Symptom burden and health-related quality of life in chronic kidney disease: A global systematic review and meta-analysis.

BACKGROUND: The importance of patient-reported outcome measurement in chronic kidney disease (CKD) populations has been established. However, there remains a lack of research that has synthesised data around CKD-specific symptom and health-related quality of life (HRQOL) burden globally, to inform focused measurement of the most relevant patient-important information in a way that minimises patient burden. The aim of this review was to synthesise symptom prevalence/severity and HRQOL data across the following CKD clinical groups globally: (1) stage 1-5 and not on renal replacement therapy (RRT), (2) receiving dialysis, or (3) in receipt of a kidney transplant. METHODS AND
FINDINGS: MEDLINE, PsycINFO, and CINAHL were searched for English-language cross-sectional/longitudinal studies reporting prevalence and/or severity of symptoms and/or HRQOL in CKD, published between January 2000 and September 2021, including adult patients with CKD, and measuring symptom prevalence/severity and/or HRQOL using a patient-reported outcome measure (PROM). Random effects meta-analyses were used to pool data, stratified by CKD group: not on RRT, receiving dialysis, or in receipt of a kidney transplant. Methodological quality of included studies was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Studies Reporting Prevalence Data, and an exploration of publication bias performed. The search identified 1,529 studies, of which 449, with 199,147 participants from 62 countries, were included in the analysis. Studies used 67 different symptom and HRQOL outcome measures, which provided data on 68 reported symptoms. Random effects meta-analyses highlighted the considerable symptom and HRQOL burden associated with CKD, with fatigue particularly prevalent, both in patients not on RRT (14 studies, 4,139 participants: 70%, 95% CI 60%-79%) and those receiving dialysis (21 studies, 2,943 participants: 70%, 95% CI 64%-76%). A number of symptoms were significantly (p < 0.05 after adjustment for multiple testing) less prevalent and/or less severe within the post-transplantation population, which may suggest attribution to CKD (fatigue, depression, itching, poor mobility, poor sleep, and dry mouth). Quality of life was commonly lower in patients on dialysis (36-Item Short Form Health Survey [SF-36] Mental Component Summary [MCS] 45.7 [95% CI 45.5-45.8]; SF-36 Physical Component Summary [PCS] 35.5 [95% CI 35.3-35.6]; 91 studies, 32,105 participants for MCS and PCS) than in other CKD populations (patients not on RRT: SF-36 MCS 66.6 [95% CI 66.5-66.6], p = 0.002; PCS 66.3 [95% CI 66.2-66.4], p = 0.002; 39 studies, 24,600 participants; transplant: MCS 50.0 [95% CI 49.9-50.1], p = 0.002; PCS 48.0 [95% CI 47.9-48.1], p = 0.002; 39 studies, 9,664 participants). Limitations of the analysis are the relatively few studies contributing to symptom severity estimates and inconsistent use of PROMs (different measures and time points) across the included literature, which hindered interpretation.
CONCLUSIONS: The main findings highlight the considerable symptom and HRQOL burden associated with CKD. The synthesis provides a detailed overview of the symptom/HRQOL profile across clinical groups, which may support healthcare professionals when discussing, measuring, and managing the potential treatment burden associated with CKD. PROTOCOL REGISTRATION: PROSPERO CRD42020164737.

Introduction

Chronic kidney disease (CKD) has an estimated global prevalence of 9.1% (700 million people) and is associated with a major increased risk of early death for those affected, with 4.6% of deaths annually attributable to impaired kidney function [1]. In addition, CKD represents a substantial health economic burden, with advancement from stage 3 to 4/5 associated with a 1.3-to 4.2-fold increase in costs, and progression to end-stage renal disease (ESRD) estimated to cost $20,000–$100,000 per patient per year [2].

Patients with CKD experience an increased risk of hospitalisation and mortality [3], and reduced health-related quality of life (HRQOL), which is independently associated with cardiovascular disease events and death [4-6]. Patient-reported outcomes, including HRQOL and symptoms, are often identified by patients with CKD as more important to them than clinical outcomes such as survival [7].

There has been an increasing move towards models of remote and virtual care for patients with CKD [8], accelerated by the emergence of COVID-19, within which, capture of symptom and HRQOL data are seen as key adjuncts to support optimal care [9-11]. However, there remains a lack of research that has synthesised global data on CKD-specific symptom and HRQOL burden to inform collection of the most relevant patient-important data in a way that minimises patient burden.

The aim of this study was to (1) produce a comprehensive and consolidated global synthesis of symptom prevalence/severity and HRQOL across CKD treatment groups, (2) explore which symptom/HRQOL domains are modified by CKD and may be attributable to the disease, and (3) determine which patient-reported outcome measures (PROMs) are currently available to capture symptom prevalence/severity and HRQOL in CKD.

Methods

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed (S1 Appendix), and the study protocol was registered with PROSPERO (CRD42020164737) (S9 Appendix). The protocol and analysis methods were developed prospectively.

Search strategy and data sources

The following databases were searched from 1 January 2000 until 6 February 2020 (searches updated on 1 September 2021): Ovid MEDLINE, Ovid PsycINFO, and EBSCO CINAHL (for the full search strategy, see S2 Appendix). Two authors (2 of BRF, SD, and DK) independently assessed selected articles for eligibility at the title/abstract and full-text stages, with disagreements resolved through discussion.

Inclusion and exclusion criteria

Studies were included if they met the following criteria: (1) published in or after January 2000; (2) written in English; (3) included adult (≥18 years) patients with CKD at stage 1–5 not receiving renal replacement therapy (RRT), those receiving dialysis, or those in receipt of a kidney transplant; (4) reported prevalence and/or severity of symptoms and/or HRQOL measured using a PROM; and (5) used a cross-sectional or longitudinal study design. Studies were excluded if they (1) were editorials, conference abstracts, reports of qualitative findings, or systematic reviews; (2) solely reported symptoms or HRQOL that were not self-reported by patients (e.g., clinician-reported); or (3) were not reported in English.

Data extraction

The following data were independently extracted into a pre-piloted spreadsheet by 2 authors (2 of BRF, SD, and DK) and disagreements resolved through discussion: study information (year conducted, country of origin, single/multi-centre, cross-sectional/longitudinal design), study population (inclusion/exclusion criteria, CKD stage, estimated glomerular filtration rate [eGFR], co-morbidity indices, demographics), and study outcomes (measures used, symptom prevalence and severity, HRQOL PROM scores). Where possible, we also attempted to extract data from the included studies that were collected from contemporaneous (ideally matched) non-CKD control populations.

Quality appraisal

Methodological quality of included studies was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Studies Reporting Prevalence Data [12]. Studies were assessed for adequacy of sampling (frame and method), sample size and description, data analysis, and comparability of outcomes across studies. Two authors independently conducted the appraisal (BRF and SD), and disagreements were resolved through discussion, or by a third reviewer (DK) where required.

Data analysis

We followed established guidelines for systematic reviews of observational epidemiological studies reporting prevalence with a focus on estimating the global burden of disease [12]. As outlined in the protocol, prevalence/severity data were pooled using either a random or fixed effects model depending on the heterogeneity of the included studies. Heterogeneity was determined using Cochran’s Q test at a significance level of 0.10. Heterogeneity was quantified using the I2 statistic (acceptable heterogeneity defined as I2 < 70%) [13]. All analyses had high heterogeneity; therefore, a random effects model was used. Subgroup analysis was performed based on the stage of CKD (categorised as not on RRT, on dialysis, or in receipt of a kidney transplant), if there were 3 or more studies within a subgroup. Publication bias was assessed where meta-analyses included 10 or more studies using Egger’s test for funnel plot asymmetry, with a significance level of p < 0.05 [14]. Using Stata, the metaprop (meta-analysis of binomial data) command was used to summarise prevalence data, and the metan command was used to summarise severity and HRQOL scores [15,16].

To aid comparison of symptom severity data provided across different outcome measures, all mean severity scores were converted to a 0–100 scale, where a higher score indicates greater severity. For HRQOL scores, 100 represents the best possible quality of life. For example, the Beck Depression Inventory (BDI-II) scale results in a severity score of 0–63; therefore, a score of 43 would convert to 68.3 on a 0–100 scale: 43/63 × 100. Symptom severity scores were also combined using random effects meta-analysis.

A weighted composite summary score for the Kidney Disease Quality of Life (KDQOL) instrument—KDQOL Summary Score (KSS)—was calculated by combining the ‘symptoms and problems’ (12 items), ‘effects of kidney disease’ (8 items), and ‘burden of kidney disease’ (4 items) domains. This summary score was calculated using the recommended method reported by Peipert et al. [17], in which mean scores and standard deviations for each of the 3 domains were combined, weighted by the number of items per domain.

