Abstract
Introduction
Chronic kidney disease (CKD) can negatively impact the quality of life (QoL) of patients and caregivers. Determinants of QoL may vary between countries and healthcare systems. Given the global prevalence of CKD, this multinational study aimed to quantify the impact of CKD on QoL for patients and caregivers worldwide.
Methods
Patients with CKD, caregivers and matched general population participants were recruited in Australia, Germany, Egypt, Italy, Mexico, Taiwan, the UK and the US. QoL was assessed by patient and caregiver response to EQ-5D-5L, and also to the CarerQol-7D instrument for caregivers. Subgroups were stratified by dialysis-dependence status.
Results
A total of 1382 patients and 813 caregivers were recruited. Across the surveyed country cohorts, patients reported significantly decreased EQ-5D-5L index scores versus matched general population cohorts (0.57–0.89 vs. 0.93–0.96, respectively; all p < 0.005), with greater impairment in dialysis-dependent patients versus non-dialysis-dependent patients (0.51–0.79 vs. 0.65–0.93, respectively). Patients typically reported significantly greater impairments across all EQ-5D-5L domains versus the general population. Caregivers reported lower mean EQ-5D-5L index scores versus matched general population cohorts (0.73–0.93 vs. 0.93–0.97, respectively). Caregivers reported mean CarerQol-7D index scores between 63.0 and 79.6, with numerically lower scores for caregivers of dialysis-dependent patients.
Conclusion
This is the first study that characterises the QoL burden of CKD in patients and caregivers on a multinational scale. Patients and caregivers experience a considerable QoL burden, particularly when dialysis-dependent. Strategies to alleviate burden, including prevention of CKD progression, financial and social supports, are required but may vary according to local context.
Graphical Abstract
Supplementary Information
The online version contains supplementary material available at 10.1007/s12325-025-03455-6.
Keywords: Caregiver, Caretaker, CKD stage, Haemodialysis, Peritoneal dialysis, Translational
Key Summary Points
| Why carry out this study? |
| Chronic kidney disease (CKD) is known to adversely affect patients' and caregivers' quality of life; however, the impact and contributing factors on a global scale remain unknown. |
| This is the first study that characterises the quality-of-life burden of CKD on patients and unpaid caregivers at a multinational scale (Australia, Egypt, Germany, Italy, Mexico, Taiwan, UK, and USA), and across all stages of disease, versus respective general populations. |
| What was learned from the study? |
| The data presented highlights the need to implement intervention programs that support patients, from earlier stages of CKD through to kidney failure, and to support caregivers in managing the condition of the person they care for. |
| To mitigate the burden of CKD, especially among dialysis-dependent patients and caregivers, future strategies should prioritise the provision of support, including medical, social and financial support systems. |
| The study also showed some variation in outcomes between countries that merit further investigation to tailor strategies to address relevant factors with each country. |
Digital Features
This article is published with digital features, including a graphical abstract, to facilitate understanding of the article. To view digital features for this article, go to 10.6084/m9.figshare.30646886.
Introduction
Patients with chronic kidney disease (CKD) experience a progressive decline in health-related quality of life (HRQoL) in line with advancing disease, particularly as kidney failure approaches [1, 2]. Patients with CKD experience multiple symptoms and require increasingly frequent hospital visits as the disease progresses [3]. In addition, patients with CKD typically have accompanying comorbidities, most commonly hypertension, type 2 diabetes, and cardiovascular disease, with recent studies showing that a majority of adults with CKD have at least one comorbidity [4–6]. In early CKD stages, HRQoL is often influenced by comorbidities [1, 7].
As CKD advances, patients often rely on informal caregivers, such as family members, for support. This support often includes transportation to medical appointments, medication management, and emotional support, especially for those requiring dialysis or a kidney transplant [8, 9]. Caring for people with CKD has been associated with substantial burden and decreased psychological well-being for caregivers. [10, 11] However, studies have shown that informal caregiving is associated with better adherence to treatment regimens, quality of life (QoL), and improved patient survival, demonstrating its value to those affected by CKD [12, 13]. A number of factors, including access to healthcare and social support, may impact QoL for both patients and caregivers. As these factors can vary substantially between countries, a global sample can help characterise the QoL burden of CKD in patients and caregivers. Currently, there are limited data available to characterise the burden that caring for patients with CKD can exert, with most available data pertaining only to those caring for patients on dialysis or with kidney failure [10, 14–16].
There is an unmet need for a systematic investigation of the known QoL burden on a large cohort of patients across several countries, and to investigate the lesser-known burden in caregivers, including data collection using instruments designed for this purpose. Therefore, the Patient, Carer and Economic burden (PaCE) CKD study aims to enhance understanding of patient and caregiver experiences of CKD including the impact on QoL. The aim of the surveys and analysis presented in this article was to measure the effect of CKD on patient and caregiver QoL across eight countries.
Methods
Study Design
Participants across eight countries (Australia, Egypt, Germany, Italy, Mexico, Taiwan, UK, and USA) were enrolled in a non-interventional cross-sectional survey aimed at quantifying the QoL burden of CKD. For surveys of HRQoL in patients with CKD, data are presented for seven countries (excluding Italy, due to issues in data collection) in this article. Surveys including baseline characteristics and CarerQoL-7D for QoL in caregivers are presented for all countries; EQ-5D-5L is not reported for the Italian cohort.
Participant Recruitment
Participants were recruited via online research panels and patient advocacy groups. All participants were required to be a citizen or permanent resident, aged 18 years or older, who were not an employee of a pharmaceutical company or medical device manufacturer. A general population cohort for each country was also enrolled, matched to patients and caregiver cohorts by age group, gender, and area of residence (e.g. metro, regional, rural).
Criteria for enrolment as a patient required a diagnosis of CKD from a healthcare professional over three months prior to enrolment. CKD was diagnosed across multiple parameters with patients and caregivers independently reporting CKD disease stage at time of survey completion.
Caregivers were required to provide regular, ongoing unpaid assistance to a family member, neighbour, or friend with diagnosed CKD. Caregivers could not be a formal paid caregiver and must have been providing care for at least three months prior to enrolment, for a minimum of one hour in the four weeks up to enrolment.
The general population sample excluded participants with CKD, or a health issue significantly impacting their HRQoL, ability to work, social life and/or relationships, financial status, or that requires a specialist doctor appointment at least three times/year, or necessitates assistance with everyday tasks.
Patients and caregivers were required to state whether they or the patient they cared for were in receipt of dialysis. Patients were also asked the modality, how long for, and whether procedures were conducted at home or in a clinic/hospital. Illogical answer combinations were screened and removed. Patients and caregivers were also required to state whether they or the patient they cared for had received a kidney transplant and, if so, whether it was currently functioning.
Data cleaning and structuring involved several steps. Respondents were removed from the final sample if they finished the survey unreasonably quickly, had duplicate internet protocol addresses or invalid or nonsensical open-text responses.
EQ-5D-5L
For individuals with CKD and caregivers, HRQoL was measured using the validated EQ-5D-5L instrument for all cohorts, except for Italy [17]. The EQ-5D-5L comprises five domains: mobility, anxiety/depression, usual activities, self-care, and pain/discomfort. Responses were converted to index scores using the latest EQ-5D-5L value set recommended for each country by EuroQol. EQ-5D index scores were estimated using value sets that were considered applicable and representative for the respective national populations [18–24]. The index ranges, typically, from 0–1, with a higher number equating to better HRQoL. In addition, the EQ visual analogue scale (VAS) was used, ranging from 0–100, with higher scores indicating better health.
CarerQol-7D
The validated CarerQol-7D instrument was used to measure the impact of informal caregiving for those with CKD on caregivers across all countries [25, 26]. The survey was not conducted in the matched general population cohorts as the survey is appropriate only for caregivers. The scale ranges from 0–100, with higher numbers indicating better caregiver QoL. CarerQol-7D was measured via several domains including support with carrying out care tasks, financial problems because of care tasks and problems combining care tasks with daily activities. As per EQ-5D-5L, responses were converted to scores using published tariffs for each country.
