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. 2024 Mar 11;19(3):e0300259. doi: 10.1371/journal.pone.0300259

Characteristics and clinical outcomes of patients with kidney failure of unknown aetiology from ANZDATA registry

Lucy S Wang 1, Venkat Vangaveti 2,3, Monica S Y Ng 1,4,5,‡,*, Andrew J Mallett 2,3,4,6,‡,*
Editor: Mohamed E Elrggal7
PMCID: PMC10927112  PMID: 38466666

Abstract

Introduction

Kidney failure of unknown aetiology (uESKD) is also heavily location dependent varying between 27% in Egypt to 54% in Aguacalientes, Mexico. There is limited information about the characteristics of people with uESKD in Australia and New Zealand, as well as their clinical outcomes on kidney replacement therapy.

Methods

Data on people commencing kidney replacement therapy 1989–2021 were received from the Australia and New Zealand Dialysis and Transplant (ANZDATA) registry. Primary exposure was cause of kidney failure–uESKD or non-uESKD (known-ESKD). Primary outcome was mortality. Secondary outcome was kidney transplantation. Dialysis and transplant cohorts were analysed separately. Cox Proportional Hazards Regression models were used to evaluate correlations between cause of kidney failure and mortality risk. Subgroup analyses were completed to compare mortality risk in people with uESKD to those with diabetic nephropathy, autosomal dominant polycystic kidney disease (ADPKD), glomerular disease and other kidney diseases.

Results

This study included 60,448 people on dialysis and 20,859 transplant recipients. 1-year, 3-year and 5-year mortality rates in people with uESKD on dialysis were 31.6%, 58.7% and 77.2%, respectively. 1-year, 3-year and 5-year mortality rates in transplant recipients with uESKD were 2.8%, 13.8% and 24.0%, respectively. People with uESKD on dialysis had a higher mortality risk compared to those without uESKD on univariable and multivariable analyses (adjusted hazard ratio [AHR] 1.10, 95% CI 1.06–1.16, p<0.001). Transplant recipients with uESKD have a higher mortality risk compared to those without uESKD on univariable and multivariable analyses (AHR 1.17, 95% CI 1.01–1.35, p<0.05). People with uESKD had similar likelihood of kidney transplantation compared to people with known-ESKD.

Conclusion

People with uESKD on kidney replacement therapy have higher mortality risk compared to people with other kidney diseases. Further studies are required to identify contributing factors to these findings.

Introduction

Kidney failure of unknown aetiology (uESKD) is also heavily location dependent varying between 27% in Egypt to 54% in Aguacalientes, Mexico [1–3]. uESKD is defined as kidney failure cases where there other causes of kidney diseases such as diabetes, hypertension, glomerular disease have been excluded as potential causes [1]. Inroads to identify causes of uESKD have been made with advances in genetic kidney diagnoses, however, 80% of initially uESKD remains without a causal diagnosis [4]. Therefore, there are no cause-specific treatment options, disease recurrence risks are unquantifiable and referral for transplant may be delayed due to uncertain recurrence risk. There is limited information about the characteristics of this group of patients; as well as their clinical outcomes after KRT initiation, including mortality risk and likelihood of kidney transplantation. Information about clinical outcomes of people with uESKD is essential to guide disease prognostication, patient counselling and KRT modality selection. This Australian and New Zealand Dialysis and Transplant (ANZDATA) registry analysis aimed to profile, at a population level, the characteristics, mortality risk and likelihood of kidney transplantation for people receiving KRT due to uESKD. We hypothesised that people with uESKD would have similar mortality risk and reduced likelihood of kidney transplantation compared to people with known-ESKD.

Materials and methods

Study population

This population-based cohort study included people over 18 years old who initiated kidney replacement therapy in Australia and New Zealand between 1 January 1989–31 December 2021. Demographic, comorbidity, kidney failure and outcome data were extracted from the Australia and New Zealand Dialysis and Transplant (ANZDATA) registry in de-identified format and accessed on 1st April 2022. This access did not include access to information that could identify individual participants during or after data collection. The dialysis cohort included all adults who received dialysis as sole kidney replacement therapy modality (Fig 1). The transplant cohort included all adults who received a kidney transplant (Fig 1). Ethics approvals were received from ANZDATA executive (Request ID: 42579) and Metro North Human Research and Ethics Committee (Reference: LNR/2019/QRBW/58238). Written informed consent to the ANZDATA Registry was not required as a national quality assurance registry program. This study was reported per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines [5].

Fig 1. Flow chart demonstrating stratification of patient cohorts.

Fig 1

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Variables

Primary exposure was kidney disease type classified as kidney failure of unknown aetiology (uESKD) or non-uESKD (known-ESKD) based on kidney failure cause codes in ANZDATA. Cases not caused by diabetic nephropathy, glomerular disease, hypertension or any other identifiable cause are classified as uESKD in ANZDATA. In ANZDATA, cause of kidney failure is denoted by treating kidney specialist based on clinical features and may not be biopsy- nor genetically- proven. Primary outcomes measures were mortality in the dialysis and transplant cohort; and kidney transplantation in all patients on KRT. Age and comorbidities were recorded at time of dialysis commencement for dialysis cohort and time of kidney transplant in transplant cohort. Age was classified by 10 year intervals. Comorbidities included diabetes, coronary artery disease and peripheral vascular disease which were denoted by treating kidney specialist. First KRT modality included haemodialysis, peritoneal dialysis and pre-emptive transplant. Dialysis and transplant era were classified in 10 year intervals.

Statistical analysis

Baseline variables were summarised using counts and percentages and assessed by χ2 tests of independence with Bonferroni correction for multiple testing (S1 and S2 Tables). Continuous variables were assessed with one way Analysis of Variance (ANOVA) with Bonferroni correction. Results were considered statistically significant if p<0.005.

Median follow-up time for dialysis and transplant cohorts was calculated using reverse Kaplan-Meier estimator. Univariable and multivariable Cox proportional hazards models were used to calculate the association between exposures and covariables with outcome variables (mortality, kidney transplantation). In the dialysis cohort analyses, covariates included gender, ethnicity, smoking status, body mass index (BMI) diabetes status, first dialysis modality and dialysis vintage. In the transplant cohort analyses; recipient gender, ethnicity, age, smoking status BMI, comorbidities, first KRT modality, human leukocyte antigen (HLA) mismatch and transplant era were included as covariates. In the kidney transplantation analyses, recipient gender, ethnicity, age, smoking status BMI, comorbidities, first KRT modality, HLA mismatch and transplant era were included as covariates. Hazard ratios (HRs) and 95% confident intervals (CIs) were calculated for each characteristic. Results were considered statistically significant if p<0.05.

