Impact of initial dialysis modality on the survival of patients with ESRD: A propensity-score-matched study

doi:10.21203/rs.3.rs-2481089/v1

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Impact of initial dialysis modality on the survival of patients with ESRD: A propensity-score-matched study

https://doi.org/10.21203/rs.3.rs-2481089/v1

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published 26 Oct, 2023

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Background

Studies comparing survival of hemodialysis (HD) and peritoneal dialysis (PD) patients are controversial. This study evaluated the impact of initial dialysis modality on the survival of patients with end-stage renal disease (ESRD) in a matched-pair cohort.

Methods

A retrospective cohort study was performed on ESRD patients who initiated renal replacement treatment between January 1, 2010, and December 31, 2018. Propensity score matching was applied to balance the baseline conditions, and multivariate Cox regression analysis was applied to compare mortality between HD and PD patients and evaluate correlations between mortality and various baseline characteristics. Subgroup analysis was performed with respect to diabetes status.

Results

There were 739 patients in our center in the Chinese National Renal Data System (CNRDS) between 2010 and 2018. Of these, 125 PD patients were matched with 125 HD patients. The 1-, 2-, and 3-year survival rates were 96.5%, 90.7%, and 82.5%, respectively, in the HD group and 99.5%, 97.8%, and 92.5%, respectively, in the PD group (log-rank P < 0.001). Among the propensity score-matched cohorts, no significant differences in Kaplan–Meier curves were observed between the two groups (log-rank P = 0.514). Age at dialysis initiation, CCI, congestive heart failure and cerebrovascular disease were risk factors in the multivariable-adjusted model. In subgroups defined by diabetes status, the Kaplan‒Meier survival curve showed that PD survival was significantly higher than that of HD (log-rank P = 0.022).

Conclusions

HD and PD were not significantly different with regard to survival of patients with ESRD. PD was associated with better survival in diabetic ESRD patients.

Hemodialysis

Peritoneal dialysis

Mortality

End-stage renal disease

Propensity score matching

An increasing incidence of end-stage renal disease (ESRD) has caused a substantial increase in the number of patients requiring renal replacement therapy (RRT) [1]. Hemodialysis (HD) and peritoneal dialysis (PD) are two common forms of dialysis therapy for ESRD [2].

Whether there exists a survival advantage for either HD or PD has been an area of intense interest and controversy over the past few years. Randomized controlled trials (RCTs) to assess the independent effect of HD and PD on survival have been impossible to conduct thus far [3]. Because dialysis modality selection is generally based on consideration of all aspects by patient and physician. Several observational studies have demonstrated that there is no difference in survival between dialysis modalities [4–7]. Some studies have shown that HD is associated with better survival [8], while some studies indicate that PD patients have better survival [9–11]. Recently, a survival advantage associated with PD has been reported in younger ESRD patients, and a survival advantage associated with HD has been reported in older patients [12]. However, in general, comparative mortality studies on this subject remain controversial. There is a need to further clarify whether the initial dialysis modality may impact survival.

Propensity-score-matched analysis reduces bias resulting from the nonrandom nature of the treatment assignment seen in observational studies [13]. Therefore, we conducted a study in our center to evaluate the impact of the initial dialysis modality on the survival of patients with ESRD by using a propensity-score-matched cohort.

2.1 Study cohort

The study was approved by the institutional review board of Zhongshan Hospital of Traditional Chinese Medicine Affiliated to Guangzhou University of Traditional Chinese Medicine (approval No.2022ZSZY-LLK-453) and complied with the Declaration of Helsinki. The requirement for informed consent was waived because the study was retrospective. This retrospective cohort study was performed with all patients in the Chinese National Renal Data System (CNRDS) who initiated maintenance dialysis in our center between January 1, 2010, and December 31, 2018. The inclusion criterion was judged by a clinician. Patients were excluded for the following reasons: lack of baseline data, younger than 18 years old, follow-up less than 3 months, and other dialysis methods for more than 3 months before enrollment. Full-time staff were responsible for the system information registration and all of the maintenance dialysis patients’ follow-up in our center. Hence, the data of the cohort were relatively complete and reliable.

2.2 Data collection

Data on baseline demographics, comorbid conditions, and laboratory test results were obtained by retrieved from our inpatient system and then compared with the data from the CNRDS. Demographic data included the data of birth, sex, start of dialysis, and primary kidney disease. Comorbidities were identified at baseline by the International Classification of Diseases, 9th and 10th Revision (ICD-9 and ICD-10) codes, and the Charlson comorbidity index (CCI) was calculated based on Quan et al.’s method [14]. Laboratory indicators included blood urea nitrogen, serum creatinine, triglycerides, cholesterol, plasma albumin and hemoglobin.

