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. 2020 Dec 30;15(12):e0244639. doi: 10.1371/journal.pone.0244639

Progression of coronary artery calcification in conventional hemodialysis, nocturnal hemodialysis, and kidney transplantation

Thijs T Jansz 1,2, Akin Özyilmaz 3,4, Franka E van Reekum 1, Franciscus T J Boereboom 2, Pim A de Jong 5, Marianne C Verhaar 1, Brigit C van Jaarsveld 6,*
Editor: Ping-Hsun Wu7
PMCID: PMC7773242  PMID: 33378347

Abstract

Introduction

Cardiovascular disease is the leading cause of death in end-stage renal disease (ESRD) and is strongly associated with vascular calcification. An important driver of vascular calcification is high phosphate levels, but these become lower when patients initiate nocturnal hemodialysis or receive a kidney transplant. However, it is unknown whether nocturnal hemodialysis or kidney transplantation mitigate vascular calcification. Therefore, we compared progression of coronary artery calcification (CAC) between patients treated with conventional hemodialysis, nocturnal hemodialysis, and kidney transplant recipients.

Methods

We measured CAC annually up to 3 years in 114 patients with ESRD that were transplantation candidates: 32 that continued conventional hemodialysis, 34 that initiated nocturnal hemodialysis (≥4x 8 hours/week), and 48 that received a kidney transplant. We compared CAC progression between groups as the difference in square root transformed volume scores per year (ΔCAC SQRV) using linear mixed models. Reference category was conventional hemodialysis.

Results

The mean age of the study population was 53 ±13 years, 75 (66%) were male, and median dialysis duration was 28 (IQR 12–56) months. Median CAC score at enrollment was 171 (IQR 10–647), which did not differ significantly between treatment groups (P = 0.83). Compared to conventional hemodialysis, CAC progression was non-significantly different in nocturnal hemodialysis -0.10 (95% CI -0.77 to 0.57) and kidney transplantation -0.33 (95% CI -0.96 to 0.29) in adjusted models.

Conclusions

Nocturnal hemodialysis and kidney transplantation are not associated with significantly less CAC progression compared to conventional hemodialysis during up to 3 years follow-up. Further studies are needed to confirm these findings, to determine which type of calcification is measured with CAC in end-stage renal disease, and whether that reflects cardiovascular risk.

Introduction

Cardiovascular disease is the leading cause of death among patients with end-stage renal disease [1, 2]. This high cardiovascular mortality is strongly associated with vascular calcification [3, 4], which occurs frequently and progresses rapidly in end-stage renal disease [2, 5]. Vascular calcification can be measured at various sites, such as the coronary arteries, and vascular calcification in end-stage renal disease is promoted by phosphate, which is frequently elevated in end-stage renal disease [6, 7].

Phosphate levels are considerably lower in patients who dialyze longer and more frequently, such as in frequent nocturnal hemodialysis [8, 9]. By improving phosphate control, nocturnal hemodialysis could mitigate progression of vascular calcification, but progression of vascular calcification in nocturnal hemodialysis has never been compared to conventional hemodialysis. Similarly, it is thought that kidney transplantation could halt progression of vascular calcification. However, only two previous studies compared progression of vascular calcification between kidney transplant recipients and patients on hemodialysis [10, 11]. These studies had important limitations, as in one study those on hemodialysis were not transplantation-eligible and therefore not comparable to kidney transplant recipients [11], whereas both studies did not account for calcification at baseline, which is strongly associated with progression [12].

We therefore set out to compare progression of vascular calcification between conventional hemodialysis, nocturnal hemodialysis, and kidney transplantation. To this end, we conducted the NOCTx study, a prospective study that measured coronary artery calcification (CAC) annually during 3 years in 3 groups of patients with end-stage renal disease: transplantation-eligible patients that were treated with conventional hemodialysis, transplantation-eligible patients that switched from conventional to nocturnal hemodialysis, and patients on dialysis that received a kidney transplant.