In sensitivity analyses, Cox proportional hazard models were calculated for primary outcomes with non-ESKD were subclassified into diabetic nephropathy, glomerular disease, autosomal dominant polycystic kidney disease (ADPKD) and other kidney diseases (S1 Table). Diabetic nephropathy, glomerular disease and ADPKD were selected as each disease has known demographic features and outcomes. Hypertension was classified with other kidney diseases as it is unclear if hypertension is the cause of kidney failure or consequence an undiagnosed kidney disease [6]. Adjusted sub-distribution HRs (ASHRs) were generated using Fine and Gray’s proportional hazards models where mortality and kidney transplantation were competing risks [7]. Results were considered statistically significant if p<0.05.

Only complete cases were included in the analyses. All analyses were conducted in SPSS software (IBM Corp. Released 2021. IBM SPSS Statistics for Windows, Version 28.0. Armonk, NY: IBM Corp).

Results

Participant demographics

Sixty thousand four hundred and forty-eight people on dialysis were included in the study with 3,640 people with uESKD, 24,513 people with diabetic nephropathy, 10,450 people with glomerular disease, 2,188 people with ADPKD and 19,657 with other kidney disease (Fig 1 and S2 Table). Twenty thousand eight hundred and fifty-nine people received kidney transplants– 880 recipients had uESKD, 2,458 recipients had diabetic nephropathy, 8,957 recipients had glomerular disease, 2,831 recipients had ADPKD and 5,733 recipients had other kidney disease (S3 Table). Median follow-up times for the dialysis and transplant cohorts were 10 years and 14 years respectively.

Mortality

In people on dialysis, 1 year, 3 year and 5 year mortality rates were 19.2%, 39.7% and 53.1% respectively (S2 Table). People on dialysis with uESKD had increased mortality risk compared to people with known-ESKD (AHR 1.10, 95% CI 1.06–1.16, Table 1) on multivariable analysis. On subgroup analysis, people with uESKD had similar mortality risk compared to other kidney diseases (S4 Table). Kidney transplant recipients had 1 year, 3 year and 5 year mortality rates of 0.6%, 2.4% and 4.7% respectively (S3 Table). Kidney transplant recipients with uESKD had increased mortality risk compared to those with known-ESKD (AHR 1.17, 95% CI 1.01–1.35, Table 2). On subgroup analysis, recipients with uESKD had similar mortality risk to those with other kidney diseases (S5 Table). Recipients with glomerular disease or ADPKD had reduced mortality risk while those with diabetic nephropathy had increased mortality risk.

Table 1. Unadjusted + adjusted hazard ratios + 95% CI for association between kidney disease and mortality in dialysis cohort.

Effect Unadjusted Adjusted
HR 95% CI HR 95% CI
Disease status
 uESKD 1.15*** 1.11–1.20 1.10*** 1.06–1.16
 Known-ESKD Ref Ref
Gender
 Male Ref Ref
 Female 0.93*** 0.91–0.95 1.01 1.05–1.1
Ethnicity
 White Ref Ref
 Non-white 0.75*** 0.73–0.76 0.87*** 0.85–0.89
Age
 < 20 Years Ref Ref
 20–39 Years 0.72*** 0.61–0.86 0.70*** 0.58–0.84
 40–59 Years 1.30** 1.09–1.54 1.18 0.98–1.4
 60–79 Years 1.84*** 1.53–2.10 1.62*** 1.35–1.94
Smoking status
 Never Ref Ref
 Former 1.17*** 1.14–1.19 1.07** 1.05–1.10
 Current 1.07*** 1.04–1.11 1.21*** 1.17–1.25
BMI (kg/m2)
 <18.5 Ref Ref
 18.5–24.9 0.85*** 0.81–0.90 0.76*** 0.72–0.80
 25–29.9 0.81*** 0.77–0.85 0.71*** 0.67–0.75
 >30 0.71*** 0.67–0.75 0.67*** 0.64–0.72
Comorbidities
 Diabetes mellitus 1.03*** 1.01–1.05 1.19*** 1.16–1.21
 Coronary artery disease 1.57*** 1.54–1.60 1.27*** 1.24–1.30
 Peripheral vascular disease 1.49*** 1.46–1.52 1.23*** 1.20–1.26
First KRT modality
 Haemodialysis Ref Ref
 Peritoneal dialysis 1.03** 1.01–1.05 1.01 0.99–1.04
Dialysis vintage
 1989–1998 Ref Ref
 1999–2008 0.85*** 0.83–0.87 0.85*** 0.83–0.88
 2009–2018 0.67*** 0.66–0.69 0.69*** 0.67–0.71
 2018–2021 0.33*** 0.31–0.36 0.37*** 0.34–0.41
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Abbreviations: BMI = body mass index, CI = confidence interval, HR = hazard ratio, KRT = kidney replacement therapy, ref = reference, uESKD = kidney failure of unknown aetiology.

Significance level:

*<0.05

**<0.01

***<0.001.

Table 2. Unadjusted + adjusted hazard ratios and 95% CI for association between kidney disease status and mortality in transplant cohort.

Effect Unadjusted Adjusted
HR 95% CI HR 95% CI
Recipient disease status
 uESKD 1.17* 1.03–1.33 1.17* 1.01–1.35
 Known-ESKD Ref Ref
Recipient gender
 Male Ref Ref
 Female 0.86*** 0.82–0.91 0.96 0.90–1.02
Recipient ethnicity
 White Ref Ref
 Non-white 0.82*** 0.77–0.87 0.81*** 0.76–0.88
Recipient age
 < 20 Years Ref Ref
 20–39 Years 1.56*** 1.31–1.86 1.27*** 1.03–1.58
 40–59 Years 4.11*** 3.48–4.84 3.53*** 2.87–4.34
 60–79 Years 8.1*** 6.89–9.65 7.36*** 5.95–9.10
Recipient smoking status
 Never Ref Ref
 Former 1.67*** 1.57–1.77 1.22*** 1.14–1.31
 Current 1.75*** 1.61–1.90 1.76*** 1.62–0.92
Recipient BMI (kg/m2)
 <18.5 Ref Ref
 18.5–24.9 1.58*** 1.38–1.81 0.79** 0.68–0.92
 25–29.9 2.12*** 1.85–2.44 0.84* 0.72–0.99
 >30 2.40*** 2.08–2.77 0.94 0.80–1.11
Recipient comorbidities
 Diabetes mellitus 2.7*** 2.61–2.98 2.03*** 1.87–2.20
 Coronary artery disease 2.58*** 2.40–2.78 1.30*** 1.19–1.42
 Peripheral vascular disease 2.89*** 2.63–3.17 1.48*** 1.32–1.64
First KRT modality
 Haemodialysis Ref Ref
 Peritoneal dialysis 0.96 0.91–0.10 1.05 0.98–1.12
 Pre-emptive 0.54*** 0.47–0.61 0.73*** 0.64–0.84
HLA mismatch
 0 Mismatch Ref Ref
 1–3 Mismatch 1.23*** 1.08–1.40 1.25** 1.08–1.44
 4–6 Mismatch 1.36*** 1.19–1.55 1.35*** 1.16–1.56
Transplant era
 1989–1998 Ref Ref
 1999–2008 0.74*** 0.70–0.79 0.68*** 0.63–0.73
 2009–2018 0.65*** 0.60–0.711 0.42*** 0.38–0.46
 2018–2021 0.38*** 0.27–0.52 0.21*** 0.15–0.29
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Abbreviations: BMI = body mass index, HLA = human leukocyte antigen, KRT = kidney replacement therapy, ref = reference, uESKD = kidney failure of unknown aetiology.

