The CONVINCE randomized trial found positive effects on quality of life for patients with chronic kidney disease treated with hemodiafiltration

In the CONVINCE trial, the primary analysis demonstrated a survival benefit for patients receiving high-dose hemodiafiltration (HDF) as compared with high-flux hemodialysis (HD). A secondary objective was to evaluate effects on health-related quality of life (HRQoL); assessed in eight domains (physical function, cognitive function, fatigue, sleep disturbance, anxiety, depression, pain interference, social participation) applying instruments from the Patient-Reported Outcome Measurement Information System (PROMIS) before randomization and every three months thereafter. In total 1360 adults with dialysis-dependent chronic kidney disease, eligible to receive high-flux HDF (23 liters or more), were randomized (1:1); 84% response rate to all questionnaires. Both groups reported a continuous deterioration in all HRQoL domains. Overall, raw score changes from baseline were more favorable in the HDF group, resulting in a significant omnibus test after a median observation period of 30 months. Most relevant single raw score differences were reported for cognitive function. Patients receiving HDF reported a decline of -0.95 units (95% confidence interval - 2.23 to +0.34) whereas HD treated patients declined by -3.90 units (-5.28 to - 2.52). A joint model, adjusted for mortality differences, utilizing all quarterly assessments, identified a significantly slower HRQoL decline in physical function, cognitive function, pain interference, and social participation for the HDF group. Their physical health summary score declined -0.46 units/year slower compared to the HD group. Thus, the CONVINCE trial showed a beneficial effect of high-dose hemodiafiltration for survival as well as a moderate positive effect on patients' quality of life, most pronounced with respect to their cognitive function.RegistrationNTR7138 on the International Clinical Trials Registry Platform In the CONVINCE trial, the primary analysis demonstrated a survival benefit for patients receiving high-dose hemodiafiltration (HDF) as compared with high-flux hemodialysis (HD). A secondary objective was to evaluate effects on health-related quality of life (HRQoL); assessed in eight domains (physical function, cognitive function, fatigue, sleep disturbance, anxiety, depression, pain interference, social participation) applying instruments from the Patient-Reported Outcome Measurement Information System (PROMIS) before randomization and every three months thereafter. In total 1360 adults with dialysis-dependent chronic kidney disease, eligible to receive high-flux HDF (23 liters or more), were randomized (1:1); 84% response rate to all questionnaires. Both groups reported a continuous deterioration in all HRQoL domains. Overall, raw score changes from baseline were more favorable in the HDF group, resulting in a significant omnibus test after a median observation period of 30 months. Most relevant single raw score differences were reported for cognitive function. Patients receiving HDF reported a decline of -0.95 units (95% confidence interval - 2.23 to +0.34) whereas HD treated patients declined by -3.90 units (-5.28 to - 2.52). A joint model, adjusted for mortality differences, utilizing all quarterly assessments, identified a significantly slower HRQoL decline in physical function, cognitive function, pain interference, and social participation for the HDF group. Their physical health summary score declined -0.46 units/year slower compared to the HD group. Thus, the CONVINCE trial showed a beneficial effect of high-dose hemodiafiltration for survival as well as a moderate positive effect on patients' quality of life, most pronounced with respect to their cognitive function. NTR7138 on the International Clinical Trials Registry Platform Lay SummaryPeople with end-stage chronic kidney disease have a life-limiting condition. As the disease progresses further, many of those may require renal replacement therapy. Compared with widely used hemodialysis, hemodiafiltration improves the clearance of specific types of uremic toxins. In the CONVINCE clinical trial, 1360 patients on high-flux hemodialysis were randomly assigned to continue