Vernooij et al. BMC Nephrology (2021) 22:70 https://doi.org/10.1186/s12882-021-02265-6 RESEARCH ARTICLE Open Access The probability of receiving a kidney transplantation in end-stage kidney disease patients who are treated with haemodiafiltration or haemodialysis: a pooled individual participant data from four randomised controlled trials Robin W. M. Vernooij1,2, Way Law1,3, Sanne A. E. Peters2,4,5, Bernard Canaud6,7, Andrew Davenport8, Muriel P. C. Grooteman9, Fatih Kircelli10, Francesco Locatelli11, Francisco Maduell12, Marion Morena13, Menso J. Nubé9, Ercan Ok10, Ferran Torres14,15, Mark Woodward4,5,16, Peter J. Blankestijn1*, Michiel L. Bots2 on behalf of the HDF Pooling project investigators Abstract Background: Due to a critical shortage of available kidney grafts, most patients with Stage 5 Chronic Kidney Disease (CKD5) require bridging dialysis support. It remains unclear whether treatment by different dialysis modalities changes the selection and/or preparation of a potential transplant candidate. Therefore, we assessed whether the likelihood of receiving kidney transplant (both living or deceased kidney donors) differs between haemodialysis (HD) and online haemodiafiltration (HDF) in patients with CKD5D. Methods: Individual participant data from four randomised controlled trials comparing online HDF with HD were used. Information on kidney transplant was obtained during follow-up. The likelihood of receiving a kidney transplant was compared between HD and HDF, and evaluated across different subgroups: age, sex, diabetes, history of cardiovascular disease, albumin, dialysis vintage, fistula, and level of convection volume standardized to body surface area. Hazard ratios (HRs), with corresponding 95% confidence intervals (95% CI), comparing the effect of online HDF versus HD on the likelihood of receiving a kidney transplant, were estimated using Cox proportional hazards models with a random effect for study. (Continued on next page) * Correspondence: p.j.blankestijn@umcutrecht.nl 1 Department of Nephrology and Hypertension, University Medical Center Utrecht, Utrecht, the Netherlands Full list of author information is available at the end of the article © The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Vernooij et al. BMC Nephrology (2021) 22:70 Page 2 of 9 (Continued from previous page) Results: After a median follow-up of 2.5 years (Q1 to Q3: 1.9–3.0), 331 of the 1620 (20.4%) patients with CKD5D received a kidney transplant. This concerned 22% (n = 179) of patients who were treated with online HDF compared with 19% (n = 152) of patients who were treated with HD. No differences in the likelihood of undergoing a kidney transplant were found between the two dialysis modalities in both the crude analyse (HR: 1.07, 95% CI: 0.86–1.33) and adjusted analysis for age, sex, diabetes, cardiovascular history, albumin, and creatinine (HR: 1.15, 95%- CI: 0.92–1.44). There was no evidence for a differential effect across subgroups based on patient- and disease- characteristics nor in different categories of convection volumes. Conclusions: Treatment with HD and HDF does not affect the selection and/or preparation of CKD5D patients for kidney transplant given that the likelihood of receiving a kidney transplant does not differ between the dialysis modalities. These finding persisted across a variety of subgroups differing in patient and disease characteristics and is not affected by the level of convection volume delivered during HDF treatment sessions. Introduction better prognostic factors (e.g. age or comorbidities) that Kidney transplantation is the treatment of choice for pa- can also affect the likelihood of receiving a kidney trans- tients with Stage 5 Chronic Kidney Disease (CKD5). Yet, plantation. Therefore, the aim of our study was to exam- due to an aging population and an increased prevalence ine, in a pooled individual patient data analysis of four of CKD5 in patients with diabetes and hypertension [1], randomised controlled trials, first, whether the likelihood a critical shortage exists of available kidney grafts for of receiving transplantation differs between HDF and HD, transplantation [2, 3]. Consequently, most patients with and second, whether the probability of receiving a kidney CKD5 require bridging dialysis support (CKD5D). The transplantation differed according to patient-, disease-, or role of the different dialysis modalities, i.e. haemodialysis other treatment-related characteristics. (HD), peritoneal dialysis (PD), or haemodiafiltration (HDF), with respect to the selection and/or preparation Methods of receiving kidney transplantation has been the topic of Study design and study populations persistent discussion [4–6]. While most previous re- A pooled individual participant data (IPD) meta-analysis search regarding the