Significance level:

*<0.05

**<0.01

***<0.001.

Kidney transplantation

People with uESKD on KRT had similar likelihood of kidney transplantation compared to people with known-ESKD (Table 3). On subgroup analysis, uESKD had similar kidney transplantation compared to people with other kidney diseases (S6 Table). Death censored kidney transplantation was increased in people with uESKD compared to people with known-ESKD (AHR 1.24, 95% CI 1.18–1.29, S7 Table). Demographic features such as age between 40–59 years old, BMI between 25–29.9, peritoneal dialysis as first KRT modality and more recent KRT initiation were associated with increased likelihood of kidney transplant. People of female gender, age between 60–79 years old and current smoking status with comorbidities were associated with reduced likelihood of kidney transplant.

Table 3. Unadjusted + adjusted hazard ratios + 95% CI for association between kidney disease status and kidney transplantation.

Effect Unadjusted Adjusted
HR 95% CI HR 95% CI
Disease status
 uESKD 1.01 0.94–1.08 0.99 0.94–1.08
 Known-ESKD Ref Ref
Gender
 Male Ref Ref
 Female 0.85*** 0.83–0.88 0.84*** 0.81–0.86
Ethnicity
 White Ref Ref
 Non-white 1.00 0.97–1.03 0.92*** 0.89–0.95
Age
 < 20 Years Ref Ref
 20–39 Years 0.87*** 0.82–0.92 0.97 0.95–1.1
 40–59 Years 1.26*** 1.19–1.32 1.38*** 1.30–1.46
 60–79 Years 0.89*** 0.844–0.95 0.86** 0.85–0.97
Smoking status
 Never Ref Ref
 Former 1.03 0.99–1.06 1.02 0.99–1.06
 Current 0.83*** 0.80–0.88 0.89*** 0.85–0.94
BMI (kg/m2)
 <18.5 Ref Ref
 18.5–24.9 1.04 0.98–1.1 1.05 0.98–1.1
 25–29.9 1.27*** 1.19–1.35 1.14*** 1.06–1.22
 >30 1.28*** 1.2–1.36 1.05 0.97–1.1
Comorbidities
 Diabetes mellitus 0.76*** 0.73–0.79 0.62*** 0.60–0.65
 Coronary artery disease 0.68*** 0.65–0.71 0.80*** 0.76–0.84
 Peripheral vascular disease 0.62*** 0.58–0.66 0.83*** 0.78–0.89
First KRT modality
 Haemodialysis Ref Ref
 Peritoneal dialysis 1.2*** 1.20–1.28 1.24*** 1.20–1.28
 Pre-emptive 2.1*** 2.0–2.2 1.54*** 1.46–0.1.61
KRT onset year
 1989–1998 Ref Ref
 1999–2008 3.07*** 2.9–3.2 3.6*** 3.4–3.8
 2009–2018 23.8*** 22.4–25.41 32.7*** 30.5–35.0
 2018–2021 304.5*** 266.7–347.7 468.8*** 406.4–540.9
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Abbreviations: ATSI = Aboriginal and Torres Strait Islander, BMI = body mass index, HR = hazard ratio, KRT = kidney replacement, therapy, ref = reference, uESKD = kidney failure of unknown aetiology.

Significance level:

*<0.05

**<0.01

***<0.001.

Discussion

This study showed that people with uESKD have increased mortality risk but similar likelihood of kidney transplantation compared to people with known-ESKD. The prevalence of uESKD in people on dialysis and transplant was 6.0% and 4.2% respectively, which is lower than rates in United Kingdom (14.9%) [8], Europe (17.0%) [9], Brazil (24%) [10] and Mexico (54%) [3]. This difference in uESKD prevalence is likely multifactorial in the context of different occupational and environmental exposures; and access/utilisation of advanced diagnostic tests such as genetic testing. The high prevalence of uESKD in Mexico has been linked to intense work in strong heat, increased environmental degradation with exposure to heavy metals, widespread use of pesticides and reduced access to diagnostic testing to identify the cause of kidney failure [11].

People with uESKD on dialysis had increased mortality risk compared to people with known-ESKD. On subgroup analysis, uESKD had increased mortality risk compared to diabetic nephropathy, glomerular disease and ADPKD. Reasons for this finding is likely multifactorial–absence of cause-specific treatment for extra-kidney manifestations, older age at KRT initiation and socioeconomic factors. These results are different to those reported by Gutierrez-Peña et al. where people in Aguascalientes, Mexico, on KRT with uESKD had superior survival compared to those with known-ESKD on age-adjusted analyses [3]. In the aforementioned study, a significant proportion of known-ESKD participants had diabetic nephropathy which was associated with inferior mortality outcomes compared to people with other causes of kidney failure [3].

Kidney transplant recipients with uESKD have increased mortality risk compared to those known-ESKD. On subgroup analysis, uESKD performed similarly compared to other kidney diseases. Glomerular disease and ADPKD were associated with superior post-transplant mortality outcomes compared to those with other kidney diseases–likely contributing to the outcomes seen in the binary (uESKD vs. known-ESKD) exposure analyses. A previous ANZDATA analysis identified that transplant recipients with uESKD had similar mortality risk compared to recipients with commonly-recurring glomerular diseases [12]. Commonly-recurring glomerular diseases carry higher mortality risks associated with increased risk of graft failure and higher immunosuppression burden [12]. Graft failure data was not accessible to test this hypothesis. The finding that recipients with uESKD have similar mortality risk compared to other kidney diseases was also identified in an USRDS study of younger transplant recipients [13].