Population Analyses
Participants were stratified for subgroup analyses based on whether they or the patient they cared for were dependent on dialysis to control their condition. Additionally, patients and caregivers who were enrolled were required to report their CKD stage between 1 and 5 to the best of their knowledge. The prevalence of CKD globally is approximately distributed among patients by stage 1 (4%), stage 2 (4%), stage 3 (8%), followed by few patients at stages 4 (0.4%) and 5 (0.1%) [27]. To attain a mix of patients from all stages of disease, including from dialysis-dependent patients, this study aimed at a quota of ≥ 30% of respondents receiving dialysis in each country. EQ-5D index scores are reported according to CKD stage, with CKD stages 1–3 denoting early CKD and stages 4–5 denoting advanced disease, given the inherent bias of collecting self-reported disease severity data.
Statistical Analyses
Data were summarised descriptively, with mean and standard deviation (SD) reported for numeric variables (unless the median was specified), and the frequency and percentage were reported for categorical variables. Results were represented per country for each outcome to characterise the burden of CKD across global settings. Univariate linear regression analysis was undertaken to examine the relationship between a group variable and QoL index scores, with statistical significance considered at a threshold of p < 0.05. The regression models determined the influence of CKD (vs. general population), dialysis status or key demographic variables including, age, gender, employment status or area of residence. Descriptive analysis of data and the linear regression models were performed using R software.
Ethical Approval
This study was reviewed by an international Institutional Review Board (IRB), Pearl IRB, and was granted an exemption from a full review due to its low/negligible risk nature determined to be exempt in accordance with FDA 21 56.104 and 45CFR46.104 (Protocol #21-CAPP-102). All participants provided electronic informed consent.
Results
A total of 4642 participants were enrolled onto the PaCE CKD study across eight countries, with outcomes reported in this analysis derived from 4,384 participants (with no outcomes presented for patient and matched general population Italian cohorts). Outcomes in this article are presented for 1382 (range 150–222) patients with CKD and 813 (range 53–139) caregivers, matched to 1377 and 812 general population participants, respectively. An overview of total patient and caregiver demographics, and disease state, are provided in Tables 1 and 2. Full details of patient and caregiver demographic characteristics, for total populations and total matched general population cohorts are reported in the supplementary materials (Tables S1 and S2), as are those stratified by dialysis status (Tables S3 and S4). This study was reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines; the completed STROBE checklist is available in the supplementary materials (Table S5).
Table 1.
Self-reported characteristics of participants with CKD
| AUS | DEU | EGY | GBR | MEX | TWN | USA | Overall | |
|---|---|---|---|---|---|---|---|---|
| Pop. size, n | 150 | 201 | 222 | 212 | 208 | 190 | 199 | 1382 |
| Age group, n (%) | ||||||||
| < 20 y | 1 (0.7) | 0 (0.0) | 0 (0.0) | 2 (0.9) | 0 (0.0) | 0 (0.0) | 0 (0.0) | 3 (0.2) |
| 20–29 y | 26 (17.3) | 13 (6.5) | 33 (14.9) | 15 (7.1) | 30 (14.4) | 3 (1.6) | 4 (2.0) | 124 (9.0) |
| 30–39 y | 31 (20.7) | 34 (16.9) | 87 (39.2) | 68 (32.1) | 77 (37.0) | 7 (3.7) | 34 (17.1) | 338 (24.5) |
| 40–49 y | 33 (22.0) | 46 (22.9) | 60 (27.0) | 70 (33.0) | 55 (26.4) | 37 (19.5) | 31 (15.6) | 332 (24.0) |
| 50–59 y | 21 (14.0) | 63 (31.3) | 30 (13.5) | 20 (9.4) | 30 (14.4) | 88 (46.3) | 39 (19.6) | 291 (21.1) |
| 60–69 y | 25 (16.7) | 37 (18.4) | 11 (5.0) | 25 (11.8) | 14 (6.7) | 36 (18.9) | 51 (25.6) | 199 (14.4) |
| 70–79 y | 13 (8.7) | 7 (3.5) | 1 (0.5) | 10 (4.7) | 2 (1.0) | 19 (10.0) | 39 (19.6) | 91 (6.6) |
| ≥ 80 y | 0 (0.0) | 1 (0.5) | 0 (0.0) | 2 (0.9) | 0 (0.0) | 0 (0.0) | 1 (0.5) | 4 (0.3) |
| Gender,a n (%) | ||||||||
| Male | 70 (46.7) | 139 (69.2) | 130 (58.6) | 150 (70.8) | 110 (52.9) | 147 (77.4) | 108 (54.3) | 854 (61.8) |
| Female | 77 (51.3) | 57 (28.4) | 92 (41.4) | 60 (28.3) | 97 (46.6) | 42 (22.1) | 91 (45.7) | 516 (37.3) |
| Other | 2 (1.3) | 0 (0.0) | 0 (0.0) | 2 (0.9) | 1 (0.5) | 0 (0.0) | 0 (0.0) | 5 (0.4) |
| Prefer not to answer | 1 (0.7) | 5 (2.5) | 0 (0.0) | 0 (0.0) | 0 (0.0) | 1 (0.5) | 0 (0.0) | 7 (0.5) |
| CKD stage (self-report), n (%) | ||||||||
| Stage 1 | 22 (14.7) | 42 (20.9) | 31 (14.0) | 16 (7.5) | 26 (12.5) | 3 (1.6) | 13 (6.5) | 153 (11.1) |
| Stage 2 | 36 (24.0) | 38 (18.9) | 61 (27.5) | 53 (25.0) | 43 (20.7) | 85 (44.7) | 22 (11.1) | 338 (24.5) |
| Stage 3a | 26 (17.3) | 41 (20.4) | 50 (22.5) | 43 (20.3) | 46 (22.1) | 52 (27.4) | 62 (31.2) | 320 (23.2) |
| Stage 3b | 17 (11.3) | 33 (16.4) | 25 (11.3) | 29 (13.7) | 43 (20.7) | 15 (7.9) | 35 (17.6) | 197 (14.3) |
| Stage 4 | 12 (8.0) | 15 (7.5) | 16 (7.2) | 14 (6.6) | 22 (10.6) | 12 (6.3) | 27 (13.6) | 118 (8.5) |
| Stage 5/RRT | 32 (21.3) | 30 (14.9) | 31 (14.0) | 52 (24.5) | 25 (12.0) | 23 (12.1) | 36 (18.1) | 229 (16.6) |
| Do not know | 5 (3.3) | 2 (1.0) | 8 (3.6) | 5 (2.4) | 3 (1.4) | 0 (0.0) | 4 (2.0) | 27 (2.0) |
| Have you ever received a kidney transplant? n (%) | ||||||||
| Yes | 30 (20.0) | 23 (11.4) | 6 (2.7) | 51 (24.1) | 25 (12.0) | 0 (0.0) | 22 (11.1) | 157 (11.4) |
| No | 120 (80.0) | 178 (88.6) | 216 (97.3) | 161 (75.9) | 183 (88.0) | 190 (100.0) | 177 (88.9) | 1225 (88.6) |
| What type of dialysis are you receiving? n (%) | ||||||||
| PD | 13 (8.7) | 29 (14.4) | 16 (7.2) | 29 (13.7) | 41 (19.7) | 8 (4.2) | 20 (10.1) | 156 (11.3) |
| HD | 32 (21.3) | 56 (27.9) | 108 (48.6) | 85 (40.1) | 76 (36.5) | 21 (11.1) | 44 (22.1) | 422 (30.5) |
| Not receiving | 105 (70.0) | 116 (57.7) | 98 (44.1) | 98 (46.2) | 91 (43.8) | 161 (84.7) | 135 (67.8) | 804 (58.2) |
| How long have you been receiving dialysis? n (%) | ||||||||
| < 5 m | 3 (2.0) | 7 (3.5) | 6 (2.7) | 8 (3.8) | 8 (3.8) | 2 (1.1) | 3 (1.5) | 37 (2.7) |
| 5 m–2 y | 27 (18.0) | 30 (14.9) | 44 (19.8) | 51 (24.1) | 52 (25.0) | 13 (6.8) | 32 (16.1) | 249 (18.0) |
| 2–5 y | 10 (6.7) | 37 (18.4) | 47 (21.2) | 48 (22.6) | 51 (24.5) | 11 (5.8) | 16 (8.0) | 220 (15.9) |
| 5–10 y | 5 (3.3) | 6 (3.0) | 21 (9.5) | 6 (2.8) | 6 (2.9) | 2 (1.1) | 10 (5.0) | 56 (4.1) |
| > 10 y | 0 (0.0) | 5 (2.5) | 6 (2.7) | 1 (0.5) | 0 (0.0) | 1 (0.5) | 3 (1.5) | 16 (1.2) |
| Not receiving | 105 (70.0) | 116 (57.7) | 98 (44.1) | 98 (46.2) | 91 (43.8) | 161 (84.7) | 135 (67.8) | 804 (58.2) |
| Where do you receive your dialysis? n (%) | ||||||||
| Home | 5 (3.3) | 5 (2.5) | 0 (0.0) | 9 (4.2) | 33 (15.9) | 8 (4.2) | 13 (6.5) | 73 (5.3) |
| Clinic/hospital | 40 (26.7) | 80 (39.8) | 124 (55.9) | 105 (49.5) | 84 (40.4) | 21 (11.1) | 51 (25.6) | 505 (36.5) |
| Not receiving | 105 (70.0) | 116 (57.7) | 98 (44.1) | 98 (46.2) | 91 (43.8) | 161 (84.7) | 135 (67.8) | 804 (58.2) |
AUS Australia, DEU Germany, EGY Egypt, GBR United Kingdom, m months, MEX Mexico, TWN Taiwan, USA United States of America, y years
aThe options available for the participant to select for gender identity were ‘male’, ‘female’, ‘non-binary/gender fluid’, ‘prefer to self-describe (please specify)’ and ‘prefer not to answer’
Table 2.