2.3 Outcomes and exposures

The outcome data were retrospectively retrieved from the CNRDS and inpatient systems. The main outcome was all-cause mortality. The censor event included the patient switching to another dialysis modality, undergoing a kidney transplant, transferring to another dialysis center or reaching the end of follow-up (December 31, 2021).

2.4 Statistical analysis

All statistical analyses were performed using IBM SPSS Statistics software version 25.0 (IBM Corporation, Armonk, NY, USA) and GraphPad Prism 9 software (GraphPad Software, San Diego, CA, USA). Continuous variables that were normally distributed are presented as the mean ± standard deviation (SD), and t tests were used for comparison. Nonnormally distributed variables are presented as the median and rank, and the Mann‒Whitney U test was used for comparisons between groups. Categorical variables are presented as numbers (percentages) and were analyzed by the chi-square test. The Kaplan‒Meier survival curve was used to compare the overall survival between the initial dialysis modalities, and the significance of the difference was tested by the log-rank method.

Univariate and multivariate Cox proportional hazards regression models were used to compare the hazard ratios (HRs) with 95% confidence intervals (CIs) for death between the PD and HD patients, using the time from initial dialysis to censoring as the timescale. The results with a P value < 0.05 were considered statistically significant. Subgroup analysis was performed with respect to diabetes status.

Propensity score matching (PSM) was used to reduce selection bias to balance baseline status. The characteristics used in PSM were the same as the variables in the multivariate Cox regression model.

3.1 Patients and data

The study cohort profile is shown in Fig. 1. There were 739 patients in the CNRDS registered by our center during the study period. A total of 52 patients were excluded for the following reasons: lack of baseline data (n = 22), younger than 18 years old (n = 1), followed up less than 3 months (n = 14), and underwent other dialysis methods for more than 3 months before enrollment (n = 15). Among the 687 patients included, 497 had undergone HD, and 190 had undergone PD.

A propensity score was calculated in this cohort, and patients who were initially treated with HD were propensity score matched 1:1 with those who started with PD. A total of 125 matched pairs of patients were included in the final analyses.

3.2 Patient characteristics at baseline

The baseline characteristics are shown in Table 1. The unmatched case-mix differences between HD and PD patients were significant. HD patients were older (56.23 ± 15.97 vs. 47.61 ± 13.45, P < 0.001) and presented a higher CCI value (5.35 ± 2.13 vs. 4.10 ± 1.74, P < 0.001) than PD patients. Compared with PD patients, HD patients also had higher rates of diabetes, congestive heart failure and cerebrovascular disease. In terms of kidney primary disease, the rate of obstructive nephropathy was higher in the PD group. Regarding laboratory tests, blood urea nitrogen and plasma albumin were higher in the HD group, while cholesterol showed the opposite trend.