People on KRT with uESKD had similar likelihood of kidney transplantation compared to people with known-ESKD. On death-censored kidney transplantation, people with uESKD had higher kidney transplantation rates compared to people with known-ESKD suggesting that the increased mortality risk of people with uESKD may be contributing to the results seen in the headline analyses. All people on KRT were included in the kidney transplantation analyses, however an unknown proportion would have been deemed unsuitable for transplantation. As such, it was not possible to assess kidney transplantation solely in those who were suitable for transplantation. Subset analysis of patients suitable for transplantation will be possible in the future with the recent addition of “suitability for kidney transplant” in ANZDATA data collection.

In this study, uESKD performed similarly to other causes of kidney failure in subgroup analyses for demographics, mortality and kidney transplantation, suggesting that uESKD may overlap with conditions in the “other kidney disease” category. Chronic kidney disease of uncertain aetiology (CKDu) observed in low and middle income countries mainly occurs in agricultural communities affecting young males [14]. In our analyses, uESKD was associated with increased age which may be due to reduced appetite for higher risk diagnostic procedures such as kidney biopsies in older people with atrophic kidneys [15]. This disparity further signals that uESKD as recorded in ANZDATA is different to CKDu reported elsewhere and that uESKD is highly jurisdiction-dependent. Further study is required to elucidate the potential genetic, occupational, and environmental factors causing uESKD in Australia and New Zealand.

Limitations included the use of retrospective observational data, thereby confounded by measurement bias, and unmeasured factors not collected by ANZDATA. Primary kidney disease classifications in ANZDATA are based on clinician classification as the dominant cause, and are not always biopsy- or genetically-proven. Furthermore, advances in diagnostic approaches and disparities in access to such diagnostics can lead to inconsistencies in uESKD definition across regions and over time.

Conclusions

People with uESKD on KRT had increased mortality risks compared to known-ESKD. uESKD has similar likelihood of kidney transplantation compared to known-ESKD. On subgroup analysis, the uESKD group had similar demographic features compared to other kidney diseases and performed similarly on outcome measures, suggesting that uESKD may include people with “other kidney diseases”. Further studies are required to confirm this hypothesis and correlated uESKD recorded in ANZDATA to CKDu in other jurisdictions.

Supporting information

S1 Table. Breakdown of kidney failure causes in other kidney disease group.

(DOCX)

pone.0300259.s001.docx (20.2KB, docx)
S2 Table. Characteristics and medical conditions of the dialysis cohort.

(DOCX)

pone.0300259.s002.docx (24.7KB, docx)
S3 Table. Characteristics and medical conditions of the transplant cohort.

(DOCX)

pone.0300259.s003.docx (25.7KB, docx)
S4 Table. Subgroup analysis evaluating association between kidney disease status and mortality in dialysis cohort.

(DOCX)

pone.0300259.s004.docx (19.1KB, docx)
S5 Table. Subgroup analysis evaluating association between kidney disease status and mortality in transplant cohort.

(DOCX)

pone.0300259.s005.docx (20.2KB, docx)
S6 Table. Subgroup analysis evaluating association between kidney disease status and kidney transplantation in KRT cohort.

(DOCX)

pone.0300259.s006.docx (19.8KB, docx)
S7 Table. Death-censored kidney transplantation competing risk analysis.

(DOCX)

pone.0300259.s007.docx (19.5KB, docx)
S8 Table. Modified STROBE statement.

(DOCX)

pone.0300259.s008.docx (22.1KB, docx)

Acknowledgments

The authors are grateful for the significant contributions of the Australian and New Zealand nephrology community (physicians, surgeons, database managers, nurses, people receiving KRT) in providing information for and maintaining the ANZDATA database. The data that supports the findings of this study were obtained from the ANZDATA–data request ID 42579. Restrictions apply to the availability of these data, which were used under license for this study. Data are available from www.anzdata.org.au, subject to the registry’s data release policies. MSYN acknowledges the Robert and Janelle Bird Postdoctoral Research Fellowship. AJM acknowledges support from a Queensland Health Advancing Clinical Research Fellowship.

Data Availability

Data Availability Statement The authors confirm that all data underlying the findings are fully available upon request and without restriction. The primary dataset for this manuscript was generated and made available to the authors by the Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry, Adelaide, Australia. Data used in this study belongs to the ANZDATA registry. Data stored in ANZDATA is collected and stored on behalf of all Australian and New Zealand renal units. The ANZDATA data usage agreement between the ANZDATA Registry and the authors does not allow the authors to make the data publicly available. The authors confirm that all data underlying the findings can be obtained without restriction directly from the ANZDATA Registry on request (email address requests@anzdata.org.au, website https://www.anzdata.org.au/anzdata/services/data-policies/). The authors of this paper did not access the data via special access privileges and only gained access to the data after the data request was approved by the ANZDATA.

Funding Statement

The author(s) received no specific funding for this work.

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Decision Letter 0

Mohamed E Elrggal

26 Nov 2023

PONE-D-23-34616Characteristics and clinical outcomes of patients with kidney failure of unknown aetiology from ANZDATA registryPLOS ONE

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Reviewer #1: Reviewers comments

Characteristics and clinical outcomes of patients with kidney failure of unknown etiology from ANZDATA registry

General comment

1. Well done to the authors for submitting this paper for possible publication

2. It will helpful to come up clearly with the definition of uESKD. It should have a diagnostic criteria clearly similar to literature and other studies authors hope to compare their study to.

3. Most sentences need a senior author to read through to conform to manuscript standards

4. CKDu is a fairly new area or study but there has been a lot of work with clear definitions I was hoping authors will explore

5. Sentences should not be started with roman numerals

Specific comments

Abstract

1. What is eESKD exactly. In terms of definition?

2. Law of first mention for uESKD and how was it defined?

3. ‘Dependent on the region, 16% of chronic kidney disease’…. Authors should state exactly the region they quoted.

4. Smoking cannot be considered as a cause of CKD and hence should stay as a risk factor.

Material and methods

5. Was wondering why the data set ends in 2021. Could the authors add on up to at least 2022?

6. It might be helpful to define clearly all terms used in the study here.

Results

7. I suggest autors do not start sentences with numbers in manuscript

8. “Age 40-59 years old, BMI 25-29.9, peritoneal dialysis as first KRT

modality and more recent KRT..”Most sentences can be well written as academic writing to make it easier to read. Like the example above. Many such in the write up

9. ‘…current smoking status and presence of comorbidities were associated with reduced likelihood of kidney transplant. Did authors assess the likelihood ratio?