Presentation of symptom prevalence and severity focused on 2 areas: those symptoms that were most prevalent/severe across populations and those symptoms that were significantly different between populations not receiving RRT and those receiving dialysis or transplantation. The latter area is important, as it could provide insight into those symptoms that may be attributable to changes in renal function and may provide potential targets for symptom tracking in CKD.

Exploratory subgroup analysis was used to compare prevalence and score (severity and HRQOL) estimates between groups in meta-analyses (not on RRT versus dialysis, not on RRT versus transplant, and dialysis versus transplant). To account for multiple testing, sharpened false discovery rate (FDR) q-values were computed [18], and adjusted p-values are reported, with a significance level of p < 0.05. All analyses were conducted using Stata (version 15.0).

Role of the funder

The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to all the data in the report and had final responsibility for the decision to submit for publication.

Results

Included studies

Searches identified 1,521 records after deduplication, and an additional 8 were identified through citation searches of included studies. Following title/abstract screening, 631 full-text articles were obtained, with 182 excluded at this stage, leaving 449 studies for inclusion in the final syntheses (Table 1). Information on individual studies included in this review (outcomes used, study design, country of origin, population, and risk of bias) is included in S3 Appendix. The full lists of included and excluded studies are provided in S4 and S5 Appendices, respectively. The PRISMA diagram is shown in Fig 1.

Table 1

Characteristics of the included 449 studies.

Characteristic	Number of studies (%)
Publication year
2000–2005	44 (10%)
2006–2010	88 (19%)
2011–2015	126 (28%)
2016–2021	191 (43%)
Population (stage of CKD)
Not on RRT	126 (28%)
Stage 1	29 (6%)
Stage 2	44 (10%)
Stage 3	80 (18%)
Stage 4	92 (20%)
Stage 5	98 (22%)
Dialysis	274 (61%)
Haemodialysis	228 (51%)
Peritoneal dialysis	118 (26%)
Kidney transplant	139 (31%)
Country
Total*	62
US	43 (10%)
Brazil	43 (10%)
UK	36 (8%)
Turkey	30 (7%)
China	29 (6%)
South Korea	24 (5%)
Australia	18 (4%)
Netherlands	17 (4%)
Spain	16 (4%)
Italy	15 (3%)
Taiwan	15 (3%)
Japan	13 (3%)
Canada	12 (3%)
Iran	11 (2%)
Germany	10 (2%)
Recruitment
Single centre	251 (56%)
More than 1 study centre	181 (40%)
Not reported/unclear	17 (4%)
Outcomes
Symptoms	181 (40%)
Health-related quality of life	361 (80%)
Study design
Cross-sectional	385 (86%)
Longitudinal	64 (14%)

CKD, chronic kidney disease; RRT, renal replacement therapy.

*Only countries with 10 studies or more listed; full list available in S3 Appendix.

Fig 1

PRISMA diagram.

CKD, chronic kidney disease; PROM, patient-reported outcome measure.

There was a total of 199,147 participants involved in the included studies (median 146, IQR 85 to 267, range 9 to 18,015). Studies were conducted in 62 countries, with the most studies in the following countries: US, 43 (10%); Brazil, 43 (10%); UK, 36 (8%); Turkey, 30 (7%); and China, 29 (6%); the majority of studies were conducted at a single centre (251, 56%). Most studies were cross-sectional in design (385, 86%). Patients with CKD stage 1–5 who were not on RRT were included in 126 (28%) studies. The staging of patients not receiving RRT was as follows: 29 studies, stage 1; 44 studies, stage 2; 80 studies, stage 3; 92 studies, stage 4; and 98 studies, stage 5. Patients receiving dialysis were included in 274 (61%) studies (explicitly stated as haemodialysis in 228, and peritoneal dialysis in 118). Patients in receipt of a kidney transplant were included in 139 (31%) studies.

Outcome measures

The included studies utilised 67 different PROMs to collect information on symptoms and HRQOL. Eleven measures were reported in 10 or more individual studies: the 36-Item Short Form Health Survey (SF-36) in 227 studies, KDQOL in 100 studies, the 12-Item Short Form Health Survey (SF-12) in 52 studies, the BDI-II in 51 studies, the World Health Organization Quality of Life (WHOQOL-BREF) instrument in 33 studies, EuroQoL–5 Dimension (EQ-5D) in 28 studies, the Hospital Anxiety and Depression Scale (HADS) in 22 studies, the Centre for Epidemiologic Studies Depression Scale (CES-D) in 11 studies, the Patient Health Questionnaire–9 (PHQ-9) in 10 studies, the Integrated Palliative care Outcome Scale–Renal (IPOS-Renal) in 10 studies, and the Pittsburgh Sleep Quality Index (PSQI) in 10 studies.

A total of 68 different symptoms were measured across 54 PROMs (mean number of items per PROM = 22, range 1–90). No single PROM measured the majority of reported symptoms across the CKD population. The PROMs with the most comprehensive symptom coverage included the CKD Symptom Burden Index (44% of symptoms), the Dialysis Symptom Index (41%), the Memorial Symptom Assessment Scale–Short Form (33%), the Modified Transplant Symptom Occurrence and Symptom Distress Scale (33%), and the Chronic Kidney Disease Symptom Index (32%). There was little consistency across measures; some focused on a single symptom (e.g., BDI-II: depression), others included a number of symptom subdomains (e.g., HADS: anxiety and depression), and some included multiple questions, each tackling a different symptom (e.g., Disease Symptom Index: 30 individual symptom questions).

Symptom prevalence and severity

Data on symptom prevalence and severity were extracted from 181 studies. Pooled summary data are available in Table 2. Symptom prevalence data were available for 45 symptoms in patients not on RRT, for 42 symptoms in patients receiving dialysis, and for 27 symptoms in the transplant population. Symptom severity data were available for 18 symptoms in patients not on RRT, for 33 symptoms in patients receiving dialysis, and for 22 symptoms in transplant patients. Data for symptom prevalence and severity are shown in Figs 2–7.

Table 2

Prevalence and severity of symptoms across CKD populations.