selection and/or preparation of was undertaken using data from four large multicentre kidney transplantation candidates focussed on the randomised controlled trials (RCTs) comparing online comparison between PD and HD [7–9], limited evidence HDF versus HD in adult patients with CKD5 receiving is available regarding the comparison of HDF and HD chronic HD [12]. All methods carried out and reported in [10, 11]. While the convection volume in standard HD accordance with relevant guidelines [16, 17]. Detailed approximates 10 L/session, in online post-dilution HDF description of the study designs, including eligibility cri- the convection volume may amount to 23 L/1.73m2/ses- teria and treatment procedures, are provided elsewhere sion. Online HDF has been associated with a lower all- [18–21]. Briefly, the CONTRAST study included 714 pa- cause and cardiovascular mortality risk when compared tients treated by HD for > 2 months in dialysis centres in with HD, especially for the patients receiving the highest the Netherlands, Canada, and Norway. A suggested target delivered convection volume [12]. Yet, so far it is unclear convection volume of 6 L/hour, i.e. generally 24 L/per ses- whether HDF influences the eligibility and preparation sion, was proposed [18]. The ESHOL study included 906 time for receiving a renal transplant in these patients. patients treated by HD for > 3 months in Spain, with a The choice of dialysis modality might potentially affect minimum of 18 L/session of convection volume for the the selection or preparation of potential kidney transplant patients treated with online HDF [20]. The French HDF candidates due to several differences between dialysis mo- study included 391 patients, aged ≥65 years, treated by dalities. For example, several aspects of immune function HD for > 1 month, with no target online HDF convection and cytokine production, such as (micro) inflammation volume specified [21]. The Turkish HDF study, including and oxidative stress [7, 13], the hemodynamic treatment 782 patients without a specification of HD vintage, with a tolerance [11], and risk of intradialytic hemodynamic in- minimum target of 15 L/session convection volume for stability, and hence, injury to vital organs, including the online HDF treatments [19]. In all studies patients were 1: heart and brain, vary between dialysis modalities [7, 14]. 1 randomised to either continuation of HD or online Additionally, HD membranes might increase free radical HDF, generally in a thrice weekly treatment schedule. In production by activating complement factors, phagocytes, the CONTRAST study, patients in the control group were and leucocytes [14, 15]. At the same time, patients might dialysed using low flux membranes, in the other three have been selected for a specific dialysis modality due to studies high flux membranes were used. Vernooij et al. BMC Nephrology (2021) 22:70 Page 3 of 9 Study endpoints and follow-up Patients who received a kidney transplant during follow- The primary outcome differed across studies: from all- up were, on average, younger and had fewer comorbidities cause mortality [18, 20], a composite outcome of all- compared with those patients who did not receive a cause mortality and nonfatal cardiovascular events [19], kidney transplant, but no differences by sex were found to intradialytic tolerance [21]. Secondary outcomes (Table 1). Patients who received a kidney transplant had collected were cardiovascular mortality, infection mor- significantly less dialysis vintage and more arteriovenous tality, and sudden death. The outcome of interest for fistula access compared with patients who did not receive this study is kidney transplant, for which information a kidney transplant. Albumin, haemoglobin, and pre- was collected in all studies during follow-up. dialysis serum creatinine were greater, while C-reactive protein was lower, for those patients who received a trans- Statistical analysis plant. There were no apparent differences in baseline A similar statistical approach as the original IPD meta- characteristics, comorbidities, or laboratory measurements analysis has been followed [12]. Hazard ratios (HRs), with between the HD and the HDF study treatment arm for corresponding 95% confidence intervals (95% CI), com- those patients who underwent a kidney transplantation. paring the effect of online HDF versus HD on the suitabil- The patients who received online HDF did not have a ity of kidney transplant candidates were estimated using different likelihood of receiving a kidney transplantation Cox proportional hazards models with a random effect for compared with the patients receiving HD (HR: 1.07, study. Further analyses were conducted to evaluate 95%-CI: 0.86–1.33) (Table 2). When adjusted for age, whether this differed between subgroups on age (< 