Discussion

10. which is lower than rates in United Kingdom (14.9%) [7], Europe (17.0%) [8], Brazil (24%) [9] and Mexico (54%) [10]. It will be helpful to discuss why Mexico had such high prevalence or what makes the studies different from the UK, Europe and Brazil.

11. “People with uESKD on dialysis had increased mortality risk compared to people with non-uESKD. On subgroup analysis, uESKD had increased mortality risk compared to diabetic nephropathy, glomerular disease and ADPKD; but similar mortality risk compared to other kidney diseases.” It might be helpful to avoid long sentences of the results in the discussion.

12. Chronic kidney disease of uncertain aetiology (CKDu) observed in low and middle income countries mainly occurs in agricultural communities affecting young males [13]. It is fundamentally helpful to know the clear definition of uESKD in the registry. Did it meet a clear diagnostic criteria or just physician clinical judgement? Very difficult to compare to others with clear definition. …and are not always biopsy- or genetically-proven.” What proportions were biopsy proven then?” Will the findings be different with biopsy proven diagnosis?

13. Further study is required to elucidate the potential genetic, occupational, and environmental factors causing uESKD in Australia. Are there no reports at all or studies in New Zealand or Australia on the subject?

14. “Shortcomings included the use of retrospective observational data…”. I suggest limitation to the study might be a preferred term.

Conclusion

15. ‘People with uESKD on KRT had increased mortality risks compared to non-uESKD. uESKD has similar progression to kidney transplantation compared to uESKD’. Not clear in my mind the clear importance of this descriptive studies? what hypothesis or research question are authors seeking to generate or hoping to answer?

Reviewer #2: The manuscript entitled (Characteristics and clinical outcomes of patients with kidney failure of unknown aetiology from ANZDATA registry) discusses a quite important issue and highlights the prevalence and outcomes of ESRD of unknown etiology and these are my comments:

1- Abstract: correct the typo in (eESKD) in the 4th line of the introduction.

2- Materials and Methods, Statistical analysis:

a) You mentioned that baseline variables were summarised using counts and percentages and assessed by χ2 tests of independence (Table 1 and 2). In these tables, there are a lot of significant associations, so you need to perform the Bonferroni correction for a chi-square analysis for multiple comparisons.

b) In Table S2, there are some continuous variables (for example; dialysis vintage) you should mention the statistical test used.

3- Please mention what was the basis of the classification of causes of ESKD and why hypertension was not considered in your classifications.

4- Other causes of ESKD constituted a large number of your cohort. They were approximately one-third of the dialysis cohort. Please identify these causes and the percentage of each cause.

5- do you have actual numbers for cases with definite diagnosis by renal biopsy or genetic testing?

6- In my opinion, the term ''progression'' to kidney transplant is not proper and it may be better to change it to receiving kidney transplant.

**********

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Reviewer #2: No

**********

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PLoS One. 2024 Mar 11;19(3):e0300259. doi: 10.1371/journal.pone.0300259.r002

Author response to Decision Letter 0

30 Dec 2023

Responses to Editorial and Reviewer Queries PONE-D-23-34616 “Characteristics and clinical outcomes of patients with kidney failure of unknown aetiology from ANZDATA registry”

Editorial Team

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming.

- We have reviewed and completed this.

2. Thank you for stating the following in the Competing Interests section:

"I have read the journal's policy and the authors of this manuscript have the following competing interests: "M.S.Y.N. has received research grants and travel sponsorships from Avant Foundation and postdoctoral research fellowship from Royal Brisbane and Women’s Hospital Foundation."

Please confirm that this does not alter your adherence to all PLOS ONE policies on sharing data and materials, by including the following statement: "This does not alter our adherence to PLOS ONE policies on sharing data and materials.” (as detailed online in our guide for authors http://journals.plos.org/plosone/s/competing-interests). If there are restrictions on sharing of data and/or materials, please state these. Please note that we cannot proceed with consideration of your article until this information has been declared.

Please include your updated Competing Interests statement in your cover letter; we will change the online submission form on your behalf.

- This has now been updated to the following and we are thankful for your actioning in the online submission form:

“Conflict of Interest Statement

M.S.Y.N. has received research grants and travel sponsorships from Avant Foundation and postdoctoral research fellowship from Royal Brisbane and Women’s Hospital Foundation. This does not alter our adherence to PLOS ONE policies on sharing data and materials.”

3. In your Data Availability statement, you have not specified where the minimal data set underlying the results described in your manuscript can be found. PLOS defines a study's minimal data set as the underlying data used to reach the conclusions drawn in the manuscript and any additional data required to replicate the reported study findings in their entirety. All PLOS journals require that the minimal data set be made fully available. For more information about our data policy, please see http://journals.plos.org/plosone/s/data-availability.

"Upon re-submitting your revised manuscript, please upload your study’s minimal underlying data set as either Supporting Information files or to a stable, public repository and include the relevant URLs, DOIs, or accession numbers within your revised cover letter. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories. Any potentially identifying patient information must be fully anonymized.

Important: If there are ethical or legal restrictions to sharing your data publicly, please explain these restrictions in detail. Please see our guidelines for more information on what we consider unacceptable restrictions to publicly sharing data: http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions. Note that it is not acceptable for the authors to be the sole named individuals responsible for ensuring data access.

We will update your Data Availability statement to reflect the information you provide in your cover letter.

- Similar to other analyses published in PLOS ONE using data provided by the ANZDATA registry, the Data Availability statement has been updated to:

“Data Availability Statement

The authors confirm that all data underlying the findings are fully available upon request and without restriction. The primary dataset for this manuscript was generated and made available to the authors by the Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry, Adelaide, Australia. Data used in this study belongs to the ANZDATA registry. Data stored in ANZDATA is collected and stored on behalf of all Australian and New Zealand renal units. The ANZDATA data usage agreement between the ANZDATA Registry and the authors does not allow the authors to make the data publicly available. The authors confirm that all data underlying the findings can be obtained without restriction directly from the ANZDATA Registry on request (email address requests@anzdata.org.au, website https://www.anzdata.org.au/anzdata/services/data-policies/). The authors of this paper did not access the data via special access privileges and only gained access to the data after the data request was approved by the ANZDATA.”

