Although clinicians mostly focus on biochemical and physiological factors, what is of interest to our patients is the extent to which these factors influence functional status, emotional well-being, and eventually their health-related quality of life (QOL). Health care professionals frequently underestimate the health-related QOL of their patients and consider their patients more impaired than the patients themselves do.1,2 Therefore, there is growing awareness for the patient-centered health care system. A better understanding of patient-reported health status and QOL can improve patient-physician interaction and, consequently, enhance treatment adherence. In addition, it can help the clinician in making the best decisions regarding the patient’s care. Moreover, regular assessment of health-related QOL can provide longitudinal information about changes in the patient’s QOL over time. It may also reveal the functional and emotional tradeoffs of a specific treatment. Research that uses QOL measures as outcome variables will help ensure that factors affecting the whole person over a range of areas will be taken into consideration in the interpretation of the study outcomes.
PATIENT-REPORTED OUTCOMES IN EYE DISEASES
Patient-reported outcome (PRO) measures are instruments that provide a means to quantify patients’ perceptions of their health.3 They measure the impact of the disease and associated treatments on patients’ QOL and their ability to function on a day-to-day basis.3 Unlike objective measures of diseases, they measure different aspects that can be influenced by an individual’s physical health, psychological status, social relationships, personal beliefs and perception of health status, and environment.3
The PRO measures developed for patients with eye diseases may measure ocular symptoms (e.g., Glaucoma Symptom Scale), different aspects of visual function (e.g., Glaucoma Quality of Life 15 [GQL-15]), and vision-related QOL (National Eye Institute Visual Function Questionnaire 25 [NEI-VFQ-25]). More than 30 vision-specific PRO measures have been used in the context of glaucoma, and the NEI-VFQ is one of the most commonly used.4,5 It meets the criteria that a vision-related QOL instrument should have. Theoretically speaking, any vision-related QOL instrument should measure the impact of vision on everyday activities, emotional well-being, social relationships, and independence.6 In addition, it addresses the three components recommended by the World Health Organization’s International Classification of Functioning Disability and Health (WHO-ICF) for measuring health-related consequences of a disease: impairment, activity limitations, and participation restriction.7 Che Hamzah et al.5 categorized the NEI-VFQ-25 items according to the components of the WHO-ICF framework into visual function (21 items), activity (14 items), and participation (14 items). As it is evident, every single item of the NEI-VFQ-25 can be fallen into different components of the WHO-ICF framework.5,8 On the basis of this discussion, the NEI-VFQ-25 is considered a vision-related QOL measure. The Visual Function-14, the Activities of Daily Vision Scale, and GQL-15 questionnaires are three other common instruments that have been used in patients with glaucoma.4,5 The GQL-15 questionnaire was developed specifically for patients with glaucoma based on aspects of visual function that are impaired by glaucoma.9,10 These three questionnaires measure vision-related activity limitations and do not completely fulfill the criteria (discussed earlier) that a vision-related QOL should have. In other words, they measure self-reported visual disability and not vision-related QOL.11
Highlighting the importance of PRO measures, the US Food and Drug Administration has also endorsed that such instruments be included in all clinical trials as end points for disease impact and outcome assessment in glaucoma.12 Therefore, it is important to develop a glaucoma-specific QOL questionnaire and standardize it for clinical trials and population-based studies so that clinicians can compare the findings of different clinical studies with regard to the impact of glaucoma and treatments on patients’ daily activities and QOL. Although the NEI-VFQ-25 is the most commonly used vision-related QOL questionnaire in patients with glaucoma,4,5 it was not developed as a glaucoma-specific QOL questionnaire. The present review summarizes the current results of the NEI-VFQ in studies that included patients with glaucoma and that used this questionnaire to measure vision-related QOL. We also explain the different scoring systems used to interpret the NEI-VFQ results, as well as the association of the results with the severity of glaucoma based on functional and structural changes. At the end of the review, we indicate some of the shortcomings of this questionnaire in evaluating patients with glaucoma and discuss potential items that could be added to this questionnaire to make it more responsive to changes in vision-related QOL in patients with glaucoma.
SEARCH STRATEGY AND QUALITY ASSESSMENT OF ARTICLES
We identified all original articles that included patients with glaucoma and used the NEI-VFQ to measure vision-related QOL. To this end, we did a systematic search of PubMed/MEDLINE, EMBASE, and the Cochrane Controlled Trials Register. The strategy for the electronic database search was as follows: “National Eye Institute Visual Function Questionnaire AND glaucoma” and “National Eye Institute Visual Function Questionnaire AND population-based study” to retrieve publications dated between January 1, 1997 (when the NEI-VFQ was developed), and December 31, 2012. The literature search identified 65 articles. On the basis of the content of the abstracts and full texts, 13 articles were found to be eligible for inclusion (Table 1). No additional relevant article was identified through a hand search of all references of the retrieved articles. These articles were rated on methodological quality using the consensus-based standards for the selection of health measurement instruments (COSMIN) by two of the authors separately (N.N. and M.S.; Table 1).13 This quality assessment instrument provides an overall methodological quality score for each publication, using a “worst score counts” algorithm.13 The four-point rating system categorizes each measurement property as “excellent” (+++), “good” (++), “fair” (+), or “poor” (−), and an overall score is determined by applying the lowest score of any item. Studies rated as “excellent” quality have items that are scored as adequate with satisfactory evidence presented. Studies rated as “good,” “fair,” or “poor” may have information missing or flaws in the study design or statistical analysis.14 Other articles that were used in this article were retrieved by the following keywords: patient-reported outcomes, health- and vision-related quality of life questionnaire, glaucoma-specific questionnaire, Glaucoma Symptom Scale questionnaire, Glaucoma Quality of life 15 questionnaire, Rasch analysis, and psychometric property AND NEI-VFQ.
