Sharon Yeo1, Han Tun Aung2 and Louis Tong1,3,4,5*
1Singapore Eye Research Institute, Singapore
2School of Health Sciences, Ngee Ann Polytechnic, Singapore
3National Eye Centre, Singapore
4Duke-NUS Graduate Medical School, Singapore
5Yong Loo Lin School of Medicine, National University of Singapore
Received: 19 May, 2014; Accepted: 27 June, 2014; Published: 30 June, 2014
Louis Tong, Singapore National Eye Center, 11 Third Hospital Avenue, Singapore 168751, Tel: +65-62277255; Fax: +65-63224599; Email: Louis.email@example.com
Yeo S, Aung HT, Tong L (2014) The Association of Dry Eye Symptoms with Socioeconomic Factors and quality of Life. J Clin Res Ophthalmol 1(1): 006-013. DOI: 10.17352/2455-1414.000002
© 2014 Yeo S, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Dry eye; Quality of life; Dry eye symptoms
Purpose: Dry eye is a common condition with significant morbidity and socioeconomic burden. The associated demographic factors that worsen utility in dry eye patients were not known. There were many questionnaire instruments advocated for dry eye documentation but none of these have been shown to correlate to quality of life (QoL). We aimed at examining the health related utility values in a group of dry eye patients and their associations.
Methods: This was a hospital based prospective cross-sectional study conducted at the dry eye clinic of Singapore National Eye Centre. Patients with dry eye symptoms were randomized to one of the two validated symptom questionnaires, Standard Patient Evaluation of Eye Dryness (SPEED) or Symptom Assessment in Dry Eye (SANDE) questionnaires. All patients underwent an evaluation of socio economic factors and utility was assessed using Time-Trade-Off methodby 4 trained interviewers.
Results: We recruited 178 participants with dry eye symptoms (mean age was 56.4 (SD: 14.1) years, 77% female), 85 were assessed with SPEED and 93 with SANDE. The utility values encountered were skewed with only 52% of patients having a reduced utility (median=1.0) with a mean of 0.984 (SD: 0.11). The mean SPEED was 11.7 (5.6), and the mean SANDE was 56.8 (22.6). A higher symptom score was associated with a utility less than 1 with odds ratio 2.75 (95%CI 1.50-5.04). The correlation between SANDE and utility was r=-0.295 (-0.47 to -0.097) and corresponding correlation for SPEED and utility was not significant. To detect a utility less than 1, SPEED had an area under the curve (AUC) of 0.63 (95%CI 0.51-0.75) and the SANDE, 0.67 (0.56-0.77).
Conclusions: The health related QoL was relatively good in people with dry eye symptoms in this study. Increased symptoms were associated with decreasing QoL but the association was in general weak. This implied that causes of reduced QoL apart from symptoms, such as costs, treatment inconvenience or adverse effects should be explored.
Dry eye is a multifactorial condition that affects 5-35% of the population . Common symptoms of dry eyes include irritation of the eye, heaviness of the eyelids, blurring of vision, tearing and light sensitivity . These symptoms can cause a significant reduction in patient health related quality of life (QoL). Clinical studies have shown poor correlation between clinical test symptoms and self-perceived severity of the disease . Studies also have shown that utilities value of more severe dry eye is similar to condition such as class III/IV angina affecting the QoL . Correlation between reduction in QoL and presenting symptoms is unknown compared to other factors such as cost and inconvenience of treatment. This affects physician's decision on the management of the condition. In addition, there is a significant socio-economic burden to treating dry eyes. In 2009, 54,051 patients sought treatment for dry eye in the Singapore National Eye Centre (SNEC) and total costs for dry eye medications amounted to US$1,520,797.80 that year from one pharmacy alone .
Although there are different questionnaires used in the assessment of dry eye, to date, there has been no study which evaluates the correlation between the severity and frequency of the symptoms on the questionnaires and QoL. This is particularly important since symptoms of dry eyes are episodic and questionnaires administered at one time point may or may not reflect the true disease morbidity. Two of such questionnaires are the Standard Patient Evaluation of Eye Dryness (SPEED) questionnaire which consists of 2 questions graded on a scale of 0-3 on frequency and grade 0-4 on severity and Symptom Assessment in Dry Eye (SANDE) questionnaire which consists of 3 questions based on symptoms of frequency and severity. Both of these questionnaires have been published, validated and utilized in the eye clinic by the investigators [6,7].
Dry eye is a common and growing public health problem with significant morbidity and decrease in health related QoL. Uncertainty in correlation between decreased QoL with presenting symptoms and factors, or the possibility of QoL being associated with factors such as cost and inconvenience of treatment, will affect prioritization in the management of the disease. For instance, if presenting symptoms correlate poorly with the perceived QoL, more emphasis should be placed on making treatment more accessible, convenient and at lower cost. If there is a high correlation, the focus should be making current treatments more efficacious to relieve presenting symptoms, and consequently to improve QoL. The findings of this study will also help us better understand the efficacy of the questionnaires and select appropriate one foruse in future clinical trials.
Utility assessment is a formal method to quantify and understand the impact of a condition. Dry eye has been found to lower the utility value and the mean utilities for mild/moderate and severedry eye were found to be 0.72 and 0.61 respectively in Buchholz et al.'s study. Moreover, the utilities of severe dry eye patients were similar to those who required dialysis or had severe angina . There were many questionnaire instruments advocated for dry eye documentation but none of these have been evaluated for association with QoL.