Symptom	Measures	Not on RRT				Dialysis				Transplant
		Prevalence, percent (95% CI)	Number of studies (participants)	Severity* (95% CI)	Number of studies (participants)	Prevalence, percent (95% CI)	Number of studies (participants)	Severity* (95% CI)	Number of studies (participants)	Prevalence, percent (95% CI)	Number of studies (participants)	Severity* (95% CI)	Number of studies (participants)
Fatigue	9, 10, 11, 14, 15, 17, 22, 25, 27	70 (60–79)	14 (4,139)	22.8 (18.7–26.8)	1 (143)	70 (64–76)	21 (2,943)	51.1 (47.2–65.3)	8 (1,181)	48 (32–63)	8 (1,938)	56.1 (47.2–56)	8 (1,021)
Poor mobility	27	56 (34–77)	4 (303)	19 (14.5–23.5)	1 (143)	55 (49–61)	2 (240)			13 (7–20)	1 (110)
Bone or joint pain	10, 11, 14, 23	55 (40–71)	8 (3,993)			49 (36–62)	12 (1,659)	37.9 (28.6–47.1)	3 (447)	55 (49–62)	1 (230)
Drowsiness	10, 11, 25, 39	53 (40–67)	7 (448)	22.5 (18.4–26.6)	1 (143)	34 (20–48)	6 (1,066)			47 (42–52)	2 (362)	11.7 (11.2–12.2)	2 (162)
Pain	15, 24, 27, 34	53 (46–60)	7 (503)	22.5 (18–27)	1 (143)	48 (27–68)	5 (1,054)	55.9 (14.7–97.1)	2 (660)	44 (39–49)	2 (362)	46 (4.9–87.2)	2 (339)
Poor sleep	3, 10, 11, 12, 14, 23, 25, 27, 28	49 (41–58)	15 (4,444)	23.8 (18–29.5)	1 (143)	57 (52–62)	17 (2,575)	35 (28.9–40.9)	6 (1,917)	31 (14–48)	6 (1,529)	30 (22.3–37.6)	3 (404)
Sexual dysfunction	2, 10, 11, 14, 16, 21, 23, 25, 42	48 (35–62)	11 (4,080)	56.4 (32–80.8)	3 (74)	49 (40–58)	16 (1,671)	36.8 (26.7–46.8)	5 (529)	38 (27–49)	4 (402)	60.9 (46.7–75.1)	1 (20)
Itching	1, 10, 11, 14, 25, 35, 38	46 (38–55)	15 (4,208)	25 (8.2–41.8)	1 (87)	51 (41–60)	19 (3,571)	35.7 (29.2–42.3)	9 (1,863)	30 (21–38)	3 (473)
Heartburn	11	46 (43–48)	2 (1,161)			66 (49–80)	1 (38)
Muscle cramps	10, 11, 14	46 (30–62)	7 (3,710)			53 (43–62)	12 (1,569)	25.1 (21.6–28.6)	2 (330)	50 (43–62)	1 (230)
Dry skin	10, 11, 14	45 (33–57)	6 (3,263)			57 (51–64)	9 (884)	42.1 (15.3–68.8)	2 (330)
Swelling in legs	10, 11, 14, 25	45 (36–53)	8 (3,340)			39 (29–50)	9 (811)
Worrying	10, 14	44 (37–50)	4 (2,102)			44 (31–57)	8 (846)	32.3 (28.8–35.8)	2 (330)
Muscle weakness	23	43 (20–66)	3 (1,166)			68 (64–71)	2 (658)			53 (46–60)	1 (230)
Decreased appetite	10, 11, 14, 15, 23, 24, 25, 27	42 (32–52)	16 (8,408)	19.8 (14.8–24.7)	1 (143)	40 (27–54)	16 (2,576)	24.6 (1.6–47.7)	2 (821)	28 (24–32)	3 (592)	7 (4–10)	1 (134)
Shortness of breath	10, 11, 14, 15, 23, 25, 27	42 (34–51)	15 (4,809)	15 (11.3–18.7)	1 (143)	38 (28–48)	16 (2,593)	27.7 (20.3–35.2)	3 (938)	40 (36–44)	3 (592)	9 (5.6–12.4)	1 (134)
Dry mouth	10, 14, 25, 27, 33	41 (33–49)	12 (2,657)	12.5 (8.8–16.2)	1 (143)	43 (35–52)	11 (1,203)	33.6 (16–51.3)	3 (447)	41 (35–48)	1 (110)
Sleep apnoea	6	40 (23–59)	1 (30)			34 (19–53)	1 (32)
Feeling irritable	10, 11, 14	39 (17–62)	6 (3,263)			46 (27–66)	8 (784)	27.5 (23.9–31.1)	1 (230)
Trouble with memory	11	38 (15–61)	3 (1,691)			51 (30–71)	3 (696)			43 (37–50)	1 (230)
Muscle soreness	10, 14	36 (28–44)	4 (2,102)			34 (30–39)	7 (746)	25 (21.8–28.2)	1 (230)
Constipation	10, 14, 19, 25, 27, 30	35 (30–41)	11 (2,230)	22.5 (17.6–27.4)	1 (143)	32 (25–38)	13 (1,418)	15.4 (1.4–29.3)	3 (1,418)	56 (55–58)	2 (4,342)	11.7 (11.2–12.2)	1 (4,232)
Feeling sad	10, 11, 14	34 (14–53)	6 (3,263)			40 (29–52)	8 (784)	25 (21.8–28.2)	1 (230)
Numbness in hands/feet	10, 11, 14, 25	34 (29–38)	8 (3,340)			38 (28–47)	10 (1,001)	36.1 (26.6–45.5)	3 (447)
Dizziness	10, 14, 25	33 (27–38)	6 (2,179)			36 (26–46)	8 (846)	22.4 (9.4–35.3)	1 (230)
Changes in skin	25, 27	31 (17–45)	8 (1,541)	10 (6.3–13.7)	1 (143)	45 (32–58)	3 (278)			32 (23–41)	1 (110)
Headache	2, 10, 14	31 (18–44)	3 (2,002)			30 (24–37)	6 (659)	27.1 (8.3–45.9)	2 (347)	32 (23–41)	1 (110)	23.3 (17.5–29.2)	1 (100)
Feeling nervous	10, 14	31 (25–37)	4 (2,102)			35 (18–53)	7 (746)	37.5 (33.6–41.4)	1 (230)
Anxiety	4, 10, 14, 15, 20, 22, 36, 40	30 (23–37)	10 (2,361)	25.2 (14.7–35.8)	4 (352)	31 (24–38)	24 (3,656)	31.3 (26.2–36.1)	19 (3,350)	20 (5–34)	5 (865)	29.9 (24.1–35.7)	12 (1,022)
Difficulty concentrating	10, 11, 14, 23, 25, 42	30 (18–43)	10 (3,976)			38 (23–53)	8 (784)	22.5 (18.9–26.1)	1 (230)
Cough	10, 14, 25	29 (24–34)	6 (2,179)			31 (23–38)	7 (746)	20 (16.8–23.2)	1 (230)
Weight loss	11, 27	29 (7–50)	3 (1,306)			61 (43–76)	1 (38)
Restless legs	10, 11, 14, 23, 27	27 (21–33)	13 (4,732)	15 (11.3–18.7)	1 (143)	33 (22–43)	13 (1,796)	27.7 (12.7–42.8)	2 (347)	29 (24–34)	2 (340)
Nausea	11, 14, 15, 24, 27, 33	26 (22–30)	12 (6,907)	8 (5.1–10.9)	1 (143)	28 (20–37)	14 (1,932)	24.7 (12.3–37.1)	3 (938)	20 (16–25)	2 (362)	9.9 (3.7–16.1)	2 (234)
Depression	5, 7, 8, 13, 18, 20, 26, 31, 32, 37	26 (21–32)	28 (14,501)	24.6 (18.9–30.4)	17 (10,716)	40 (32–47)	65 (10,253)	29.3 (26.0–32.5)	66 (10,210)	24 (19–29)	16 (4,965)	22.2 (14.8–29.6)	21 (3,644)
Bad taste in mouth	24	26 (25–27)	1 (3,599)
Feeling bloated	2, 25	24 (14–33)	2 (77)							31 (22–40)	1 (110)
Diarrhoea	10, 11, 14, 25, 27, 30	17 (11–23)	13 (3,391)	7.5 (4.6–10.4)	1 (143)	20 (15–24)	12 (1,162)	6.5 (1–12)	3 (524)	24 (16–33)	1 (110)	17.8 (8–27.5)	2 (4,332)
Sweats	25	16 (8–24)	2 (77)
Hiccups	11	14 (12–16)	2 (1,161)			34 (20–51)	1 (38)
Chest pain	10, 14	14 (12–15)	2 (1,566)			14 (8–19)	7 (776)	25.9 (4.6–47.1)	2 (447)
Vomiting	10, 11, 14, 24, 25, 27, 33	14 (12–16)	15 (7,417)	5 (2.5–7.5)	1 (143)	14 (12–17)	11 (1,141)	27.5 (8–46.9)	2 (447)	11 (6–18)	1 (110)	13.3 (8.8–17.9)	1 (100)
Change in appearance	22, 25	11 (4–17)	2 (77)							11 (8–16)	1 (274)	79.1 (69.5–88.7)	5 (646)
Stress	29	11 (8–16)	1 (236)			24 (18–31)	1 (183)					35.7 (29.9–41.5)	1 (100)
Hair loss/growth	25	5 (0–10)	2 (77)
Indigestion	19					30 (24–37)	1 (182)	4 (2.4–5.6)	2 (294)	83 (82–84)	1 (4,232)	20 (19.5–20.5)	1 (4,232)
Abdominal pain	19, 30					44 (12–75)	4 (442)	2.5 (0.9–4.2)	2 (294)	69 (68–70)	1 (4,232)	15 (14.5–15.5)	1 (4,232)
Reflux	19							8.3 (1.7–14.8)	2 (294)			11.7 (11.1–12.2)	1 (4,232)
Blurred vision	12											63.3 (56.1–70.5)	1 (100)
Excessive appetite	12											63.3 (56.1–70.5)	1 (100)
‘Moon face’	12											63.3 (54.8–71.8)	1 (100)

RRT, renal replacement therapy. Measures: (1) 5-D Pruritus, (2) Afshar 2012, (3) AIS, (4) BAI, (5) BDI-II, (6) BQ, (7) BSI, (8) CES-D, (9) CIS, (10) CKD-SBI, (11) CKD-SI, (12) CSE, (13) DASS, (14) DSI, (15) ESAS, (16) FSFI, (17) FSS, (18) GDS 15/30, (19) GSRS, (20) HADS, (21) IIEF, (22) KTQ, (23) LUSS, (24) MDRD, (25) MSAS-SF, (26) PHQ-9, (27) IPOS-Renal, (28) PSQI, (29) PSS-4, (30) Rome II, (31) SDS, (32) TDQ, (33) TQ, (34) VAS Pain, (35) VAS Pruritus, (36) Zung SAS, (37) Zung SDS, (38) 4-Itch, (39) ESS, (40) STAI, (42) KSQ. Full names of outcome measures available in S10 Appendix.

