Health-related quality of life of children with systemic lupus erythematosus and well-being of caregivers: a cross-sectional survey in China

doi:10.21203/rs.3.rs-4861393/v1

Objectives

Systemic lupus erythematosus (SLE) in children is a chronic and severe illness. We aimed to assess the health-related quality of life (HRQoL) of children with SLE and well-being of their caregivers.

Methods

In total, 173 children with a diagnosis of SLE were recruited from a tertiary children’s hospital. The proxy-reported PedsQL™ 4.0 Generic Core Module (PedsQL GCM) was used to measure the HRQoL of children, and the 5-item World Health Organization Well-Being Index (WHO-5) was applied to measure caregivers’ well-being. Differences in scale scores and total score of PedsQL GCM were assessed by t tests and one-way ANOVA. Effect sizes were calculated for clinical relevance. Multivariate linear regression analysis was used to identify the associated factors of children’s HRQoL. Pearson correlation analysis was utilized to assess the correlation between children’s HRQoL and the well-being of their caregivers.

Results

Children with SLE were reported lower scores in physical functioning, emotional functioning, school functioning, psychosocial health summary score, and total score of PedsQL GCM compared to healthy children. The multivariate linear regression analysis shows parental employment status, perceived financial burden and the changes in body image were significantly associated with the relatively low HRQoL of children (p values < 0.05). 30.6% of caregivers had depression and 10.4% had major depression as indicated by the score of WHO-5. Scale and overall scores of PedsQL GCM were significantly correlated with the score of WHO-5 (p values < 0.05).

Conclusions

This study provides a comprehensive analysis of SLE children’s HRQoL in China and identified multiple determinants. Caregiver’s well-being was evaluated and was closely related to children’s HRQoL. We emphasizes the necessity for comprehensive support for children with SLE, their caregivers, and extended family members.

Systemic lupus erythematosus

children

quality of life

caregiver

well-being

Systemic lupus erythematosus (SLE) is a chronic autoimmune disorder characterized by the immune system mistakenly attacking its own tissues, leading to inflammation and damage in multiple organs and systems (1–3). The etiology of SLE is not fully understood, but it is thought to involve a complex interaction of genetic, environmental, and hormonal factors (4, 5). SLE predominantly affects women, with onset typically occurring in adolescence and young adulthood (6). Childhood-onset SLE constitutes a significant proportion of SLE cases, distinguished by its manifestation prior to the age of 18 (7). The incidence rates were estimated indicated ranging from 0.28 to 0.9 per 100,000 children, and prevalence rates from 3.3 to 8.8 per 100,000 children (7). Specifically, studies conducted in the United States have reported an incidence of cSLE ranging from 0.4 to 2.2 per 100,000 children (8, 9), and prevalence rates fluctuating between 9.73 to 24 per 100,000 (9, 10).

In pediatric patients, SLE can have substantial consequences, including organ damage with a particular propensity for renal involvement, which may result in potential kidney failure, inhibited growth, and developmental delays. (11, 12). Manifestations such as arthralgia, fatigue, dermatological symptoms, pyrexia, and organ impairments may obstruct their capacity to participate in daily tasks, academic pursuits, and leisure activities, thereby diminishing their overall functionality and well-being (19). Moreover, individuals with this condition may face societal impediments such as stigmatization, seclusion, and difficulties in maintaining friendships (21). Treatments frequently necessitate prolonged administration of immunosuppressive drugs, which inherently pose the risk of infectious complications and other deleterious effects (15). Additionally, these treatments can impose significant financial strain and emotional distress on families due to the constant requirement for care. Consequently, the disease and its associated treatments adversely impact the health-related quality of life (HRQoL) for both the affected children and their families.

HRQoL is a crucial concept in both clinical practice and research. It encompasses an individual's subjective evaluation of their physical, mental, emotional, and social well-being in the context of their health status and any medical conditions or treatments (16). HRQoL is multidimensional construct, molded by a range of determinants such as the severity of the health condition, its influence on daily functioning, the efficacy of interventions, social support, socioeconomic status, and individual coping strategies, etc. (17)

Addressing the unique requirements of pediatric patients diagnosed with SLE is integral to improving their quality of life and overall wellness. This can be achieved through a holistic, multidisciplinary approach that encompasses medical treatment, psychological support, and empowerment strategies (11). Consequently, we initiated a questionnaire-based investigation among Chinese pediatric patients with SLE. The primary aim of this study was to evaluate the HRQoL of pediatric SLE patients in China and to identify the factors associated with HRQoL; and the secondary aim was to assess the wellbeing of their caregivers and to investigate the correlation between children’s HRQoL and caregiver’s wellbeing.

2.1. Study design and participants

The study was conducted by the Department of Rheumatology and Immunology in Children's Hospital, Zhejiang University School of Medicine. Participants were recruited from inpatients outpatients, and a Wechat group of pediatric patients who had a diagnosis of SLE. The Wechat group is an online platform that was established and maintained by clinicians and nurses to facilitate communication between caregivers of SLE children and health professionals. The criteria for inclusion were children with a diagnosis of SLE and their caregivers being willing to participte in the study and being capable to fill in the electronic questionnaire. This online survey was conducted from February to June 2024 using a self-developed questionnaire. In total, caregivers of 173 children with SLE gave their consent and completed the questionnaire.

The study was conducted according to the Declaration of Helsinki, and the study protocol was approved by the Medical Ethics Committee of the Children's Hospital, Zhejiang University School of Medicine (2024-IRB-189). All caregivers signed a written informed consent form and voluntarily participated in this study.

2.2. General and clinical characteristics

Information on social demographic characteristics, including the child’s age, gender, the relationship of the people who fill out questionnaires with the child, maternal/paternal educational level, employment status, annual household income, extra assistant(s) except for parents who can take care of the sick child at home, place of residence (urban or rural areas), having medical insurance, perceived financial burden due to the disease, and having a sibling or siblings. Educational level was categorized into three subsequent levels based on the Chinese Standard Classification of Education, i.e., a high level is a bachelor’s degree or above; middle level includes high school, technical/vocational secondary school, and vocational high school; and low level refers to no education, primary school or middle school. Employment of parents is divided into three dimensions, i.e., both parents being employed, only father or mother employed and neither of parents employed.