This Data Availability statement with PLOS data policies and aligns to previous recently published PLOS ONE articles utilising the same data source under the same circumstances and ANZDATA Data Access Agreement:

• https://doi.org/10.1371/journal.pone.0236396

• https://doi.org/10.1371/journal.pone.0293721

• https://doi.org/10.1371/journal.pone.0249000

4. Your ethics statement should only appear in the Methods section of your manuscript. If your ethics statement is written in any section besides the Methods, please delete it from any other section.

- This has been actioned.

 

Reviewer #1

General comment

Well done to the authors for submitting this paper for possible publication

1. It will helpful to come up clearly with the definition of uESKD. It should have a diagnostic criteria clearly similar to literature and other studies authors hope to compare their study to.

- Thank you for your comment. Notably, kidney failure of unknown aetiology (uESKD) in ANZDATA is denoted by treating kidney specialist. By definition, uESKD in ANZDATA is where there is no known cause for kidney failure which involves exclusion of other causes of kidney failure such as hypertension, diabetic nephropathy, glomerular disease and genitourinary disease. This definition is similar to the definition used by Gutierrez-Peña et al. in their study of uESKD in Mexico (CKJ 2021, 14(4): 1197-1206). The definition of uESKD has been clarified in the manuscript: Primary exposure was kidney disease type classified as kidney failure of unknown aetiology (uESKD) or non-uESKD based on kidney failure cause codes in ANZDATA. In ANZDATA, cause of kidney failure is denoted by treating kidney specialist based on clinical features and may not be biopsy proven. Cases not caused by diabetic nephropathy, glomerular disease, hypertension or any other identifiable cause are classified as uESKD in ANZDATA.

2. Most sentences need a senior author to read through to conform to manuscript standards

- Sentences in the manuscript has been adjusted as suggested.

3. CKDu is a fairly new area or study but there has been a lot of work with clear definitions I was hoping authors will explore.

- CKDu is a diagnosis of exclusion – where there is no other cause of kidney disease identified. While current articles propose potential causes of CKDu such as nephrotoxins (e.g. lead, cadmium, aristolochic acid, arsenic, other environmental causes) – there is no clear cause and therefore no clear definition (BMC nephrology 2015, 16:145). In population studies, CKDu is characterised by kidney failure in young and middle aged adults with male predominance in low income agricultural communities with absence of known causes of chronic kidney disease. People with CKDu have bland urine sediment, minimal proteinuria and interstitial fibrosis +/- non-specific glomerular damage on biopsy (BMC nephrology 2015, 16:145; CKJ 2021, 14(4): 1197-1206).

Notably, Australia/New Zealand is geopolitically and socioeconomically quite different to locales with CKDu and one of the key findings of this study is that uESKD as defined in ANZDATA is not the same as CKDu seen low income agricultural communities. It may include some CKDu by definition – “kidney disease of known aetiology” but the demographic and outcome data suggest that uESKD is more likely to align the other kidney diseases group in ANZDATA. This is directly stated in our discussion:

In this study, uESKD performed similarly to other causes of kidney failure in subgroup analyses for demographics, mortality and progression to transplant, suggesting that uESKD may overlap with conditions in the “other kidney disease” category. Chronic kidney disease of uncertain aetiology (CKDu) observed in low and middle income countries mainly occurs in agricultural communities affecting young males [13]. In our analyses, uESKD was associated with increased age which may be due to reduced appetite for higher risk diagnostic procedures such as kidney biopsies in older people with atrophic kidneys [14]. This disparity further signals that uESKD as recorded in ANZDATA is different to CKDu reported elsewhere and that uESKD is highly jurisdiction-dependent. Further study is required to elucidate the potential genetic, occupational, and environmental factors causing uESKD in Australia.

4. Sentences should not be started with roman numerals

- Sentence beginning with roman numerals have been amended.

Specific comments

Abstract

1. What is uESKD exactly. In terms of definition?

- Kidney failure of unknown aetiology (uESKD) in ANZDATA is defined as causes of kidney failure where there is no cause found which involves exclusion of other causes of kidney failure such as hypertension, diabetic nephropathy, glomerular disease and genitourinary disease. This diagnosis is denoted by treating kidney specialist. This definition is similar to the definition used by Gutierrez-Peña et al. in their study of uESKD in Mexico (CKJ 2021, 14(4): 1197-1206). The definition of uESKD has been clarified in the manuscript: Primary exposure was kidney disease type classified as kidney failure of unknown aetiology (uESKD) or non-uESKD based on kidney failure cause codes in ANZDATA. Cases not caused by diabetic nephropathy, glomerular disease, hypertension or any other identifiable cause are classified as uESKD in ANZDATA. In ANZDATA, cause of kidney failure is denoted by treating kidney specialist based on clinical features and may not be biopsy- nor genetically- proven.

2. Law of first mention for uESKD and how was it defined?

- uESKD is now defined in the second sentence as suggested: uESKD is defined as kidney failure cases where traditional risk factors, including diabetes, hypertension, smoking and obesity, and other primary renal diseases are excluded as potential causes

3. ‘Dependent on the region, 16% of chronic kidney disease’…. Authors should state exactly the region they quoted.

- In the original sentence the statistic was from India (BMC Nephrology 2015, 16:145). This sentence has been adjusted to the following to report on uESKD to better match with content of article: Kidney failure of unknown aetiology (uESKD) is also heavily location dependent varying between 27% in Egypt to 54% in Aguacalientes, Mexico [1-3].

4. Smoking cannot be considered as a cause of CKD and hence should stay as a risk factor.

- This sentence has been altered to the following as suggested: [1-3]. uESKD is defined as kidney failure cases where there other causes of kidney diseases such as diabetes, hypertension, glomerular disease have been excluded as potential causes.

Material and methods

1. Was wondering why the data set ends in 2021. Could the authors add on up to at least 2022?

- The data set ends at 2021 as ANZDATA is requires approximately 2 years for data to be available. Unfortunately, it is not possible to add data from 2022 as that data would not be available until next year.

2. It might be helpful to define clearly all terms used in the study here.

- Terms have been clarified in the variables section of the article. Notably, kidney disease and comorbidity are denoted by treating kidney specialist.

Results

1. I suggest autors do not start sentences with numbers in manuscript

- This has been corrected as requested in the article.