*Severity (adjusted score), 0–100, with 100 = worst possible.

Fig 2

Pooled prevalence of patient-reported symptoms across included studies for patients not on renal replacement therapy (RRT).

Fig 7

Pooled symptom severity across included studies for patients in receipt of a kidney transplant.

Scores represent mean severity scores converted to a 0–100 scale, where a higher score indicates greater severity; vertical line at 50 for reference.

Pooled symptom severity across included studies for patients not on renal replacement therapy.

Scores represent mean severity scores converted to a 0–100 scale, where a higher score indicates greater severity; vertical line at 50 for reference. RRT, renal replacement therapy.

Pooled symptom severity across included studies for patients on dialysis.

Patients not on RRT and those receiving dialysis shared a similar profile of the most prevalent symptoms. For example, symptoms with a reported prevalence of >50% in both populations included fatigue and poor mobility, and symptoms with a reported prevalence of >45% in both populations included bone/joint pain, general pain, poor sleep, sexual dysfunction, heartburn, muscle cramps, itching, and dry skin. Fewer data were available for transplant patients; however, indigestion, abdominal pain, constipation, muscle weakness, and muscle cramps were most prevalent, being present in >50% of patients.

For patients not on RRT, the most severe symptoms included sexual dysfunction, anxiety, itching, and depression. Pain was the most severe symptom in dialysis, followed by fatigue, dry skin, and bone/joint pain. For transplant recipients, the most severe symptoms were change in appearance, blurred vision, and excessive appetite.

Trends in prevalence/severity across clinical groups and attribution

Within the included studies, data from contemporaneous non-CKD control populations were limited, and available for only 17 symptoms for prevalence and 4 for severity.

Prevalence was higher in CKD patients compared to healthy controls for 14 of 17 symptoms (bone/joint pain, fatigue, trouble with memory, muscle cramps, itching, restless legs, muscle weakness, constipation, shortness of breath, anxiety, depression, decreased appetite, diarrhoea, and abdominal pain), and lower than controls for 1 symptom (stress).

Fatigue was the most prevalent symptom in patients not on RRT and in those on dialysis. Fatigue was also the second most severe symptom in dialysis patients (adjusted severity score 51.5, 95% CI 29.1–33.8). Fig 8 displays the full results of the meta-analysis of fatigue prevalence across CKD clinical groups including controls. Fatigue prevalence in controls was 34% (95% CI 0%–70%). In comparison, fatigue prevalence was significantly higher (FDR-sharpened q-value 0.021) in patients with CKD not on RRT (70%, 95% CI 60%–79%) and in dialysis patients (70%, 95% CI 64%–76%; FDR-sharpened q-value 0.021); fatigue prevalence was significantly lower in transplant patients (48%, 95% CI 32%–63%; FDR-sharpened q-value 0.005) than in patients on RRT or dialysis, although notably not as low as in controls. A number of other symptoms followed this prevalence pattern across clinical groups. All symptom prevalence and severity data are available in S6 and S7 Appendices, and all pairwise comparisons between groups including FDR-sharpened q-values are available in S8 Appendix. Fig 9 includes the point estimates for symptom prevalence reported across the 3 study populations (with control data where available).

Fig 8

Prevalence of fatigue in chronic kidney disease.

See S4 Appendix for full references for included studies. ES, effect size; HD, haemodialysis; PD, peritoneal dialysis; RRT, renal replacement therapy.

Fig 9

Symptom prevalence comparison across groups.

CKD, chronic kidney disease; RRT, renal replacement therapy.

Patients not on RRT and those receiving dialysis had similar profiles of prevalence across most symptoms. However, exploratory subgroup analysis (including correction for multiple testing) highlighted 2 symptoms that were significantly more prevalent in the dialysis population than in patients not on RTT: depression and stress (FDR-sharpened q-value 0.021 in both cases). Seven further symptoms showed tendencies towards greater prevalence (>10% difference) in the dialysis population but did not reach adjusted statistical significance: weight loss, muscle weakness, hiccups, heartburn, changes in skin, trouble with memory, and dry skin. Drowsiness demonstrated a tendency towards lower prevalence in the dialysis population (>10% difference), but again the difference did not reach significance.

When compared to patients not on RRT and dialysis patients, the following symptoms were significantly less prevalent in patients who had received a kidney transplant: muscle weakness, fatigue, poor sleep, itching, decreased appetite, depression, dry mouth, and poor mobility (FDR-sharpened q-values 0.005–0.037). Overall, compared to the kidney transplant population, symptom prevalence was higher in patients not on RRT and patients on dialysis for 31 of 50 comparisons. However, there were 2 symptoms that reversed this pattern, constipation and indigestion, which were both significantly more prevalent in the transplant population (FDR-sharpened q-values 0.005–0.013).

HRQOL

Data on HRQOL were extracted from 361 articles. The Medical Outcomes Study SF-12 and SF-36 were reported in 52 and 227 studies, respectively, KDQOL in 100, the World Health Organization Quality of Life (WHOQOL-BREF) instrument in 33, and EQ-5D in 28.

Pooled scores are shown for SF-12/SF-36, KDQOL, and EQ-5D in Table 3 and Fig 10. For all scores, a higher number represents better quality of life (0–100 scale for SF-12/SF-36 and KDQOL, and possible range of −0.224 to 1 for EQ-5D).

Table 3

Health-related quality of life outcomes in chronic kidney disease.

Measure	Not on RRT	Dialysis	Transplant
Medical Outcomes Study 36-Item Short Form Health Survey (SF-36)
Mental Component Summary *	66.6 (66.5–66.6)	45.7 (45.5–45.8)	50.0 (49.9–50.1)
Number of studies	39	91	39
Number of participants	24,600	32,105	9,664
Physical Component Summary *	66.3 (66.2–66.4)	35.5 (35.3–35.6)	48.0 (47.9–48.1)
Number of studies	39	91	39
Number of participants	24,600	32,105	9,664
Medical Outcomes Study 12-Item Short Form Health Survey (SF-12)
Mental Component Summary *	49.8 (49.7–49.9)	45.4 (45.2–45.6)	48.2 (47.5–48.9)
Number of studies	13	36	7
Number of participants	19,447	8,910	878
Physical Component Summary *	47.5 (47.3–47.6)	35.2 (35.0–35.4)	44.6 (44.0–45.3)
Number of studies	13	36	7
Number of participants	19,447	8,910	878
Kidney Disease Quality of Life (KDQOL) instrument
KDQOL Summary Score *	73.0 (73.0–73.2)	64.6 (64.3–64.8)	83.2 (84.8–87.5)
Number of studies	19	69	10
Number of participants	30,689	12,222	1,374
Symptoms and problems *	85.9 (85.9–86.0)	73.6 (73.4–73.8)	86.1 (85.4–86.7)
Number of studies	19	69	10
Number of participants	29,689	9,807	1,374
Effects of kidney disease *	71.7 (71.5–71.8)	63.2 (63.0–63.5)	87.5 (86.7–88.2)
Number of studies	21	71	11
Number of participants	32,977	12,514	1,401
Burden of kidney disease *	50.6 (50.5–50.8)	41.7 (41.4–42.0)	72.0 (70.7–73.3)
Number of studies	21	71	11
Number of participants	32,977	13399	1,401
EuroQoL–5 Dimension (EQ-5D)
Index score ^	0.882 (0.882–0.882)	0.774 (0.767–0.781)	0.840 (0.821–0.859)
Number of studies	11	15	1
Number of participants	24,161	2,637	494

RRT, renal replacement therapy.

*Mean (95% CI) HRQOL score, 100 = best possible quality of life.

^Mean (95% CI) EQ-5D index score, 1 = best possible quality of life.

Fig 10

Health-related quality of life in CKD.

CKD, chronic kidney disease; EQ5D, EuroQoL–5 Dimension; KSS, Kidney Disease Quality of Life Summary Score; MCS, Mental Component Summary; No. pops, number of populations; PCS, Physical Component Summary; SF12, 12-Item Short Form Health Survey; SF36, 36-Item Short Form Health Survey.