We also collected a comprehensive set of clinical variables by a questionnaire including the duration of SLE, hospitalization in the last six months, the number of visiting the outpatient department in the last six months, medication use, adherence to medication, changes in body image and disease activity. The disease activity was rated by the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) by physicians.

2.3. Health-related quality of life (HRQoL)

Children’s HRQoL was measured by the proxy-reported PedsQL™ 4.0 Generic Core Module (PedsQL™ 4.0 GCM). It has been validated in China with good reliability and validity (22, 23) with multiple age-appropriate versions. For children aged 5–18 years, the instrument contains 23 items and four scales, i.e., physical functioning (eight items), emotional functioning (five items), social functioning (five items), and school functioning (five items). Five response options were provided for each item on a 0 to 4 scale (i.e., 0 = never a problem, 1 = seldom a problem, 2 = sometimes a problem, 3 = often a problem, and 4 = always a problem).A linear transformation is used to convert items to a 0–100 scale (i.e., 0 = 0, 1 = 25, 2 = 50, 3 = 75, 4 = 100). Scale scores and total scores were computed as the sum of the items divided by the number of items answered. Psychosocial summary score was computed by the sum of the items of three scales including emotional, social and school functioning divided by the number of items. A higher score indicate better HRQoL. In the present study, the Cronbach’s alpha coefficient for the whole instrument is 0.917, and the Cronbach’s alpha coefficients for each scale were 0.762 (physical functioning), 0.911 (emotional functioning), 0.870 (social functioning), and 0.762 (school functioning), respectively.

2.4. Caregiver’s Well-Being

Caregivers’ well-being was measured by the five-item World Health Organization Well-Being Index (WHO-5). The five items are: (1) ‘I have felt cheerful and in good spirits’, (2) ‘I have felt calm and relaxed’, (3) ‘I have felt active and vigorous’, (4) ‘I woke up feeling fresh and rested’ and (5) ‘My daily life has been filled with things that interest me’. Each of the 5 items is scored from 0 (none of the time) to 5 (all of the time). Thus, the raw score can vary from 0 (no well-being) to 25 (maximum well-being). A cut-off score of ≤ 50 was used to provide a ‘screening diagnosis’ for depression. When the WHO-5 score was ≤ 28, it more closely matched the degree of well-being among patients with DSM-IV major depression (24). The WHO-5 showed a sensitivity of 0.93 and a specificity of 0.83 in detecting depression (25). In our study, the Cronbach’s alpha coefficients for WHO-5 is 0.961.

2.5. Statistical analyses

Firstly, we applied descriptive analysis to calculate means and standard deviations (SDs) for continuous variables with a normal distribution, and medians with interquartile intervals (IQRs) for variables with a non-normal distribution. For categorical variables, numbers and percentages were calculated. Secondly, we compared the scores of PedsQL GCM scales, summary and total score with the norm scores of the healthy control children reported in the published literature (26, 27). Thirdly, we used the two-independent-samples T-tests and one-way ANOVA to assess the differences in scale scores, summary score and total score of PedsQL GCM across subgroups across subgroups regarding different general and clinical characteristics. In spite of the statistical significance, we also utilized effect sizes such as Cohen's d and partial eta squared (η_p²) to evaluate the clinical relevance of differences in PedsQL GCM scores across subgroups. Regarding the difference between two groups, Cohen’s d was calculated that was calculated as the absolute value of the difference in average scores divided by the largest standard deviation, and was interpreted as follows: 0.2 ≤ d < 0.5, small difference; 0.5 ≤ d < 0.8, moderate difference; and d ≥ 0.8, large difference. While in terms of the difference among three or more groups, the effect size was indicated by partial eta squared (η_p²), and is interpreted as follows: 0.01 ≤ η_p² < 0.06, small difference; 0.06 ≤ η_p² < 0.14, moderate difference; and η_p² ≥ 0.14, large difference.

For total score of PedsQL GCM, we selected variables with a statistical significance in the above analyses and included them in the multivariate linear regression model to identify the independent associated factors of children’s overall HRQoL. Lastly, Pearson correlation analysis was utilized to assess the association between the HRQoL of children and the well-being of their caregivers. Additionally, we applied the two-independent-samples T-tests to compare the differences in scores of PedsQL GCM between caregivers with and without depression as indicated by the WHO-5 score.

All the statistical analyses were conducted by the SPSS (version 27.0, SPSS Inc., Chicago, USA). A statistical significance was indicated when p < 0.05.

3.1. General characteristics of the study population

Table 1 presents the general characteristics of the study population. The median of children’s age was 13.27 years, and 82.1% were girls. 70.5% of the questionnaires were filled by mothers. 34.1% of mothers and 34.1% of fathers had a high educational level. 64.2% of parents were both employed, 29.5% of mothers or fathers were employed and 6.4% of parents did not have a job. Regarding the annual household income, 50.9% of families earned less than 100,000 RMB per year, 34.1% earned 100,000 to 200,000 RMB, and 15.0% earned more than 200,000 RMB. 69.4% of them had other people at home to look after the sick child. 59.0% of families lived in the rural areas. 87.9% of children with SLE had health insurance. 90.2% of caregivers reported that the treatment of SLE caused a financial burden.

Table 1. General characteristics of the study population (n=173)

Characteristics	Values*
Age of children, year	13.27 (11.85, 15.39)
Gender
Boy	31(17.9)
Girl	142 (82.1)
Relationship with the child
Mother	122 (70.5)
Father/Others	51(29.4)
Highest educational level of mothers
Middle school or below	78 (45.1)
High school	36 (20.8)
College/Bachelor’s degree or above	59 (34.1)
Highest educational level of fathers
Middle school or below	70 (40.5)
High school	44 (25.4)
College/Bachelor’s degree or above	59 (34.1)
Employment of parents
Both of parents were employed	111(64.2)
Only father/mother was employed	51(29.5)
Neither of parents was employed	11(6.4)
Annual household income
Below 100,000 RMB	88 (50.9)
100,000-200,000 RMB	59 (34.1)
Above 200,000 RMB	26 (15.0)
Having someone else to take care of the sick child
Yes	120 (69.4)
No	53 (30.6)
Place of residence
Urban areas	71 (41.0)
Town or rural areas	102 (59.0)
Having medical insurance
Yes	152 (87.9)
No	21 (12.1)
Perceived financial burden
Yes	156 (90.2)
No	17 (9.8)
Having a sibling or siblings
Yes	118 (68.2)
No	55 (31.8)
Number of family members in one household
three or less	44 (25.4)
four	58 (33.5)
five or above	71 (41.0)

* Values presented in this table are medians (interquatile ranges), numbers and percentages.