The National Eye Institute Visual Function Questionnaire
The NEI-VFQ was originally developed with 51 items (13 subscales) to measure patient-reported vision-dependent function and the impact of vision problems on health-related QOL across several common eye conditions including glaucoma.15,16 Later, the same developers shortened it to a 25-item questionnaire (NEI-VFQ-25), which was shown to be internally consistent, reproducible, and responsive.17 This version has been the most commonly used vision-related QOL questionnaire in studies that included patients with glaucoma.4,5 It consists of all the subscales except for the “expectation” subscale (see Appendix). The 12 subscales (number of items) that were included are as follows18: general health (1); general vision (1); near (3), distance (3), peripheral (1), and color vision (1); vision-specific role difficulties (2), dependency (3), mental health (4), and social function (2); ocular pain (2); and driving (2). There are also some optional questions under the same subscales that bring the total number to 39 (NEI-VFQ-39), and depending on the condition under study, the user may add some optional items under more important subscales to enhance the reliability and responsiveness over time.18
In recent years, the developers of the NEI-VFQ devised shorter versions of the NEI-VFQ including the 9-item (NEI-VFQ-9) and 8-item (NEI-VFQ-8) questionnaires using similar quantitative and qualitative analyses19,20 that they used when developing the NEI-VFQ-25.19,20 These two versions cover the following subscales (number of items): near vision (3), general vision (1), distance vision (1), peripheral vision (1), role limitation (1), well-being/mental health (1), and driving (1) (only in the 9-item version). Both the NEI-VFQ-9 and NEI-VFQ-8 showed high reliability across items and validity with respect to clinical markers of eye disease in a cohort of older women with a mean age of 80 years.20 Women with severe binocular visual field loss and visual acuity worse than 20/40 in the better and worse eyes had lower composite scores compared to those with no visual field loss and those with visual acuity of 20/40 or better.20 Between-group differences in composite scores in people with a particular eye disease versus those without any chronic eye diseases indicated lower composite scores in the former group except drivers with glaucoma. The NEI-VFQ-9 takes approximately 3 to 4 minutes to complete. The sensitivity and usefulness of these shortened versions in measuring vision-related QOL in patients with glaucoma and particularly in comparison to the NEI-VFQ-25 need to be further studied.
Globally, the NEI-VFQ-25 has been translated into several languages, with slightly varying degrees of reliability and validity.21–24 This questionnaire has been used in several population-based studies as well as some of the glaucoma randomized clinical trials, namely the Early Manifest Glaucoma Study,25,26 the Primary Tube Versus Trabeculectomy Study,27 and the Collaborative Initial Glaucoma Treatment Study.28 Furthermore, because the NEI-VFQ-25 is a validated and widely used instrument, it has been used as a benchmark for comparison with other PRO measures like the GQL-15, which was designed specifically to measure visual functioning in patients with glaucoma.4
As suggested by the developers of the questionnaire, scoring the NEI-VFQ, regardless of the number of items, is a two-step process.29 First, the scoring key is used to recode original numeric values to a 0 to 100 scale so that the lowest and highest possible scores are set at 0 and 100 points, respectively. Higher scores indicate better patient-reported vision-related functioning and well-being. In the second step, the average score is calculated for the items within each subscale. The version 2000 of the NEI-VFQ-25 suggests calculating a composite score as an average of all subscale scores except general health;29 however, in some instances, investigators have averaged all 12 subscales to generate a “total score”30 or “overall score.”31
In addition to the above Likert-type summary scoring method, psychometric methods (e.g., Rasch analysis) have been used to analyze the NEI-VFQ.24 With Rasch analysis, it is possible to estimate interval-scaled latent ability traits of patients with visual impairment from ordinal ratings of items in a visual function questionnaire. In addition, it is possible to objectively test the validity and reliability of the estimated measurements.32 In this regard, Massof and Fletcher33 argued that the summary scoring method has a major shortcoming because the sums of ordinal numbers do not necessarily generate valid measurement scales. Referring to the work by Wright and Linacre,34 they state that measurement instruments need to produce an interval or a ratio scale to be qualified. Using Rasch analysis, they evaluated the items on the NEI-VFQ in a group of patients with low vision as to whether they could be used to estimate vision disability on an interval scale.33 To do so, they selected 27 items of the 52-item NEI-VFQ (the field test version) that were deemed important in low-vision patients and/or were not redundant with other items. They omitted the remaining 25 items from the questionnaire and conducted Rasch analysis on responses to these 27 items.33 Among the omitted items, 11 items were related to the following subscales: ocular pain, general vision, driving, peripheral vision, and color vision; 12 items were omitted because of being redundant with other items; and 2 items were omitted because patients required further explanation of the questions when answering. The authors found near vision, distance vision, and social functioning subscales suitable for generating a valid interval visual ability scale as a single latent variable in patients with low vision. With Rasch analysis, it is possible to estimate the latent variable of interest and to assess the performance of each item as a contributor to the measurement. The strategy within the Rasch framework is to build an adaptive testing through calibrating individual items (i.e., estimate item measures for different target populations) that are meaningful to the individual patient. This way, each patient will have a custom test, which can precisely measure his/her functional capability.33
Massof35 developed a simple scoring algorithm that approximates person measure estimates from Rasch analysis. Whereas one criticism of the standard scoring was that missing data could distort the score and make its interpretation difficult or impossible for individual patients, the Massof algorithm seems immune to missing data.35 Dougherty and Bullimore36 evaluated the standard scoring method, Rasch analysis, and the Massof algorithm in 50 patients with low vision and found them to be highly correlated. The results of their Rasch analysis were in agreement with Massof’s findings that several items misfit the Rasch model and fall outside the tolerance box. The authors concluded that both Rasch analysis and the Massof algorithm may perform well in low-vision patients, whereas the standard scoring method has the disadvantage of being subject to ceiling and floor effects.36 Misfitting items were also seen in Rasch analysis conducted in studies that used Greek31 and Chinese37 versions of the NEI-VFQ-25 and included patients with age-related macular degeneration, glaucoma, cataract, dry eye, and diabetic retinopathy.