Within the generic measures of HRQOL, SF-12/SF-36 and EQ-5D, where data were available, scores were highest in controls (EQ-5D index 0.95, 95% CI 0.95–0.95) and lowest in patients on dialysis (EQ-5D index 0.78, 95% CI 0.77–0.79; SF-36 Mental Component Summary [MCS] 45.7, Physical Component Summary [PCS] 35.5; SF-12 MCS 45.4, PCS 35.2). HRQOL scores were higher in patients receiving a kidney transplant (EQ-5D index 0.84, 95% CI 0.82–0.86; SF-36 MCS 50.0, PCS 48.0; SF-12 MCS 48.2, PCS 44.8), and higher still for patients not on RRT (EQ-5D index 0.88, 95% CI 0.88–0.88; SF-36 MCS 66.6, PCS 66.3; SF-12 MCS 49.8, PCS 47.5).

For the disease-specific KDQOL measure, the KSS was 73.0 in patients not on RRT, 64.6 in patients receiving dialysis, and highest in transplant patients (84.0). This pattern was similar in the KDQOL ‘effects of kidney disease’ (not on RRT, 71.7; dialysis, 63.2; transplant, 87.5) and ‘burden of kidney disease’ subscales (not on RRT, 50.6; dialysis, 41.7; transplant, 72.0). The burden of kidney disease subscale includes items related to how much kidney disease interferes with daily life, or makes the respondent feel like a burden. The effects of kidney disease subscale includes items exploring respondents’ perceived dependency on clinicians, stress/worries, and bother associated with treatment/dietary restrictions. In the ‘symptoms and problems’ subscale, for patients not on RRT and those in receipt of a transplant, scores were homologous (85.9 and 86.1, respectively), whilst pooled scores for the dialysis population were lower (73.6). The symptoms and problems subscale items measured how bothered respondents were by certain symptoms (e.g., sore muscles, chest pain, cramps, itchy/dry skin, and fatigue) or problems associated with dialysis access.

All exploratory subgroup analyses comparing HRQOL scores between populations showed statistically significant differences, with the exception of the KDQOL symptoms and problems subscale comparison between patients not on RRT and in receipt of a transplant (FDR-sharpened q-value 0.107) (HRQOL subgroup analyses available in S8 Appendix).

Quality appraisal of included studies

Results of the quality appraisal are shown in Fig 11 and for individual studies in S3 Appendix.

Fig 11

Quality of included studies.

Yes = appraised as adequate; no = appraised as not adequate.

Whilst the majority of studies used random sampling or approached all patients on a clinic/registry list (59.5%), some used convenience or consecutive sampling (28.3%), or methods were unclear (12.2%). Sample size was deemed adequate in 61.9% of studies, and response rate in 57.7%. PROMs for symptoms or HRQOL that allowed comparison with other studies in CKD were used in 93.3% of studies (i.e., the measure had been used in CKD before, either as identified in this review or in the author description of previous use). Statistical analysis was reported in sufficient detail in 92.2% of studies.

There was evidence of publication bias (Egger’s test for funnel plot asymmetry) for 3 of 32 symptom prevalence meta-analyses including ≥10 studies; the 3 symptoms were poor sleep, numbness in hands/feet, and anxiety. No evidence of publication bias was found in meta-analyses of HRQOL data. All publication bias analyses are available in S6–S8 Appendices.

Discussion

In this study, our first aim was to provide a global synthesis of symptom/HRQOL burden across all CKD stages. Overall, patients with CKD had a significantly increased symptom burden, and lower quality of life, compared to individuals without CKD. Patients reported a range of common and/or severe symptoms, with the precise configuration depending on the stage of CKD and RRT treatment modality received. Fatigue, however, was a very common and severe symptom in all patient groups. Symptom burden and quality of life were worst in patients receiving dialysis. In general, patients who had received a kidney transplant experienced fewer and less severe symptoms, and had an improved quality of life, compared to patients with CKD not receiving RRT or patients receiving treatment with dialysis. Transplantation, however, did not restore quality of life to levels seen in those without CKD.

Identification of the burden of symptoms for patients with advanced CKD is important: Many of the symptoms reported can be mitigated by changes in clinical management [19]. This synthesis will support clinicians and patients in consultations, to ensure that all potential symptoms associated with CKD are recognised, facilitating shared decision-making regarding management [20]. In addition, the data highlight key variations in symptom burden between kidney disease modalities, allowing clinicians to identify fundamental differences and administer appropriate treatment. Moreover, the data may highlight key domains appropriate for inclusion within routine remote monitoring, a tool increasingly employed in clinical practice to support timely intervention in response to patient deterioration [8-11]. Recent reviews report on some symptoms, but do not quantify the symptom burden or accurately identify differences in symptom burden between treatment states [21,22]. The results of this study address this shortfall and provide information that has direct implications for clinical practice.

Our results concur with previous research regarding the prevalence of a number of symptoms, particularly in patients with stage 4/5 CKD. Almutary and colleagues conducted a 2013 review of symptom burden in CKD (stage 4/5 not on RRT/on dialysis), finding that the most prevalent symptoms were fatigue, feeling drowsy, pain, pruritus, and dry skin [21]. Murtagh et al. conducted a systematic review of the prevalence of symptoms in patients with end-stage renal disease, with the following prevalent symptoms highlighted: fatigue/tiredness, pruritus, constipation, anorexia, pain, sleep disturbance, anxiety, dyspnea, nausea, restless legs, and depression [22]. Differences between these studies and ours may be explained by our far larger sample size, resulting in much more precise estimates. Our study also has the advantage of comparing data across CKD clinical groups and including additional information regarding HRQOL and symptom severity.

Our second aim was to explore which symptom/HRQOL domains are modified by CKD and may be attributable to the disease. To the best of our knowledge, ours is the first study to attempt this. Our results suggest there was a significantly lower prevalence of many symptoms in kidney transplant patients, compared to patients not on RRT and dialysis patients, which may suggest attribution; these symptoms included muscle weakness, fatigue, poor sleep, itching, decreased appetite, depression, dry mouth, and poor mobility. Collecting routine data on which symptoms/HRQOL are prevalent, impactful, and directly attributable to CKD is vital to improve understanding of individuals’ experience of illness and to target treatment/support. This information can also be used alongside existing clinical data in discussions with patients to help better prepare them for CKD progression and to inform shared decisions around treatment [10]. We also found that some symptoms did not differ significantly across clinical groups and therefore may be largely unrelated to kidney function specifically, or the confidence intervals may preclude accurate interpretation. Further research may be required to explore the symptoms with broad confidence intervals, and hence greater uncertainty.

The third aim of the study was to determine which current PROMs may capture patient-important symptom/HRQOL information in a way that minimises patient burden. In total, 54 PROMs were used to collect data on symptoms across the included studies, and we found little consistency in the measures. This may be a consequence of the fact that no single tool measured >45% of symptoms reported in the population. This is problematic. At present, comprehensive measurement of symptoms would require that patients complete multiple PROMs, which may include large numbers of items or may have items that overlap. Such PROM ‘item burden’ has been widely recognised as an important threat to adherence [23]. Given the high number of symptoms experienced by patients with CKD, the use of contemporary psychometrics, encompassing item response theory (IRT) and computerised adaptive testing (CAT), may be warranted in order to develop new measures that capture sufficient information regarding all patient-important symptoms, whilst minimising questionnaire burden [24]. CATs efficiently select questions from an IRT-calibrated item bank that are targeted to an individual’s ability/trait level using an adaptive algorithm, minimising the number of items administered, for example, the Patient-Reported Outcomes Measurement Information System (PROMIS) physical function CAT [25-27]. The findings of this systematic review will contribute to the construction of an item bank as part of the RCAT (Renal Computerized Adaptive Test) study [28].

Strengths and limitations

Our findings present a comprehensive overview of the differences in symptom and HRQOL prevalence and severity between patients with CKD stage 1–5 not on RRT, patients receiving dialysis, and transplant patients. In addition, where contemporaneous data were available, we were able to compare with controls. The study included >190,000 patients with CKD (from 62 countries) throughout the trajectory of the disease and its treatment. A large quantity of data was available from different settings, and this synthesis presents strong evidence for the ongoing and considerable impact of CKD on patients’ lives. The review included data collected using PROMs only, hence data provided from CKD patients themselves. It is now widely understood that PROMs are patient centric, and provide information that is as important, if not more so, to patients than solely focusing on clinical outcomes [29-32].

Data were most frequently from cross-sectional studies, and whilst this is useful in providing an estimate of the prevalence and impact of symptoms at a population level, it does not address the day-to-day variation experienced by CKD patients and makes it challenging to draw robust conclusions around longitudinal patterns of symptom burden during the course of the disease.