3.2 Clinical characteristics of children with SLE

Clinical characteristics of children with SLE are summarized in Table 2. The median duration of living with SLE was 2.18 years. 12.1% of children visited the hospital for the first time. 45.1% of children have been hospitalized due to the disease in the last six months. The median number of visiting the hospital outpatient department in the last six months was 3.5. Regarding the currently-used medications, 11.0% of children only used steroid, 6.4% used immunosuppressants, 71.1% used both steroid and immunosuppressants, and 11.6% used other medications. 91.9% of them had good adherence. 79.8% of children were reported to have changes in body image due to SLE. The level of disease activity was mild in 37.6% children and moderate in 9.8% children.

Table 2. Clinical characteristics of children with SLE (n= 173)

Characteristic	Values*
Duration of disease, year [median (interquatile range)]	2.18 (0.86, 3.58)
First-time visit to the hospital
Yes	21 (12.1)
No	152 (87.9)
Hospitalization due to the disease in the last six months
Yes	78 (45.1)
No	95 (54.9)
Times of visiting hospitals in the last six months	3.5 (2.0, 6.0)
≤1	17 (22.4)
2	11 (14.5)
≥3	48 (63.1)
Currently-used medication
Steroid	19 (11.0)
Immunosuppressants	11 (6.4)
Steroid and immunosuppressants	123 (71.1)
Others	20 (11.6)
Adherence to the medication
Yes	159 (91.9)
No	14 (8.1)
Changes in body image
Yes	138 (79.8)
No	35 (20.2)
A specific change in body image
Facial rash/erythema	58 (42.0)
Alopecia	72 (52.2)
Growth retardation	65 (47.1)
Full moon face	105 (76.1)
Centripetal obesity	57 (41.3)
Purple stripe	44 (31.9)
Hypertrichiasis	85 (61.6)
Others	14 (10.1)
Level of disease activity
No activity	91 (52.6)
Mild activity	65 (37.6)
Moderate activity	17 (9.8)
Caregivers’ depression screened by the WHO-5 score
Depression (≤50), yes	53 (30.6)
Major depression (≤28), yes	18 (10.4)

* This table presents median, interquatile range, numbers, and percentages.

3.3. Comparing the mean scores of PedsQL GCM with the norm data

Table 3 presents the mean values and standard deviations of scale scores and total scores of PedsQL GCM measured in patients with SLE in our study and those of children as healthy controls extracted from the existing published literature (27). Regarding PedsQL GCM scale scores and total scores, the means were significantly lower compared to the healthy controls (p values<0.001) except for social functioning scale score (p=0.859). The range of effect size (Cohen’s d) was from 0.017 to 1.042.

Table 3. Comparison of the scale, summary and total scores of the PedsQL 4.0 GCM between patients and healthy reference*

	Patients (n=173)	Healthy reference^a (n=282)	Cohen’s d	p
Physical functioning	61.52 ±17.41	76.57 ±13.78	0.959	＜0.001
Emotional functioning	66.91 ±21.55	76.60 ±17.63	0.492	＜0.001
Social functioning	81.47 ±17.62	81.18 ±15.71	0.017	0.859
School functioning	61.40 ±18.74	77.52 ±17.40	0.891	＜0.001
Psychosocial Health Summary Score	70.19 ±16.51	80.13 ±14.66	0.637	＜0.001
Total Score	67.64 ±14.96	82.38 ±13.29	1.042	＜0.001

*Values presented in this table are means and standard deviations.

Abbreviation: PedsQL 4.0 GCM: Pediatric Quality of life inventory 4.0 Generic Core Module; ^aHealthy reference values for children aged ≥ 5 years are cited from the study by Hao, Tian (27).

3.4. Differences in average scale scores and the average total score of PedsQL GCM

Table 4 presents differences in average scale scores and the average total score of PedsQL GCM among all participants. We showed the variables with at least one statistically significant difference (p value < 0.05), and the rest results were presented in the Supplementary table S2. SLE children with both parents being employed, the mean scores were relatively higher in emotional functioning (p = 0.003), social functioning (p = 0.022), school functioning (p < 0.001), psychosocial health summary score (p < 0.001), as well as total score (p = 0.005). When the annual household income was between 100,000 and 200,000 RMB, the children were reported higher mean scores regarding physical function (p = 0.025), emotional function (p = 0.044), psychosocial health summary score (p = 0.006), and total scores (p = 0.003). When there was someone else who can take care of the sick child, the mean scores were higher in the school functioning scale (p = 0.029). Relatively lower mean scores of all scales and the total score were observed in families that reported a financial burden due to SLE (all p-values < 0.05). Children who visited the hospital for the first time had higher mean scores in emotional functioning scale (p = 0.015) and total scores (p = 0.029). Children who have been hospitalized due to the disease in the last six months were reported lower scors in physical function scale (p = 0.006) and school function scale (p = 0.004). Children who used steroid and immunosuppressants were reported to have relatively low score regarding physical function scale (p = 0.030), emotional function scale (p = 0.002), school function scale (p = 0.027), psychosocial health summary score (p = 0.023), and total scores (p = 0.019). SLE children who had a change or changes in body image were reported to have lower scores in all scales as well as a relatively low score in overall HRQoL (all p-values < 0.05) compared with those who did not have changes in body image. Children who had a mild level of disease activity presented lower mean scores of physical function scale compared to those with no activity and those with moderate level of disease activity (p = 0.038) .

