/2014), respectively.

Declaration of competing interest

None of the authors have conflicts of interest to disclose.

Acknowledgements

We thank Dr. Preeti Gupta for her contribution in undertaking a comprehensive literature review on specific sections of this review.

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    Percentage of work contributed by each author in the production of the manuscript is as follows: Eva Fenwick 25%; Ryan Man 20%; Tin Aung 10%; Pradeep Ramulu 20%; Ecosse Lamoureux 25%.

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