Self-reported characteristics of unpaid caregivers of patients with CKD
| Characteristic | AUS | DEU | EGY | GBR | ITA | MEX | TWN | USA | Overall |
|---|---|---|---|---|---|---|---|---|---|
| Pop. size, n (%) | 53 | 99 | 97 | 116 | 102 | 139 | 94 | 113 | 813 |
| Age group, n (%) | |||||||||
| < 20 y | 1 (1.9) | 0 (0.0) | 2 (2.1) | 1 (0.9) | 2 (2.0) | 0 (0.0) | 0 (0.0) | 1 (0.9) | 7 (0.9) |
| 20–29 y | 7 (13.2) | 6 (6.1) | 24 (24.7) | 25 (21.6) | 11 (10.8) | 23 (16.5) | 6 (6.4) | 11 (9.7) | 113 (13.9) |
| 30–39 y | 17 (32.1) | 27 (27.3) | 36 (37.1) | 40 (34.5) | 11 (10.8) | 65 (46.8) | 20 (21.3) | 48 (42.5) | 264 (32.5) |
| 40–49 y | 10 (18.9) | 24 (24.2) | 18 (18.6) | 33 (28.4) | 23 (22.5) | 27 (19.4) | 30 (31.9) | 22 (19.5) | 187 (23.0) |
| 50–59 y | 9 (17.0) | 27 (27.3) | 14 (14.4) | 11 (9.5) | 34 (33.3) | 20 (14.4) | 17 (18.1) | 14 (12.4) | 146 (18.0) |
| 60–69 y | 6 (11.3) | 14 (14.1) | 3 (3.1) | 4 (3.4) | 18 (17.6) | 4 (2.9) | 18 (19.1) | 12 (10.6) | 79 (9.7) |
| 70–79 y | 3 (5.7) | 1 (1.0) | 0 (0.0) | 2 (1.7) | 2 (2.0) | 0 (0.0) | 3 (3.2) | 4 (3.5) | 15 (1.8) |
| ≥ 80 y | 0 (0.0) | 0 (0.0) | 0 (0.0) | 0 (0.0) | 1 (1.0) | 0 (0.0) | 0 (0.0) | 1 (0.9) | 2 (0.2) |
| Gender,a n (%) | |||||||||
| Male | 27 (50.9) | 55 (55.6) | 31 (32.0) | 57 (49.1) | 21 (20.6) | 59 (42.4) | 33 (35.1) | 53 (46.9) | 336 (41.3) |
| Female | 26 (49.1) | 43 (43.4) | 66 (68.0) | 58 (50.0) | 80 (78.4) | 75 (54.0) | 61 (64.9) | 60 (53.1) | 469 (57.7) |
| Other | 0 (0.0) | 1 (1.0) | 0 (0.0) | 1 (0.9) | 1 (1.0) | 0 (0.0) | 0 (0.0) | 0 (0.0) | 3 (0.4) |
| Prefer not to answer | 0 (0.0) | 0 (0.0) | 0 (0.0) | 0 (0.0) | 0 (0.0) | 5 (3.6) | 0 (0.0) | 0 (0.0) | 5 (0.6) |
| Do you and the person with kidney disease that you care for live in the same household? n (%) | |||||||||
| Yes | 26 (49.1) | 66 (66.7) | 93 (95.9) | 59 (50.9) | 64 (62.7) | 109 (78.4) | 59 (62.8) | 67 (59.3) | 543 (66.8) |
| No | 27 (50.9) | 33 (33.3) | 4 (4.1) | 57 (49.1) | 38 (37.3) | 30 (21.6) | 35 (37.2) | 46 (40.7) | 270 (33.2) |
| What is your relationship to the person you care for? n (%) | |||||||||
|
Husband/wife/ partner |
13 (24.5) | 37 (37.4) | 41 (42.3) | 30 (25.9) | 41 (40.2) | 44 (31.7) | 28 (29.8) | 29 (25.7) | 263 (32.3) |
| Sibling | 4 (7.5) | 9 (9.1) | 15 (15.5) | 8 (6.9) | 7 (6.9) | 18 (12.9) | 9 (9.6) | 6 (5.3) | 76 (9.3) |
| Child | 4 (7.5) | 13 (13.1) | 18 (18.6) | 4 (3.4) | 18 (17.6) | 2 (1.4) | 28 (29.8) | 7 (6.2) | 94 (11.6) |
| Parent | 22 (41.5) | 29 (29.3) | 21 (21.6) | 51 (44.0) | 25 (24.5) | 38 (27.3) | 27 (28.7) | 51 (45.1) | 264 (32.5) |
| Friend | 9 (17.0) | 5 (5.1) | 2 (2.1) | 17 (14.7) | 2 (2.0) | 11 (7.9) | 2 (2.1) | 14 (12.4) | 62 (7.6) |
| Other | 1 (1.9) | 6 (6.1) | 0 (0.0) | 6 (5.2) | 9 (8.8) | 26 (18.7) | 0 (0.0) | 6 (5.3) | 54 (6.6) |
| Kidney disease stage of the person being cared for? n (%) | |||||||||
| Stage 1 | 1 (1.9) | 0 (0.0) | 7 (7.2) | 3 (2.6) | 14 (13.7) | 17 (12.2) | 0 (0.0) | 1 (0.9) | 43 (5.3) |
| Stage 2 | 7 (13.2) | 21 (21.2) | 22 (22.7) | 12 (10.3) | 17 (16.7) | 29 (20.9) | 10 (10.6) | 12 (10.6) | 130 (16.0) |
| Stage 3a | 10 (18.9) | 23 (23.2) | 24 (24.7) | 33 (28.4) | 26 (25.5) | 35 (25.2) | 17 (18.1) | 23 (20.4) | 191 (23.5) |
| Stage 3b | 4 (7.5) | 24 (24.2) | 7 (7.2) | 23 (19.8) | 19 (18.6) | 22 (15.8) | 15 (16.0) | 22 (19.5) | 136 (16.7) |
| Stage 4 | 4 (7.5) | 18 (18.2) | 2 (2.1) | 10 (8.6) | 7 (6.9) | 21 (15.1) | 19 (20.2) | 13 (11.5) | 94 (11.6) |
| Stage 5/KRT | 21 (39.6) | 8 (8.1) | 33 (34.0) | 28 (24.1) | 13 (12.7) | 14 (10.1) | 33 (35.1) | 40 (35.4) | 190 (23.4) |
| Do not know | 6 (11.3) | 5 (5.1) | 2 (2.1) | 7 (6.0) | 6 (5.9) | 1 (0.7) | 0 (0.0) | 2 (1.8) | 29 (3.6) |
| Has the person you care for ever had a kidney transplant? n (%) | |||||||||
| Yes | 14 (26.4) | 4 (4.0) | 11 (11.3) | 26 (22.4) | 8 (7.8) | 8 (5.8) | 0 (0.0) | 28 (24.8) | 99 (12.2) |
| No | 39 (73.6) | 95 (96.0) | 86 (88.7) | 90 (77.6) | 94 (92.2) | 131 (94.2) | 94 (100.0) | 85 (75.2) | 714 (87.8) |
AUS Australia, DEU Germany, EGY Egypt, GBR United Kingdom, m months, MEX Mexico, TWN Taiwan, USA United States of America, y years
a The options available for the participant to select for gender identity were ‘male’, ‘female’, ‘non-binary/gender fluid’, ‘prefer to self-describe (please specify)’ and ‘prefer not to answer’
Of the 1382 patients enrolled in the study, approximately two-thirds were male (n = 854; 61.8%) and/or were between 30–59 years of age (n = 961; 69.5%). Most patients lived in metropolitan areas or cities (n = 976, 70.6%) and were employed (n = 809, 58.5%), with the remainder most commonly retired (n = 234, 16.9%) or not working due to medical reasons (n = 167, 12.1%). Of the 813 participating caregivers, most lived with the patient they were caring for (n = 543, 66.8%) and most were supporting either a parent (n = 264; 32.5%) or partner (n = 263; 32.3%). Most caregivers were employed (n = 608; 74.8%), while 67 (8.2%) were retired; 62 (7.6%) and 9 (1.1%) were unemployed or not working due to medical reasons, respectively. The stated type of support most often provided varied by country, but accompanying or driving patients to medical appointments and helping patients with medication were tasks frequently carried out by caregivers across all countries (Table 3).