with high-flux hemodialysis or switch to high-volume hemodiafiltration. In this trial, hemodiafiltration prolonged life expectancy compared with hemodialysis. We also investigated which treatment is associated with a better quality of life and collected self-report questionnaires from both groups over the course of the study. By the end of the study, patients treated with hemodiafiltration reported a better quality of life, in particular with respect to their cognitive function, compared with those receiving hemodialysis. People with end-stage chronic kidney disease have a life-limiting condition. As the disease progresses further, many of those may require renal replacement therapy. Compared with widely used hemodialysis, hemodiafiltration improves the clearance of specific types of uremic toxins. In the CONVINCE clinical trial, 1360 patients on high-flux hemodialysis were randomly assigned to continue with high-flux hemodialysis or switch to high-volume hemodiafiltration. In this trial, hemodiafiltration prolonged life expectancy compared with hemodialysis. We also investigated which treatment is associated with a better quality of life and collected self-report questionnaires from both groups over the course of the study. By the end of the study, patients treated with hemodiafiltration reported a better quality of life, in particular with respect to their cognitive function, compared with those receiving hemodialysis. Kidney diseases are highly prevalent and associated with increased mortality.1Jha V. Garcia-Garcia G. Iseki K. et al.Chronic kidney disease: global dimension and perspectives.Lancet. 2013; 382: 260-272Abstract Full Text Full Text PDF PubMed Scopus (3088) Google Scholar The health of patients with kidney failure is affected by specific symptoms, limitations in functional status, and burden of kidney replacement therapy (KRT).2Valderrabano F. Jofre R. Lopez-Gomez J.M. Quality of life in end-stage renal disease patients.Am J Kidney Dis. 2001; 38: 443-464Abstract Full Text Full Text PDF PubMed Google Scholar Next to mortality and morbidity, physical and psychosocial aspects of perceived health, often also described as health-related quality of life (HRQoL), are important outcomes for patients with kidney disease.3Tong A. Manns B. Hemmelgarn B. et al.Establishing core outcome domains in hemodialysis: report of the Standardized Outcomes in Nephrology–Hemodialysis (SONG-HD) consensus workshop.Am J Kidney Dis. 2017; 69: 97-107Abstract Full Text Full Text PDF PubMed Google Scholar,4Verberne W.R. Das-Gupta Z. Allegretti A.S. et al.Development of an international standard set of value-based outcome measures for patients with chronic kidney disease: a report of the International Consortium for Health Outcomes Measurement (ICHOM) CKD Working Group.Am J Kidney Dis. 2019; 73: 372-384Abstract Full Text Full Text PDF PubMed Scopus (93) Google Scholar As enhancing the HRQoL of the patients is a primary objective of KRT,5Gilbert J. Lovibond K. Mooney A. Dudley J. Renal replacement therapy: summary of NICE guidance.BMJ. 2018; 363k4303PubMed Google Scholar a critical inquiry arises as to whether distinct kidney replacement treatment modalities, in particular hemodiafiltration (HDF) versus conventional hemodialysis (HD), differentially affect patient health.6Blankestijn P.J. Fischer K.I. Barth C. et al.Benefits and harms of high-dose haemodiafiltration versus high-flux haemodialysis: the comparison of high-dose haemodiafiltration with high-flux haemodialysis (CONVINCE) trial protocol.BMJ Open. 2020; 10e033228Crossref PubMed Scopus (46) Google Scholar Several mechanisms have been discussed that might lead to improved health perceptions and reduced treatment burden, including improved clearance of a broader molecular weight spectrum of uremic toxins, improvements in hemodynamic stability, anti-inflammatory effects, and correcting endothelial dysfunction.7Canaud B. Blankestijn P.J. Grooteman M.P.C. Davenport A. Why and how high volume hemodiafiltration may reduce cardiovascular mortality in stage 5 chronic kidney disease dialysis patients? a comprehensive literature review on mechanisms involved.Semin Dial. 2022; 35: 117-128Crossref PubMed Scopus (17) Google Scholar,8Lim J.-H. Park Y. Yook J.