65 vs. sex, diabetes, cardiovascular history, albumin, and ≥ 65 years), sex, history of diabetes, history of CVD, albu- creatinine, this finding remained similar (HR: 1.15, 95%- min levels (< 4 vs. ≥ 4 g/dL), dialysis vintage (< 30 vs. ≥ 30 CI: 0.92–1.44). This was consistent across all studies months), and mode of vascular access (arteriovenous (Appendix 2). No evidence was found for a differential fistula vs other). We used multiplicative interaction terms effect of online HDF compared to HD in subgroup of to explore whether differences in effect were present patients differing in sex, age, diabetes, CVD history, across subgroups. Additionally, study-specific results were albumin, dialysis vintage, and vascular access for the computed for the CONTRAST and ESHOL studies; the likelihood of receiving kidney transplantation. other trials had too few patients to be able to obtain When compared to HD, the HRs by increasing delivered precise estimates. The dose-response association between convection volume (< 19, 19–23, and > 23 l per 1.73m2 BSA online HDF and kidney transplantation was examined by per session) were 1.15 (0.82–1.61), 1.02 (0.75–1.41) and thirds of the actual (on-treatment) delivered, 1.73m2 BSA 1.06 (0.80–1.40), respectively (Table 3). The crude analyses (body surface area)-standardized, convection volume. BSA and analyses adjusted for age, albumin, creatinine, history was estimated using the formula from Gehan and George, of CVD, and history of diabetes, give similar results. as recommended by the European Best Practice Guide- lines. Delivered convection volume was standardized by Discussion dividing the delivered by patient BSA [1.73 * (patient con- In this pooled IPD analysis including four RCTs, we identi- vection volume/patient BSA)]. The association between fied no differences between pre-transplantation treatment convection volume and likelihood of receiving kidney with HD compared with pre-transplantation HDF in the transplantation was adjusted for age, sex, baseline serum likelihood of receiving kidney transplant in patients with albumin, creatinine, history of diabetes and history of CKD5D. There was no evidence to suggest that this finding CVD. Complete case analyses were conducted given that differed across subgroups of patients, nor did the delivered the specific data for (time to) transplantation was almost convection volume per sessions influence this finding. complete (n = 1 missing). All analyses were performed Due to an international shortage of available kidney using R (version 3.5.1.) and a two-sided p value of < 0.05 grafts, many patients with CKD5D in clinical practice conferred statistical significance. will have to undergo bridging dialysis support. Given that the underlying physiology of the different forms of Results dialysis varies, i.e. where HD mainly relies on diffusion, Of the 2793 patients included, 355 (12.7%) underwent a HDF consists of both diffusion and convection and is kidney transplantation during a median follow-up of 2.5 more efficient in removing middle molecules [22], this years (Q1-Q3: 1.9–3.0 years). In the CONTRAST and might have resulted in differences which could have ESHOL study, respectively, 21% (n = 151) and 20% (n = affected patient suitability for kidney transplantation. 180) of the patients included received a kidney trans- Similarly, the survival benefit of HDF, i.e. a lower all- plant during follow-up, but in the French and Turkish cause and cardiovascular mortality [12, 23–25], might studies these percentages were much smaller (n = 7 and also potentially contribute to differences selection and/ n = 17, respectively, both 2%) (Appendix 1). or preparation of kidney transplant candidates. Patients Vernooij et al. BMC Nephrology (2021) 22:70 Page 4 of 9 Table 1 Baseline characteristics of study participants by treatment allocation and transplantation during follow-up HD HDF No transplantation Transplantation p-value** No transplantation Transplantation p-value** p-value*** N 654 152 635 179 Age (year) 67.8 (13.1) 54.3 (12.3) < 0.01 67.4 (13.2) 53.6 (12.3) < 0.01 0.58 Women 227 (34.7) 59 (38.8) 0.39 219 (34.5) 64 (35.8) 0.82 0.65 History of CVD 284 (43.4) 32 (21.1) < 0.01 260 (40.9) 35 (19.6) < 0.01 0.84 Diabetes mellitus 176 (27.5) 24 (16.1) < 0.01 163 (26.0) 33 (18.4) 0.05 0.68 Dialysis vintage (months)* 27.0 (12.0–55.0) 25.5 (11.8–48.0) 0.23 26.0 (12.0–56.0) 24.0 (12.0–42.0) 0.16 0.69 Systolic BP (mmHg) 141.7 (24.3) 141.6 (21.5) 0.96 141.0 (23.9) 141.6 (21.4) 0.79 0.98 Diastolic BP (mmHg) 72.4 (14.8) 77.0 (11.6) < 0.01 72.6 (13.5) 78.8 (12.9) < 0.01 0.18 Vascular access, AVF 520 (79.5) 140 (92.1) < 0.01 526 (82.8) 160 (89.4) 0.04 0.51 Duration of a dialysis session (min) 230.7 (22.0) 232.1 (20.6) 0.45 230.7 (20.8) 234.2 (21.3) 0.05 0.38 Blood flow (ml/min)* 350 (300–400) 350 (300–400) 