2. “Age 40-59 years old, BMI 25-29.9, peritoneal dialysis as first KRT modality and more recent KRT..”Most sentences can be well written as academic writing to make it easier to read. Like the example above. Many such in the write up

- The above sentences have been corrected to: Demographic features such as age between 40-59 years old, BMI between 25-29.9, peritoneal dialysis as first KRT modality and more recent KRT initiation were associated with increased likelihood of kidney transplant. People of female gender, age between 60-79 years old and current smoking status with comorbidities were associated with reduced likelihood of kidney transplant.

3. ‘…current smoking status and presence of comorbidities were associated with reduced likelihood of kidney transplant. Did authors assess the likelihood ratio?

- We assessed hazard ratio for association of demographic factors with outcomes of mortality and kidney transplant as we used Cox Proportional Hazard Regression modelling. These are reported in tables 1-3.

Discussion

1. Which is lower than rates in United Kingdom (14.9%) [7], Europe (17.0%) [8], Brazil (24%) [9] and Mexico (54%) [10]. It will be helpful to discuss why Mexico had such high prevalence or what makes the studies different from the UK, Europe and Brazil.

- The following sentence has been added to explain the high prevalence of uESKD in Mexico: The high prevalence of uESKD in Mexico has been linked to intense work in strong heat, increased environmental degradation with exposure to heavy metals, widespread use of pesticides and reduced access to diagnostic testing to identify the cause of kidney failure [10].

2. “People with uESKD on dialysis had increased mortality risk compared to people with non-uESKD. On subgroup analysis, uESKD had increased mortality risk compared to diabetic nephropathy, glomerular disease and ADPKD; but similar mortality risk compared to other kidney diseases.” It might be helpful to avoid long sentences of the results in the discussion.

- The sentences have been shortened as requested: People with uESKD on dialysis had increased mortality risk compared to people with non-uESKD. On subgroup analysis, uESKD had increased mortality risk compared to diabetic nephropathy, glomerular disease and ADPKD.

3. Chronic kidney disease of uncertain aetiology (CKDu) observed in low and middle income countries mainly occurs in agricultural communities affecting young males [13]. It is fundamentally helpful to know the clear definition of uESKD in the registry. Did it meet a clear diagnostic criteria or just physician clinical judgement? Very difficult to compare to others with clear definition. …and are not always biopsy- or genetically-proven.” What proportions were biopsy proven then?” Will the findings be different with biopsy proven diagnosis?

- As requested, we have clarified the definition of uESKD in ANZDATA in the methods section: Cases not caused by diabetic nephropathy, glomerular disease, hypertension or any other identifiable cause are classified as uESKD in ANZDATA. In ANZDATA, cause of kidney failure is denoted by treating kidney specialist based on clinical features and may not be biopsy- nor genetically- proven. The purpose of this study was to describe uESKD as reported in ANZDATA registry. We have noted in the discussion that uESKD as described in the ANZDATA registry is different to CKDu observed in low and middle income countries as the demographic is more consistent with unclassified “other” kidney diseases.

The proportion of diagnoses in this analysis that are biopsy proven are 23,640 (27.6%). We have reported number of biopsy proven diagnoses in each category in Supplementary Tables S1 and S2. Notably, many diagnoses (e.g. ADPKD, CAKUT, reflux nephropathy, diabetic nephropathy) are not diagnosed by biopsy – completing subgroup analyses on the biopsy-proven cohort would result in significant selection bias.

4. Further study is required to elucidate the potential genetic, occupational, and environmental factors causing uESKD in Australia. Are there no reports at all or studies in New Zealand or Australia on the subject?

- There are no linkage studies investigating genetic, occupational, environmental factors associated uESKD as described in ANZDATA which is different to CKDu as discussed previously.

5. “Shortcomings included the use of retrospective observational data…”. I suggest limitation to the study might be a preferred term.

- Shortcomings has been changed to limitations as requested.

Conclusion

1. ‘People with uESKD on KRT had increased mortality risks compared to non-uESKD. uESKD has similar progression to kidney transplantation compared to uESKD’. Not clear in my mind the clear importance of this descriptive studies? what hypothesis or research question are authors seeking to generate or hoping to answer?

- There is limited information on clinical outcomes of people with uESKD in Australia and New Zealand – particularly at a population level. There was concern considering that as the cause of uESKD is unknown; recurrence risk after kidney transplant is also unknown – potentially leading to reluctance for physicians to list patients for kidney transplant. Reassuringly, people with uESKD have similar transplantations rates as people with ESKD with a known cause. Furthermore, information regarding mortality risk in people with uESKD is important for counselling discussions. This is discussed in the second paragraph of the discussion. We have also added a sentence to discuss our hypotheses: We hypothesised that people with uESKD would have similar mortality risk and reduced kidney transplantation rates compared to people with non-uESKD.

 

Reviewer #2

The manuscript entitled (Characteristics and clinical outcomes of patients with kidney failure of unknown aetiology from ANZDATA registry) discusses a quite important issue and highlights the prevalence and outcomes of ESRD of unknown etiology and these are my comments:

1. Abstract: correct the typo in (eESKD) in the 4th line of the introduction.

- This this been corrected as suggested.

2. Materials and Methods, Statistical analysis:

a) You mentioned that baseline variables were summarised using counts and percentages and assessed by χ2 tests of independence (Table S1 and S2). In these tables, there are a lot of significant associations, so you need to perform the Bonferroni correction for a chi-square analysis for multiple comparisons.

- We performed Bonferroni correction as requested. This has been added to the methods section.

b) In Table S2, there are some continuous variables (for example; dialysis vintage) you should mention the statistical test used.

- Continuous variables were assessed using χ2 tests of independence reported with Bonferroni correction for multiple testing.

3. Please mention what was the basis of the classification of causes of ESKD and why hypertension was not considered in your classifications.

- The basis of the subgroup classification was to divide non-uESKD into subgroups with known demographic features and outcomes such as diabetic nephropathy, glomerular disease and ADPKD. In contrast, hypertension is a non-specific subgroup where it is unclear if hypertension is the cause or consequence of disease processes. This has been included in the methods section: Diabetic nephropathy, glomerular disease and ADPKD were selected as each disease has known demographic features and outcomes. Hypertension was classified with other kidney diseases as it is unclear if hypertension is the cause of kidney failure or consequence an undiagnosed kidney disease [6].

4. Other causes of ESKD constituted a large number of your cohort. They were approximately one-third of the dialysis cohort. Please identify these causes and the percentage of each cause.

- We have included causes of other ESKD in Table S1.

5. Do you have actual numbers for cases with definite diagnosis by renal biopsy or genetic testing?

- We have included number of biopsy-proven cases in Table S2 and S3. We do not have data on genetically-proven cases.