-M. et al.Randomized controlled trial of medium cut-off versus high-flux dialyzers on quality of life outcomes in maintenance hemodialysis patients.Sci Rep. 2020; 10: 7780Crossref PubMed Scopus (0) Google Scholar Previous study findings on the effects of HDF versus HD on HRQoL have been inconclusive. Some observational studies supported the assumption that HDF is accompanied by better perceived HRQoL.9Borrelli S. Minutolo R. De Nicola L. et al.Quality of life of hemodialysis patients in Central and Southern Italy: cross-sectional comparison between hemodiafiltration with endogenous reinfusion (HFR) and bicarbonate hemodialysis.G Ital Nefrol. 2016; 33 (gin/33.3.8)Google Scholar,10Knezevic M.Z. Djordjevic V.V. Radovanovic-Velickovic R.M. et al.Influence of dialysis modality and membrane flux on quality of life in hemodialysis patients.Renal Fail. 2012; 34: 849-855Crossref PubMed Scopus (0) Google Scholar A prospective randomized controlled trial (RCT) found positive effects for HDF compared with HD on disease-specific symptoms and other aspects of HRQoL,11Karkar A. Abdelrahman M. Locatelli F. A randomized trial on health-related patient satisfaction level with high-efficiency online hemodiafiltration versus high-flux dialysis.Blood Purification. 2015; 40: 84-91Crossref PubMed Scopus (0) Google Scholar a finding that is partially supported by other randomized trials.12Kantartzi K. Panagoutsos S. Mourvati E. et al.Can dialysis modality influence quality of life in chronic hemodialysis patients? low-flux hemodialysis versus high-flux hemodiafiltration: a cross-over study.Renal Fail. 2013; 35: 216-221Crossref PubMed Scopus (0) Google Scholar,13Morena M. Jaussent A. Chalabi L. et al.Treatment tolerance and patient-reported outcomes favor online hemodiafiltration compared to high-flux hemodialysis in the elderly.Kidney Int. 2017; 91: 1495-1509Abstract Full Text Full Text PDF PubMed Scopus (138) Google Scholar However, within the Convective Transport Study (n = 714), comparing effects of HDF with low-flux HD on HRQoL, no meaningful group differences were observed.14Mazairac A.H. de Wit G.A. Grooteman M.P. et al.Effect of hemodiafiltration on quality of life over time.Clin J Am Soc Nephrol. 2013; 8: 82-89Crossref PubMed Scopus (49) Google Scholar Several other studies equally did not find considerable differences.15den Hoedt C.H. Mazairac A.H. van den Dorpel M.A. et al.Effect of hemodiafiltration on mortality, inflammation and quality of life.Hemodiafiltration-A New Era. 2011; 168: 39-52Crossref Scopus (5) Google Scholar, 16Hill K.E. Kim S. Crail S. et al.A comparison of self-reported quality of life for an Australian haemodialysis and haemodiafiltration cohort.Nephrology (Carlton). 2017; 22: 624-630Crossref Scopus (2) Google Scholar, 17Smith J.R. Zimmer N. Bell E. et al.A randomized, single-blind, crossover trial of recovery time in high-flux hemodialysis and hemodiafiltration.Am J Kidney Dis. 2017; 69: 762-770Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar, 18Stefánsson B.V. Abramson M. Nilsson U. Haraldsson B. Hemodiafiltration improves plasma 25-hepcidin levels: a prospective, randomized, blinded, cross-over study comparing hemodialysis and hemodiafiltration.Nephron Extra. 2012; 2: 55-65Crossref PubMed Google Scholar A systematic review from 2014, including 6 RCTs evaluating HDF, concluded that the current evidence was too inconsistent to draw conclusions about the effect of HDF versus HD on HRQoL.19Nistor I. Palmer S.C. Craig J.C. et al.Convective versus diffusive dialysis therapies for chronic kidney failure: an updated systematic review of randomized controlled trials.Am J Kidney Dis. 2014; 63: 954-967Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar A meta-analysis from 2018 reported that HDF was associated with significantly increased social activity compared with HD; however, HDF did not improve other HRQoL-related domains.20Suwabe T. Barrera-Flores F.J. Rodriguez-Gutierrez R. et al.Effect of online hemodiafiltration compared with hemodialysis on quality of life in patients with ESRD: a systematic review and meta-analysis of randomized trials.PLoS One. 2018; 13e0205037Crossref Scopus (25) Google Scholar To date, there is a lack of conclusive evidence stemming from large-scale RCTs comparing the impact of HDF versus HD on perceived