0.82 350 (320–400) 350 (300–400) 0.35 0.27 Dialysis single pool Kt/V 1.52 (0.30) 1.53 (0.31) 0.92 1.6 (0.3) 1.5 (0.3) 0.30 0.83 Hemoglobin (g/dL) 11.9 (1.4) 11.9 (1.2) 0.41 11.9 (1.4) 12.2 (1.3) < 0.01 0.07 Phosphorus (mg/dL) 4.8 (1.5) 5.0 (1.4) 0.14 4.8 (1.5) 5.2 (1.5) < 0.01 0.08 B-2 microglobulin (mg/L)* 25.9 (19.8–36.2) 28.5 (20.9–38.1) 0.43 25.8 (18.8–34.9) 26.7 (18.7–34.3) 0.88 0.19 BMI after dialysis (kg/m2) 25.4 (4.6) 24.6 (4.0) 0.06 25.1 (5.0) 25.1 (4.0) 0.97 0.25 Albumin (g/dL) 4.0 (0.4) 4.2 (0.4) < 0.01 4.1 (0.4) 4.2 (0.4) < 0.01 0.61 C-reactive protein (mg/L)* 5.7 (3.4–12.8) 4.9 (1.6–8.4) < 0.01 6.2 (3.1–14.1) 4.9 (1.6–9.9) < 0.01 0.51 Predialysis creatinine (mg/dL) 8.7 (2.7) 9.7 (2.8) < 0.01 8.4 (2.7) 9.9 (2.7) < 0.01 0.56 Cholesterol (mmol/L) 3.7 (1.0) 3.7 (1.2) 0.90 3.7 (0.9) 3.6 (0.9) 0.48 0.59 Body Surface Area (m2) 1.8 (0.2) 1.8 (0.2) 0.62 1.8 (0.2) 1.8 (0.2) 0.42 0.96 Convection volume (L)* – – – 22.8 (19.8–25.4) 22.9 (20.0–25.9) 0.40 – Values are n (%) for categorical variables, and mean (standard deviation) or *median (Q1-Q3) for continuous variables ** p-values indicates differences between the patients who did not receive transplantation versus those who did in, respectively, the HD and HD arm *** p-values indicates differences between the patients who received transplantation in the HD arm versus the patients who received transplantation in the HDF arm CVD cardiovascular disease, BP blood pressure, AVF arteriovenous fistula, BMI body mass index treated with HDF have a better preservation of left ven- kidney transplantation during follow-up was very low tricle function [24, 26], and less intradialytic hypotensive (2%) and therefore not included in our main analysis. episodes [11, 20, 27], which might preclude or defer This might be explained by several factors related to patients from receiving a kidney transplantation. Conse- either local healthcare policy, cultural differences, or pa- quently, taking these reasons into account, one could tient characteristics and personal intention. For example, hypothesise that pre-transplantation treatment with although the rate of kidney transplant per million inhab- HDF might make EKSD patients more suitable for a itants is higher in Turkey than the rest of Europe, this is kidney transplantation. However, in this study, due to largely caused by a higher rate of living kidney trans- randomisation, we were able to exclude measured and plants [28]. Given that the majority of kidney transplants unmeasured confounding by indication on better prog- in our study come from deceased donors and not living nostic factors (e.g. age and comorbidities) that affect the donors, this might explain the low transplantation rate likelihood of receiving a kidney transplantation. At the in this study. On the other hand, the average age of the same time, there is no hypothesis that major determi- patients included in the French study was 76 years due nants of transplant candidate selection, such as donor to advanced age being a selection criterion [21], compared specific antibodies or human leukocyte antigens (HLA) with the other studies (mean age: 64.1 years, 65.4 years, matching, will be affected by the specific dialysis modality. and 56.5 years in, respectively, CONTRAST, ESHOL, and Therefore, we conclude that the decision-making of Turkish study) [18–20], meaning that most transplant patient suitability for kidney transplant does not depend candidates were excluded. Consequently, the French and on the specific choice of dialysis modality. Turkish studies were underpowered to analyse the likeli- In the French and the Turkish study, both part of the hood of receiving a kidney transplant. The criteria of kid- IPD meta-analysis, the proportion of patients receiving a ney transplantation were according to the local policies Vernooij et al. BMC Nephrology (2021) 22:70 Page 5 of 9 Table 2 Hazard ratio and 95% confidence intervals for receiving that patients treated by HDF received fewer kidney transplantation comparing HDF versus HD, overall and in transplants compared with HD patients [29]. predefined strata We were unable to examine post-transplantation patient Transplantation P-value for and graft survival due a limited follow-up after transplant- interaction ation (median time of follow-up post-transplantation: 24 Overall 1.07 (0.86–1.33) – months), limited number of post-transplantation events, Sex Male 1.01 (0.77–1.33) and differences in transplantation rates between countries. Female 1.21 (0.85–1.73) 0.42 The different effects between HD and HDF in terms of Age < 60 years 1.27 (0.96–1.68) oxidative stress, immune function, and hemodynamic treat- ≥ 60 years 0.87 (0.62–1.23) 0.09 ment tolerance, on the success of kidney transplantation Diabetes No 1.05 (0.83–1.34) remain an interesting area of research. There are