A limitation is that we excluded non-English-language papers, meaning some potentially relevant studies may not have been included in our analysis. In addition, many symptom severity estimates came from single studies, and inconsistent use of PROMs across this literature hindered interpretation, especially with regard to clinical significance. This necessitated standardisation of severity scores onto a 0–100 scale to support meaningful synthesis [33]. Moreover, whilst there was information available in some of the studies on the severity of CKD, symptom burden with respect of excretory kidney function was limited, so the evolution of symptoms during the progression of CKD could not be assessed.

A further limitation was the considerable heterogeneity of included studies. This was not unexpected, as heterogeneity can be a common problem in systematic reviews of global prevalence data [12]. However, we followed established guidelines in our analysis [12], which suggest that in the presence of significant heterogeneity, random effects meta-analysis may be an appropriate method of generating a distribution that allows estimation of population differences with a quantifiable degree of probability.

Future research

The findings of this review highlight several areas that warrant further research. In particular, additional high-quality studies exploring symptom severity are required in order to generate more precise estimates. We also found that there were fewer studies exploring symptom burden/HRQOL in the transplant population compared to other CKD groups. Finally, historical and ongoing use of many different symptom/HRQOL PROMs across studies poses particular challenges for those wishing to synthesise data. Future studies should focus on more consistent use of recommended outcome measures, such as those included in internationally endorsed core outcome sets [34,35], to facilitate comparisons between studies and enhance the generalisability of findings.

Conclusion

This systematic review provides a detailed overview of the symptom/HRQOL profile across CKD clinical groups, with fatigue particularly prevalent, both in patients not on RRT and in those receiving dialysis. A number of symptoms were less prevalent and/or severe within the post-transplantation population, which may suggest attribution to CKD. HRQOL in patients with CKD was significantly worse than in individuals without the disease, particularly so in patients receiving dialysis. In general, patients receiving a transplant experienced lower symptom prevalence and severity and improved disease-specific quality of life, but this still did not reach the level of HRQOL of people without CKD. The findings of this review may support healthcare professionals when discussing, measuring, and managing the potential treatment burden associated with CKD.

PRISMA checklist.

(DOC)

Click here for additional data file.

Ovid MEDLINE search strategy.

(DOCX)

Click here for additional data file.

Information on included studies.

(XLSX)

Click here for additional data file.

List of included studies.

(DOCX)

Click here for additional data file.

List of excluded studies.

(DOCX)

Click here for additional data file.

Symptom prevalence across studies.

(XLSX)

Click here for additional data file.

Symptom severity across studies.

(XLSX)

Click here for additional data file.

Pairwise group comparisons.

(XLSX)

Click here for additional data file.

Review protocol.

(DOCX)

Click here for additional data file.

Summary of symptom outcome measures.

(XLSX)

Click here for additional data file.

25 Mar 2021

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9 Aug 2021

Dear Dr. Fletcher,

Thank you very much for submitting your manuscript "Symptom burden and health-related quality of life in chronic kidney disease: a systematic review and meta-analysis." (PMEDICINE-D-21-01326R1) for consideration at PLOS Medicine.

Your paper was evaluated by a senior editor and discussed among all the editors here. It was also discussed with an academic editor with relevant expertise, and sent to three independent reviewers, including a statistical reviewer. The reviews are appended at the bottom of this email and any accompanying reviewer attachments can be seen via the link below:

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As you can see below, the reviewers have pointed out a number of concerns with the paper, including with the reporting of the methods and results. I am afraid that we will not be able to accept the manuscript for publication in the journal in its current form; however, we would consider a revised version that completely addresses the reviewers' and editors' comments. Obviously we cannot make any decision about publication until we have seen the revised manuscript and your response, and we plan to seek re-review by one or more of the reviewers.

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Requests from the editors:

1. Please completely address all reviewer comments, particularly the concerns mentioned by Reviewer 2 regarding reporting of the data extraction and analysis methods, and assessment of heterogeneity, including how the high degree of heterogeneity impacts pooling across studies in terms of prevalence and severity, and the interpretation of the meta analyses.

2. Please update the search to the present time (currently through February of 2020 and updated through October 2020).

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Please combine the Methods and Findings sections into one section, “Methods and findings”. Please provide the dates of search, types of study designs included, exclusion criteria including language exclusions, and synthesis/appraisal methods. Please mention how you evaluated study quality and risk of bias, including publication bias.

4. Abstract: Methods and Findings: Please present quantitative data in support of the main findings of the meta analysis. As the last sentence of the Methods and Findings, please describe the main limitation(s) of the study's methodology.

5. Author summary: At this stage, we ask that you include a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract. Please see our author guidelines for more information: https://journals.plos.org/plosmedicine/s/revising-your-manuscript#loc-author-summary

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8. Methods: Thank you for noting that your study protocol was registered. Please note whether the protocol and analysis methods were developed prospectively. Please make sure that the Methods section transparently describes when analyses were planned, and when/why any data-driven changes to analyses took place.

9. Methods: Please provide a list of excluded studies and reasons for exclusion.

10. Methods: Please note how publication bias was assessed.

11. Results: As mentioned by Reviewer 1, please include a table with each study summarizing the design, instruments used, outcome measures, size, etc. and include quality assessment and risk of bias for each.

12. Results: Please provide an assessment of how results differ by excluding studies judged to be at high risk of bias.

13. Results: Meta-analysis for fatigue prevalence across CKD levels: Please provide both p values and 95% CIs for comparisons of fatigue prevalence between groups, in the text as well as in Figure 3.

14. Discussion: Please present and organize the Discussion as follows: a short, clear summary of the article's findings; what the study adds to existing research and where and why the results may differ from previous research; strengths and limitations of the study; implications and next steps for research, clinical practice, and/or public policy; one-paragraph conclusion.

15. Figure 4: Please provide an X axis label. The individual symptoms are difficult to read on the left, please increase the font size.Please provide the meta analysis results for each symptom shown in Figure 4 as displayed for Figure 3.

16. PRISMA diagram: Please note the “other sources” for the 8 additional records identified. Please note the reasons for records excluded at each stage.

17. PRISMA Checklist: When completing the checklist, please use section and paragraph numbers, rather than page numbers.

Comments from the reviewers:

Reviewer #1: The stated aim of this review is to produce a comprehensive and consolidated synthesis of symptom prevalence/severity and HRQOL across CKD stage and treatment groups.

Comments:

"The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed (PRISMA checklist, supplementary appendix 1) and the study protocol was registered with PROSPERO (CRD42020164737)."

The authors have suitably provided the PRISMA checklist in the supplementary material.

Can they also please provide a copy of the study protocol in the supplementary material?

"Three authors (BF, SD, DK) independently assessed selected articles for eligibility at the title/abstract and full-text stages."

Can the authors please confirm if the articles were triple checked, or were they divided up between the three assessors?

Were there any cases of disagreement? If so, how were these resolved?

Also, were the authors of similar expertise and experience?

"The following data were independently extracted into a pre-piloted spreadsheet by three authors (BF, SD, DK)..."

As for the previous comment, can the authors please provide similar clarifications for the data extraction process?

"Symptom prevalence data, and mean HRQOL scores were combined using random-effects meta-analysis. To aid comparison of symptom severity data provided across different outcome measures, all mean severity scores were converted to a 0-100 scale, where a higher score indicates greater severity. For HRQOL scores, 100 represents best possible quality of life. Symptom severity scores were also combined using random effects meta-analysis. A weighted composite summary score (Kidney Summary Score or KSS) for the Kidney Disease Quality of Life (KDQOL) instrument was calculated by combining the 'Symptom/Problems', 'Effects' and 'Burden' domains, using the method reported by Peipert et al. (2019). Exploratory subgroup analysis was used to compare prevalence and score (severity and HRQOL) estimates between groups in meta-analyses (predialysis v dialysis, predialysis v transplant and dialysis v transplant). To account for multiple testing, sharpened False Discovery Rate (FDR) q-values were computed, and adjusted p-values are reported."

and

"Random effects meta-analyses were used to pool data on symptom prevalence and severity, and HRQOL scores. We stratified meta-analyses by CKD status: Stage 1-5 not on dialysis (predialysis), on dialysis, and post renal transplantation."

The authors have applied a technically appropriate and rigorous statistical methodology.

Can the authors please discuss heterogeneity within the methods, results and conclusions?

It is noted that I2 in Figure 3 is > 95%, which is substantially high and may mean the results of the meta-analysis are misleading.

Can the authors confirm whether Figure 6 and Table 4 show the same thing?

If so, it is suggested to remove one of these to avoid duplication.

It is also suggested to replace the List of Included studies in Appendix 3, with a table describing each (type, size, dates, location etc.) study with its associated JBI quality assessment.