HRQoL.21Mitchell C.R. Hornig C. Canaud B. Systematic review to compare the outcomes associated with the modalities of expanded hemodialysis (HDx) versus high-flux hemodialysis and/or hemodiafiltration (HDF) in patients with end-stage kidney disease (ESKD).Semin Dial. 2023; 36: 86-106Crossref Scopus (7) Google Scholar To fill this research gap, the CONVINCE trial included a state-of-the-art HRQoL assessment, secondarily to its primary end point, mortality.22Blankestijn P.J. Vernooij R.W.M. Hockham C. et al.Effect of hemodiafiltration or hemodialysis on mortality in kidney failure.N Engl J Med. 2023; 389: 700-709Crossref PubMed Scopus (69) Google Scholar CONVINCE was an open-label RCT to assess the benefits and harms of high-dose HDF compared with high-flux HD on all-cause mortality, cardiovascular events, hospitalizations, patient-reported outcomes, including HRQoL, and cost-effectiveness. The CONVINCE protocol has been previously detailed,22Blankestijn P.J. Vernooij R.W.M. Hockham C. et al.Effect of hemodiafiltration or hemodialysis on mortality in kidney failure.N Engl J Med. 2023; 389: 700-709Crossref PubMed Scopus (69) Google Scholar,23Vernooij R.W.M. Bots M.L. Strippoli G.F.M. et al.CONVINCE in the context of existing evidence on haemodiafiltration.Nephrol Dial Transplant. 2022; 37: 1006-1013Crossref Scopus (12) Google Scholar and registered as NTR7138 on the International Clinical Trials Registry Platform. Patients were treated at 61 centers in 8 European countries (Supplementary Table S1), screened and enrolled from November 2018 to April 2021. Participants remained in the trial until the observation period ended in April 2023, after the intended minimal observation period of 24 months had been reached for the final enrolled patient. CONVINCE was an investigator-initiated trial, designed and overseen by a steering committee comprising academic and dialysis providers, conducted, and analyzed independently of the financial contributors. The study was funded by the European Commission (Horizon 2020 research and innovation program, agreement 754803). The scientific committee (Supplementary Table S2) had final responsibility for the interpretation of the data and the preparation of the manuscript. CONVINCE was monitored by an academic contract research organization, Julius Clinical (www.juliusclinical.org), following standard operation procedures. Each site that randomized ≥1 patients was visited at least once, and more often when >31 patients had been enrolled. Periodic contacts were undertaken by video call or telephone. All data were reviewed by Julius Clinical for completeness and accuracy. Patients aged ≥18 years were included, on HD treatment for ≥3 months, likely to achieve high-dose HDF (≥23 L in postdilution mode), willing to have dialysis sessions with duration of ≥4 hours, 3 times a week. Participants needed to be able to complete the questionnaires without assistance in their local language. Written informed consent was obtained in accordance with the Declaration of Helsinki, laws and regulations, and the General Data Protection Regulation Directive (regulation 2016/679). Participants who successfully completed the screening procedures were randomly assigned in a 1:1 ratio to receive either high-dose HDF or continuation of high-flux HD. The allocation to the study arm was concealed and performed by a centralized block randomization scheme, stratified by center, using a central interactive web response system managed by Julius Clinical. Because of the nature of the study, it was not possible to blind participants, or site investigators for participants' treatment assignment. The central investigator team, including the statistics team, remained blinded throughout the duration of the study. The intervention was high-dose HD with online production of substitution fluid and ultrapure bicarbonate-based dialysis fluid. High-dose HDF was defined as a convection volume of ≥23 L per session in postdilution mode. The comparison group received conventional HD using high-flux dialysis membranes and ultrapure bicarbonate-based dialysis fluid as standard of dialysis care.6Blankestijn P.J. Fischer K.I. Barth C. et al.Benefits and harms of high-dose haemodiafiltration versus high-flux haemodialysis: the comparison of high-dose