Table 1

Baseline characteristics by modality at dialysis initiation before and after matching
Characteristics	Before Matching			After Matching
Characteristics	All HD (n = 497)	All PD (n = 190)	P	Matched HD (n = 125)	Matched PD (n = 125)	P
Demographic data
Female (n)	188 (37.83%)	78 (41.05%)	0.44	49 (39.2%)	52 (41.6%)	0.70
Age at dialysis initiation (years)	56.23 ± 15.97	47.61 ± 13.45	<0.01	50.04 ± 15.51	49.61 ± 13.97	0.82
Duration of follow up (months)	54.56 (36.73, 81.13)	56.78 (39.75, 76.70)	0.83	54.36 (38.30, 90.76)	56.57 (39.90, 75.13)	0.77
Kidney primary disease
Diabetic nephropathy (n)	114 (22.94%)	22 (11.58%)	0.05	14 (11.2%)	17 (13.6%)	0.57
Glomerulus nephritis (n)	188 (37.83%)	53 (27.89%)	0.94	42 (33.6%)	40 (32.0%)	0.79
Polycystic kidney (n)	14 (2.82%)	4 (2.11%)	0.99	3 (2.4%)	4 (3.2%)	1.00
Obstructive nephropathy (n)	29 (5.83%)	19 (10.00%)	<0.01	12 (9.6%)	10 (8.0%)	0.66
Other or unknown (n)	152 (30.58%)	92 (48.42)	<0.01	54 (43.2%)	54 (43.2%)	1.00
Comorbidities
Charlson Comorbidities Index (CCI)	5.35 ± 2.13	4.10 ± 1.74	<0.01	4.58 ± 2.03	4.38 ± 1.86	0.40
Diabetes (n)	171 (34.41%)	38 (20.00%)	<0.01	31 (24.8%)	29 (23.2%)	0.77
Cardiovascular disease (n)	144 (28.97%)	45 (23.68%)	0.16	33 (26.4%)	31 (24.8%)	0.77
Congestive heart failure (n)	104 (20.93%)	10 (5.26%)	<0.01	6 (4.8%)	9 (7.2%)	0.42
Cerebrovascular disease (n)	104 (20.93%)	12 (6.32%)	<0.01	17 (13.6%)	12 (9.6%)	0.32
Chronic pulmonary disease (n)	50 (10.06%)	36 (18.95%)	<0.01	22 (17.6%)	19 (15.2%)	0.61
Laboratory tests
Serum Urea (mmol/L)	28.30 ± 8.32	22.73 ± 9.09	<0.01	24.92 ± 6.47	25.43 ± 9.20	0.62
Serum creatinine (umol/L)	977 (798, 1227)	972 (779, 1165)	0.56	947 (787, 1158)	973 (818, 1169)	0.55
Triglyceride (mmol/L)	1.46 (1.01, 2.11)	1.46 (1.09, 2.22)	0.67	1.58 (1.12, 2.61)	1.47 (1.09, 2.33)	0.44
Cholesterol (mmol/L)	4.40 ± 1.27	5.24 ± 1.30	<0.01	4.94 ± 1.29	4.99 ± 1.20	0.77
Plasma albumin (g/L)	37.26 ± 4.11	35.76 ± 5.94	<0.01	37.09 ± 4.37	36.73 ± 4.54	0.52
Hemoglobin (g/L)	97.74 ± 22.01	96.56 ± 23.65	0.28	96.44 ± 21.34	97.01 ± 24.62	0.85
HD Hemodialysis, PD Peritoneal dialysis
Bold values indicate significant statistical differences.

After propensity score matching, 125 HD and 125 PD patients had similar characteristics, which suggested that these patients were likely eligible for either modality (Table 1).

3.3 Outcomes

3.3.1 Survival rates

The median follow-up period was 62.5 months for the HD patients and 75.7 months for the PD patients. A total of 217 (31.6%) death events occurred in the whole study cohort. The 1-, 2-, and 3-year survival rates were 96.5%, 90.7%, and 82.5%, respectively, in the HD group and 99.5%, 97.8%, and 92.5%, respectively, in the PD group (log-rank P < 0.001, Fig. 2A). Among the propensity score-matched cohorts, no significant differences in Kaplan–Meier curves were observed between the two groups (log-rank P = 0.514, Fig. 2B).

3.3.2 Factors associated with survival

In the total study cohort, the univariate Cox regression model suggested that age at dialysis initiation, diabetic nephropathy, CCI, diabetes, cardiovascular disease, congestive heart failure and cerebrovascular disease were risk factors for all-cause mortality. Age at dialysis initiation, CCI, congestive heart failure and cerebrovascular disease were also risk factors in the multivariable-adjusted model. Age at dialysis initiation and cerebrovascular disease remained risk factors in multivariate Cox regression after using propensity scores to eliminate the differences in baseline characteristics. The HR of cerebrovascular disease increased from 1.94 (95% CI: 1.42–2.64) to 2.36 (95% CI: 1.19–4.69). Both univariate and multivariate Cox regression suggested that female sex was a protective factor. The HR of females decreased from 0.64 (95% CI: 0.48–0.86) to 0.41 (95% CI: 0.23–0.74) after propensity score matching (Table 2).