Table 4 Means and standard deviations of PedsQL 4.0 GCM total scores and domain scores (n = 173)

Characteristics	Physical functioning	Emotional functioning	Social functioning	School functioning	Psychosocial Health Summary Score	Total score
Employment status of caregivers
Both of parents were employed (n=111)	62.89 ± 16.70	71.04 ± 19.93	83.87 ± 15.01	65.26 ± 18.32	73.66 ± 15.01	70.29 ± 13.78
Only father/mother was employed (n=51)	57.54 ± 17.94	59.61 ± 21.26	75.78 ± 21.83	52.14 ± 18.28	62.54 ± 17.82	61.36 ± 16.07
Neither of parents was employed (n=11)	66.19 ± 20.29	59.09 ± 28.79	83.64 ± 15.67	62.50 ± 10.34	68.33 ± 15.19	68.15 ± 14.79
p value	0.125	0.003	0.022	<.001	<.001	0.005
Effect size* (ɧ_p²)	0.02	0.07	0.04	0.10	0.09	0.07
Annual household income
Below 100,000 RMB (n=88)	58.66 ± 16.89	62.90 ± 20.59	78.75 ± 18.64	58.22 ± 17.70	65.99 ± 15.30	63.84 ± 13.21
Above 100,000 RMB (n=85)	64.49 ± 17.55	71.06 ± 21.85	84.29 ± 16.13	64.66 ± 19.33	74.50 ± 16.69	71.55 ± 15.71
p value	0.028	0.012	0.038	0.035	0.001	0.001
Effect size (Cohen’s d)	0.34	0.39	0.32	0.35	0.53	0.53
Financial burden
Yes (n=156)	60.26 ± 16.64	64.52 ± 20.80	80.03 ± 17.73	59.59 ± 17.96	68.40 ± 15.94	66.09 ± 14.24
No (n=17)	73.16 ± 20.46	88.82 ± 15.36	94.71 ± 9.27	77.67 ± 18.31	86.33 ± 12.62	81.67 ± 14.37
p value	0.003	<.001	<.001	<.001	<.001	<.001
Effect size (Cohen’s d)	0.69	1.33	1.04	1.00	1.25	1.09
Taking care of the children
Yes (n=120)	61.77 ± 18.48	67.96 ± 22.03	82.25 ± 17.95	63.71 ± 18.27	71.72 ± 16.90	68.92 ± 15.57
No (n=53)	60.97 ± 14.88	64.53 ± 20.41	79.72 ± 16.88	56.63 ± 18.97	67.04 ± 15.36	65.02 ± 13.37
p value	0.780	0.336	0.385	0.029	0.104	0.135
Effect size (Cohen’s d)	0.05	0.16	0.15	0.38	0.29	0.27
First onset of symptoms
Yes (n=21)	67.26 ± 21.73	77.62 ± 21.13	84.76 ± 18.06	69.71 ± 21.83	77.35 ± 18.68	75.06 ± 17.44
No (n=152)	60.73 ± 16.66	65.43 ± 21.25	81.02 ± 17.57	60.34 ± 18.12	69.27 ± 16.06	66.70 ± 14.41
p value	0.107	0.015	0.363	0.052	0.057	0.029
Effect size (Cohen’s d)	0.34	0.58	0.21	0.47	0.46	0.52
Current medications
Steroid (n=19)	62.17 ± 18.66	68.68 ± 21.01	82.89 ± 12.94	69.62 ± 20.86	75.77 ± 16.59	73.16 ± 16.02
Immunosuppressants (n=11)	69.89 ± 22.37	75.91 ± 27.91	85.91 ± 20.71	65.00 ± 20.37	75.61 ± 21.80	73.62 ± 21.02
Steroid and immunosuppressants (n=123)	59.35 ± 16.19	63.41 ± 20.17	79.67 ± 17.90	58.73 ± 17.02	67.74 ± 15.24	65.36 ± 13.32
Others (n=20)	69.69 ± 18.11	81.75 ± 20.08	88.75 ± 16.69	70.62 ± 23.37	78.75 ± 17.68	74.80 ± 16.93
p value	0.030	0.002	0.137	0.027	0.023	0.019
Effect size (ɧ_p²)	0.05	0.09	0.03	0.06	0.06	0.07
The child has been hospitalized due to the disease in the last six months
Yes (n=78)	57.57 ± 16.07	64.94 ± 19.11	80.45 ± 17.93	56.56 ± 13.50	67.73 ± 13.62	64.90 ± 12.55
No (n=95)	64.77 ± 17.88	68.53 ± 23.34	82.32 ± 17.41	64.72 ± 21.04	71.87 ± 18.11	69.53 ± 16.20
p value	0.006	0.267	0.490	0.004	0.113	0.051
Effect size (Cohen’s d)	0.42	0.17	0.11	0.46	0.26	0.32
Adherence
Yes (n=159)	62.11 ± 17.50	66.86 ± 21.65	81.48 ± 18.02	62.97 ± 18.00	70.79 ± 16.59	68.30 ± 15.01
No (n=14)	54.91 ± 15.49	67.50 ± 21.10	81.43 ± 12.62	43.33 ± 18.26	63.33 ± 14.48	60.14 ± 12.50
p value	0.139	0.915	0.989	<.001	0.134	0.070
Effect size (Cohen’s d)	0.44	0.03	0.00	1.08	0.48	0.59
There has been a change in body image since the child became ill
Yes (n=138)	59.69 ± 16.67	63.88 ± 19.01	79.57 ± 16.56	58.79 ± 17.10	67.89 ± 14.39	65.45 ± 13.09
No (n=35)	68.75 ± 18.64	78.86 ± 26.63	89.00 ± 19.81	71.83 ± 21.52	79.39 ± 21.01	76.41 ± 18.63
p value	0.006	0.003	0.004	<.001	0.007	0.004
Effect size (Cohen’s d)	0.51	0.65	0.52	0.67	0.64	0.68
Disease activity
No (n=91)	64.66 ± 17.57	70.33 ± 22.53	83.68 ± 17.51	62.01 ± 18.71	71.46 ± 16.61	69.00 ± 15.41
Mild (n=65)	57.55 ± 16.88	62.00 ± 20.54	78.23 ± 17.88	59.21 ± 19.03	67.05 ± 16.76	64.51 ± 14.62
Moderate (n=17)	59.93 ± 16.13	67.35 ± 16.87	82.06 ± 16.21	68.18 ± 16.92	76.97 ± 11.61	73.81 ± 10.06
p value	0.038	0.058	0.162	0.318	0.110	0.080
Effect size (ɧ_p²)	0.04	0.03	0.02	0.02	0.03	0.03

*Effect size: we calculated Cohen’s d for independent t-tests and partial eta squared (η_p²) for ANOVAs to estimate the effect size. Effect sizes are indicated as small (d = 0.2, η_p² = 0.01), medium (d = 0.5, η_p² = 0.06), and large (d = 0.8, η_p² = 0.14) effects by Cohen’s d and η_p².