Table 3.
Characterisation of caregiver support
| What sort of care/support do you provide for the person you care for? n (%) | AUS | DEU | EGY | GBR | ITA | MEX | TWN | USA |
|---|---|---|---|---|---|---|---|---|
| Accompany or drive them to medical appointments | 49 (92.5) | 89 (89.9) | 83 (85.6) | 89 (76.7) | 79 (77.5) | 120 (86.3) | 75 (79.8) | 101 (89.4) |
| Advocacy (e.g. helping them dispute a treatment or a decision) | 19 (35.8) | 33 (33.3) | 36 (37.1) | 42 (36.2) | 58 (56.9) | 47 (33.8) | 5 (5.3) | 52 (46.0) |
| Behavioural support (e.g. dealing with behaviours such as aggression or social withdrawal) | 19 (35.8) | 22 (22.2) | 23 (23.7) | 32 (27.6) | 17 (16.7) | 36 (25.9) | 1 (1.1) | 45 (39.8) |
| Encourage them to seek help or talk about their feelings | 26 (49.1) | 46 (46.5) | 26 (26.8) | 70 (60.3) | 34 (33.3) | 76 (54.7) | 14 (14.9) | 58 (51.3) |
| Help them get to social gatherings | 24 (45.3) | 37 (37.4) | 26 (26.8) | 48 (41.4) | 36 (35.3) | 47 (33.8) | 18 (19.1) | 55 (48.7) |
| Help them get to work | 4 (7.5) | 12 (12.1) | 10 (10.3) | 15 (12.9) | 2 (2.0) | 19 (13.7) | 0 (0.0) | 20 (17.7) |
| Help with communication (e.g. reading, writing, helping them articulate themselves in conversations) | 20 (37.7) | 37 (37.4) | 23 (23.7) | 39 (33.6) | 11 (10.8) | 39 (28.1) | 5 (5.3) | 46 (40.7) |
| Help with dependants and childcare | 11 (20.8) | 26 (26.3) | 30 (30.9) | 34 (29.3) | 15 (14.7) | 44 (31.7) | 9 (9.6) | 35 (31.0) |
| Help with general household duties (e.g. cleaning, food preparation, running errands, shopping, laundry) | 38 (71.7) | 67 (67.7) | 52 (53.6) | 95 (81.9) | 48 (47.1) | 100 (71.9) | 70 (74.5) | 91 (80.5) |
| Help with medications (e.g. remind, organise or help them take medications) | 37 (69.8) | 87 (87.9) | 84 (86.6) | 102 (87.9) | 57 (55.9) | 115 (82.7) | 52 (55.3) | 100 (88.5) |
| Help with mobility (e.g. walking, getting out of bed) | 25 (47.2) | 40 (40.4) | 45 (46.4) | 61 (52.6) | 20 (19.6) | 67 (48.2) | 5 (5.3) | 59 (52.2) |
| Help with organising and handling finances (e.g. budgeting, assisting with online banking, making financial decisions for them, managing their accounts) | 21 (39.6) | 44 (44.4) | 11 (11.3) | 45 (38.8) | 48 (47.1) | 46 (33.1) | 3 (3.2) | 47 (41.6) |
| Help with personal care (e.g. eating, showering, dressing) | 20 (37.7) | 42 (42.4) | 55 (56.7) | 50 (43.1) | 22 (21.6) | 60 (43.2) | 22 (23.4) | 57 (50.4) |
| Help with property maintenance (e.g. as mowing lawns, cleaning gutters etc.) | 23 (43.4) | 31 (31.3) | 27 (27.8) | 71 (61.2) | 19 (18.6) | 48 (34.5) | 3 (3.2) | 58 (51.3) |
| Pay for medical bills (e.g., tests, doctor fees, hospital bills etc.) | 22 (41.5) | 47 (47.5) | 29 (29.9) | 27 (23.3) | 4 (3.9) | 75 (54.0) | 74 (78.7) | 43 (38.1) |
| Pay for medicines (e.g., prescription and over the counter medicine) | 31 (58.5) | 66 (66.7) | 26 (26.8) | 36 (31.0) | 11 (10.8) | 92 (66.2) | 72 (76.6) | 47 (41.6) |
| Pay for non-medical bills (e.g., electricity, water, insurance, phone, internet etc.) | 25 (47.2) | 38 (38.4) | 21 (21.6) | 33 (28.4) | 6 (5.9) | 62 (44.6) | 52 (55.3) | 37 (32.7) |
| Picking up medications | 39 (73.6) | 82 (82.8) | 71 (73.2) | 95 (81.9) | 62 (60.8) | 81 (58.3) | 49 (52.1) | 93 (82.3) |
| Provide administrative support (e.g. filling out forms, sending emails or making phone calls on their behalf) | 28 (52.8) | 59 (59.6) | 34 (35.1) | 66 (56.9) | 63 (61.8) | 81 (58.3) | 19 (20.2) | 64 (56.6) |
| Provide emotional support (e.g. listening and talking to them) | 40 (75.5) | 72 (72.7) | 72 (74.2) | 91 (78.4) | 71 (69.6) | 101 (72.7) | 83 (88.3) | 89 (78.8) |
| Provide other financial support | 21 (39.6) | 59 (59.6) | 12 (12.4) | 34 (29.3) | 15 (14.7) | 64 (46.0) | 21 (22.3) | 42 (37.2) |
| Schedule medical appointments | 29 (54.7) | 79 (79.8) | 56 (57.7) | 74 (63.8) | 45 (44.1) | 86 (61.9) | 29 (30.9) | 88 (77.9) |
| Take them to the hospital during emergencies | 35 (66.0) | 67 (67.7) | 49 (50.5) | 76 (65.5) | 54 (52.9) | 82 (59.0) | 18 (19.1) | 70 (61.9) |
| Talking to healthcare professionals | 35 (66.0) | 43 (43.4) | 77 (79.4) | 81 (69.8) | 69 (67.6) | 80 (57.6) | 48 (51.1) | 89 (78.8) |
| Other | 1 (1.9) | 1 (1.0) | 0 (0.0) | 1 (0.9) | 3 (2.9) | 1 (0.7) | 0 (0.0) | 0 (0.0) |
AUS Australia, DEU Germany, EGY Egypt, GBR United Kingdom, ITA Italy, MEX Mexico, TWN Taiwan, USA United States of America