Table 2

Risk factors for mortality assessed by univariate and multivariate Cox regression model
Variables	Univariate (n = 687)
Variables	HR (95% CI)	P	HR (95% CI)	P	HR (95% CI)	P
Sex (female vs male)	0.67 (0.51–0.89)	0.01	0.64 (0.48–0.86)	<0.01	0.41 (0.23–0.74)	<0.01
Age at dialysis initiation (≥ 65 years)	3.92 (2.99–5.15)	<0.01	2.35 (1.71–3.23)	<0.01	2.56 (1.26–5.18)	0.01
Diabetic nephropathy (n)	2.25 (1.67–3.04)	<0.01	1.14 (0.75–1.73)	0.54	1.49 (0.66–3.37)	0.34
CCI (≥ 5)	4.11 (2.97–5.69)	<0.01	1.77 (1.17–2.68)	0.01	1.20 (0.60–2.39)	0.60
Diabetes (n)	2.46 (1.87–3.23)	<0.01	1.32 (0.89–1.96)	0.16	1.43 (0.69–2.98)	0.34
Cardiovascular disease (n)	1.40 (1.04–1.87)	0.03	1.23 (0.88–1.70)	0.22	0.88 (0.47–1.64)	0.68
Congestive heart failure (n)	2.19 (1.61–2.98)	<0.01	1.77 (1.25–2.51)	<0.01	1.34 (0.54–3.33)	0.53
Cerebrovascular disease (n)	3.16 (2.37–4.22)	<0.01	1.94 (1.42–2.64)	<0.01	2.36 (1.19–4.69)	0.01
Triglyceride (mmol/L)	0.88 (0.78–0.99)	0.04	0.98 (0.86–1.12)	0.81	1.00 (0.81–1.24)	0.99
Plasma albumin (g/L)	0.95 (0.93–0.98)	<0.01	0.98 (0.95–1.01)	0.21	0.98 (0.93–1.04)	0.55
Hemoglobin (g/L)	0.98 (0.97–0.99)	<0.01	0.98 (0.97–0.99)	<0.01	0.97 (0.96–0.98)	<0.01
Dialysis methods (HD vs PD)	2.06 (1.43–2.97)	<0.01	1.09 (0.73–1.64)	0.68	1.04 (0.61–1.78)	0.89
PSM, Propensity scoring matching; HR, Hazard ratio; 95% CI, 95% confidence interval; CCI, Charlson comorbidities index; HD, Hemodialysis; PD, Peritoneal dialysis.
^a Variables adjusted in multivariate Cox regression model: Sex, Age at dialysis initiation, CCI, Diabetes, Cardiovascular disease, Congestive heart failure, Cerebrovascular disease, Triglyceride, Plasma albumin, Hemoglobin, Dialysis methods.
^b The characteristics used in PSM were the same as the variables in the multivariate Cox regression model.
Bold values indicate significant statistical differences.

3.3.3 Subgroup analyses by diabetes status

According to the interaction effect analysis, all patients after PSM were divided into two groups based on diabetes status. In the diabetes group, the all-cause mortality rate ratio of HD to PD was 2.665 (95% CI: 1.118–6.352). In the nondiabetes group, the all-cause mortality rate ratio of HD to PD was 0.831 (95% CI: 0.447–1.545).

In the diabetes group, the 1-, 2-, and 3-year survival rates of the PD group were 100.0, 100.0, and 88.9%, respectively, while those of the HD group were 90.3, 77.0, and 66.8%, respectively. The Kaplan‒Meier survival curve showed that the survival rate of PD was significantly higher than that of HD (log-rank P = 0.022, Fig. 2C). In the nondiabetes group, there was no significant difference in the survival rate between HD and PD patients (Fig. 2D).

In this retrospective observational cohort study, we compared the impact of the initial dialysis modality on the survival of patients with ESRD beginning dialysis in our center between January 1, 2010, and December 31, 2018. Our study showed that mortality was significantly higher in patients initiating dialysis with HD than those initiating dialysis with PD in the whole cohort, but in the propensity score-matched cohort, there was no difference between HD and PD patients. We also found that PD was more favorable with respect to survival than HD in patients with diabetes.

Randomized controlled trials assessing the independent effect of HD and PD on survival have been impossible to conduct [3]. Several studies reported that there is no difference in survival between the modalities [4–7], which is consistent with our findings. Several studies also reported favorable outcomes of PD in younger patients or during the first 1–2 years of dialysis treatment compared to the outcomes of HD [12, 15, 16]. We did not find any interaction between age and dialysis modality related to outcomes, and the concern about increased mortality in PD patients if treatment is continued beyond 1–2 years was also not supported by our study.

In another subgroup analysis of our matched cohort, significantly better survival was shown in patients with diabetes whose treatment was initiated with PD versus those initiating with HD. This is contradictory to the results of several studies, which have claimed that patients with diabetes mellitus did worse on PD than on HD [17, 18], while favorable outcomes of PD were reported in patients without diabetes [10, 19]. It was generally recognized in previous studies that PD therapy may affect blood glucose control in ESRD patients because the dialysate used for PD contains glucose [20–22], and diabetic patients are prone to developing disorders of lipid metabolism [23], which might accelerate the process of arteriosclerosis and increase the incidence of cardiovascular events [24, 25]. There were also some studies that found no interactions between diabetes mellitus and initial modality concerning mortality [9, 10, 26].