3.5. Determinants of the overall HRQoL of SLE children

Table 5 shows the associated factors of the overall HRQoL of SLE children from multivariate linear regression analysis. Employment status of caregivers (β: −6.06; 95% CI: −11.25, −0.86; p = 0.023), perceiving a financial burden due to SLE (β: −9.99; 95% CI: −17.84, −2.15; p=0.013), and having a change/changes in body image (β: −8.32; 95% CI: −14.07, −2.56; p = 0.005) were statistically significantly associated with the total score of PedsQL 4.0 GCM. Age, duration of disease, annual household income, first time visit for the hospital, and medication were not statistically significantly associated with the total score of PedsQL 4.0 GCM (p values > 0.05).

Table 5 Associations of selected variables with the total score of PedsQL 4.0 by multivariate linear regression analyses

Variables	Total score
Variables	β (95% CI）	P value
Age	-0.17 (-1.01, 0.68)	0.697
Duration of SLE	-0.92 (-1.96, 0.12)	0.081
Employment status of caregivers
Both of parents were employed (n=111)	Reference
Only father/mother was employed (n=51)	-6.06 (-11.25, -0.86)	0.023
Neither of parents was employed (n=11)	0.06 (-9.04, 9.16)	0.989
Annual household income
Above 100,000 RMB (n=85)	Reference
Below 100,000 RMB (n=88)	-2.46 (-7.41, 2.49)	0.327
Perceived financial burden due to SLE
No (n=17)	Reference
Yes (n=156)	-9.99 (-17.84, -2.15)	0.013
First time visit to the hospital
Yes (n=21)	Reference
No (n=152)	-5.64 (-12.93, 1.65)	0.129
Currently-used medication
Steroid (n=19)	Reference
Immunosuppressants (n=11)	1.57 (-9.53, 12.66)	0.780
Steroid and immunosuppressants (n=123)	-1.89 (-10.13, 6.35)	0.650
Others (n=20)	1.83 (-8.31, 11.97)	0.722
Changes in body image
No (n=35)	Reference
Yes (n=138)	-8.32 (-14.07, -2.56)	0.005
Adjusted R²	0.22

Abbreviation: CI, confident interval

3.6. The correlation of PedsQL 4.0 GCM total scores and domain scores with WHO-5 scores of caregivers

Table 6 shows the correlation of PedsQL 4.0 GCM total scores and domain scores with WHO-5 scores of caregivers using correlation analysis. It demonstrated that scale scores, psychosocial health summary score and total score of PedsQL 4.0 GCM are statistically significantly correlated with caregivers’ well-being score (p values < 0.05). In addition, when caregivers had depression, the quality of life of children were relevantly lower compared to their peers whose parents did not have depression.

Table 6. Caregiver’s well-being and its correlation with children’s HRQoL

	WHO-5 score		Depression
	r	p	Yes	No	p
Physical functioning	0.250	< 0.001	57.61 ± 17.27	63.26 ± 17.26	0.049
Social functioning	0.472	< 0.001	72.26 ± 19.77	85.54 ± 14.95	< 0.001
Emotional functioning	0.460	< 0.001	56.13 ± 17.45	71.67 ± 21.53	< 0.001
School functioning	0.460	< 0.001	51.82 ± 17.02	65.38 ±18.03	< 0.001
Psychosocial Health Summary score	0.524	< 0.001	60.76 ± 15.91	74.10 ± 15.18	< 0.001
Total score	0.482	< 0.001	60.10 ± 14.84	70.78 ± 13.91	< 0.001

The current research has delineated a comprehensive profile of health-related quality of life (HRQoL) in Chinese children diagnosed with Systemic Lupus Erythematosus (SLE), as well as the welfare of their caregivers. The findings of our study indicated a significant impairment in the physical, emotional, social, and school functioning of children with SLE, alongside a marked deterioration in their overall HRQoL compared to the reference data from healthy children(27). Moreover, we discerned several determinants of HRQoL in children with SLE, including the employment status of the parents, the financial implications, and alterations in body image attributable to SLE. Additionally, a correlation was observed between the well-being of caregivers and the HRQoL of the children.

Children’s health-related quality of life and its determinants

Our research revealed a significant disparity in the HRQoL between children diagnosed with SLE and their healthy counterparts across all scales and the overall HRQoL(27). Effect sizes indicated that the clinical relevance of this disparity in children's HRQoL can be classified as large in terms of physical functioning, school functioning, and the total score of PedsQL GCM. Conversely, the effect sizes of emotional, social, and psychosocial health summary scores ranged from small to moderate. Compared with their healthy counterparts, SLE children demonstrate a higher propensity for multi-organ damage, cognitive dysfunction, and elevated mortality rates, attributable to the persistent and pervasive nature of the disease(28, 29). This often culminates in insufficient or non-existent participation in school activities and social interactions. Consequently, their academic performance, peer relationships, and psychosocial functioning may be adversely affected.

Our research determined a significant correlation between the socioeconomic status of caregivers or family and the health-related quality of life of children. The employment status of parents and the perceived financial burden due to SLE were found to be significantly associated with the overall HRQoL in children with SLE and with domain scores of PedsQL GCM, even after adjusting for other variables. This finding aligns with previous studies that have also highlighted the impact of a family's financial situation on children's quality of life (30-32). The financial strain can precipitate a deficiency in medical resources and healthcare services, thereby creating a disparity where families with superior financial stability can afford enhanced medications and medical care for their children. This discrepancy can potentially impact the effectiveness of treatments and subsequently influence the quality of life for children. It is therefore imperative that we intensify our focus on the influence of financial burden on children’s HRQoL. It is recommended that more targeted social support be extended to these families, including health insurance, daycare services, and other social subsidies or benefits. Additionally, our findings indicated an improvement in the children's HRQoL when supplementary caregiving assistance was provided at home for the sick child. This observation was consistent with previous research, which has demonstrated a positive correlation between additional home-based caregivers, beyond the parents, and an enhancement in children's HRQoL (33, 34).

