The relationship between disease activity and quality of life in systemic lupus erythematosus

S. Khanna1, H. Pal2, R. M. Pandey3 and R. Handa1

1 Department of Medicine, 2 Department of Psychiatry and 3 Department of Biostatistics, All India Institute of Medical Sciences, New Delhi, India.

Correspondence to: R. Handa. E-mail: rohinihanda{at}hotmail.com


    Abstract
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 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 Supplementary data
 References
 
Objective. To determine the quality of life (QOL) in SLE patients and correlate it with disease activity.

Methods. Lupus patients fulfilling the ACR 1997 criteria for SLE were included in this cross-sectional study. Patients were administered the World Health Organization Quality of Life—Bref (WHOQOL-Bref) to assess their quality of life. Disease activity was measured using Mexican Systemic Lupus Erythematosus Disease Activity Index (Mex-SLEDAI).

Results. The study group comprised 73 lupus patients (70 females and three males) with mean age 35.22 ± 11.15 yr and mean disease duration 5.62 ± 5.14 yr. Mean Mex-SLEDAI score was 3.31 ± 3.19. Higher disease activity scores were associated with lower QOL scores in the physical (P = 0.001) and psychological domains (P = 0.01) but showed no significant correlation with the domains of social and environmental QOL. Patients with clearly active and probably active disease showed significantly lower scores in the physical (P = 0.01) and psychological (P = 0.02) domains than patients with inactive disease. However, no significant difference was found in the domains of social and environmental QOL. Age or disease duration did not affect the QOL in any of the domains.

Conclusions. Physical and psychological QOL are impaired to a larger extent in active lupus. However, social and environmental QOL do not correlate with the disease activity status in lupus patients.

KEY WORDS: SLE, Disease activity, Quality of life, Mex-SLEDAI, WHOQOL


    Introduction
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 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 Supplementary data
 References
 
Systemic lupus erythematosus is a chronic autoimmune disorder, characterized by periods of active disease and remission. The survival of SLE patients has significantly improved over the past years [1, 2]. There is now a growing realization that physical attributes of health do not fully measure disease status in chronic conditions like SLE. Psychosocial factors such as pain, apprehension, difficulty in fulfilling personal and family responsibilities, financial burden and diminished cognition are equally important and must also be encompassed [3]. Assessing the quality of life (QOL) is thus an important measure to appraise how much the disease process and its treatment is affecting an individual.

WHO has defined QOL as ‘individuals' perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns’ [4]. It is a broad-ranging concept affected in a complex way by the person's physical health, psychological state, personal beliefs and social relationships and their relationship to salient features of their environment. Measures of QOL consider the effects of the disease or its treatment from the patient's perspective and determine the need for social, emotional and physical support during illness.

There is paucity of literature on QOL issues in lupus patients from Asia [5, 6]. Also, existing studies on the relationship of disease activity with QOL are equivocal. While some studies on QOL in SLE have shown that disease activity correlates with QOL [7, 8], others have shown that QOL in SLE patients does not correlate with the disease status [5, 9–12].

We therefore planned a cross-sectional study to assess the QOL in patients with SLE and correlate the QOL with the disease activity in these subjects.


    Materials and methods
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 Supplementary data
 References
 
Patient selection
SLE patients fulfilling the American College of Rheumatology 1997 revised criteria for lupus [13, 14] were included in this cross-sectional study. Patients with overlap syndromes were excluded. Patients were informed of the objectives of the study and verbal consent obtained. Out of the 75 patients approached, two refused consent. In consonance with the practice at our institution, ethics committee approval was not obtained.

Data collection
The demographic and clinical data of the patients were recorded; disease activity was measured using the Mexican Systemic Lupus Erythematosus Disease Activity Index (Mex-SLEDAI). Patients were administered the World Health Organization Quality of Life—Bref (WHOQOL-Bref) to measure the QOL. A patient education booklet, ‘Handout on Health—Systemic Lupus Erythematosus’ was prepared in English and Hindi and distributed amongst patients included in the study.