haemodiafiltration with high-flux haemodialysis (CONVINCE) trial protocol.BMJ Open. 2020; 10e033228Crossref PubMed Scopus (46) Google Scholar,22Blankestijn P.J. Vernooij R.W.M. Hockham C. et al.Effect of hemodiafiltration or hemodialysis on mortality in kidney failure.N Engl J Med. 2023; 389: 700-709Crossref PubMed Scopus (69) Google Scholar To assess the generic HRQoL, we followed suggestions by the International Consortium for Health Outcomes Measurements,4Verberne W.R. Das-Gupta Z. Allegretti A.S. et al.Development of an international standard set of value-based outcome measures for patients with chronic kidney disease: a report of the International Consortium for Health Outcomes Measurement (ICHOM) CKD Working Group.Am J Kidney Dis. 2019; 73: 372-384Abstract Full Text Full Text PDF PubMed Scopus (93) Google Scholar applying the Patient-Reported Outcome Measurement Information System (PROMIS)-29 v2.0 profile, a commonly used instrument of the PROMIS.24Cella D. Riley W. Stone A. et al.The Patient-Reported Outcomes Measurement Information System (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005–2008.J Clin Epidemiol. 2010; 63: 1179-1194Abstract Full Text Full Text PDF PubMed Scopus (3429) Google Scholar This instrument includes 4-item short forms for 7 health domains (physical function, fatigue, sleep disturbance, depression, anxiety, pain interference, and ability to participate in social roles and activities) as well as a single item measuring pain intensity.25Cella D. Choi S.W. Condon D.M. et al.PROMIS(®) adult health profiles: efficient short-form measures of seven health domains.Value Health. 2019; 22: 537-544Abstract Full Text Full Text PDF PubMed Scopus (349) Google Scholar These scales cover core domains also recommended by the Standardized Outcomes in Nephrology initiative.3Tong A. Manns B. Hemmelgarn B. et al.Establishing core outcome domains in hemodialysis: report of the Standardized Outcomes in Nephrology–Hemodialysis (SONG-HD) consensus workshop.Am J Kidney Dis. 2017; 69: 97-107Abstract Full Text Full Text PDF PubMed Google Scholar As fatigue was identified as particularly relevant, 2 additional PROMIS items from the fatigue item bank were added. A 4-item PROMIS cognitive function short form26Iverson G.L. Marsh J.M. Connors E.J. Terry D.P. Normative reference values, reliability, and item-level symptom endorsement for the PROMIS® v2.0 cognitive function-short forms 4a, 6a and 8a.Arch Clin Neuropsychol. 2021; 36: 1341-1349Crossref Scopus (23) Google Scholar was administered to cover another prespecified patient-reported outcome domain by the Standardized Outcomes in Nephrology initiative in all countries except Romania, as translations were not available for this particular domain. PROMIS-29 v2.0 domains were aggregated to physical and mental health summary scores.27Hays R.D. Spritzer K.L. Schalet B.D. Cella D. PROMIS(®)-29 v2.0 profile physical and mental health summary scores.Qual Life Res. 2018; 27: 1885-1891Crossref PubMed Scopus (341) Google Scholar The physical health summary score is largely determined by physical function and pain scores, whereas the insidMHS mainly represents affective health (depression, anxiety), fatigue, sleep disturbance, as well as social participation. PROMIS scores are calibrated to a T-score metric with a representative US general population mean of 50 and an SD of 10. Patient-reported outcomes were collected at baseline, and then every 3 months thereafter until the end of the study period, or completion of treatment due to mortality, study withdrawal, renal transplantation, or loss to follow-up. Further patient-reported assessments used in the study were a symptom list from the KDQoL, collected quarterly over the course of the study, and a health use module collected every 6 months, including the EQ-5D, the SF-12, and the PHQ-9 for the purpose to use in the economic evaluation. Although this article primarily reports the comparative HRQoL outcomes as measured by the PROMIS instruments, we report postintervention data on these scales to ensure comprehensive reporting. We followed recent analysis recommendations from the SISAQOL group,28Coens C. Pe M. Dueck A.C. et al.International standards for the analysis of quality-of-life and patient-reported outcome endpoints in cancer randomised controlled trials: recommendations of the SISAQOL Consortium.Lancet Oncol. 