Regarding severity of condition, 25.1% (n = 347) reported advanced (Stages 4–5) CKD, 41.8% (n = 578) reported they were dialysis-dependent, and 11.4% (n = 157) reported they had received a kidney transplant. Of the dialysis-dependent patients, 27.0% (n = 156) were receiving peritoneal dialysis, with considerably more patients receiving haemodialysis (n = 422; 73.0%), and dialysis was most often received in the hospital or clinic (n = 505; 87.4%) versus home. A proportion of patients did not know their CKD stage (Figure S1), suggesting mixed understanding of the severity of their condition. Approximately 21.0% of caregivers reported that they support patients in stages 1–2 of CKD (n = 173), with twice the proportion of caregivers caring for patients in stages 3a and 3b (n = 327, 40.2%). Over one-third of caregivers (n = 284; 34.9%) reported caring for patients with advanced disease (stages 4–5) to the best of their knowledge, and a remainder of caregivers did not know the CKD stage of the patient they were caring for (n = 29; 3.6%; Figure S1). In addition to CKD stage, caregivers reported whether the patient was receiving kidney replacement therapy, with over half (n = 481; 59.2%) of the total cohort reported caring for dialysis-dependent patients and a smaller proportion of respondents reported caring for patients who had undergone kidney transplant (n = 99; 12.2%). There was therefore a disparity between these disease characteristics due to self-reporting issues.
Health-Related Quality of Life in Patients with CKD
Patients with CKD had lower EQ-5D-5L index scores compared to matched general population cohorts across all countries (Fig. 1), with EQ-5D-5L index scores ranging from 0.57 to 0.89 in cohorts of patients with CKD versus 0.93–0.96 in matched populations. Linear regression analyses showed significantly lower EQ-5D-5L index scores in patients compared to the general population (p < 0.001 for all countries except Taiwan, p = 0.004; Table S6). Univariate analyses of key demographic covariates (age, gender, employment status or area of residence) did not consistently demonstrate statistically significant effects in all countries; however, patients in all cohorts were observed to have significantly higher index scores if they were employed versus those who were unemployed. Patients were more likely to report problems across all EQ-5D domains versus the general population (Fig. 2), most frequently reporting problems with pain/discomfort, anxiety/depression and carrying out usual activities. Patients in nearly all countries reported statistically significant effects across all domains (all p < 0.001) that were indicative of reduced QoL, with the exception of the Taiwan cohorts (Table S7).
Fig. 1.
Histograms of EQ-5D-5L index scores for patients versus matched general population (top) and for dialysis-dependent versus non dialysis-dependent patients (bottom). Higher numbers indicate better health-related quality of life. AUS Australia, DEU Germany, EGY Egypt, GBR United Kingdom, MEX Mexico, TWN Taiwan, USA United States of America
Fig. 2.
Problems reported across EQ-5D-5L domains by patients versus matched general population cohorts (top) and patients who are receiving dialysis versus those who are not (bottom). EQ-5D domains are measured by 5 categories: anxiety/depression, mobility, pain/discomfort, selfcare and usual activities in A patients versus the matched general population and B dialysis-dependent patients versus non dialysis-dependent patients. AUS Australia, DEU Germany, EGY Egypt, GBR United Kingdom, MEX Mexico, TWN Taiwan, USA United States of America
When considering EQ-5D-5L index scores reported by patients receiving of dialysis versus those who did not, mean index scores ranged from 0.51 to 0.79 in the dialysis-dependent subgroups and from 0.65 to 0.93 in the non-dialysis-dependent subgroups (Fig. 1; Table 5). Linear regression analyses showed statistical associations in EQ-5D-5L index scores with the requirement for dialysis in the Egypt (p = 0.017), Mexico (p = 0.001), Taiwan (p < 0.001) and UK (p = 0.031) cohorts (Table S8). Considering the influence of key covariates, employment was observed to have a statistically significant association with improved index scores in all subgroup analyses. Dialysis-dependent subgroups often reported more problems across domains than non-dialysis-dependent individuals (Fig. 2), with statistically associations most observed in relation to problems with self-care (six countries; Table S9). EQ-5D-5L index scores in those with advanced CKD (stages 4–5) were typically lower than those with milder CKD (stages 1–3), with notably lower HRQoL observed in the Egypt cohort (Figure S2). Similarly, dialysis-dependent patients generally reported lower EQ VAS scores than non-dialysis-dependent patients, indicating worse overall self-reported health, with incremental mean values for dialysis-dependent patients ranging from 18.2 lower (Taiwan, 64.3 vs. 82.5) to 4.2 higher (USA, 61.0 vs. 56.8) than for non-dialysis-dependent patients (Table S10).
Table 5.