In the current research, it was noted that children who were visiting the hospital for the first time demonstrated improved emotional functioning and overall HRQoL. It is plausible to infer that the protracted course of SLE could have a detrimental effect on the emotional well-being and quality of life of children. The experience of hospitalization was associated with worse physical health and academic performance. This is primarily due to the fact that children who require hospitalization often present with severe complications such as rash, alopecia, infection, osteoporosis, aseptic bone necrosis, and arthritis. These conditions may induce pain or other physical discomforts, subsequently leading to a deficiency in time and energy necessary for daily activities and learning. This can adversely impact their academic performance and overall quality of life (28).

In the present research, it was observed that SLE children administered with both corticosteroids and immunosuppressants exhibited a relatively low quality of life. Oral and intravenous corticosteroids are frequently employed as the primary treatment for SLE (29). In certain cases, if the condition of the child remains uncontrolled following a reduction in steroid dosage, immunosuppressants may be prescribed. The combination of multiple medications has been found to effectively manage the disease. A meta-analysis has demonstrated that biological therapies exhibit a steroid-sparing effect(35). However, these therapies may also induce side effects, including infection and leukopenia, which can detrimentally affect the psychological wellbeing and daily life of patients diagnosed with Systemic Lupus Erythematosus (SLE). Our research also revealed a significant correlation between medication adherence and enhanced school performance, with a notably large effect size. Non-adherence was found to be associated with factors such as forgetfulness, a high pill burden, adverse side effects, and a perceived lack of improvement in symptoms (36). Given that deficits in medication adherence are linked to increased morbidity, mortality, and healthcare costs (37), it is essential to enhance the adherence and self-management skills of children and adolescents.

In our research, we found a significant association between alterations in body image and all domains of children’s HRQoL, as well as their overall HRQoL, with a moderate effect size. Furthermore, even after accounting for other covariates, the alteration in body image remained significantly correlated with the total score of PedsQL GCM. During the initial phases of the disease, alterations in physical appearance may not be immediately discernible. However, over time, manifestations such as skin rashes, obesity, and a characteristic 'moon face' resulting from steroid therapy may become apparent. These changes in body image can induce not only physical discomforts but also psychological distress in children, often leading to a sense of inferiority. This can subsequently deter them from active participation in social and school activities. Consequently, their peer relationships is often adversely affected by these physical changes, potentially leading to feelings of isolation and interpersonal conflicts.

In our study, we observed no dose-response correlation between the severity of disease activity and the HRQOL in SLE children. Children with mild disease activity demonstrated the most impaired physical functioning in comparison to their counterparts with no disease activity and those with moderate disease activity. This phenomenon could potentially be attributed to the stability of disease activity due to therapeutic intervention, which consequently has a minimal impact on patients with disease activity (38, 39). Furthermore, it is crucial to consider that the limited sample size of children exhibiting moderate disease activity may potentially constrain the statistical power of the study. This is consistent with previous studies conducted by Moorthy et al. on a limited cohort of children diagnosed with SLE, which indicated a lack of a strong correlation between disease activity and quality of life (40,41). The deleterious effects of SLE, particularly in relation to renal, central nervous system, and joint involvement, significantly impact the physical functioning of pediatric SLE patients (42-45).

Caregiver’s well-being and its correlation with children’s health-related quality of life

In the current research, it was determined that 30.6% of caregivers for children with Systemic Lupus Erythematosus (SLE) exhibited symptoms of depression, as measured by the World Health Organization-5 (WHO-5) scale. Among them, approximately one third may be experiencing major depression. Furthermore, children’s HRQoL was lower when their caregivers were screened with depression compared to their counterparts. These findings underscore the urgent need to prioritize the mental health and welfare of caregivers for SLE children. The mental well-being of caregivers is a critical factor influencing HRQoL of their children. Typically, parents who maintain a positive and optimistic demeanor tend to observe a more favorable prognosis for their children(46, 47). The holistic support of both parents and extended family is essential for the upbringing and enhancement of self-management skills in children. It is crucial for these parents to initially accept and comprehend the nature of this disease, fostering a positive and optimistic attitude. Parental attitudes significantly influence the emotional development of children; thus, a pessimistic outlook may inadvertently instill a lack of confidence in them. Rather than dwelling on ‘why my child has SLE’, it is more constructive to look forward and focus on prospective solutions and interventions. Our finding is corresponding to previous research on the impact of caregivers’ HRQoL on that of their children (34, 48, 49).

Strengths and limitations

The present study investigated HRQoL of SLE children and well-being of their caregivers in China with a relatively large sample size. We underscore the familial role in managing chronic disease patients, adopting a family ecosystem perspective. Secondly, we have evaluated a comprehensive set of general and clinical characteristics as the potential associated factors of children’s HRQoL. We utilized effect sizes to interpret clinical relevance in addition to statistical significance. However, there are several limitations warranting for attention. This study is a single-center investigation. The research was conducted at a Children's Hospital, a national clinical research center for child health, which exemplifies a relatively advanced level of diagnostic and therapeutic capabilities. Notably, there have been no recorded fatalities in the Department of Allergy Immunology and Rheumatology from which the study participants were recruited. However, this institution may not be representative of hospitals of varying standards across China. Despite the high standard of diagnosis and treatment, the quality of life for these individuals remains significantly lower than that of healthy counterparts, an issue that continues to warrant attention. Another limitation of this study is its cross-sectional design, which lacks follow-up quality of life measurements over time, thereby hindering the ability to establish relevant causality. In our research, children with SLE were evaluated using a proxy-reported questionnaire. However, it may be more advantageous to utilize both proxy- and self-reported outcomes for a more comprehensive assessment.

The current research provides a comprehensive analysis of health-related quality of life (HRQoL) in Chinese children diagnosed with SLE, in addition to examining the well-being of their caregivers. Several factors were identified as having a significant association with children’s HRQoL, including parental employment status, financial burden, and changes in body image attributable to SLE. A correlation was observed between the well-being of caregivers and children’s HRQoL. This study emphasizes the necessity for comprehensive support for children with SLE, their caregivers, and extended family members.

Ethics approval and consent to participate: The study protocol was conducted according to the Declaration of Helsinki, and was approved by the Medical Ethics Committee of the Children's Hospital, Zhejiang University School of Medicine (2023-IRB-189). All caregivers gave their consents and voluntarily participated in the study.

Availability of data and materials: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests: The authors declare that they have no competing interests.