multiple Yes 1.26 (0.74–2.13) 0.54 studies that have compared post-transplantation outcomes History of CVD No 1.17 (0.92–1.50) [30–41]. Yet, these studies all compared the post- transplantation outcomes for patients who underwent pre- Yes 0.88 (0.55–1.43) 0.30 transplantation treatment with PD versus HD. Therefore, it Albumine (g/dL) < 4 1.09 (0.72–1.64) remains unclear as to whether the choice of pre-dialysis ≥4 1.06 (0.82–1.38) 0.92 treatment modality affects post-transplantation survival, Creatinine (mg/dl), < 8 0.91 (0.60–1.37) and future research is required to elucidate this further. predialysis ≥8 1.14 (0.87–1.47) 0.37 The strengths of our study are that we analysed IPD from Dialysis vintage < 30 months 1.13 (0.85–1.50) the largest available set of RCTs and made appropriate ≥ 30 months 1.00 (0.71–1.40) 0.58 adjustment for measured and unmeasured confounders. Fistula No 1.44 (0.70–2.97) Consequently, we produced the most reliable evidence on Yes 1.04 (0.83–1.31) 0.40 whether the likelihood of receiving a kidney transplant dif- fered between HD and HDF for patients with CKD5D. However, our study is subject to some limitations. The four (e.g. guidelines) of the countries of the included studies. trials were not primarily designed to study the likelihood of Given the pragmatic nature of all trials included, this does patients receiving kidney transplants, since the primary not differ from actual clinical practice. end-point was mortality and differences between trials in Most of the previous studies on the likelihood of re- terms of study design and methodology, and in- and exclu- ceiving a kidney transplant has focussed on the compari- sion criteria of patients remain. Therefore, we do not draw son of HD versus PD, and the role of HDF in access to any causal conclusions in terms of renal transplantation transplantation has rarely been investigated. One meta- and dialysis modalities. We explored these clinical differ- analysis of Wang et al., including six studies with 2727 ences in a wide range of subgroup analyses, which illus- patients, reported a borderline significant increase (RR: trated that our findings were robust for all explored factors, 1.20, 95% CI: 1.00–1.44) in the likelihood of receiving a including patient characteristics and comorbidities. This kidney transplant among patients treated with HDF might be limited by the fact that our study population con- compared to those patients treated with HD [10]. How- sisted largely of European Caucasian patients. Finally, the ever, the limitations of this review are aggregated data, average follow-up duration in the studies in our IPD dataset without subgroup analyses. These findings are contra- was approximately 2.5 years [12], while the average waiting dicted by an observational registry study, including 28, time for kidney transplantation in Europe might be longer 407 patients (median follow-up: 1.95 years), that found [42, 43], and the median waiting time in US is 3.6 years [3]. Potentially, a greater number of patients could have re- Table 3 Hazard ratio and 95% confidence intervals for ceived a kidney transplant after the end of our data collec- transplantation by delivered BSA-standardized convection tion, however, it is unlikely that this would influence our volume in litres per 1.73m2 per treatment with standard haemodialysis as a reference findings given that we have not found any difference in the HD HDF convection volume likelihood of undergoing kidney transplantation between – < 19 19–23 > 23 the two treatment modalities in any subgroup or the level Total patients 806 211 230 359 of convection volume delivered during treatment sessions. In conclusion, online HDF, compared with conven- Number of renal 152 (18.9%) 49 (23.2%) 52 (22.6%) 77 (21.4%) transplantations tional HD, does not affect the likelihood of receiving a Crude ref. 1.15 (0.82–1.61) 1.02 (0.75–1.41) 1.06 (0.80–1.40) kidney transplant. This finding holds across a variety of Adjusteda ref. 1.35 (0.95–1.90) 1.15 (0.82–1.60) 1.06 (0.79–1.41) important clinical subgroups and is not affected by a Adjusted for age, sex, albumin, creatinine, history of cardiovascular diseases, the level of convection volume delivered during HDF and diabetes. Values are hazard ratios and 95% confidence intervals treatment sessions. Vernooij et al. BMC Nephrology (2021) 22:70 Page 6 of 9 Appendix 1 Table 4 Baseline characteristics of the patients who received transplantation during follow-up stratified by study CONTRAST ESHOL French study Turkish study p-value N 151 (21.1) 180 (19.6) 7 (1.8) 17 (2.2) Age (year) 53.4 (12.3) 54.4 (12.3) 67.7 (2.7) 44.5 (12.9) < 0.001 Female sex 63 (41.7) 60 (33.3) 3 (42.9) 7 (41.2) 0.446 History of CVD 33 (21.9) 34 (18.9) – 3 (33.3) 0.364 Diabetes mellitus 30 (20.3) 27 (15.0) 1 (16.7) 5 (29.4) 0.372 Dialysis vintage (months)* 26.0 (14.0–44.0) 23.0 (10.8–44.3) 32.3 (21.7–48.7) 55.8 (27.8–75.0) 0.013 Systolic BP (mmHg) 147.6 (21.5) 136.5 (20.0) 141.7 (24.6) 125.9 (11.0) < 0.001 Diastolic BP (mmHg) 80.0 (10.7) 76.3 (13.3) 72.5 (5.8) 74.7 (7.8) 0.017 Vascular access, AVF 130 (86.1) 170 (94.4) 3 (42.9) 15 (88.2) < 0.001 Duration of a dialysis session (min) 227.6 (22.1) 237.8 (18.9) 225.0 (36.7) 237.5 (3.6) < 0.001 Blood flow (ml/min)* 300 (275–325) 400 (350–400) 310 (300–335) 309.2 (297.4–346.3) < 0.001 Dialysis single pool Kt/V 1.4 (0.2) 1.7 (0.3) 1.7 (0.2) 1.4 (0.3) < 0.001 Hemoglobin (g/dL) 11.9 (1.1) 12.2 (1.3) 11.0 (1.4) 11.8 (1.3) 0.013 Phosphorus (mg/dL) 5.2 (1.5) 5.0 (1.4) 4.5 (1.9) 4.9 (1.1) 0.291 B-2 microglobulin (mg/L)* 32.3 (24.6–40.7) 20.9 (16.3–26.9) 23.0 (21.0–27.2) 26.2 (23.9–28.3) < 0.001 2 BMI after dialysis (kg/m ) 24.9 (3.7) 24.8 (4.2) 24.1 (1.6) 24.4 (5.0) 0.934 Albumin (g/dL) 4.1 (0.4) 4.2 (0.4) 4.0 (0.4) 4.0 (0.3) 0.108 C-reactive protein (mg/L)* 2.3 (0.9–6.8) 5.0 (2.6–10.4) 1.9 (0.9–6.6) 1.0 (0.2–1.3) < 0.001 Predialysis creatinine (mg/dL) 11.1 (2.6) 8.6 (2.4) 7.3 (2.4) 9.1 (2.2) < 0.001 Cholesterol (mmol/L) 3.7 (1.1) – 4.7 (1.2) 4.5 (1.1) 0.001 Body Surface Area (m2) 1.9 (0.2) 1.8 (0.2) 1.7 (0.2) 1.7 (0.2) < 0.001 Values are n (%) for categorical variables, and mean (standard deviation) or *median (Q1- Q3) for continuous variables CVD cardiovascular disease, BP blood pressure, AVF arteriovenous fistula, BMI body mass index Appendix 2 Table 5 Hazard ratio and 95% confidence intervals of transplantation comparing HDF versus. HD stratified by study CONTRAST p-value for interaction ESHOL p-value for interaction Hazard ratio (95%-CI) Hazard ratio (95%-CI) Overall 1.06 (0.77–1.45) – 1.19 (0.88–1.61) – Sex Male 1.00 (0.66–1.52) 1.09 (0.75–1.58) Female 1.14 (0.69–1.86) 0.70 1.43 (0.85–2.40) 0.40 Age < 60 years 1.47 (0.98–2.19) 1.27 (0.85–1.88) ≥ 60 years 0.65 (0.38–1.11) 0.02 1.08 (0.68–1.72) 0.61 Diabetes No 1.02 (0.71–1.46) 1.16 (0.83–1.61) Yes 1.42 (0.68–2.99) 0.43 1.29 (0.60–2.78) 0.80 History of CVD No 1.16 (0.81–1.67) 1.29 (0.92–1.80) Yes 0.80 (0.40–1.59) 0.35 0.97 (0.48–1.94) 0.46 Albumin < 4 g/dL 0.98 (0.57–1.69) 1.56 (0.81–3.02) ≥ 4 g/dL 1.07 (0.72–1.60) 0.80 1.12 (0.79–1.59) 0.38 Dialysis vintage < 30 months 1.28 (0.83–1.98) 1.07 (0.74–1.55) ≥ 30 months 0.85 (0.52–1.38) 0.21 1.47 (0.87–2.47) 0.33 Fistula No 1.65 (0.66–4.08) 1.58 (0.45–5.48) Yes 1.00 (0.71–1.41) 0.32 1.19 (0.87–1.63) 0.67 Vernooij et al. BMC Nephrology (2021) 22:70 Page 7 of 9 Appendix 3 Ede: G.W. Feith; Groene Hart Hospital, Gouda: H.G. List of study investigators Peltenburg; Haga Hospital, The Hague: M. van Buren; Isala The HDF Pooling project group comprises of all princi- Clinics, Zwolle: J.J.G. Offerman; Jeroen Bosch Hospital, pal investigators of the individual studies that participate Hertogenbosch: E.K. Hoogeveen; Maasland Hospital, Sit- in the HDF Pooling project. tard: F. de Heer; Maasstad Hospital, Rotterdam: P.J. van de ESHOL investigators: Francisco Maduell, Francesc Ven; Martini Hospital, Groningen: T.K. Kremer Hovinga; Moreso, Mercedes Pons, Rosa Ramos, Josep Mora-Macià, Medical Center Alkmaar: W.A. Bax; Onze Lieve Vrouwe Jordi Carreras, Jordi Soler, Ferran Torres, Josep M. Gasthuis, Amsterdam: J.O. Groeneveld; Oosterschelde Campistol, and Alberto Martinez-Castelao M. Pons, B. Hospital, Goes: A.T.J. Lavrijssen; Rijnland Hospital, Insensé, C. Perez, and T. Feliz (CETIRSA, Barcelona); R. Leiderdorp: A.M. Chrander-Van der Meer; Rijnstate Ramos, M. Barbetta, and C. Soto (Hospital San Antonio Hospital, Arnhem: L.J.M. Reichert; Slingeland Hospital, Abad, Vilanova i la Geltru); J. Mora, A. Juan, and O. Ibrik Doetinchem: J. Huussen; St. Elisabeth Hospital, Tilburg: (Fresenius Medical Care,Granollers); A. Foraster and J. P.L.Rensma; St. Fransiscus Gasthuis, Rotterdam: Y. Carreras (DiaverumBaix Llobregat, Hospitalet); F. Moreso, Schrama; University Medical Center St. Radboud, Nijmegen: J. Nin, and A. Fernández (Fresenius Medical Care, Hospi- H.W. van Hamersvelt; University Medical Center Utrecht, talet); J. Soler, M. Arruche, C. Sánchez, and J. Vidiella Utrecht: W.H. Boer; VieCuri Medical Center, Venlo: W.H. (Fresenius Medical Care, Reus); F. Barbosa, M. Chiné, and van Kuijk; VU University Medical Center, Amsterdam: S. Hurtado (Fresenius Medical Care Diagonal, Barcelona); M.G. Vervloet; Zeeuws-Vlaanderen Hospital, Terneuzen: J. Llibre, A. Ruiz, M. Serra, M. Salvó, and T. Poyuelo I.M.P.M.J. Wauters. Norway: Haukeland University (CETIRSA, Terrassa); F. Maduell, M. Carrera, N. Fontseré, Hospital, Bergen: I. Sekse. M. Arias, and Josep M. Campistol (Hospital Clínic, Turkish HDF Study investigators: Ercan Ok, Gulay Barcelona); A. Merín and L. Ribera (Fresenius Medical Asci, Huseyin Toz, Ebru Sevinc Ok, Fatih Kircelli, Mum- Care Julio Verne, Barcelona); J.M. Galceran, J. Mòdol, E. taz