In addition to Rasch-fit statistics, the lack of unidimensionality has further been confirmed for the NEI-VFQ-25 using principal component analysis.36 Unidimensionality is another characteristic needed to make a questionnaire valid; it means all items contributing to a single score fit within a single construct, and if violated, reporting a single overall score derived from all questions is not appropriate, and the measurement is not meaningful.38,39 Therefore, the key question is how many constructs the NEI-VFQ measures and what they represent. To answer this question, Pesudovs et al.40 used Rasch analysis on the NEI-VFQ-39 completed by patients on a cataract surgery waiting list and found two main constructs: visual functioning and socio-emotional issues. This is consistent with other studies showing that a subset of NEI-VFQ visual functioning items taps the same construct as other vision-specific instruments such as the Visual Functioning 14, the Visual Activities Questionnaire, and the Activities of Daily Vision Scale.41,42 It may also explain why there is a weak correlation between the total NEI-VFQ-25 score (as a vision-related QOL questionnaire) and the global rating of QOL obtained by generic health-related QOL questionnaires (e.g., the SF-36 Short Form Health Survey questionnaire).43–45 Because visual functioning and socio-emotional constructs are too different to be combined for generating a total score, some investigators suggest that the two constructs should be scored and reported separately.40 Despite the above works and criticisms, the standard scoring method suggested by the developers has been the predominant approach and was used in all reported studies discussed in the next sections.
The NEI-VFQ-25 in Patients with Glaucoma
Despite different study designs, patient populations, definitions of glaucoma, and using only standard scoring system, several studies have reported that patients with glaucoma have lower total and subscale scores compared to those without glaucoma (Table 1).31,46–50 In addition, items with the highest and lowest scores were similar in the glaucoma and control groups (Table 1). As it is indicated in Table 1, expectations, general health, general vision, and role difficulties were items with the lowest scores in patients with glaucoma. In a systemic review of literature by Evans et al.,51 results of three versions of NEI-VFQ instruments (51, 39, and 25 items) have shown that expectations, general health, general vision, and peripheral vision were affected the most in patients with glaucoma. They also concluded that mental aspects of the NEI-VFQ seemed to be affected more than physical aspects in patients with glaucoma compared to those with age-related macular degeneration. Interestingly, peripheral vision subscale is not among the items that were mostly affected (i.e., lowest score) in patients with glaucoma in most of the studies listed in Table 1.
Some of the factors that have been reported in one or more studies to have a negative association with the overall NEI-VFQ-25 score include difficulty in eye drop use,30 perception of health worsening in the last year,30 number of comorbidities,30 topical drug adverse effects,52 worse visual field in worse, and better eyes.53 Parrish et al.54 and Balkrishnan et al.30 could not define any relationship between the number of glaucoma medications and NEI-VFQ results. Muir et al.55 reported that patients with glaucoma with lower health literacy (≤8th grade level) did not have worse total NEI-VFQ-25 scores compared to those with a higher literacy (≥9th grade level), but they showed signs of increased dependency. Similarly, Labiris et al.56 did not find any significant correlation between education and the total score and most subscale scores except for the general health and central vision subscale scores, which had mild to moderate positive correlations. Normal variations in personality characteristics have been shown to influence how patients with glaucoma complete their NEI-VFQ-25.57 Warrian et al.57 reported that neuroticism (negative), extraversion (negative) and conscientiousness (positive) shared statistically significant associations with a variety of NEI-VFQ total and subscale score measurements. According to Parrish,58 patients’ perception of QOL might change after glaucoma has been diagnosed as an effect of the disease process and elicited anxiety; this issue needs to be further investigated.
Correlation of the NEI-VFQ-25 with Structural and Functional Changes
Only one study in our search has investigated the correlation between NEI-VFQ-25 and disease severity, as measured by the appearance of the optic nerve head in patients with glaucoma. Labiris et al.56 reported a statistically significantly negative correlation between cup-to-disc ratio and the total NEI-VFQ-25 score in both the worse (Pearson r = −0.274, p value = 0.008) and better eyes (Pearson r = −0.250, p value = 0.017) of 100 patients with glaucoma. However, the authors did not provide any information about the severity of glaucoma in their study, so generalizability of this finding is limited.