Funding: There is no funding related to the present study.

Authors' contributions: L.F, M.L. and G.B. were involved in the study conceptualization and design. L.F., F.L., L.Y., and Z.L. collected data. L.G., Y.S., and L.Y. carried out statistical analyses. L.F., L.G., and Y.S. prepared Table 1-6. L.F.,Y.W., and G.B. wrote the main manuscript texts. A.R. prepared the supplementary tables. M.L. and G.B. supervised the whole project. All authors reviewed the manuscript and provided critical revisions of the article for important intellectual content. All the authors contributed to the interpretation of the data and approved the article's final version.

Acknowledgements:

We gratefully thank all the SLE patients and their caregivers who were willing to participate in this study. We thank the Pediatric Evidence-based Medical and Clinical Research Laboratory, an internal institute of the National Clinical Research Center for Child Health, for the great support in terms of methodology and data analysis.

Ameer MA, Chaudhry H, Mushtaq J, Khan OS, Babar M, Hashim T et al (2022) An Overview of Systemic Lupus Erythematosus (SLE) Pathogenesis, Classification, and Management. Cureus 14(10):e30330
Durcan L, O'Dwyer T, Petri M (2019) Management strategies and future directions for systemic lupus erythematosus in adults. Lancet 393(10188):2332–2343
Kuhn A, Bonsmann G, Anders HJ, Herzer P, Tenbrock K, Schneider M (2015) The Diagnosis and Treatment of Systemic Lupus Erythematosus. Dtsch Arztebl Int 112(25):423–432
Zhu Z, Liang Z, Liany H, Yang C, Wen L, Lin Z et al (2015) Discovery of a novel genetic susceptibility locus on X chromosome for systemic lupus erythematosus. Arthritis Res Therapy 17(1):349
Moulton VR, Suarez-Fueyo A, Meidan E, Li H, Mizui M, Tsokos GC (2017) Pathogenesis of Human Systemic Lupus Erythematosus: A Cellular Perspective. Trends Mol Med 23(7):615–635
Fava A, Petri M (2019) Systemic lupus erythematosus: Diagnosis and clinical management. J Autoimmun 96:1–13
Kamphuis S, Silverman ED (2010) Prevalence and burden of pediatric-onset systemic lupus erythematosus. Nat Rev Rheumatol 6(9):538–546
Denardo BA, Tucker LB, Miller LC, Szer IS, Schaller JG (1994) Demography of a regional pediatric rheumatology patient population. Affiliated Children's Arthritis Centers of New England. J Rhuematol 21(8):1553–1561
Hiraki LT, Feldman CH, Liu J, Alarcón GS, Fischer MA, Winkelmayer WC, Costenbader KH (2012) Prevalence, incidence, and demographics of systemic lupus erythematosus and lupus nephritis from 2000 to 2004 among children in the US Medicaid beneficiary population. Arthr Rhuem 64(8):2669–2676
Kurahara DK, Grandinetti A, Fujii LLA, Tokuda AA, Galario JA, Han MJ et al (2007) Visiting consultant clinics to study prevalence rates of juvenile rheumatoid arthritis and childhood systemic lupus erythematosus across dispersed geographic areas. J Rhuematol 34(2):425–429
Blamires J, Foster M, Napier S, Dickinson A (2023) Experiences and Perspectives of Children and Young People Living with Childhood-Onset Systemic Lupus Erythematosus-An Integrative Review. Child (Basel). ;10(6)
Chandwar K, Aggarwal A (2023) Systemic Lupus Erythematosus in Children. Indian J Pediatr
Kammeyer R, Ogbu EA, Cooper JC, Stolz E, Piquet AL, Fuhlbrigge RC et al Cognitive dysfunction in pediatric systemic lupus erythematosus: current knowledge and future directions. Child Neuropsychol. 1–29
Warchoł-Biedermann K, Mojs E, Sikorska D, Kotyla P, Teusz G, Samborski W (2022) Psychological Implications to the Therapy of Systemic Lupus Erythematosus. Int J Environ Res Public Health. ;19(23)
Lazar S, Kahlenberg JM (2023) Systemic Lupus Erythematosus: New Diagnostic and Therapeutic Approaches. Annu Rev Med 74:339–352
Yin S, Njai R, Barker L, Siegel PZ, Liao Y (2016) Summarizing health-related quality of life (HRQOL): development and testing of a one-factor model. Popul Health Metr 14:22
Siqeca F, Yip O, Mendieta MJ, Schwenkglenks M, Zeller A, De Geest S et al (2022) Factors associated with health-related quality of life among home-dwelling older adults aged 75 or older in Switzerland: a cross-sectional study. Health Qual Life Outcomes 20(1):166
Olesińska M, Saletra A (2018) Quality of life in systemic lupus erythematosus and its measurement. Reumatologia 56(1):45–54
Kaul A, Gordon C, Crow MK, Touma Z, Urowitz MB, van Vollenhoven R et al (2016) Systemic lupus erythematosus. Nat Rev Dis Primers 2:16039
Fernandez H, Cevallos A, Jimbo Sotomayor R, Naranjo-Saltos F, Mera Orces D, Basantes E (2019) Mental disorders in systemic lupus erythematosus: a cohort study. Rheumatol Int 39(10):1689–1695
Drenkard C, Theis KA, Daugherty TT, Helmick CG, Dunlop-Thomas C, Bao G et al (2022) Depression, stigma and social isolation: the psychosocial trifecta of primary chronic cutaneous lupus erythematosus, a cross-sectional and path analysis. Lupus Sci Med. ;9(1)
Chen R, Hao Y, Feng L, Zhang Y, Huang Z (2011) The Chinese version of the Pediatric Quality of Life Inventory™(PedsQL™) Family Impact Module: cross-cultural adaptation and psychometric evaluation. Health Qual Life Outcomes 9:1–10
Ji Y, Chen S, Li K, Xiao N, Yang X, Zheng S, Xiao X (2011) Measuring health-related quality of life in children with cancer living in Mainland China: feasibility, reliability and validity of the Chinese Mandarin version of PedsQL 4.0 Generic Core Scales and 3.0 Cancer Module. Health Qual Life Outcomes 9(1):1–13
Löwe B, Spitzer RL, Gräfe K, Kroenke K, Quenter A, Zipfel S et al (2004) Comparative validity of three screening questionnaires for DSM-IV depressive disorders and physicians’ diagnoses. J Affect Disord 78(2):131–140