Summary of health-related quality of life outcomes in dialysis-dependent subgroups
| Outcome | AUS | DEU | EGY | GBR | ITA | MEX | TWN | USA |
|---|---|---|---|---|---|---|---|---|
| Patients with CKD | ||||||||
| EQ-5D-5L index | ||||||||
| DD, n | 105 | 116 | 98 | 98 | NR | 91 | 161 | 135 |
| Mean (SD) | 0.82 (0.19) | 0.75 (0.26) | 0.65 (0.24) | 0.68 (0.27) | NR | 0.74 (0.18) | 0.93 (0.12) | 0.65 (0.27) |
| Median (range) | 0.89 (0.27, 0.88) | 0.84 (− 0.10, 1.00) | 0.71 (− 0.48, 1.00) | 0.72 (− 0.18, 1.00) | NR | 0.78 (0.08, 1.00) | 1.00 (0.17, 0.93) | 0.70 (− 0.12, 1.00) |
| NDD, n | 45 | 85 | 124 | 114 | NR | 117 | 29 | 64 |
| Mean (SD) | 0.79 (0.09) | 0.72 (0.27) | 0.51 (0.35) | 0.60 (0.25) | NR | 0.66 (0.21) | 0.66 (0.20) | 0.59 (0.27) |
| Median (range) | 0.81 (0.51, 0.88) | 0.80 (− 0.08, 1.00) | 0.59 (− 0.57, 1.00) | 0.67 (− 0.14, 1.00) | NR | 0.72 (0.08, 1.00) | 0.74 (0.10, 0.93) | 0.61 (− 0.11, 1.00) |
| Caregivers for patients with CKD | ||||||||
| EQ-5D-5L index | ||||||||
| DD, n | 19 | 35 | 45 | 38 | NR | 48 | 49 | 21 |
| Mean (SD) | 0.83 (0.22) | 0.88 (0.13) | 0.79 (0.21) | 0.75 (0.24) | NR | 0.85 (0.14) | 0.94 (0.07) | 0.77 (0.27) |
| Median (range) | 0.89 (0.23, 1.00) | 0.91 (0.46, 1.00) | 0.84 (0.32, 1.00) | 0.82 (− 0.02, 1.00) | NR | 0.87 (0.24, 1.00) | 0.94 (0.78, 1.00) | 0.88 (0.00, 1.00) |
| NDD, n | 34 | 64 | 52 | 78 | NR | 91 | 45 | 92 |
| Mean (SD) | 0.92 (0.16) | 0.91 (0.11) | 0.68 (0.27) | 0.83 (0.18) | NR | 0.76 (0.20) | 0.93 (0.08) | 0.82 (0.21) |
| Median (range) | 0.98 (0.15, 1.00) | 0.97 (0.53, 1.00) | 0.71 (0.27, 1.00) | 0.86 (0.18, 1.00) | NR | 0.80 (0.17, 1.00) | 0.94 (0.66, 1.00) | 0.88 (0.10, 1.00) |
| CarerQol-7D | ||||||||
| DD, n | 34 | 35 | 124 | 78 | 41 | 90 | 45 | 92 |
| Mean (SD) | 72.2 (17.1) | 76.0 (17.4) | 76.3 (21.4) | 66.1 (19.4) | 68.2 (22.3) | 69.6 (19.1) | 77.7 (9.0) | 62.4 (17.6) |
| Median (range) | 74.3 (41.9, 97.0) | 81.8 (18.5, 100.0) | 82.3 (18.2, 100.0) | 68.2 (18.2, 100.0) | 76.8 (11.5, 97.1) | 75.7 (18.2, 95.9) | 81.3 (55.6, 95.6) | 67.4 (13.8, 92.0) |
| NDD, n | 19 | 64 | 98 | 38 | 88 | 48 | 49 | 21 |
| Mean (SD) | 72.8 (18.9) | 78.2 (15.1) | 83.4 (18.2) | 70.8 (19.7) | 79.6 (14.3) | 72.4 (17.2) | 79.8 (8.0) | 65.4 (16.3) |
| Median (range) | 72.5 (14.3, 100.1) | 81.9 (34.4, 97.0) | 91.9 (18.2, 100.0) | 76.8 (17.0, 95.9) | 81.9 (16.9, 100.0) | 72.1 (28.5, 100.0) | 81.6 (63.6, 95.9) | 71.1 (26.3, 85.2) |
AUS Australia, CKD chronic kidney disease, DD dialysis-dependent, DEU Germany, EGY Egypt, GBR United Kingdom, ITA Italy, MEX Mexico, NDD non-dialysis-dependent, TWN Taiwan, SD standard deviation, USA United States of America
Quality of Life in Caregivers of Patients with CKD
EQ-5D-5L
Similarly to patients with CKD, caregivers consistently experienced reduced EQ-5D-5L index scores versus matched general populations cohorts (Fig. 3), with EQ-5D-5L index scores ranging from 0.73 to 0.93 in cohorts of caregivers versus 0.93–0.97 in matched general populations. Linear regression analysis highlighted statistically significant reductions in EQ-5D-5L index scores for caregivers versus the general population in all countries (Australia, p = 0.002; others, p < 0.001; Table S11), except for the Taiwanese cohort, in which caregivers and the general population had equivalent index scores (0.93, p = 0.446). Analysis of other covariates showed no statistically significant differences between demographics subgroups based on age, gender, employment status or area of residence. Caregivers often reported problems across all EQ-5D domains (Fig. 4), most consistently reporting anxiety/depression and pain/discomfort, with statistically significant effects observed across all domains in all countries, except for Taiwan (Table S12).
Fig. 3.
EQ-5D-5L index scores for caregivers of patients with CKD compared with general population (top) and caregivers of dialysis-dependent patients compared to non-dialysis-dependent patients (bottom). Higher numbers indicate better health-related quality of life. AUS Australia, DEU Germany, EGY Egypt, GBR United Kingdom, MEX Mexico, TWN Taiwan, USA United States of America
Fig. 4.
Problems reported across EQ-5D-5L domains by caregivers versus matched general population cohorts. EQ-5D domains are measured by 5 categories: anxiety/depression, mobility, pain/discomfort, selfcare and usual activities in caregivers versus the matched general population. AUS Australia, DEU Germany, EGY Egypt, GBR United Kingdom, MEX Mexico, TWN Taiwan, USA United States of America
Those who cared for dialysis-dependent patients did not consistently experience a worse overall EQ-5D-5L index scores than those caring for patients who were not in receipt of dialysis (Fig. 3; Table 5). However, regarding specific domains, caregivers of dialysis-dependent patients frequently reported challenges with anxiety/depression, self-care and usual activities, whereas issues with mobility and pain/discomfort were less consistent (Fig. 4). Caregivers of dialysis-dependent patients did not consistently report lower EQ VAS scores than caregivers of non-dialysis-dependent patients (Table S10). There was no consistent direction of any associations that were of statistical significance, based on dialysis status, age, gender, employment status or area of residence (Table S13). In addition, caregivers of patients with earlier stages of CKD had higher index scores, but, in most countries, they were generally comparable, except for Egypt and Mexico (Figure S2).
CarerQol-7D
Mean CarerQol-7D index estimates ranged between 63.0 and 79.6 across the caregiver populations (Table 4), with no consistent statistical associations across demographic subgroups (age, gender, employment status or area of residence) with univariate analysis (Table S14). Caregivers frequently reported challenges related to insufficient support, balancing caregiving with daily activities, and its impact on their mental health (Fig. 5). Caregivers of dialysis-dependent patients reported scores consistently lower than caregivers for non-dialysis-dependent patients (Table 5), but only the Egypt (p = 0.044) and Italy (p = 0.004) cohorts were statistically significant (Table S14). Significant differences with regards to “support with carrying out my care tasks, when I need it” were estimated in four countries (Italy, p = 0.004; Taiwan, p = 0.017; UK, p = 0.033; USA, p = 0.005), with higher estimates predominately in the dialysis-dependent subgroups (Table S15).
Table 4.