Several studies have investigated the association of NEI-VFQ-25 results with the severity of glaucoma based on functional changes measured by different visual field tests (e.g., Esterman binocular visual field test) and severity grading systems (e.g., mean deviation [MD], the Advanced Glaucoma Intervention Study score [AGIS], the Collaborative Initial Glaucoma Treatment Study [CIGTS] score, Hodapp-Anderson-Parrish score). Parrish58 reported that Esterman binocular visual field impairment was statistically significantly correlated with the following NEI-VFQ subscales: general vision (r = −0.47), near vision (r = −0.52), distance vision (r = −0.56), social functioning (r = −0.53), mental health (r = −0.47), role difficulties (r = −0.49), dependency (r = −0.59), driving (r = −0.52), color vision (r = −0.47), and peripheral vision (r = −0.51). Wren et al.28 found statistically significantly mild to moderate correlations between MD and the total score and between MD and most NEI-VFQ subscale scores in both the better and worse eyes. Suzukamo et al.47 reported statistically significantly moderate correlation between MD and distance vision, driving, peripheral vision, and dependency in both the better and worse eyes of patients with glaucoma. Mean deviation had a significantly moderate correlation with mental health, composite score, role limitation, and social function only in the better eyes. Jampel et al.46 documented significantly weak correlation between the overall NEI-VFQ-25 score and MD (in the better eye; r =0.32, p value < 0.001) and the AGIS score (in the worse eye; r =0.22, p value < 0.001). In a heterogeneous group of patients with ocular hypertension and primary open-angle glaucoma, van Gestel et al.53 investigated the relationship between visual field defects and GQL-15 results, vision-specific (NEI-VFQ-25), and generic QOL instruments (EQ-5D and the Health Utilities Index mark 3). They found a statistically significant interaction between visual field loss and the GQL-15 results and between visual field loss and the NEI-VFQ-25 scores in both the better and worse eyes. In the Los Angeles Latino Eye Study, the linear regression β coefficients for the association between visual field loss (based on MD) and NEI-VFQ-25 subscales were statistically significant for color vision (β = 0.65), driving (β = 1.50), near vision (β = 0.59), dependency (β = 1.14), mental health (β = 0.70), role function (β = 0.73), and composite (β = 0.53) in the better eye and for dependency (β = 0.71), driving (β = 0.86), and mental health (β = 0.53) in the worse eye.50 Labiris et al.31 found a significant correlation between average MD (−3.2 dB) both in the better and worse eyes of patients with glaucoma with most subscales: general vision, near vision, social functioning (the better eye), dependency (the better eye), driving (the worse eye), color vision (the better eye), and peripheral vision; the strongest correlations were for near and general vision. The same group of investigators also reported a significant correlation between the total NEI-VFQ-25 score and functional indices including MD, pattern standard deviation, the AGIS score, the CIGTS score, and Hodapp-Anderson-Parrish score in both the worse and better eyes of patients with glaucoma.56 In a group of 192 patients with different types of glaucoma, Kulkarni et al.59 reported that the total NEI-VFQ-25 score was most highly correlated with the MD of the Humphrey Visual Field in the better eye.
In validating the Japanese version of the NEI-VFQ-25, Suzukamo et al.47 assessed correlations with undefined “visual field deficits” in their group of patients with glaucoma and found strong correlations with distance vision, driving, and peripheral vision subscales. Swada et al.60 used the Japanese version to assess vision-specific QOL in 200 patients with glaucoma and to evaluate how it correlated with visual function. In addition to visual acuity, high correlations with QOL were observed with the central 10° MD in the better eye and the central 30° MD in the worse eye. The MD level at which patients began to demonstrate lower QOL was −2 to −12 dB in the better eye and −7 to −16 dB in the worse eye. They concluded that the loss of visual function in both the better and the worse eye was significantly correlated to vision-specific QOL, which began to decline at the same time as the early visual field defects became manifest.
Potential Improvements to the NEI-VFQ
Although the NEI-VFQ-25 is the most commonly used vision-related QOL questionnaire in patients with glaucoma,4,5 we suggest that some modifications of the questionnaire might improve its utility in patients with glaucoma.
Contrast Sensitivity and Adaptation to Light Changes
To have a more specific vision-related QOL measure in patients with glaucoma, it is important to know which aspects of vision affect patients’ everyday lives. The NEI-VFQ fails to address loss of contrast sensitivity.61 Using the Assessment of Disability Related to Vision (ADREV) instrument, Richman et al.61 demonstrated that binocular visual acuity and contrast sensitivity best predict the ability of patients with glaucoma to perform daily activities, indicating that the NEI-VFQ might be a more accurate reflection of function if it included questions about contrast sensitivity. The ADREV assesses nine items including reading in reduced illumination, recognizing facial expression, detecting computer motion, reading signs at a distance, finding objects, navigating an obstacle course, putting sticks into holes, dialing a telephone simulation, and matching socks. The questions were scored on a scale of 0 to 100, with 100 corresponding to the best QOL. Their study included 192 patients with glaucoma with an average MD of −10.10 dB (range, −32.7 to 2.6 dB) in the better eye and −16.6 (range, −40.0 to 1.15) in the worse eye. The mean total ADREV score was 47.38 ± 11.43. The total ADREV score was more strongly associated with binocular visual acuity (logMAR; r = −0.79, p < 0.001) and binocular contrast sensitivity (Pelli-Robson test; r =0.80, p < 0.001) than monocular and binocular visual field test results or optic disc damage.61,62 Compared to visual acuity, which usually remains good until the end stages of the glaucoma, Richman et al.61 concluded that contrast sensitivity (particularly monocular assessment) could provide highly valuable insight into understanding how well patients with glaucoma are able to function. In fact, changes in contrast sensitivity are reported to occur early in the course of glaucoma.63,64
The GQL-15 instrument has identified five factors (near vision, peripheral vision, dark adaptation and glare, personal care and household tasks, and outdoor mobility) as the main areas of difficulties encountered by patients with glaucoma.9,10 The latter four factors accounted for almost 72% of the variability in the patients’ questionnaire responses. With increasing severity of binocular visual field loss, there was an increase in the number of self-reported visual problems.9,10 The validity of this new subset of questions based on these factors was shown to be statistically significant (r = 0.037, p < 0.05) for the correlation between a measure of the severity of binocular visual field loss and the mean score of the variables used in the glaucoma-specific subgroup of questions.9,10 With this background, questions measuring patients’ contrast sensitivity, glare sensitivity, and dark adaptation are potential items that could be added to the NEI-VFQ to make it more responsive to changes in vision-related QOL in patients with glaucoma.