There are several reasons why our results may diverge from those of previous studies comparing outcomes in PD and HD in patients with diabetes. First, therapy skills, including elective dialysate and automated peritoneal dialysis (APD) prescription while avoiding glucose load, might have been responsible for our favorable results. Second, the team responsible for training, management and follow-up of PD patients was of high quality in our single center, which might account for the different results of this single center study compared to other studies. Moreover, when PD fails, it is common to switch to HD; therefore, the mortality rate of these patients was lower than that of HD patients. There were also reports consistent with our discovery that PD showed better outcomes in diabetes patients [27, 28].

With regard to the risk factors associated with survival, we found that age, sex, and cerebrovascular disease were risk factors, which are not totally consistent with those reported by other studies. Some studies [6, 29–31] discovered that age and diabetes were risk factors associated with death. Another study in eastern China [10] followed up 22,379 patients for a median of 29 months and found that age, diabetic nephropathy, and cardiovascular disease were risk factors.

There are several limitations of this study worth mentioning. The main limitation is that it was not a randomized study but rather a retrospective observational cohort study, and propensity score matching can account only for observed confounders. Despite propensity score matching and adjustment for several confounding factors, residual confounding cannot be excluded. Therefore, this study may not be completely free of bias due to confounding. Second, only baseline laboratory test results were recorded, which might be altered during dialysis treatment. Therefore, the laboratory tests shown in this study could not reflect the situation of patients in the treatment process. Third, the study population was small (250 patients), and the survival rates of only the first 3 years were compared.

In conclusion, our study showed that the two modes of dialysis were not significantly different with regard to the survival of patients with ESRD. PD was associated with better survival in diabetic ESRD patients. More research is needed to verify whether PD may be a therapy of priority in diabetic ESRD patients.

ESRD: End-stage renal disease; HD: Hemodialysis; PD: Peritoneal dialysis; RCT: Randomized controlled trial; CCI: Charlson comorbidities index; CNRDS: Chinese National Renal Data System; SD: Standard deviation; PSM: Propensity score matching; HR: Hazard ratio; CI: Confidence interval; APD: automated peritoneal dialysis.

Acknowledgements

We thank all doctors, nursing staff and IT engineers of the CNRDS database for their excellent assistance in registering data from ESRD patients.

Author’ contributions

The authors confirm that the manuscript has been read and approved by all the named authors and that there are no other persons who satisfied the criteria for authorship but are not listed. The order of authors listed in the manuscript has been approved by all the authors. Li Liu, Juan Xu and Man-yu Liao collected data and prepared figures; Li Liu and Qing-xiu Huang performed statistical analysis; Li Liu and Jie Pang wrote the main manuscript text; and Yan-lin Li and Lin-na Liu reviewed the final version of the paper.

Funding

This work was supported by the Foundation of National Key Clinical Department (Traditional Chinese Medicine), China (Grant No. [2014]80), the Project of Guangdong Provincial Famous Traditional Chinese Medicine Studio (Grant No. [2019]283), the Research Fund of Guangdong Provincial Administration of Traditional Chinese Medicine (Grant No. 20223020) and Research project of Zhongshan Health Bureau (Grant No. 2021J181).

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request and with permission of Zhongshan Hospital of Traditional Chinese Medicine Affiliated to Guangzhou University of Traditional Chinese Medicine.

Ethical approval and consent to participate

This study was conducted in accordance with the ethical principles of the Helsinki Declaration, and approved by the institutional review board of Zhongshan Hospital of Traditional Chinese Medicine Affiliated to Guangzhou University of Traditional Chinese Medicine (approval No.2022ZSZY-LLK-453). With the approval of the institutional review board of Zhongshan Hospital of Traditional Chinese Medicine Affiliated to Guangzhou University of Traditional Chinese Medicine, the data used in this study were exempted from patient consent.

Consent for publication

Not Applicable.

Competing interests

The authors declare that they have no competing interests.

Author details

¹Department of Nephrology, Zhongshan Hospital of Traditional Chinese Medicine Affiliated to Guangzhou University of Traditional Chinese Medicine, Zhongshan, 528400, Guangdong Province, China.

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No competing interests reported.

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Impact of initial dialysis modality on the survival of patients with ESRD: A propensity-score-matched study

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Abstract

Background

Methods

Results

Conclusions

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1 Introduction

2 Materials And Methods

2.1 Study cohort

2.2 Data collection

2.3 Outcomes and exposures

2.4 Statistical analysis

3 Results

3.1 Patients and data

3.2 Patient characteristics at baseline

3.3 Outcomes

3.3.1 Survival rates

3.3.2 Factors associated with survival

3.3.3 Subgroup analyses by diabetes status

4 Discussion

5 Conclusion

Abbreviations

Declarations

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