Summary of health-related quality of life outcomes in patients and caregivers versus the general population
| Outcome | AUS | DEU | EGY | GBR | ITA | MEX | TWN | USA |
|---|---|---|---|---|---|---|---|---|
| Patients with CKD | ||||||||
| EQ-5D-5L index | ||||||||
| Patients, n | 150 | 201 | 222 | 212 | NR | 208 | 190 | 199 |
| Mean (SD) | 0.81 (0.17) | 0.74 (0.26) | 0.57 (0.32) | 0.64 (0.27) | NR | 0.70 (0.20) | 0.89 (0.17) | 0.63 (0.27) |
| Median (range) | 0.86 (0.27, 1.00) | 0.82 (− 0.10, 1.00) | 0.71 (− 0.57, 1.00) | 0.70 (− 0.18, 1.00) | NR | 0.74 (0.08, 1.00) | 1.00 (0.10, 1.00) | 0.68 (− 0.12, 1.00) |
| Gen. popn., n | 150 | 201 | 221 | 212 | NR | 204 | 190 | 199 |
| Mean (SD) | 0.96 (0.06) | 0.96 (0.06) | 0.93 (0.14) | 0.95 (0.08) | NR | 0.94 (0.07) | 0.93 (0.11) | 0.95 (0.08) |
| Median (range) | 0.97 (0.44, 1.00) | 1.00 (0.55, 1.00) | 1.00 (0.11, 1.00) | 1.00 (0.65, 1.00) | NR | 0.95 (0.00, 1.00) | 0.97 (0.20, 1.00) | 1.00 (0.52, 1.00) |
| Caregivers for patients with CKD | ||||||||
| EQ-5D-5L index | ||||||||
| Caregivers, n | 53 | 99 | 97 | 116 | NR | 139 | 94 | 113 |
| Mean (SD) | 0.89 (0.19) | 0.90 (0.12) | 0.73 (0.25) | 0.81 (0.21) | NR | 0.79 (0.18) | 0.93 (0.07) | 0.81 (0.22) |
| Median (range) | 0.94 (0.15, 0.89) | 0.94 (0.46, 1.00) | 0.76 (0.27, 1.00) | 0.86 (− 0.02, 1.00) | NR | 0.84 (0.17, 1.00) | 0.94 (0.66, 1.00) | 0.88 (0.00, 1.00) |
| Gen. popn., n | 53 | 99 | 97 | 116 | NR | 138 | 94 | 113 |
| Mean (SD) | 0.97 (0.03) | 0.96 (0.08) | 0.93 (0.19) | 0.94 (0.09) | NR | 0.94 (0.07) | 0.93 (0.09) | 0.94 (0.11) |
| Median (range) | 0.97 (0.89, 1.00) | 1.00 (0.55, 1.00) | 1.00 (− 0.55, 1.00) | 1.00 (0.47, 1.00) | NR | 0.95 (0.56, 1.00) | 0.94 (0.53, 1.00) | 1.00 (0.45, 1.00) |
| CarerQol-7D (caregivers only) | ||||||||
| Caregivers, n | 53 | 99 | 97 | 116 | 102 | 138 | 94 | 113 |
| Mean (SD) | 72.4 (17.6) | 76.8 (16.6) | 79.6 (20.2) | 67.6 (19.5) | 76.8 (17.2) | 70.6 (18.4) | 78.8 (8.5) | 63.0 (17.3) |
| Median (range) | 72.9 (14.3, 100.1) | 81.9 (18.5, 100.0) | 91.1 (18.2, 100.0) | 71.1 (17.0, 100.0) | 81.1 (11.5, 100.0) | 75.4 (18.2, 100.0) | 81.4 (55.6, 95.9) | 67.7 (13.8, 92.0) |
AUS Australia, CKD chronic kidney disease, DEU Germany, EGY Egypt, GBR United Kingdom, ITA Italy, MEX Mexico, SD standard deviation, TWN Taiwan, USA United States of America
Fig. 5.
CarerQol-7D domains in caregivers of dialysis-dependent patients versus caregivers of non-dialysis-dependent patients. AUS Australia, DEU Germany, EGY Egypt, GBR United Kingdom, MEX Mexico, TWN Taiwan, USA United States of America. 1 For the domains ‘Fulfilment from carrying out my care tasks’ and ‘Support with carrying out my care tasks when I need it’, light blue bars correspond to ‘Fulfilment’ and ‘Support’, respectively, with dark blue columns corresponding to ‘No fulfilment’ and ‘No support’, respectively
Discussion
CKD is a major global healthcare challenge with a substantial impact on healthcare systems, patients and their informal caregivers. This study has characterised the substantial global QoL burden associated with CKD, with QoL significantly reduced in patients and informal caregivers compared to matched members of the general population. Our study demonstrates that patients with CKD often report experiencing pain, anxiety and depression, which worsens as disease progresses towards dialysis. The findings of this study align with systematic reviews that show HRQoL declines as CKD progresses, with greatest deterioration in dialysis-dependent patients [1, 2]. It should be noted that study outcomes were adjusted to population norms for each national general population which are subject to a significant degree of variation [28, 29], and any direct comparisons should be considered in this context. In addition, caregivers across the CKD cohort (from stages 1–5) reported reduced EQ-5D index scores compared to matched general population controls, with the reduction remaining largely consistent through to dialysis. As far as the authors are aware, this is the first study to provide detailed multinational analysis of the QoL burden on unpaid caregivers for those with CKD across all stages, addressing a key knowledge gap for healthcare and policy decision-makers.
This study highlighted the considerable burden of caregivers of patients with CKD according to CarerQol-7D (country cohorts ranging 63.0–79.6), and comparison with published data show that scores were comparable or lower than caregivers of patients with many other major and/or chronic diseases, such as juvenile arthritis (82.7) [30], dementia (77.6) [26], degenerative cervical myelopathy (64.1) [31], sickle cell disease (80.7) [32] and breast cancer (92.4) [33]. The increased burden caregivers of patients with CKD experience may be explained in part due to the need to support and attend frequent hospital visits, particularly as CKD progresses to advanced stages [3]. Patients with earlier stages of CKD may often be asymptomatic, but in this study caregivers of those with milder CKD frequently reported impaired QoL, and it should be noted that the presence of comorbidities could have influenced outcomes presented here. A positive correlation between the incidence of comorbidities and increased care burden has previously been reported in patients with CKD and caregivers [34–36]. Furthermore, it is notable that a majority of patients included across cohorts were male (61.8%), while the inverse was true for caregivers (41.3%). Women have reportedly worse HRQoL on kidney replacement therapy than men [37, 38], and worse QoL than men if caregiving for patients with CKD [39]. While the overall study samples may be comparable to known prevalence of CKD [27] and caregivers [40], study outcomes should be considered in this context.
When considering patients on dialysis or with advanced CKD, smaller disparities in EQ-5D-5L index scores were generally observed in Australia, the USA and European countries versus those at an early stage of disease, with greater disparities in Egypt, Mexico and Taiwan. There were less pronounced differences in observed QoL between caregivers of people with CKD who are dialysis-dependent versus non-dialysis-dependent than for patients. Nevertheless, we noted numerically lower CarerQol-7D scores reported by caregivers of dialysis-dependent patients in all countries, with a less consistent pattern demonstrated according to EQ-5D-5L and EQ VAS. These observations are not entirely in line with previous studies that generally showed worsened QoL for caregivers of patients on dialysis [11, 14, 39]. This observation may be driven by a number of factors, such as reluctance to report negative outcomes or treatment modalities. Peritoneal dialysis has been shown to be associated with higher patient QoL than haemodialysis in patients [41], so treatment modality differences may partly influence the reported HRQoL of caregivers in different countries. However, given limitations of sample size and scope of the present study, this association should be explored in future studies, particularly in countries with higher prevalence of peritoneal dialysis such as Mexico [42].
The authors identified that analysis of the Taiwanese patient and caregiver cohorts demonstrated a much smaller proportional reduction of scores versus other cohorts in this study across all measured instruments, though dialysis-dependent patients did report worsened HRQoL in line with other countries, particularly according to EQ VAS responses. This may be explained as a result of multiple factors. As the study is multinational, the responses are likely to have been influenced to a degree by cultural bias, as has been seen previously in questionnaires such as the 36-Item Short Form Survey (SF-36) [43]. The cultural reluctance of participants from Taiwan to share trauma has been reported previously [44, 45], suggesting that the reported burden may be underestimated. This, coupled with early detection of disease and high quality of care [46], could be contributing factors to the observed responses. Additionally, the enrolled dialysis population in Taiwan was considerably smaller versus other countries; when considering the whole patient population, the low number of dialysis patients may have disproportionately skewed the data versus other countries with higher proportions of patients on dialysis. However, no enrolled patients had received a kidney transplant, which reflects the low kidney transplantation rates in Taiwan [47]. However, HRQoL has been seen to recover to that of early CKD once patients were post-kidney transplant [1, 2]. Therefore, in the analysis of participants from Taiwan, this should have the effect of lowering the QoL compared with countries with higher kidney transplant rates. Further research should explore the factors contributing to higher QoL in caregivers in Taiwan, and the social, economic and cultural factors that may drive differences in outcomes between nations.