Questions related to driving remain an issue with the NEI-VFQ-25. Although the rate of missing data for the driving item in the field test sample was as high as 40%, the questions on driving were retained because the developers reasoned that “driving is highly valued and difficulty with driving may motivate persons to seek eye care.”15,29 The reason for missing data for driving is that subjects who do not drive or stopped driving because of reasons not related to vision do not respond to the question. High rates of missing values (as high as 60% to 90%) have also been observed with questions in the driving subscale in the translated versions of the NEI-VFQ-25.24,37,65 This could explain why results with the driving subscale have been inconsistent; in some studies, it is among the items with the highest scores,66,67 and in some others, it is among the items with the lowest scores (Table 1).17,38,68 Therefore, the current NEI-VFQ subscale about driving does not seem to be effective and could be replaced with other question(s) covering social and visual functioning aspects of driving. A more generic item about independent mobility, such as “the ability to travel independently to places farther than walking distance,” would be a good replacement.
Length of the Questionnaire
The length of the NEI-VFQ can also be a challenge, particularly in large, multipurpose, population-based studies involving a variety of other questionnaires. Longer surveys can result in a poorer response rate, which in turn can affect validity.69 In systematic reviews of randomized trials using postal surveys, higher response rates were noted when shorter questionnaires were used.70,71 As discussed earlier, the eight- and nine-item NEI-VFQ questionnaires were devised from the NEI-VFQ by the developers.19,20 The important issue is that these shortened versions should still meet the criteria for a valid vision-related QOL questionnaire (discussed earlier).
Differential Item Functioning
Differential item functioning (DIF) analysis, which is also referred to measurement bias, occurs when people from different subpopulations (e.g., sex, ethnicity, nationality, severity of t disease, comorbidities) with the same latent trait (ability/skill) have a different likelihood to give a certain response to a questionnaire or test.72 In a study by Pesudovs et al,40 536 patients from the cataract surgery waiting list who completed the NEI-VFQ were stratified by sex, age (<74 and ≥74 years), cataract status (bilateral versus awaiting cataract surgery in second eye), systemic comorbidity (present or absent), and ocular comorbidity (present or absent). On the DIF analysis, the authors evaluated the impact of the above factors on patients’ responses to the NEI-VFQ items as small or absent, minimal (but probably inconsequential), or notable. They reported that sex “minimally” affected patients’ responses to three items (i.e., picking out and matching their own clothes, driving at night, driving in difficult conditions, such as in bad weather, during rush hour, on the freeway, or in city traffic). It means that it is probable that males and females with the same latent trait respond to these items differently. In addition, they found that the presence or absence of systemic comorbidities could “minimally” influence patients’ responses to the general health subscale. Other factors such as severity of glaucoma and different translations with regard to the NEI-VFQ should be further studied by DIF analysis.
In general, patients with glaucoma have lower vision-related QOL compared to those without glaucoma. As visual field loss advances, patients’ QOL impacted even more. Expectations, general health, general vision, and role difficulties were the NEI-VFQ subscales that were most likely to be impacted by glaucoma. Peripheral vision subscale was not among the subscales that were mostly affected (i.e., lowest score) by glaucoma in patients with mild to moderate severity of the disease. The driving subscale is difficult to interpret because of the large rates of missing data to this subscale.
Because the FDA endorses the use of PRO measures in clinical trials,12 it is important to have a specific vision-related QOL questionnaire for patients with glaucoma and to standardize it for clinical trials and population-based studies so that the impact of the disease and treatments on patients’ daily activities and QOL among different studies can be compared. Unlike the GQL-15 questionnaire, which is a glaucoma-specific PRO instrument to measure vision-related activity limitations and not vision-related QOL,11 the NEI-VFQ-25 meets the criteria that a vision-related QOL questionnaire should have. In addition, it is one the most commonly used vision-related QOL questionnaires in research studies of patients with glaucoma.4,5
In this review, we suggested that further modifications and additional changes of this questionnaire might improve its utility as a PRO instrument in patients with glaucoma. Contrast sensitivity, glare sensitivity, and dark adaptation are potential items that could be added to the questionnaire to make it more responsive to changes in vision-related QOL in patients with glaucoma. This might help detect changes in the vision-related QOL of patients with glaucoma in early stages of the disease and with minor changes in disease severity. In addition, more questions with regard to peripheral vision might be considered in the questionnaire. The effect of several factors (e.g., different translations and, most importantly, severity of glaucoma) on responses to the NEI-VFQ items and those items that we suggested to be added to the questionnaire (i.e., contrast sensitivity, glare sensitivity, and dark adaptation) should be further studied by DIF analysis. The correlation between the NEI-VFQ-25 and the structural and functional changes needs to be more clarified. It is important to find out at what stages of functional and structural damages the questionnaire (particularly the visual functioning construct) starts showing changes.