2020; 21: e83-e96Abstract Full Text Full Text PDF PubMed Scopus (185) Google Scholar to assess overall HRQoL changes. The difference between HDF and HD in mean change from baseline was assessed after an observation period of 30 respectively 36 months, using an omnibus test for all 8 scales to avoid multiple testing. For this analysis, we used the available data at both time points only and did not impute any missing values. In particular, patients who died or received a kidney transplant during the course of the study have been excluded. Within the statistical analysis plan published in advance,6Blankestijn P.J. Fischer K.I. Barth C. et al.Benefits and harms of high-dose haemodiafiltration versus high-flux haemodialysis: the comparison of high-dose haemodiafiltration with high-flux haemodialysis (CONVINCE) trial protocol.BMJ Open. 2020; 10e033228Crossref PubMed Scopus (46) Google Scholar a linear-mixed model of change from baseline was chosen as the primary analytic method (see Supplementary Methods). This model estimates the trajectory of individual patients, based on all available data at all follow-up time points. To be included, patients had to complete the baseline assessment and at least 1 follow-up. No missing data were imputed because the linear-mixed model deals with missing information appropriately, when data are missing at random.29Peters S.A. Bots M.L. den Ruijter H.M. et al.Multiple imputation of missing repeated outcome measurements did not add to linear mixed-effects models.J Clin Epidemiol. 2012; 65: 686-695Abstract Full Text Full Text PDF PubMed Scopus (109) Google Scholar The effect of HDF compared with HD on continuous health domains was modeled as the change from baseline per year. We modeled group allocation and time since randomization (quarterly) as well as their interaction as fixed effects.30Rizopoulos D.J.M. an R package for the joint modelling of longitudinal and time-to-event data.J Stat Software. 2010; 35: 1-33Crossref PubMed Google Scholar The respective baseline score was controlled for, and a random intercept was included as well as a random slope for time since randomization for each participant. Mortality and perceived health are likely to be dependent outcomes, as patients more likely to decease may report a more compromised health state and quality of life beforehand and vice versa.31Mapes D.L. Lopes A.A. Satayathum S. et al.Health-related quality of life as a predictor of mortality and hospitalization: the Dialysis Outcomes and Practice Patterns Study (DOPPS).Kidney Int. 2003; 64: 339-349Abstract Full Text Full Text PDF PubMed Scopus (691) Google Scholar,32Nakano J. Fukushima T. Tanaka T. et al.Physical function predicts mortality in patients with cancer: a systematic review and meta-analysis of observational studies.Support Care Cancer. 2021; 29: 5623-5634Crossref PubMed Scopus (39) Google Scholar Hence, for missing observations of patient-reported outcome data due to death, the statistical assumption of missing at random may be violated. Because the risk of death is different between treatment groups, linear-mixed model results may therefore be biased.33Touraine C. Cuer B. Conroy T. et al.When a joint model should be preferred over a linear mixed model for analysis of longitudinal health-related quality of life data in cancer clinical trials.BMC Med Res Method. 2023; 23: 36Crossref Scopus (0) Google Scholar To investigate the robustness of the linear-mixed model results against such a violation, we thus additionally applied a joint model,34Chesnaye N.C. Tripepi G. Dekker F.W. et al.An introduction to joint models—applications in nephrology.Clin Kidney J. 2020; 13: 143-149Crossref PubMed Scopus (0) Google Scholar which takes the potential dependency of self-reported health status measures and observed differences on mortality rates into account.22Blankestijn P.J. Vernooij R.W.M. Hockham C. et al.Effect of hemodiafiltration or hemodialysis on mortality in kidney failure.N Engl J Med. 2023; 389: 700-709Crossref PubMed Scopus (69) Google Scholar In the joint model, the longitudinal model was specified as described above. Time to event (all-cause mortality) was modeled using a Weibull relative risk model, with value and slope of the health outcome as predictor. Robustness of linearity assumptions were assessed. As measures of efficacy, we report point estimates, the respective 95% confidence intervals, and P values for both the main and interaction effect of group allocation from the longitudinal model. Sample size calculations were based on the expected effect on mortality and described in the statistical analysis plan.23Vernooij R.W.M. Bots M.L. Strippoli G.F.M. et al.CONVINCE in the context of existing evidence on haemodiafiltration.Nephrol Dial Transplant. 