Measuring instruments
Mex-SLEDAI
The Mex-SLEDAI was used to measure the disease activity. Mex-SLEDAI, a modified version of SLEDAI, was developed by Guzman et al. in 1992 primarily for use in developing countries, where the facilities for estimation of dsDNA antibodies and C3 complement levels may not be easily or always available [15]. The Mex-SLEDAI has been validated against the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) and the Lupus Activity Criteria Count (LACC) and shown to be as reliable as the SLEDAI (rs = 0.894 vs 0.867). Its correlation with the expert's visual analogue scale (VAS) was similar to SLEDAI (rs = 0.678 for SLEDAI and 0.677 for Mex-SLEDAI). Mex-SLEDAI has a sensitivity of 85.7% and a specificity of 100%. It was shown to be 30% cheaper than SLEDAI and 15% cheaper to administer than LACC [15] and is appropriate for use in a developing country like India.

Mex-SLEDAI rates a descriptor as present if it has occurred in the past 10 days. Disease activity is defined for 10 main clinical variables instead of the original 24 variables which require laboratory confirmation, viz. neurological disorder, renal disorder, vasculitis, haemolysis, thrombocytopenia, myositis, arthritis, mucocutaneous disorder, serositis, fever, fatigue, leucopenia and lymphopenia. It is an ordinal scale which gives a composite score ranging from 0 to 32. A higher score implies greater disease activity [15]. Patients scoring less than 2 are said to have clearly inactive disease, those scoring between 2 and 5 are categorized as probably active, while those scoring more than 5 are said to be clearly active [16, 17].

WHOQOL-Bref
WHOQOL-Bref is a 26-item abbreviated version of the WHOQOL-100 [4, 18]. WHOQOL-Bref has been shown to correlate at 0.9 with the WHOQOL-100 with good discriminant validity, content validity and test–retest reliability [18, 19].

WHOQOL-Bref (Appendix 1, available as supplementary data at Rheumatology Online) is based on a four-domain structure: physical (seven items), psychological (six items), social (three items) and environmental (eight items). A time frame of 15 days is indicated in the assessment. It uses a Likert-type five-point scale to grade the patient's response to the QOL items. Twenty-four of the 26 questions are used to compute the QOL scores. The scale gives continuous scores ranging from 4 to 20 for each domain. A higher score signifies better QOL. Keeping in view that QOL is best measured by the patient himself/herself and not his or her physician or nurse [20], the questionnaire was administered to the patients. The patients were given a choice amongst the English and the validated Hindi versions of the questionnaire. Domain scores were calculated according to the WHO guidelines [21].

Data analysis
Statistical analysis was carried out using SPSS® 10.0. This comprises descriptive analysis of the domain scores of WHOQOL, Pearson correlation coefficients to compare the Mex-SLEDAI and the WHOQOL scores, comparison of means using t tests, one-way analysis of variance (ANOVA) and Mann–Whitney U tests to compare the QOL scores amongst the various groups of disease activity. A P value <0.05 was regarded as statistically significant, except for correlation coefficients, where a P value of <0.01 was used to correct the effect of multiple comparisons.


    Results
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 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 Supplementary data
 References
 
The 73 patients included in the study comprised 70 females and three males (mean age 35.22 ± 11.15 yr; range 16–68 yr). The mean disease duration was 5.62 ± 5.14 yr (range 1 month to 21 yr; median 4 yr). The mean Mex-SLEDAI score was 3.31 ± 3.19 (range 0–12.5). Of this cohort, 22 patients had inactive disease, while 36 had probably active disease and 15 patients had clearly active disease. The clinical characteristics of the patients are shown in Table 1.


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TABLE 1. Clinical and laboratory characteristics of the patients (n = 73)

 
The WHOQOL-Bref showed mean scores of 12.98 ± 3.01 in the domain of physical QOL and 12.94 ± 3.11 in the psychological domain. The QOL scores were the highest in the domain for the social QOL, with a mean of 15.39 ± 3.53, followed by the environmental domain, which showed a mean of 14.11 ± 2.48 (Table 2). Pearson correlation coefficients were used to correlate the Mex-SLEDAI scores with the four domains of the WHOQOL. Disease activity scores showed a significant negative correlation with the domains of physical (r = –0.41, P = 0.00) and psychological (r = –0.30, P = 0.01) QOL. However, the domains of social (r = –0.09, P = 0.46) and environmental (r = –0.14, P = 0.23) QOL did not show any significant correlation with the disease activity scores (Table 3).