In addition, different scoring methods of this questionnaire including Rasch analysis and the Massof algorithm need to be investigated in larger studies with a wider range of glaucoma disease severity. Future studies should further examine the issues of unidimensionality and person separation reliability (a measure of precision that shows an instrument could distinguish individuals with different abilities) of the modified questionnaire including suggested items to determine the constructs measured in patients with glaucoma and to eliminate poorly fitting or redundant items. The scores of two different constructs of the NEI-VFQ-25 (i.e., visual functioning and socio-economical) should be reported separately. As suggested by the developers of the NEI-VFQ, the questionnaire can be reduced to a shorter instrument. Another issue that should be further investigated is the impact of patient satisfaction from the clinical care setting on the results of the vision-related QOL measure.
Anne L. Coleman
Jules Stein Eye Institute, David Geffen School of Medicine
University of California at Los Angeles
100 Stein Plaza
Los Angeles, CA 90095
The authors did not receive any financial support from any public or private sources. The authors have no financial or proprietary interest in any product, method, or material described herein.
Received January 5, 2013; accepted May 15, 2013.
The appendix (National Eye Institute Visual Functioning Questionnaire – 25 [VFQ-25], version 2000) is available at http://links.lww.com/OPX/A132.
1. Abresch RT, Jensen MP, Carter GT. Health quality of life in peripheral neuropathy. Phys Med Rehabil Clin Am 2001; 12: 461–72.
2. Abresch RT, Carter GT, Jensen MP, Kilmer DD. Assessment of pain and health-related quality of life in slowly progressive neuromuscular disease. Am J Hosp Palliat Care 2002; 19: 39–48.
3. Meadows KA. Patient-reported outcome measures: an overview. Br J Community Nurs 2011; 16: 146–51.
4. Spaeth G, Walt J, Keener J. Evaluation of quality of life for patients with glaucoma. Am J Ophthalmol 2006; 141 (Suppl. 1): S3–14.
5. Che Hamzah J, Burr JM, Ramsay CR, Azuara-Blanco A, Prior M. Choosing appropriate patient-reported outcomes instrument for glaucoma research: a systematic review of vision instruments. Qual Life Res 2011; 20: 1141–58.
6. Elliott DB, Pesudovs K, Mallinson T. Vision-related quality of life. Optom Vis Sci 2007; 84: 656–8.
7. McDougall J, Wright V, Rosenbaum P. The ICF model of functioning and disability: incorporating quality of life and human development. Dev Neurorehabil 2010; 13: 204–11.
8. Cieza A, Geyh S, Chatterji S, Kostanjsek N, Ustun B, Stucki G. ICF linking rules: an update based on lessons learned. J Rehabil Med 2005; 37: 212–8.
9. Nelson P, Aspinall P, O’Brien C. Patients’ perception of visual impairment in glaucoma: a pilot study. Br J Ophthalmol 1999; 83: 546–52.
10. Nelson P, Aspinall P, Papasouliotis O, Worton B, O’Brien C. Quality of life in glaucoma and its relationship with visual function. J Glaucoma 2003; 12: 139–50.
11. Khadka J, Pesudovs K, McAlinden C, Vogel M, Kernt M, Hirneiss C. Reengineering the Glaucoma Quality of Life-15 Questionnaire with Rasch analysis. Invest Ophthalmol Vis Sci 2011; 52: 6971–7.
12. Varma R, Richman EA, Ferris FL, Bressler NM. Use of patient-reported outcomes in medical product development: a report from the 2009 NEI/FDA Clinical Trial Endpoints Symposium. Invest Ophthalmol Vis Sci 2010; 51: 6095–103.
13. Mokkink LB, Terwee CB, Patrick DL, Alonso J, Stratford PW, Knol DL, et al. The COSMIN checklist for assessing the methodological quality of studies on measurement properties of health status measurement instruments: an international Delphi study. Quality of Life Research 2010; 19: 539–49.
14. Terwee CB, Bot SD, de Boer MR, van der Windt DA, Knol DL, Dekker J, Bouter LM, de Ve HC. Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol 2007; 60: 34–42.
15. Mangione CM, Berry S, Spritzer K, Janz NK, Klein R, Owsley C, Lee PP. Identifying the content area for the 51-item National Eye Institute Visual Function Questionnaire: results from focus groups with visually impaired persons. Arch Ophthalmol 1998; 116: 227–33.
16. Mangione CM, Lee PP, Pitts J, Gutierrez P, Berry S, Hays RD, and the NEI-VFQ Field Test Investigators. Psychometric properties of the National Eye Institute Visual Function Questionnaire (NEI-VFQ). Arch Ophthalmol 1998; 116: 1496–504.
17. Mangione CM, Lee PP, Gutierrez PR, Spritzer K, Berry S, Hays RD. National Eye Institute Visual Function Questionnaire Field Test Investigators. Development of the 25-item National Eye Institute Visual Function Questionnaire. Arch Ophthalmol 2001; 119: 1050–8.
19. Coleman AL, Yu F, Ensrud KE, Stone KL, Cauley JA, Pedula KL, Hochberg MC, Mangione CM. Impact of age-related macular degeneration on vision-specific quality of life: follow-up from the 10-year and 15-year visits of the Study of Osteoporotic Fractures. Am J Ophthalmol 2010; 150: 683–91.
20. Kodjebacheva G, Coleman AL, Ensrud KE, Cauley JA, Yu F, Stone KL, Pedula KL, Hochberg MC, Mangione CM. Reliability and validity of abbreviated surveys derived from the National Eye Institute Visual Function Questionnaire: the study of osteoporotic fractures. Am J Ophthalmol 2010; 149: 330–40.