Reviewer #2: Thank you for the opportunity to review this manuscript describing the symptom burden and health-related quality of life in CKD using a systematic review and meta-analysis of the published literature 2000 to Feb 2020. The authors used three main search engines to retrieve the publications (MEDLINE, PschINFO, CINAHL), which yielded 415 studies to include in the review and meta-analysis. This is an interesting number since only 4 years before, a systematic review published in PLOS One (https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0179733) only identified 66 publications using an additional search engine (EMBASE) that covered the same patient-reported outcome measures in CKD. I have major concerns regarding the methodology that was used - particularly for meta-analyses, largely regarding pooling of the data across study populations that used different study instruments without formal assessment of heterogeneity that would indicate if it would be worthwhile to pool the results. The authors already note in that the outcome measures (pg 8) there was "little consistency across measures". The methods section is very under developed and the reader cannot clearly understand the methods used. Additionally, I have concerns about description of prevalence and severity of symptoms as the true denominator is unknown and is affected by publication bias and ascertainment bias (e.g., more studies and instruments asked about pain and fatigue rather than itching - does that mean that itching is less important to the patients?). The discussion is also under-developed. I think the paper would be strengthened by reporting the number of studies/instruments that included particular symptom measures, what the typical reported level of that symptom is across stages of CKD (if possible) without formal analyses since the ability to pool is likely not sufficient.

Throughout manuscript - please use alternative term for "pre-dialysis" - for example, non-dependent CKD as not all patients with CKD will go on to develop dialysis

Abstract

- Background: clarify what "treatment groups" means and what does inform capture mean?

- Methods: indicate end year of search

- Conclusion: why only highlight the systematic review portion

Introduction

- Spelling error for vulnerable

-

Methods:

- Why was EMBASE not included?

- Formal tests of heterogeneity?

- Data analysis section - underdeveloped and need more elaboration of how the studies were pooled and how the instruments were harmonized for pooling - for example - if there was any mention of fatigue in the PROM - was it "counted" as a measure of fatigue? - again how was severity of that measure scored?

- need to also describe how mean HRQOL scores were determined across different instruments - were these also standardized?

- How was a severity score determined?

- How was the weighted composite summary score constructed - need more elaboration than a prior citation

- Suggest that instead of exploratory meta-analyses comparing scores across stages of CKD - first describe the differences

Figure 1 - I think they are misleading - I think is affected by publication bias - is it really symptom prevalence or prevalence of symptoms asked prior studies?

Figure 2 - it very difficult to interpret these without learning more about the severity scores

Figure 3 - what does this add to Figures 1?

Figure 4 - as above for figure 2 - need more description about severity scores

Table 3- was individual level used to pool these results or are they from averages (means) reported in the published papers?

Trends in prevalence (page 21)

- The authors note that "data from non-CKD control populations are sparse" which is not possible as there are many many studies that have used legacy PROMS, including SF-36 in non-CKD populations that can provide normative data for comparison https://hqlo.biomedcentral.com/articles/10.1186/s12955-017-0625-9

Discussion

- I think it is misleading to report there was lower prevalence of symptoms in transplant compared to non-dialysis CKD or dialysis since the denominator differs so much, there were fewer studies and the outcome measures could have asked fewer questions

- On page 29 - "we found little consistently in the PROMS used to capture data around symptoms in CKD" - how do the authors justify meta-analyzing the data?

- Suggest the authors include the following citation in their writing about the use of IRT and CAT to develop new measures - as this has been developed by the PROMIS program using mixed methods - https://www.healthmeasures.net/explore-measurement-systems/promis

- The introduction provides background on how this will inform ePROs - I didn't see further discussion on this - which surveys collected were collected with digital/electronic means?

Reviewer #3: Thank you for the opportunity to review this paper.

It has clearly involved a considerable amount of work to synthesise the mass of data, for which the authors deserve credit.

My main comments concern the framing of the work, some commentary of the methods and then a view on the conclusions reached. This is an important area that requires focus.

The introduction produces the background and rationale for the work but the section on electronic reporting seemed redundant. It was not part of the study. It conflates the definitions of symptoms and the tools used with the operational method to collect those tools. So it did not seem to add anything to the objectives or the methodology.

The introduction lays out three clear objectives for the work 'The aim of this study was to: (i) produce a comprehensive and consolidated synthesis of symptom prevalence/severity and HRQOL across CKD treatment groups; (ii) explore which symptoms/HRQOL domains are modified by CKD and may be attributable to the disease; (iii) determine which PRO measures (PROMs) are currently available to capture symptom prevalence/severity and HRQOL in CKD.'

It was not clear how these objectives were achieved from the discussion. It would be useful to reflect back those challenges as a summary of the study.

Turning to the data itself, there was some discussion on control groups but again it was difficult to pick out the narrative of symptom evolution from normality through to CKD (and across the stages of CKD) to renal replacement therapy (dialysis and transplantation). Figure 4 helps in one sense (and is the fatigue line missing the mark for the dialysis population?) but it only covers prevalence. The burden comes from both prevalence and from severity. A discussion on this two dimensional view of symptom burden would be valuable. That would provide insight into the utility of measures as drivers to improve care for people with kidney disease.

A minor note on the methods - it was unclear whether those reviewing the papers did so independently and then a consensus was reached where needed. There is also a typo on manuscript page 3 line 10.

Any attachments provided with reviews can be seen via the following link:

[LINK]

2 Dec 2021

Submitted filename: PLOS Medicine response to reviewer comments 30Nov21.docx

Click here for additional data file.

11 Jan 2022

Dear Dr. Fletcher,

Thank you very much for submitting your manuscript "Symptom burden and health-related quality of life in chronic kidney disease: a global systematic review and meta-analysis." (PMEDICINE-D-21-01326R2) for consideration at PLOS Medicine.

Your revised paper was evaluated by a senior editor and discussed among all the editors here. It was also discussed with an academic editor with relevant expertise, and sent to two of the original reviewers, including a statistical reviewer. The reviews are appended at the bottom of this email and any accompanying reviewer attachments can be seen via the link below:

[LINK]

Giving the remaining points noted by one reviewer, I am afraid that we will not be able to accept the manuscript for publication in the journal in its current form, but we will consider another revised version that addresses the reviewers' and editors' comments. Obviously we cannot make any decision about publication until we have seen the revised manuscript and your response, and we plan to seek re-review by one or more of the reviewers.

In revising the manuscript for further consideration, your revisions should address the specific points made by each reviewer and the editors. Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments, the changes you have made in the manuscript, and include either an excerpt of the revised text or the location (eg: page and line number) where each change can be found. Please submit a clean version of the paper as the main article file; a version with changes marked should be uploaded as a marked up manuscript.

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***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***

We ask every co-author listed on the manuscript to fill in a contributing author statement, making sure to declare all competing interests. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. If new competing interests are declared later in the revision process, this may also hold up the submission. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT. You can see our competing interests policy here: http://journals.plos.org/plosmedicine/s/competing-interests.

Please use the following link to submit the revised manuscript:

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Your article can be found in the "Submissions Needing Revision" folder.

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Please ensure that the paper adheres to the PLOS Data Availability Policy (see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it.

We look forward to receiving your revised manuscript.

Sincerely,

Caitlin Moyer, Ph.D.

Associate Editor

PLOS Medicine

plosmedicine.org

-----------------------------------------------------------

Requests from the editors:

1. Please completely address the remaining points of Reviewer 2.

2. Abstract: Methods and Findings: Please explicitly describe the participants/comparator groups among the patients with CKD included.

3. Abstract: Methods and Findings: Please mention the types of/any restrictions on design of studies included (e.g. longitudinal, cross-sectional).

4. Abstract: Line 43-44: Please mention how (the specific tools used) methodological quality and risk of bias were assessed.

5. Abstract: For the main outcomes described, it would be helpful to note the numbers of studies/patients included for each.

6. Abstract: Line 49: Please define the abbreviation “RRT” at first use.

7. Abstract: Line 51-52: Please mention the comparison group for this analysis, and please report 95% CIs and p values for each symptom mentioned.

8. Abstract: Lines 54-58: Please also report the p values for these comparisons.

9. Methods: Line 124-125: Please reference the supporting information file that contains the study protocol.

10. Methods: Please mention the types of studies/designs included. The search did not include non-English language sources of studies (45 studies excluded for this reason). Please acknowledge and discuss this as a limitation.

11. Methods: Please provide complete details for the fixed and random effects models used. Please indicate for which analyses fixed vs. random effects models were used.