Yilmaz, Ender Hur, Meltem Sezis Demirci, Cenk Moliner, and A. Ramirez (Fundació Althaia, Manresa); J. Demirci, Soner Duman, Ali Basci, Siddig Momin Adam, Aguilera and M. Alvarez (Hospital Santa Tecla, Ismet Onder Isik, Murat Zengin, Gultekin Suleymanlar, Tarragona); B. de la Torre and M. Molera (Diaverum Mehmet Emin Yilmaz and Mehmet Ozkahya Pinar Bonanova, Barcelona); J. Casellas and G. Martín (Dia- Ergin, Alfert Sagdic, Erkan Kayali, Can Boydak, Taskin verum IHB, Barcelona); E. Andres and E. Coll (Fundació Colak, Sihli Caliskan, Hakan Kaplan, Hasibe Ulas, Sait Puigvert, Barcelona); M. Valles and C. Martínez (Hospital Kirbiyik, Hakan Berktas and Necati Dilbaz. Josep Trueta, Girona); E. Castellote (Hospital General, French HDF Study investigators: Bernard Canaud, Vic); J.M. Casals, J. Gabàs, and M. Romero (Diaverum, Jean-Paul Cristol, Marion Morena, Hélène Leray-Moragues, Mataró); A. Martinez-Castelao and X. Fulladosa (Hospital Leïla Chenine, Marie-Christine Picot, Audrey Jaussent, Universitari Bellvitge, Hospitalet); M. Ramirez-Arellano Claire Belloc, Mélodie Lagarrigue (University Hospital Cen- and M. Fulquet (Hospital de Terrassa); A. Pelegrí, M. el ter, Montpellier), Lotfi Chalabi (AIDER, Montpellier), Alain Manouari, and N. Ramos (Diaverum Verge de Montserrat, Debure, Messaoud Ouziala, Jean-Jacques Lefevre (ATS, St Santa Coloma); J. Bartolomé (Centre Secretari Coloma, Denis), Damien Thibaudin, Hesham Mohey, Christian Barcelona); R. Sans (Hospital de Figueres); E. Fernández Broyet, Aida Afiani, (University Hospital Center, Saint and F. Sarró (Hospital Arnau de Vilanova, Lleida); T. Etienne), Marie-Odile Serveaux, Laure Patrier (University Compte (Hospital Santa Creu, Tortosa); F. Marco and R. Hospital Center, Nîmes), François Maurice, Jean-Pierre Mauri (Diaverum Nephros, Barcelona); and J. Bronsoms Rivory (CHL, Castelnau le Lez), Philippe Nicoud (La Vallée (Clínica Girona), J.A. Arnaiz, H. Beleta, and A. Pejenaute Blanche center, Chamonix), Claude Durand, Michel (UASP Farmacología Clínica, Hospital Clínic Barcelona), Normand (Saint Martin polyclinic, Pessac), Bruno Seigneu- F. Torres, J. Ríos, and J. Lara (Biostatistics Unit, School of ric (University Hospital Center, Toulouse), Eric Magnant Medicine, Universitat Autònoma de Barcelona). (Centre Hémodialyse Provence, Aix en Provence), Lynda CONTRAST investigators: P.J. Blankestijn, M.P.C. Azzouz (Artic 42, St Priest en Jarez), Mohamed Shariful Grooteman, M.J.Nubé, P.M. ter Wee, M.L. Bots; M.A. Islam, Sandor Vido (University Hospital Center, Nice), van den Dorpel, Canada: Georges-L. Dumont Regional Hilaire Nzeyimana, Danièle Simonin (ECHO Michel Ange Hospital, Moncton: M. Dorval; CHUM St. Luc Hospital, center, Le Mans), Yamina Azymah, Ibrahim Farah, Montréal: R. Lévesque. The Netherlands: Academic Jean-Philippe Coindre (Hospital center, Le Mans), Medical Center, Amsterdam: M.G. Koopman; Catharina Olivier Puyoo, Marie-Hélène Chabannier, Richard Ibos, Hospital, Eindhoven: C.J.A.M. Konings; Dialysis Clinic Fabienne Rouleau (Centre Néphrologique d’Occitanie, Noord, Beilen: W.P. Haanstra; Dianet Dialysis Centers, Muret), Carlos Vela, Josiane Joule (Hospital center, Perpi- Utrecht: M. Kooistra and B. van Jaarsveld; Fransiscus gnan), François Combarnous (Tonkin clinic, Villeurbanne), Hospital, Roosendaal: T. Noordzij; Gelderse Vallei Hospital, Cécile Turc-Baron, Francis Ducret, Philippe Pointet, Isabelle Vernooij et al. BMC Nephrology (2021) 22:70 Page 8 of 9 Rey (Hospital center, Annecy), Jacky Potier (Hospital center, Grant Program, and the Netherlands Organization for Cherbourg), Jean- Christophe Bendini, Franck Perrin (St Health Research and Development (ZONMw Grant 170, Georges clinic, Nice), Kristian Kunz (University Hospital 882,802). The French HDF study was supported by a Center, Strasbourg), Gaëlle Lefrancois, Angélique Colin, national grant from the Health Ministry (Programme Sophie Parahy, Irima Dancea, Stéphanie Coupel, Angelo Hospitalier de Recherche Clinique, PHRC) as a mean to Testa (ECHO center, Rezé), Philippe Brunet, Gaétan Lebrun, improve care and outcome of elderly chronic disease Dominique Jaubert (University Hospital Center AP-HM, patients. Marseille), Catherine Delcroix, Frédéric Lavainne, Anne Acknowledgements Lefebvre (University Hospital Center, Nantes), Marie-Paule Not applicable. Guillodo, Dominique Le Grignou (AUB, Brest), Assia Djema (Hospital center, Cholet), Mehadji Maaz, Sylvie Chiron (Hos- Authors’ contributions RWMV, MLB, and PJB drafted the report. RWMV and ML did the analyses. All pital center, Colmar), Maxime Hoffmann, Pascale Depraetre authors contributed to the interpretation of the data, the preparation of the (Louvière clinic, Lille), Atman Haddj-Elmrabet, Véronique manuscript, and the decision to submit for publication. RWMV, MLB, and PJB Joyeux (University