While this study has a number of strengths, as a multinational study that enrolled participants at all stages of CKD, including a sufficient sample of patients who are receiving or have received kidney replacement therapy, it is important to note key limitations of the PaCE CKD study to provide context to the study outcomes. While purposive sampling methods were used, the samples generated may not have been truly representative of the CKD populations for each country. A recent study reported a weaker association with anxiety/depression in patients with mild to moderate CKD, potentially reflecting the inclusion of participants with more advanced CKD in this study [48], highlighting the importance of contextualising patient HRQoL or caregiver QoL with disease stage and other key population characteristics. Furthermore, while detailed descriptions or definitions of dialysis modalities or CKD severity categories were provided within questionnaires, accurate responses were contingent upon a sufficient understanding of the technical classifications of the disease and treatment; this is particularly relevant when considering outcomes in patients dependent on self-reported CKD stage. Nevertheless, all survey outcomes have been validated by local clinical experts.
Patients’ comorbidities, such as coronary heart disease, were not accounted for in this study. The observed impairment in HRQoL for patients and the impact of caregivers QoL may be influenced by the comparatively high rate of comorbidities in patients with CKD and the overlap in high care requirements [4–6]. Previous studies have identified the presence of comorbidities such as diabetes, cardiovascular diseases and anaemia as causes of reduced HRQoL in patients with CKD [49–51]. Further studies have also reported that comorbidities have an adverse effect on QoL in people with CKD and in people caring for those with CKD and on dialysis [34, 50, 52].
The conclusions that may be drawn from CarerQol-7D study data reported here are limited to comparisons with cohorts from published studies and are not matched to a general population cohort. Nonetheless, the reduction observed in CarerQol-7D scores in caregivers for patients with CKD may be considerable, between 63.0 and 79.6 out of a possible 100. It is worth noting that, although the trends seen here mirror those reported by national studies, the ability to compare data on QoL of caregivers between published studies is limited in part by the variance of tools used to collect the data. Tools include the Adult Carer Quality of Life Questionnaire (AC-QoL), Short Form 6D (SF-6D) and SF-36 questionnaire, Burden Scale for Family Caregivers—short version (BSFC-s), Carer Experience Scale (CES), Novak & Guest Caregiver Burden Inventory (CBI), Zarit questionnaire for caring burden and WHOQOL-BREF quality of life questionnaire [14, 34, 53, 54]. A more uniform approach to surveying caregiver experiences could improve comparability of studies across countries and disease populations.
Patient-reported outcome measures form the basis of the data collected here, with the EQ-5D-5L index indicating a person’s preference for a particular health state, such as a lower preference for dialysis treatment; there is a potential for bias in the results due to individual response style and personality of the respondents. Additionally, differences in responses seen in each national cohort are common due to variation employment levels, educational status, income, healthcare systems and availability, as well as cultural norms affecting responses [37]. Finally, data from low-income countries were not provided in this analysis, which could have provided valuable insight [55], as low-income countries have a reduced ability to deliver consistent kidney care and the caregiver QoL burden is reportedly higher in these counties [34, 56, 57].
Conclusion
This is the first study that characterises the QoL burden of CKD in patients and caregivers on a multinational scale and demonstrates that there is a global QoL burden for patients with CKD compared with the matched general population. By understanding the struggles of day-to-day life for patients and informal caregivers from a QoL perspective, decision-makers could create evidence-based policies that put the patient and informal caregivers at the centre and aim to target support to the areas of greatest need. Evidence-based interventions should aim to reduce CKD progression to prevent the greater burden on QoL that is evident among patients with kidney failure, particularly when dialysis-dependent. There is a need to support caregivers with their management of patients’ disease and to implement interventional programs to support patients from early stages of CKD through to advanced disease and/or dialysis, but also to support their caregivers to allow them to maintain QoL.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
The authors thank all participants of the PaCE CKD study. The authors would also like to thank Janani Rangaswami for her valuable feedback as a key clinical expert during the early phase of the study. In addition, the authors thank Declan Monro, Nelson-Odin Jones and Fran Maron of Community and Patient Preference Research (CaPPRe) for their technical assistance.
Medical Writing/Editorial Assistance
Medical writing support was provided by Peter Gabb and Rowena Jenkins of Health Economics and Outcomes Research Ltd., which was funded by AstraZeneca in accordance with Good Publication Practice (GPP3) guidelines (http://www.ismpp.org/gpp3).
Author Contributions
Simon Fifer, Thames Kularatne, Juan Jose Garcia Sanchez, and Surendra Pentakota conceptualised and designed the study. Simon Fifer and Thames Kularatne were responsible for data analysis. Ricardo Correa-Rotter, Mai-Szu Wu, Richard Hull, Ciro Esposito, Helmut Reichel, Steven Chadban, Juan Jose Garcia Sanchez, Surendra Pentakota, Thames Kularatne, Simon Fifer, and Hesham M. Elsayed contributed to interpretation of the results, preparation and review of the manuscript, and approval of the final manuscript for publication.
Funding
This work was supported by AstraZeneca who provided support for data collection, analysis, and medical writing for this study. AstraZeneca also funded the journal’s Rapid Service and Open Access fees.
Data Availability
All data generated or analysed during this study are included in this published article/as supplementary information files.
Declarations
Conflict of interest
Ricardo Correa Rotter has received honoraria as consultant from AstraZeneca, Boehringer Ingelheim, Bayer, Chinook, AbbVie, Novo Nordisk and Lilly, and research support from AstraZeneca, Boehringer Ingelheim, Roche, Lilly, Chinook and Novo Nordisk. He has received honoraria/speaking fees from AstraZeneca, Boehringer Ingelheim, Novo Nordisk and Amgen. Mai-Szu Wu has received support from AstraZeneca for their contributions to this work, and payment/honoraria for lectures, presentations, and manuscript writing. He has received payment/honoraria from Baxter, Bayer, GSK, Novartis, Pfizer and Sanofi for lectures and presentations and honoraria for advisory board participation from AstraZeneca, Bayer, GSK, Novartis and Sanofi. Richard Hull has received speaking fees from AstraZeneca, Boehringer Ingelheim, Bayer and Thornton Ross Stada Group, and honoraria for advisory board participation from Novartis, Travere Therapeutics and Vifor Fresenius. Ciro Esposito has received payment/honoraria from AstraZeneca, Otsuka, Travere Therapeutics and Vifor Fresenius for speaker fees and advisory board. Helmut Reichel has no conflicts to disclose. Steven Chadban has received payment/honoraria from AstraZeneca, Boehringer Ingelheim, and Bayer for speaker fees and advisory boards. Juan Jose Garcia Sanchez and Surendra Pentakota are employees of AstraZeneca. Simon Fifer and Thames Kularatne are employees of CaPPRe PTY Ltd. which received fees from AstraZeneca to conduct this study. CaPPRe has consulted to AbbVie, Amgen, Bristol Myers Squibb, Celgene, CSL Behring, Edwards LifeSciences, Gilead, GSK, Ipsen, Janssen, Medtronic, Novo Nordisk, Roche, Sanofi, Seqirus, Shire, UCB, and Vertex outside of the submitted work. Hesham M. Elsayed has received payment/honoraria from AstraZeneca, Boehringer Ingelheim, Bayer, and GSK for symposia and is Emeritus Professor of Nephrology, ESNT President Elect, and Academic Director of RRT WKA Fellowship.
Ethical Approval
This study was reviewed by an international Institutional Review Board, Pearl IRB, and was granted an exemption from a full review due to its low/negligible risk nature in accordance with FDA 21 56.104 and 45CFR46.104. (Protocol #21-CAPP-102). All participants provided electronic informed consent.
Footnotes
Prior Presentation: Interim analyses from this study have been presented at the following conferences: the 60th European Renal Association (ERA) Congress (15-18 June, 2023; Milan, Italy; poster number 3990), the American Society of Nephrology (ASN) Kidney Week 2023 (1-5 November; Philadelphia, PA, USA; poster numbers TH-PO1048 AND TH-PO1049), and the 61st ERA Congress, (23-26 May, 2024; Stockholm, Sweden; poster number PCR153 AND PCR208).
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Supplementary Materials
Data Availability Statement
All data generated or analysed during this study are included in this published article/as supplementary information files.