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TABLE 2. Mex-SLEDAI and WHOQOL scores

 

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TABLE 3. Pearson correlation (r) between disease activity and QOL scores

 
The mean QOL scores amongst the three groups of disease activity were computed using one-way ANOVA and a post hoc Tukey's test. The QOL scores were significantly higher in patients with inactive (n = 22) disease than in patients with probably active (n = 36) and clearly active (n = 15) disease in the domains of physical (P = 0.01) and psychological (P = 0.02) QOL. However, no significant difference in the mean scores was found amongst the three groups in the domains of social and environmental QOL (Table 4, Fig. 1).


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TABLE 4. Mean difference in QOL scores amongst different groups of disease activity

 


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FIG. 1. Distribution of the mean QOL scores amongst the three groups of disease activity.

 
Of the 73 patients in our cohort, 25 had arthritis at the time of assessment. These patients exhibited significantly lower QOL scores in all the four domains of the WHOQOL-Bref than patients who did not have arthritis. Forty-three out of the 73 lupus patients with complaints of fatigue had lower scores in all the four domains of the WHOQOL-Bref than patients who did not complain of fatigue. Mucocutaneous disorder, seen in 36 out of the 73 patients, was associated with significantly lower psychological QOL scores, while other domains were unaffected. A non-parametric Mann–Whitney U test was done to see the distribution of scores amongst the disease descriptors of fever and renal disorder. Fever greater than 38°C (after excluding infection) was present in 12 patients. These patients showed lower scores in the domain of physical health, while other domains showed no significant difference. The presence of active renal disorder (n = 14) did not lead to a difference in the QOL scores in any of the domains (Table 5). Since only one patient each in the study group had vasculitis and serositis while none of the patients exhibited any neurological disorder, myositis, haemolysis, thrombocytopenia, leucopenia or lymphopenia at the time of assessment, these variables were not studied.


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TABLE 5. Mean QOL scores amongst descriptors of disease activity

 
Forty-seven of the 73 patients opted for the Hindi version of the WHOQOL-Bref and 26 for the English version of the questionnaire. Of the 47 patients who preferred the Hindi version, 28 (60%) had received education beyond high school. In case of the English version, 25 of the 26 (96%) patients had received education beyond high school. The mean QOL scores in those who had used the Hindi version of WHOQOL-Bref were compared with the scores of those who had used the English version (physical domain, 12.62 ± 2.87 vs 13.69 ± 3.19, P = 0.16; psychological domain, 12.64 ± 2.98 vs 13.49 ± 3.33, P = 0.27; social domain, 15.03 ± 3.43 vs 16.03 ± 3.69, P = 0.25; environmental domain, 13.83 ± 2.56 vs 14.63 ± 2.26, P = 0.18). There was no statistical difference between the two groups.

To study the influence of disease duration, the study population was divided into two groups: those with a disease duration less than 4 yr and those with duration greater than 4 yr, based upon the median disease duration. There was no significant difference in the quality of life scores in any of the domains in the two groups (Table 6).


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TABLE 6. Relationship of QOL scores to disease duration

 
Age showed no significant relationship with the QOL scores in any of the domains. Gender analysis was not carried out as only three out of 73 patients were males.