21. Rossi GC, Milano G, Tinelli C. The Italian version of the 25-item National Eye Institute Visual Function Questionnaire: translation, validity, and reliability. J Glaucoma 2003; 12: 213–20.
22. Baker RS, Bazargan M, Calderón JL, Hays RD. Psychometric performance of the National Eye Institute Visual Function Questionnaire in Latinos and non-Latinos. Ophthalmology 2006; 113: 1363–71.
23. Toker E, Onal S, Eraslan M, Eyriparmak M. The Turkish version of the National Eye Institute Refractive Error Quality of Life Instrument: translation, validity and reliability. Qual Life Res 2008; 17: 1269–76.
24. Chan CW, Wong D, Lam CL, McGhee S, Lai WW. Development of a Chinese version of the National Eye Institute Visual Function Questionnaire (CHI-VFQ-25) as a tool to study patients with eye diseases in Hong Kong. Br J Ophthalmol 2009; 93: 1431–6.
25. Hyman LG, Komaroff E, Heijl A, Bengtsson B, Leske MC. Early Manifest Glaucoma Trial Group. Treatment and vision-related quality of life in the early manifest glaucoma trial. Ophthalmology 2005; 112: 1505–13.
26. Leske MC, Heijl A, Hyman L, Bengtsson B. Early Manifest Glaucoma Trial: design and baseline data. Ophthalmology 1999; 106: 2144–53.
27. Gedde SJ, Schiffman JC, Feuer WJ, Parrish RK 2nd, Heuer DK, Brandt JD; Tube Versus Trabeculectomy Study Group. The tube versus trabeculectomy study: design and baseline characteristics of study patients. Am J Ophthalmol 2005; 140: 275–87.
28. Wren PA, Musch DC, Janz NK, Niziol LM, Guire KE, Gillespie BW; CIGTS Study Group. Contrasting the use of 2 vision-specific quality of life questionnaires in subjects with open-angle glaucoma. J Glaucoma 2009; 18: 403–11.
30. Balkrishnan R, Bond JB, Byerly WG, Camacho FT, Anderson RT. Medication-related predictors of health-related quality of life in glaucoma patients enrolled in a medicare health maintenance organization. Am J Geriatr Pharmacother 2003; 1: 75–81.
31. Labiris G, Katsanos A, Fanariotis M, Tsirouki T, Pefkianaki M, Chatzoulis D, Tsironi E. Psychometric properties of the Greek version of the NEI-VFQ 25. BMC Ophthalmol 2008; 8: 4.
32. Massof R. The measurement of vision disability. Optom Vis Sci 2002; 79: 516–52.
33. Massof RW, Fletcher DC. Evaluation of the NEI Visual Functioning Questionnaire as an interval measure of visual ability in low vision. Vision Res 2001; 41: 397–413.
34. Wright BD, Linacre JM. Observations are always ordinal; measurements, however, must be interval. Arch Phys Med Rehabil 1989; 70: 857–60.
35. Massof RW. An interval-scaled scoring algorithm for visual function questionnaires. Optom Vis Sci 2007; 84: 689–704.
36. Dougherty BE, Bullimore MA. Comparison of scoring approaches for the NEI VFQ-25 in low vision. Optom Vis Sci 2010; 87: 543–8.
37. Wang CW, Chan CL, Jin HY. Psychometric properties of the Chinese version of the 25-item National Eye Institute Visual Function Questionnaire. Optom Vis Sci 2008; 85: 1091–9.
38. Mallinson T. Why measurement matters for measuring patient vision outcomes. Optom Vis Sci 2007; 84: E675–82.
39. Pesudovs K, Burr JM, Harley C, Elliott DB. The development, assessment, and selection of questionnaires. Optom Vis Sci 2007; 84: 663–74.
40. Pesudovs K, Gothwal VK, Wright T, Lamoureux EL. Remediating serious flaws in the National Eye Institute Visual Function Questionnaire. J Cataract Refract Surg 2010; 36: 718–32.
41. Massof RW. Application of stochastic measurement models to visual function rating scale questionnaires. Ophthalmic Epidemiol 2005; 12: 103–24.
42. Massof RW, Ahmadian L. What do different visual function questionnaires measure? Ophthalmic Epidemiol 2007; 14: 198–204.
43. La Grow SJ. Predicting perceived quality of life scores from the National Eye Institute 25-Item Visual Function Questionnaire. Optom Vis Sci 2007; 84: 785–8.
44. Swamy BN, Chia E-M, Wang JJ, Rochtchina E, Mitchell P. Correlation between vision- and health-related quality of life scores. Acta Ophthalmol (Oxf) 2009; 87: 335–9.
45. Revicki D, Rentz A, Harnam N, Thomas V, Lanzetta P. Reliability and validity of the National Eye Institute Visual Function Questionnaire-25 in patients with age-related macular degeneration. Invest Ophthalmol Vis Sci 2010; 51: 712–7.
46. Jampel HD, Schwartz A, Pollack I, Abrams D, Weiss H, Miller R. Glaucoma patients’ assessment of their visual function and quality of life. J Glaucoma 2002; 11: 154–63.
47. Suzukamo Y, Oshika T, Yuzawa M, Tokuda Y, Tomidokoro A, Oki K, Mangione CM, Green J, Fukuhara S. Psychometric properties of the 25-item National Eye Institute Visual Function Questionnaire (NEI VFQ-25), Japanese version. Health Qual Life Outcomes 2005; 3: 65.
48. Broman AT, Munoz B, Rodriguez J, Sanchez R, Quigley HA, Klein R, Snyder R, West SK. The impact of visual impairment and eye disease on vision-related quality of life in a Mexican-American population: Proyecto VER. Invest Ophthalmol Vis Sci 2002; 43: 3393–8.