Topp CW, Østergaard SD, Søndergaard S, Bech P (2015) The WHO-5 Well-Being Index: a systematic review of the literature. Psychother Psychosom 84(3):167–176
Chan LF, Chow SM, Lo SK (2005) Preliminary validation of the Chinese version of the Pediatric Quality of Life Inventory. Int J Rehabil Res 28(3):219–227
Hao Y, Tian Q, Lu Y, Chai Y, Rao S (2010) Psychometric properties of the Chinese version of the Pediatric Quality of Life Inventory 4.0 generic core scales. Qual Life Res 19(8):1229–1233
Levy DM, Kamphuis S (2012) Systemic lupus erythematosus in children and adolescents. Pediatr Clin 59(2):345–364
Charras A, Smith E, Hedrich C (2021) Systemic lupus erythematosus in children and young people. Curr Rheumatol Rep 23:1–15
Mizukami A, Trinh MT, Hoang TP, Shibanuma A, Ong KIC, Jimba M (2023) Determinants of health-related quality of life among patients with systemic lupus erythematosus in Hanoi, Vietnam. BMC Rheumatol 7(1):16
Phuti A, Schneider M, Tikly M, Hodkinson B (2018) Living with systemic lupus erythematosus in the developing world. Rheumatol Int 38:1601–1613
Tektonidou MG, Lewandowski LB, Hu J, Dasgupta A, Ward MM (2017) Survival in adults and children with systemic lupus erythematosus: a systematic review and Bayesian meta-analysis of studies from 1950 to 2016. Ann Rheum Dis 76(12):2009–2016
Putera AM, Irwanto I, Maramis MM, Prasetyo RV, Soemyarso NA, Noer MS (2020) Effect of mental health problems on the quality of life in children with lupus nephritis. Neuropsychiatr Dis Treat. :1583–1593
Uzuner S, Durcan G, Sahin S, Bahali K, Barut K, Kilicoglu AG et al (2021) Caregiver burden and related factors in caregivers of patients with childhood-onset systemic lupus erythematosus. Clin Rheumatol 40(12):5025–5032
Oon S, Huq M, Godfrey T, Nikpour M (eds) (2018) Systematic review, and meta-analysis of steroid-sparing effect, of biologic agents in randomized, placebo-controlled phase 3 trials for systemic lupus erythematosus. Seminars in arthritis and rheumatism; : Elsevier
Harry O, Crosby LE, Smith AW, Favier L, Aljaberi N, Ting TV et al (2019) Self-management and adherence in childhood-onset systemic lupus erythematosus: what are we missing? Lupus 28(5):642–650
Costedoat-Chalumeau N, Pouchot J, Guettrot-Imbert G, Le Guern V, Leroux G, Marra D et al (2013) Adherence to treatment in systemic lupus erythematosus patients. Best Pract Res Clin Rheumatol 27(3):329–340
Thumboo J, Strand V (2007) Health-related quality of life in patients with systemic lupus erythematosus: an update. Annals Acad Med Singap 36(2):115
Elera-Fitzcarrald C, Fuentes A, González LA, Burgos PI, Alarcón GS, Ugarte-Gil MF (2018) Factors affecting quality of life in patients with systemic lupus erythematosus: important considerations and potential interventions. Expert Rev Clin Immunol 14(11):915–931
Moorthy LN, Harrison M, Peterson M, Onel K, Lehman TJ (2005) Relationship of quality of life and physical function measures with disease activity in children with systemic lupus erythematosus. Lupus 14(4):280–287
Moorthy LN, Peterson M, Onel KB, Harrison MJ, Lehman TJ (2005) Quality of life in children with systemic lupus erythematosus. Curr Rheumatol Rep 7(6):447–452
Hersh AO, von Scheven E, Yazdany J, Panopalis P, Trupin L, Julian L et al (2009) Differences in long-term disease activity and treatment of adult patients with childhood‐and adult‐onset systemic lupus erythematosus. Arthritis Care Res 61(1):13–20
Ambrose N, Morgan T, Galloway J, Ionnoau Y, Beresford M, Isenberg D (2016) Differences in disease phenotype and severity in SLE across age groups. Lupus 25(14):1542–1550
Tucker L, Uribe A, Fernandez M, Vila L, McGwin G, Apte M et al (2008) Adolescent onset of lupus results in more aggressive disease and worse outcomes: results of a nested matched case–control study within LUMINA, a multiethnic US cohort (LUMINA LVII). Lupus 17(4):314–322
Ahn GE, Ramsey-Goldman R (2012) Fatigue in systemic lupus erythematosus. Int J Clin Rheumatol 7(2):217
García-Fernández FP, Arrabal‐Orpez MJ, Rodríguez‐Torres MC, Gila‐Selas C, Carrascosa‐García I, Laguna‐Parras JM (2014) Effect of hospital case‐manager nurses on the level of dependence, satisfaction and caregiver burden in patients with complex chronic disease. J Clin Nurs 23(19–20):2814–2821
Ljungholm L, Klinga C, Edin-Liljegren A, Ekstedt M (2022) What matters in care continuity on the chronic care trajectory for patients and family carers?—A conceptual model. J Clin Nurs 31(9–10):1327–1338
Sattoe JN, van Staa A, Moll HA, nl OYOFRGoh (2012) The proxy problem anatomized: child-parent disagreement in health related quality of life reports of chronically ill adolescents. Health Qual Life Outcomes 10:1–13
Tunnicliffe DJ, Singh-Grewal D, Craig JC, Howell M, Tugwell P, Mackie F et al (2017) Healthcare and research priorities of adolescents and young adults with systemic lupus erythematosus: a mixed-methods study. J Rhuematol 44(4):444–451

No competing interests reported.

SLESupplementarymaterials.docx

Health-related quality of life of children with systemic lupus erythematosus and well-being of caregivers: a cross-sectional survey in China

Status:

Version 1

Abstract

Objectives

Methods

Results

Conclusions

Introduction

Methods

2.1. Study design and participants

2.2. General and clinical characteristics

2.3. Health-related quality of life (HRQoL)

2.4. Caregiver’s Well-Being

2.5. Statistical analyses

Results

Discussion

Conclusions

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1