2022; 37: 1006-1013Crossref Scopus (12) Google Scholar The achieved sample size provides >95% power to identify small group HRQoL single-domain differences (effect sizes >0.2) in all 3 types of analyses. Analyses were performed using R (version 4.1.2) and detailed in the statistical analyses plan. Between November 2018 and April 2021, 1407 patients were assessed for eligibility; 47 did not meet the eligibility criteria, or declined their participation. The remaining 1360 patients were randomized, of whom 683 patients were assigned to HDF and 677 to HD (Figure 1). Patients had been on KRT for >2.5 years on average, with a mean age of 62 years, with a majority of men (63%; Table 1 and Supplementary Table S3).Table 1Summary characteristics and patient-reported health status at baselineVariableTotal (n = 1360)High-flux hemodialysis (n = 677)High-dose hemodiafiltration (n = 683)Sociodemographic variables Age, yr62.4 ± 13.562.3 ± 13.562.5 ± 13.5 Women, n (%)504 (37.1)257 (38.0)247 (36.2)Biomedical variables Cardiovascular disease, n (%)aCardiovascular disease includes history of any 1 or more of: angina, myocardial infarction, coronary stent or dotter procedure and coronary artery bypass graft, diagnosis of congestive heart failure, atrial fibrillation, TIA, cerebrovascular accident, abdominal aortic aneurysm or intermittent claudication, placement of pacemaker or internal defibrillator, carotid endarterectomy, stent or dotter procedure, bypass surgery or amputation of the arteries of the lower extremities, and stent or dotter procedure of the renal arteries.612 (45.0)316 (46.7)296 (43.3) Diabetes, n (%)481 (35.4)251 (37.1)230 (33.7) Body mass index, kg/m227.4 ± 5.727.5 ± 5.727.4 ± 5.6 Body surface area, m2bBody surface area was calculated using the Du Bois formula.1.9 ± 0.21.9 ± 0.21.9 ± 0.2 Systolic blood pressure/predialysis, mm Hg141 ± 22141 ± 22141 ± 22 Diastolic blood pressure/predialysis, mm Hg73 ± 1572 ± 1573 ± 14 Hemoglobin, g/dl11.3 ± 1.211.3 ± 1.211.3 ± 1.2 Serum creatinine, mg/dlcGeometric mean of predialysis and postdialysis serum measurements.7.4 ± 2.47.3 ± 2.37.4 ± 2.5 C-reactive protein, median (IQR), mg/l5 (2–10)4 (2–10)5 (2–11) Blood flow rate, ml/mindBlood flow rate through extracorporeal circuit.368 ± 55367 ± 56369 ± 54 Single-pool Kt/V, median (IQR)eThe single-pool urea Kt/V for hemodialysis is a dimensionless measure of the adequacy of small-molecule removal provided by a single dialysis treatment. In this measure, K represents the urea clearance by the dialyzer, t represents the treatment time, and V represents the urea distribution volume.1.6 (1.4–1.8)1.6 (1.4–1.8)1.6 (1.5–1.8) Dialysis vintage, median (IQR), mo33 (15–72)30 (14–67)35 (16–78)Region, n (%) Eastern Europe467 (34.3)233 (34.4)234 (34.3) Southern Europe452 (33.2)226 (33.4)226 (33.1) Western Europe441 (32.4)218 (32.2)223 (32.7)Patient-reported outcomes Health domainsPhysical function44.0 ± 9.943.8 ± 9.944.3 ± 10.0Cognitive function51.3 ± 9.351.5 ± 8.951.1 ± 9.7Fatigue50.3 ± 9.350.3 ± 9.550.2 ± 9.1Sleep disturbance49.0 ± 9.349.0 ± 9.249.1 ± 9.4Depression50.3 ± 9.050.2 ± 9.150.5 ± 9.0Anxiety49.4 ± 9.349.5 ± 9.349.3 ± 9.4Pain interference51.9 ± 9.751.5 ± 9.752.3 ± 9.7Social participation51.8 ± 10.551.7 ± 10.451.9 ± 10.5 Summary scoresPROMIS physical health44.8 ± 10.144.5 ± 10.145.1 ± 10.2PROMIS mental Health50.3 ± 8.950.2 ± 9.050.3 ± 8.8SF-12 physical component score42.4 ± 9.242.4 ± 9.142.5 ± 9.2SF-12 mental component score47.9 ± 12.048.3 ± 11.847.5 ± 12.2EQ-5D health utility0.8 ± 0.30.8 ± 0.20.8 ± 0.2EQ-5D VAS68.0 ± 21.068.3 ± 20.768.2 ± 20.8EQ-5D, xxx; IQR, interquartile range; PROMIS, Patient-Reported Outcome Measurement Information System; SF-12, xxx; TIA, trans