12. Discussion: Line 381, Line 461: Please temper claims of primacy with “To the best of our knowledge” or similar.

13. Table 1: Please note that “Population” indicates stage of CKD. Please indicate in the table that values are number of studies and (%) if accurate. It may be helpful to include a legend for the table, defining all abbreviations (RRT) in the legend.

14. Table 3: Please clarify the values presented in the table.

15. Figure 4: Please include a legend describing all abbreviations used.

16. S3 Appendix, S6 appendix, S7 appendix: Please include a legend for this table, defining all abbreviations and color-coding used. We suggest choosing a color-coding scheme that avoids the need to distinguish red and green.

17. S8 Appendix: Separate titles and legends for each item (each tab) in this file would be helpful to understand which comparisons are being shown and what is illustrated in each table.

18. PRISMA Checklist: Thank you for including the PRISMA checklist. Please use section and paragraph numbers to refer to locations within the text. Please do not use page numbers or line numbers.

Comments from the reviewers:

Reviewer #1: The authors have satisfactorily responded to each comment in turn, amending the manuscript as required.

Reviewer #2: Thank you for the opportunity to review this revised manuscript describing the symptom burden and health related quality of life in CKD.

I do think this revision is improved but is not yet ready for publication. The authors have addressed many of my concerns but did not directly respond to the second paragraph of text of my original review. Some concerns were addressed in separate comments but I am still concerned that the discussion is largely underdeveloped. It lacks synthesis and interpretation of the study's findings and largely repeats the study's findings, which is particularly apparent in the second paragraph of the discussion. The third paragraph of the discussion also contains too many details about the cited study - please only highlight main similarities. The entire discussion could be strengthened by including more interpretation.

Other concerns

- Methods: I am concerned about the psychometric validity of rescoring the the self-reported scores to 100. Are there any previous studies or citations that have reported rescaling of the scores to 100?

- Figures - please clarify what the word prevalence indicates ? Is it the % of those included in each of the studies that reported the symptom? Please provide that explanation in the Figure legend.

Any attachments provided with reviews can be seen via the following link:

[LINK]

1 Feb 2022

Submitted filename: Response to editors BF01022022.docx

Click here for additional data file.

14 Feb 2022

Dear Dr. Fletcher,

Thank you very much for re-submitting your manuscript "Symptom burden and health-related quality of life in chronic kidney disease: a global systematic review and meta-analysis." (PMEDICINE-D-21-01326R3) for review by PLOS Medicine.

I have discussed the paper with my colleagues and the academic editor and it was also seen again by one of the reviewers. I am pleased to say that provided the remaining editorial and production issues are dealt with we are planning to accept the paper for publication in the journal.

The remaining issues that need to be addressed are listed at the end of this email. Any accompanying reviewer attachments can be seen via the link below. Please take these into account before resubmitting your manuscript:

[LINK]

***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***

In revising the manuscript for further consideration here, please ensure you address the specific points made by each reviewer and the editors. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments and the changes you have made in the manuscript. Please submit a clean version of the paper as the main article file. A version with changes marked must also be uploaded as a marked up manuscript file.

Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. If you haven't already, we ask that you provide a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract.

We expect to receive your revised manuscript within 1 week. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

We ask every co-author listed on the manuscript to fill in a contributing author statement. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT.

Please ensure that the paper adheres to the PLOS Data Availability Policy (see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it.

To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript.

Please note, when your manuscript is accepted, an uncorrected proof of your manuscript will be published online ahead of the final version, unless you've already opted out via the online submission form. If, for any reason, you do not want an earlier version of your manuscript published online or are unsure if you have already indicated as such, please let the journal staff know immediately at plosmedicine@plos.org.

If you have any questions in the meantime, please contact me or the journal staff on plosmedicine@plos.org.

We look forward to receiving the revised manuscript by Feb 21 2022 11:59PM.

Sincerely,

Caitlin Moyer, Ph.D.

Associate Editor

PLOS Medicine

plosmedicine.org

------------------------------------------------------------

Requests from Editors:

1. Title: Please capitalize the first word of the subtitle, please remove the punctuation after “meta-analysis” and please be sure to update the title in the manuscript submission system: “Symptom burden and health-related quality of life in chronic kidney disease: A global systematic review and meta-analysis”

2. Abstract: Methods and Findings: Please report the p values in addition to the 95% CIs for quality of life measures compared between patients on dialysis and patients not on RRT, or those who received kidney transplant, rather than reporting as p<0.01.

3. Throughout: In-text reference call-outs: Please include a space between the end of the preceding word and the bracketed reference number, for example [1].

4. Results: Lines 373-376: Please provide a reference in the text to where the data of exploratory analyses comparing HRQOL scores between populations can be found.

5. Discussion: Line 450: Please replace “compliance” with “adherence” in this sentence.

6. Discussion: Line 459: We suggest removing the URL from the text, and including the website in the reference list.

7. Discussion: Please slightly re-organize the discussion as follows. After the discussion of strengths and limitations of the study, please discuss the implications and next steps for research, clinical practice, and/or public policy, followed by your one-paragraph Conclusion.

8. Lines 508-542: Please remove the “Funding and Conflicts of Interest” section from the main text, and please be sure all information is complete and accurately entered into the manuscript submission system.

9. Figure 1: Please define all abbreviations (PROM, CKD) in the legend.

10. Figure 2: Please define all abbreviations (CKD, RRT) in the legend.

11. Figure 3 (all parts): A short description of the symptom severity score would be helpful in the legend. Please also explain the vertical line at the score of 50. Please define all abbreviations (RRT, CKD) in the legend.

12. Figure 4: It would be helpful if the categories could be made to stand out more easily (Control, Patients not on RRT, etc. ).Please define all abbreviations used in the legend.

13. Figure 5: Please define all abbreviations used (CKD, RRT) in the legend.

14. Figure 6: Please change “lowerci” and “upperci” to Lower CI/Upper CI to match the formatting in other tables. In the legend, please define all abbreviations used. Please define all abbreviations (CKD, RRT) in the legend.

15. Figure 7: In the legend, please clarify if “yes” and “no” correspond to the question of risk of bias, or with the adequacy appraisal (being reported as adequate or not).

16. Table 1: Please note that the full list of countries represented is not included. We suggest including the full list, if not in Table 1, please include such a list and please mention where a full list of the 62 countries may be found.

17. Table 2: Please provide some additional context for the different PROM described in the legend. Please define “RRT” in the legend.

18. Table 3: Please define all abbreviations (e.g. HRQOL, CKD) in the legend.

19. We suggest providing a short descriptive legend for each Supporting Information Table.

20. S3 Appendix: Please define all abbreviations used in a legend for the Table.

21. S8 Appendix: Please provide a descriptive legend for each tab in the file, including defining all abbreviations used and clarifying the values presented in red for prevalence and severity quartile tabs.

Comments from Reviewers:

Reviewer #2: This revision is much improved and adequately addressed my prior concerns. There are multiple spelling errors throughout the manuscript. For example, "clincial" on page 34, "acurate" on page 35. "Finaly" on page 36. Please carefully correct any spelling/grammatical errors.

Additionally, please clarify what "latter group" on the beginning of page 35 refers to. Please ensure each Table and Figure has footnote definition for RRT and HRQOL, as appropriate.

Any attachments provided with reviews can be seen via the following link:

[LINK]

21 Feb 2022

Submitted filename: Response to editors BF21022022.docx

Click here for additional data file.

23 Feb 2022

Dear Dr Fletcher,

On behalf of my colleagues and the Academic Editor, Sanjay Basu, I am pleased to inform you that we have agreed to publish your manuscript "Symptom burden and health-related quality of life in chronic kidney disease: A global systematic review and meta-analysis." (PMEDICINE-D-21-01326R4) in PLOS Medicine.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. Please be aware that it may take several days for you to receive this email; during this time no action is required by you. Once you have received these formatting requests, please note that your manuscript will not be scheduled for publication until you have made the required changes.

Please also address the following editorial requests:

-S3 Appendix, S6 Appendix, S8 Appendix, and S10 Appendix: We suggest moving the descriptive legends to a fixed location of the file (a row just below the title, for example) rather than placing it within a text box over the table.

-S8 Appendix: In the legend, please define “predialysis” as those not on RRT (similar to the main text). Please include legends for “Prevalence quartiles” and “Severity quartiles” tabs, including an explanation for the values in red font.

In the meantime, please log into Editorial Manager at http://www.editorialmanager.com/pmedicine/, click the "Update My Information" link at the top of the page, and update your user information to ensure an efficient production process.

PRESS

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To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Thank you again for submitting to PLOS Medicine. We look forward to publishing your paper.

Sincerely,

Caitlin Moyer, Ph.D.

Associate Editor

PLOS Medicine