6. In my opinion, the term ''progression'' to kidney transplant is not proper and it may be better to change it to receiving kidney transplant.

- Thank you for your feedback. We have removed the word “progression” from kidney transplantation terminology in text.

Attachment

Submitted filename: uESKD KF_Response To Reviewers_PLOSOne Resubmission1.pdf

pone.0300259.s009.pdf (139.5KB, pdf)

Decision Letter 1

Mohamed E Elrggal

19 Feb 2024

PONE-D-23-34616R1Characteristics and clinical outcomes of patients with kidney failure of unknown aetiology from ANZDATA registryPLOS ONE

Dear Dr. Mallett,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

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1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

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Reviewer #1: Yes

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Thank you for the responses and congratulations to the authors.

Most comments have been well addressed.

I have no further comments for the authors

Reviewer #2: Thanks to the authors for the corrections and modifications that were made. I have few additional comments.

1- You classified them as uESKD and non-uESKD. In my opinion, it would sound better to replace non-uESKD with known ESKD.

2- In the results, you stated that the median follow-up time for the dialysis was 3 years. This indicates that at least 50% of the patients were followed for only 3 years. Then you mentioned that the mortality rate for people on dialysis at 5 years was 53.1%. I think these numbers need to be revised.

3- In conclusion; uESKD has similar likelihood of kidney transplantation compared to uESKD. Please revise and correct this sentence.

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Reviewer #1: Yes: Dr. Elliot Koranteng Tannor

Reviewer #2: No

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PLoS One. 2024 Mar 11;19(3):e0300259. doi: 10.1371/journal.pone.0300259.r004

Author response to Decision Letter 1

22 Feb 2024

Responses to Editorial and Reviewer Queries PONE-D-23-34616R1

“Characteristics and clinical outcomes of patients with kidney failure of unknown aetiology from ANZDATA registry”

Editorial Team

1. Thank you for response to our reviewers' comments. Still, some minor adjustments need to be made before final acceptance. Please address the reviewers' comments and send the manuscript back.

Thank you so much for your and the Reviewers’ time and input which we greatly value. We have addressed the additional queries below.

Reviewer #1

2. Thank you for the responses and congratulations to the authors. Most comments have been well addressed. I have no further comments for the authors.

We appreciate your input and previous queries.

Reviewer #2

3. You classified them as uESKD and non-uESKD. In my opinion, it would sound better to replace non-uESKD with known ESKD.

This is a good point which we take on board. The first instance of mentioning this in the abstract and main manuscript we have used the term “non-uESKD (known-ESKD)“ to signify what this group is and then used “known-ESKD” thereafter.

4. In the results, you stated that the median follow-up time for the dialysis was 3 years. This indicates that at least 50% of the patients were followed for only 3 years. Then you mentioned that the mortality rate for people on dialysis at 5 years was 53.1%. I think these numbers need to be revised.

Thank you for astutely pointing this out. We have investigated further and recalculated the median follow-up times using the reverse Kaplan-Meier estimator and have updates the results and statistical methodology accordingly. This methodology is more appropriate for calculating median follow-up times in cohorts such as this, and we thank the reviewer for identifying this. (New methods for estimating follow-up rates in cohort studies - PMC (nih.gov, PharmaSUG-2019-ST-081.pdf)

5. In conclusion; uESKD has similar likelihood of kidney transplantation compared to uESKD. Please revise and correct this sentence.

We have corrected this.

Attachment

Submitted filename: uESKD KF_Response To Reviewers_PLOSOne Resubmission2.pdf

pone.0300259.s010.pdf (76.7KB, pdf)

Decision Letter 2

Mohamed E Elrggal

26 Feb 2024

Characteristics and clinical outcomes of patients with kidney failure of unknown aetiology from ANZDATA registry

PONE-D-23-34616R2

Dear Dr. Mallett,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Mohamed E Elrggal

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Mohamed E Elrggal

1 Mar 2024

PONE-D-23-34616R2

PLOS ONE

Dear Dr. Mallett,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

* All references, tables, and figures are properly cited

* All relevant supporting information is included in the manuscript submission,

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Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

If we can help with anything else, please email us at customercare@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Mohamed E Elrggal

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Table. Breakdown of kidney failure causes in other kidney disease group.

    (DOCX)

    pone.0300259.s001.docx (20.2KB, docx)
    S2 Table. Characteristics and medical conditions of the dialysis cohort.

    (DOCX)

    pone.0300259.s002.docx (24.7KB, docx)
    S3 Table. Characteristics and medical conditions of the transplant cohort.

    (DOCX)

    pone.0300259.s003.docx (25.7KB, docx)
    S4 Table. Subgroup analysis evaluating association between kidney disease status and mortality in dialysis cohort.

    (DOCX)

    pone.0300259.s004.docx (19.1KB, docx)
    S5 Table. Subgroup analysis evaluating association between kidney disease status and mortality in transplant cohort.

    (DOCX)

    pone.0300259.s005.docx (20.2KB, docx)
    S6 Table. Subgroup analysis evaluating association between kidney disease status and kidney transplantation in KRT cohort.

    (DOCX)

    pone.0300259.s006.docx (19.8KB, docx)
    S7 Table. Death-censored kidney transplantation competing risk analysis.

    (DOCX)

    pone.0300259.s007.docx (19.5KB, docx)
    S8 Table. Modified STROBE statement.

    (DOCX)

    pone.0300259.s008.docx (22.1KB, docx)
    Attachment

    Submitted filename: uESKD KF_Response To Reviewers_PLOSOne Resubmission1.pdf

    pone.0300259.s009.pdf (139.5KB, pdf)
    Attachment

    Submitted filename: uESKD KF_Response To Reviewers_PLOSOne Resubmission2.pdf

    pone.0300259.s010.pdf (76.7KB, pdf)

    Data Availability Statement

    Data Availability Statement The authors confirm that all data underlying the findings are fully available upon request and without restriction. The primary dataset for this manuscript was generated and made available to the authors by the Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry, Adelaide, Australia. Data used in this study belongs to the ANZDATA registry. Data stored in ANZDATA is collected and stored on behalf of all Australian and New Zealand renal units. The ANZDATA data usage agreement between the ANZDATA Registry and the authors does not allow the authors to make the data publicly available. The authors confirm that all data underlying the findings can be obtained without restriction directly from the ANZDATA Registry on request (email address requests@anzdata.org.au, website https://www.anzdata.org.au/anzdata/services/data-policies/). The authors of this paper did not access the data via special access privileges and only gained access to the data after the data request was approved by the ANZDATA.

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