    Discussion
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 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 Supplementary data
 References
 
The growing realization that traditional assessments of physical health alone are unsatisfactory measures of the impact of disease has led to increasing interest in QOL measures in recent years. Disease activity and damage are relatively easy to quantify in SLE and several validated measures, such as Mex-SLEDAI and the SLICC index, are available [15, 22]. QOL is difficult to measure and there is no consensus on the single best instrument to use. Most studies report an impaired QOL in lupus patients [7, 9]. However, studies of relationship of disease activity with QOL in lupus have shown equivocal results, some studies [5, 9–12] showing no relationship while others have shown worsening QOL with increasing disease activity [7, 8]. The vast majority of studies on QOL in SLE have emerged from the developed countries of Europe and North America [7, 9], with few data from Asian countries [5, 6, 23]. There are no data on QOL in lupus patients from the Indian subcontinent. Also the instruments used to assess QOL in lupus have included the Euroqol EQ-5D, SF-20 MOS SF-36 indices [7, 8, 22]. The cross cultural comparability of these instruments has not been demonstrated [18]. This makes their direct application in developing countries questionable.

Our study included 73 patients with lupus attending the rheumatology clinic at a tertiary care teaching hospital in North India. We preferred to use WHOQOL-Bref as a measure of QOL. This measure gives a reliable, valid and responsive assessment of QOL that is applicable across cultures [18]. The WHOQOL-Bref is a 26-item questionnaire derived from the 100-item parent WHOQOL-100. This parsimonious instrument can be used in place of the 100-item parent questionnaire when time is restricted, respondent burden must be minimized and where facet level detail is unnecessary. WHOQOL-Bref has been validated in Hindi [18]. One advantage of the WHOQOL instruments is that they include a domain on environment. This may be particularly appropriate in Asian countries where environment may play a key role in determining health status and access to health-care. There have been concerns about assessment of the social domain by WHOQOL-Bref. Saxena et al. have shown that the domain scores produced by WHOQOL-Bref correlate at around 0.9 with the WHOQOL-100 domain scores [18]. Similarly, results from a recent large study using cross-sectional data obtained from a survey of 11 830 adults across 23 countries confirm that WHOQOL-Bref is a sound, cross-culturally valid assessment of QOL, as reflected by all its four domains: physical, psychological, social and environmental [24].

Our study revealed greater impairment of QOL in physical and psychological domains. Patients scored higher in the social and environmental domains. This seems to be a reflection of the strong family support system prevalent in India and many other Asian countries. This may counter the negative influence of suboptimal health-care delivery systems in India. Our results show that disease activity negatively correlates with the physical and psychological domains, while the social and environmental domains are not related. Access to health and social care is an important item in the environmental domain in WHOQOL-Bref. In the context of India, unlike that of developed Western societies, the expectation of people and patients from the health-care system is not high. Difficulty in access to health-care is a fact of life, widely accepted. Similarly, there is hardly any social security system in place. The lack of negative correlation between QOL scores in the environmental domain and disease activity scores is probably because of low expectation in the first place. The negative correlation of disease activity and QOL in lupus has also been noted by other authors [7, 8].

Age and disease duration did not affect QOL in our study. The WHOQOL-Bref takes into account how the respondent felt over the last 2 weeks. Thus, the disease activity at a particular point of time would seem to affect QOL more than disease duration. Other workers, too, have reported that disease activity in SLE seems to influence QOL much more than disease duration [8–10].

Interestingly, arthritis and fatigue were the two clinical descriptors having negative impact on all domains of QOL, while QOL in patients with renal disease was no different from that in patients without active lupus nephritis. This may be because of the fact that renal disease in lupus is most often clinically silent and picked up primarily on investigations. The cross-sectional nature of our study is a drawback. A longitudinal study with multiple QOL evaluations in the same patient would have been ideal.

In conclusion, our study demonstrated that physical and psychological QOL are impaired to a greater extent in active lupus than social and environmental QOL. Arthritis and fatigue are the two most important clinical descriptors which negatively affect QOL in all domains. Age and disease duration did not affect the QOL in any of the domains. Larger longitudinal studies are needed to assess the relationship between the disease activity and QOL in lupus. QOL measures should be incorporated into the routine care of all patients with SLE.

The authors have declared no conflicts of interest.


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 Materials and methods
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 Supplementary data
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{keh376i1}

    Supplementary data are available

    at Rheumatology Online.


    References
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 Materials and methods
 Results
 Discussion
 Supplementary data
 References
 

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Submitted 29 April 2004; revised version accepted 16 July 2004.



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