Hospital Center, Rennes), Dominique vouch for the validity of the study and are responsible for the integrity of the work as a whole. The HDF Pooling project group comprises of all principal Fleury, Laurence Vrigneaud, Vincent Lemaitre (Hospital investigators of the individual studies that participate in the HDF Pooling center, Valenciennes), Didier Aguilera, Abdallah Guerraoui project (Appendix 3). The authors read and approved the final manuscript. (Hospital center, Vichy), Alain Cremault, Achour Laradi, Francois Babinet (ECHO Pole Santé Sud center, Le Mans). Funding Funding details are listed in Appendix 4. RWMV, PJB, and MLB are funded by The writing executive committee, whose membership the CONVINCE study (European Union’s Horizon 2020 research and did not include representatives of the financial contribu- innovation programme under grant agreement No 754803). tors, has final responsibility for the interpretation of the Availability of data and materials data, the preparation of the manuscript and the decision Requests for access to the data of the HDF pooling project can be directed to submit for publication. The executive committee the corresponding author. Requests will be handled by the executive vouches for the validity and completeness of the re- committee of the HDF pooling project. ported data. Ethics approval and consent to participate All patients provided necessary informed consent to participate in the Appendix 4 present study and ethical approval was obtained in the individual studies. All methods were carried out in accordance with relevant guidelines and Funding regulations. The CONTRAST was approved by both a central medical ethics The HDF Pooling project was designed, conducted, and review board and local ethics committees of the participating hospitals. The analysed independently of the financial contributors of local ethics committee of Ege University Izmir, Turkey, approved the study protocol of the Turkish study. The ESHOL study was approved by the ethics the individual studies as listed below. Study data were committee of each participating centre. The French study was approved by collected and retained by the investigators and were not the Montpellier University Hospital ethics committee. available for the financial contributors of the individual Consent for publication studies. SAEP and the meetings of the representatives of Not applicable. the combined authors of the four studies were financially supported by the EuDial working group. EuDial is an of- Competing interests ficial working group of the European Renal Association None declared. – European Dialysis Transplant Association (ERA- Author details EDTA, http://era-edta.org/eudial/European_Dialysis_ 1 Department of Nephrology and Hypertension, University Medical Center Working_Group.html. No industry funding was received Utrecht, Utrecht, the Netherlands. 2Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, for any part of or activity related to the present analysis. the Netherlands. 3Wai-ping Law, Renal unit, Department of medicine, Queen The Turkish HDF study was supported by European Elizabeth Hospital, Hong Kong, PR China. 4The George Institute for Global Nephrology and Dialysis Institute with an unrestricted Health, School of Public Health, Imperial College, London, UK. 5The George Institute for Global Health, University of New South Wales, Sydney, Australia. grant. The study was performed in Fresenius Medical 6 Global Medical Office, Fresenius Medical Care Deutschland, Bad Homburg, Care haemodialysis clinics in Turkey. ESHOL was Germany. 7Montpellier University, School of Medicine, Montpellier, France. 8 supported by The Catalan Society of Nephrology and by University College London, Centre for Nephrology, Royal Free Hospital, London, UK. 9Department of Nephrology and Amsterdam Cardiovascular grants from Fresenius Medical Care and Gambro through Sciences (ACS), Amsterdam University Medical Centers, VU University, the Catalan Society of Nephrology. The CONTRAST study Amsterdam, The Netherlands. 10Division of Nephrology, Ege University was supported by a grant from the Dutch Kidney Founda- School of Medicine, Izmir, Turkey. 11Department of Nephrology, Alessandro Manzoni Hospital, past director, Lecco, Italy. 12Nephrology Department, tion (Nierstichting Nederland Grant C02.2019), and unre- Hospital Clinic, Barcelona, Spain. 13PhyMedExp, University of Montpellier, INSE stricted grants from Fresenius Medical Care, Netherlands, RM, CNRS, Biochemistry/Hormonology department, University Hospital and Gambro Lundia AB, Sweden. Additional support was Center of Montpellier, Montpellier, France. 14Biostatistics Unit, School of Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain. 15Medical received from the Dr. E.E. 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