This study aimed to ascertain:
- The utility values of dry eye patients in SNEC and demographic, socioeconomic factors that may affect the utility,
- The association, if any between symptoms of dry eye and the utility, and if this is affected by demographic and socioeconomic factors, and
- The sensitivity and specificity of the dry eye symptoms in detecting a reduced utility.
This was a hospital-based prospective cross-sectional study conducted at the dry eye clinic of Singapore National Eye Centre. A total of 178 subjects with dry eye symptoms participated in this study. They were randomized to one of the two validated symptom questionnaires, SPEED or SANDE. Subjects were asked about their general health and the severity and frequency of dry eye symptoms assessed with either the SANDE or the SPEED randomly. Socio-economic status was evaluated using the parameters gross monthly income, highest educational level and type of residential home. Utilities were measured with the time-trade-off method as described below. The interviewers were trained in asking the 2 questionnaires in a standardized way.
Approval was obtained from the institutional review board, and written informed consent was obtained from all subjects. The study complied with the Tenets of the Declaration of Helsinki for human research.
The subjects recruited were 21 years old and above, with symptomatic dry eyes. These inclusion criteria applied to patients referred to the dry eye clinic of Singapore National Eye Center, having been diagnosed as ‘dry eye' by another ophthalmologist. Patients with any eye conditions thatwere not dry eye-related such as ocular allergy, infection, irritation, age-related macular degeneration, or intraocular inflammation were excluded from the study. Patients with corrected visual acuity of worse than 6/12 in the better eye were also excluded. Patients with Sjogren syndrome were diagnosed by a rheumatologist. When undiagnosed patients present with dry mouth and dry eye, our protocol was to perform the assays for anti-SSA and anti-SSB antibodies. If these showed a positive result, a referral would be made to the rheumatology department for further evaluation and diagnosis of the systemic condition. Since such patients continued to visit the eye clinic, we were able to classify them as Sjogren syndrome.
51% of patients who participated in this study hadchronic illness such as rheumatoid arthritis, diabetes mellitus, sjogren syndrome or thyroid disease.
The SANDE questionnairerequired subjects to mark an ‘X' on a 100 mm horizontal Visual Analogue scale (VAS) based on the frequency and severity of discomfort, blurring of vision and sensitivity to light. The extreme left of thescale representingcomplete absence of symptom, while the extreme right represents severe and constant dry eye symptom. The magnitudes were measured with a ruler and recorded in millimeters. Then, the global SANDE score was obtained by square rooting the multiplication of the frequency and severity of the dry eye symptoms. As the SANDE was applied to the symptoms of discomfort, blurring and photophobia, the worst global score of the symptoms was used in the subsequent analysis .
For the SPEED questionnaire, subjects were asked to rate the frequency and severity of dryness, soreness, burning and eye fatigue on a frequency scale of 0 to 3, where 0 being “never” and 3 being “constant”. Severity of the symptoms are graded on a scale of 0 to 4, where 0 being “not severe” and 4 being “very severe”. The SPEED score was obtained by the summation of the frequency and severity scores with a maximum score of 32. To compare scores with the SANDE, the SPEED scoreswere then normalized to transformed SPEED scores that were comparable with SANDE score. The formula is provided in supplementary file 1.
The utility question was a hypothetical question where subjects were given a “dry eye-free” life scenario and how much of their life expectancy they were willing to trade-off. Theutility values were calculated based on the formula: Utility value=(remaining years of life expected - time trade-off (TTO))/ (remaining years of life), with TTO in years.The remaining years of life expected was computed as the mean life expectancy for men/women subtracting the current age. The closer the utility value was to 1.0, the better the quality of life associated with dry eye symptoms.
SPSS Statistics Version 21 was used to analyze the data. Spearman rho was used in the calculation ofthe confidence intervals for correlation coefficient and the confidence intervalvalues were generated with the online calculator: http://how2stats.blogspot.sg/2011/09/confidence-intervals-for-correlations.html. Binomial confidence intervals were used in the calculation of proportions of subjects with utility value of less than one with the link,http://statpages.org/confint.html.
Overall178 participants were recruited (Table 1), with 85 answering the SPEED questionnaire and 93 the SANDE questionnaire. There was no difference in the gender composition, age, ethnicity, income, and highest level of education attained between participants who were randomized to each questionnaire. The mean presenting corrected visual acuity of the participants was 6/7.5, whereas the mean age was 56.4 (SD: 14.1) years with 77% female.
In this study, 8 subjects had diabetes mellitus, 10 had Sjogren syndrome, 20 had rheumatoid arthritis and 14 had thyroid disease.
A considerable proportion of utility values were close to 1, table 2 shows the proportion of participants who had a utility value of less than 1. The proportions of utility values that were less than 1 were not significantly different between those with different genders, ethnicity, income, education level and housing type (p>0.05). There were a significantly higher proportion of subjects with ages lesser or equal to 50 years oldhaving a utility of less than 1 (p=0.049).
Supplementary Table 1 shows the mean and SD of the utilities. The mean utility of the participants was skewed with only 52% of patients having a reduced utility from 1. The median utility was 1 and mean was 0.984 (SD: 0.11). The frequency distribution of the utility (histogram) is shown in figure 1. There were no significant difference in the utility between the participants who answered the SANDE and SPEED (p>0.05). We found that 92 out of 178(51.7%) of the participants had a utility value of less than 1.
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