49. Wu SY, Hennis A, Nemesure B, Leske MC; Barbados Eye Studies Group. Impact of glaucoma, lens opacities, and cataract surgery on visual functioning and related quality of life: the Barbados Eye Studies. Invest Ophthalmol Vis Sci 2008; 49: 1333–8.
50. McKean-Cowdin R, Wang Y, Wu J, Azen SP, Varma R; Los Angeles Latino Eye Study Group. Impact of visual field loss on health-related quality of life in glaucoma: the Los Angeles Latino Eye Study. Ophthalmology 2008; 115: 941–8.e1.
51. Evans K, Law SK, Walt J, Buchholz P, Hansen J. The quality of life impact of peripheral versus central vision loss with a focus on glaucoma versus age-related macular degeneration. Clin Ophthalmol 2009; 3: 433–45.
52. Nordmann JP, Auzanneau N, Ricard S, Berdeaux G. Vision related quality of life and topical glaucoma treatment side effects. Health Qual Life Outcomes 2003; 1: 75.
53. van Gestel A, Webers CA, Beckers HJ, van Dongen MC, Severens JL, Hendrikse F, Schouten JS. The relationship between visual field loss in glaucoma and health-related quality-of-life. Eye (Lond) 2010; 24: 1759–69.
54. Parrish RK, Gedde SJ, Scott IU, Feuer WJ, Schiffman JC, Mangione CM, Montenegro-Piniella A. Visual function and quality of life among patients with glaucoma. Arch Ophthalmol 1997; 115: 1447–55.
55. Muir KW, Santiago-Turla C, Stinnett SS, Herndon LW, Allingham RR, Challa P, Lee PP. Health literacy and vision-related quality of life. Br J Ophthalmol 2008; 92: 779–82.
56. Labiris G, Katsanos AA, Fanariotis M, Zacharaki F, Chatzoulis D, Kozobolis VP. Vision-specific quality of life in Greek glaucoma patients. J Glaucoma 2010; 19: 39–43.
57. Warrian KJ, Spaeth GL, Lankaranian D, Lopes JF, Steinmann WC. The effect of personality on measures of quality of life related to vision in glaucoma patients. Br J Ophthalmol 2009; 93: 310–5.
58. Parrish RK 2nd. Visual impairment, visual functioning, and quality of life assessments in patients with glaucoma. Trans Am Ophthalmol Soc 1996; 94: 919–1028.
59. Kulkarni KM, Mayer JR, Lorenzana LL, Myers JS, Spaeth GL. Visual field staging systems in glaucoma and the activities of daily living. Am J Ophthalmol 2012; 154: 445–51.e3.
60. Sawada H, Fukuchi T, Abe H. Evaluation of the relationship between quality of vision and visual function in Japanese glaucoma patients. Clin Ophthalmol 2011; 5: 259–67.
61. Richman J, Lorenzana LL, Lankaranian D, Dugar J, Mayer J, Wizov SS, Spaeth GL. Importance of visual acuity and contrast sensitivity in patients with glaucoma. Arch Ophthalmol 2010; 128: 1576–82.
62. Altangerel U, Spaeth GL, Steinmann WC. Assessment of function related to vision (AFREV). Ophthalmic Epidemiol 2006; 13: 67–80.
63. Korth MJ, Jünemann AM, Horn FK, Bergua A, Cursiefen C, Velten I, Budde WM, Wisse M, Martus P. Synopsis of various electrophysiological tests in early glaucoma diagnosis: temporal and spatiotemporal contrast sensitivity, light- and color-contrast pattern-reversal electroretinogram, blue-yellow VEP. Klin Monbl Augenheilkd 2000; 216: 360–8.
64. Velten IM, Korth M, Horn FK, Budde WM. Temporal contrast sensitivity with peripheral and central stimulation in glaucoma diagnosis. Br J Ophthalmol 1999; 83: 199–205.
65. Lin JC, Chie WC. Psychometric validation of the Taiwan Chinese version of the 25-Item National Eye Institute Visual Functioning Questionnaire. J Eval Clin Pract 2010; 16: 619–26.
66. Lin JC, Yang MC. Correlation of visual function with health-related quality of life in glaucoma patients. J Eval Clin Pract 2010; 16: 134–40.
67. Wu P, Xi S, Xia H, Lu H, Guo W. Survey on vision-related quality of life and self-management among patients with glaucoma. J Glaucoma 2012 [Epub ahead of print].
68. Ramulu PY, West SK, Munoz B, Jampel HD, Friedman DS. Driving cessation and driving limitation in glaucoma: the Salisbury Eye Evaluation Project. Ophthalmology 2009; 116: 1846–53.
69. Smeeth L, Fletcher AE. Improving the response rates to questionnaires. Several common sense strategies are effective. BMJ 2002; 324: 1168–9.
70. Edwards P, Roberts I, Clarke M, DiGuiseppi C, Pratap S, Wentz R, Kwan I. Increasing response rates to postal questionnaires: systematic review. BMJ 2002; 324: 1183.
71. Nakash RA, Hutton JL, Jorstad-Stein EC, Gates S, Lamb SE. Maximizing response to postal questionnaires. A systematic review of randomized trials in health research. BMC Med Res Methodol 2006; 6: 5.
72. Teresi JA. Different approaches to differential item functioning in health applications. Advantages, disadvantages and some neglected topics. Med Care 2006; 44 (11 Suppl. 3): S152–70.