Materials and methods

Study design and population

NOCTx (NCT00950573) is a prospective study designed to compare CAC progression between different renal replacement therapies. NOCTx included patients that continued chronic conventional hemodialysis or peritoneal dialysis after at least 2 months on dialysis, patients that switched from conventional hemodialysis to nocturnal hemodialysis (≥4x 8 hours per week), and patients on dialysis who received a kidney transplant 2–3 months before enrollment. Patients were eligible when aged between 18 and 75 years and were candidates for transplantation when on dialysis. NOCTx excluded patients with a life expectancy <3 months, pre-emptive transplantation, non-adherence to dialysis regimens, drug abuse, and pregnancy. All participants gave written informed consent. NOCTx has been approved by the Medical Ethics Committee of the University Medical Center Utrecht and was conducted according to the Declaration of Helsinki.

Between December 2009 and February 2016, 329 patients were screened for eligibility in 8 Dutch dialysis centers including two academic hospitals where transplantation procedures took place during that period. NOCTx included 181 of these patients, who underwent study exams at University Medical Center Utrecht at enrollment and after 1, 2, and 3 years. Patients left the study if they switched renal replacement therapy, except for 8 patients on dialysis that received a kidney transplant within 6 months after enrollment and continued participation in the kidney transplantation group. For the current study, we excluded patients treated with peritoneal dialysis (n = 31).

Treatment characteristics

Patients were treated according to the Kidney Disease: Improving Global Outcomes (KDIGO) 2009 guidelines by the attending nephrologists [13]. Conventional hemodialysis (3x 4 hours per week, in-center) and nocturnal hemodialysis (4-6x 8 hours per week, at home) were delivered with a default dialysate calcium concentration of 1.50 mmol/L. Kidney transplant recipients received standard immunosuppressant regimens consisting of a calcineurin inhibitor (tacrolimus), mycophenolate mofetil, and prednisolone in tapering doses. All live donors provided written informed consent that was freely given. Deceased donors were nationally registered organ donors whose organs were allocated by Eurotransplant (Leiden, the Netherlands).

CAC measurements

CAC scores were determined at each study exam using non-enhanced prospectively triggered cardiac multi-slice computed tomography (iCT 256 or IQon, Philips Medical Systems, Best, the Netherlands). Acquisition parameters were as follows: 120 kV, 40–50 mAs, rotation time 270 ms, and 128 x 0.625 mm collimation (iCT 256) / 64 x 0.625 mm collimation (IQon). To improve imaging quality, metoprolol was given intravenously if heart rate was above 60/min. We used a calcium threshold of ≥130 Hounsfield units. A single reader (TJ) read all scans blinded for treatment group and chronologically per patient, in order to exclude coronary segments with severe motion artefacts or stents at a given scan from an entire set. We used calcium volume scores as primary outcome measure and also calculated Agatston scores. These scores are highly correlated (Spearman’s ρ = 0.99). Reproducibility of coronary artery calcification measurements has been shown to be excellent (intraclass correlation coefficient >0.95) [14].

Other variables

At each study exam, study personnel collected data on laboratory parameters (total calcium, albumin, phosphate, and parathyroid hormone) by averaging values of routine measurements of the 3 months preceding the study exam. Residual urine production was classified as present (≥100 mL/24h) or absent. We assessed history of kidney disease, current dialysis schedule, and presence of comorbidities by chart review, and evaluated medication use by medication inventory.

We estimated glomerular filtration rate with the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) 2009 equation for kidney transplant recipients. We defined dialysis duration as the time between the first day of dialysis and enrollment, minus the time with a functioning kidney transplant. Cardiovascular events were defined as any myocardial infarction, percutaneous coronary intervention, coronary artery bypass grafting, aortic aneurysm repair, stroke, new intermittent claudication, peripheral artery angioplasty or bypass grafting.

Statistical analyses

We reported normally distributed variables as mean (± standard deviation), non-normally distributed variables as median (interquartile range, IQR), and categorical data as number (percentage). We compared normally distributed variables with Student’s t-tests between two groups and with one-way analyses of variance between three, non-normally distributed variables with Mann-Whitney-U tests between two groups and with Kruskal-Wallis tests between three, and categorical variables with chi-squared tests.

The associations of treatment group with CAC progression were evaluated by defining CAC progression as change per year in square root transformed volume scores (ΔCAC SQRV). This approach, also known as Hokanson’s method, accounts for interscan variability [15] and has been used by others [16, 17]. The outcome variable in this approach (ΔCAC SQRV) is normally distributed, enabling adjustments for potential confounders. We adjusted these analyses for CAC SQRV at enrollment and used mixed-effects to account for repeated measurements. We adjusted for factors related to calcification [18]: age (years), sex, presence of diabetes mellitus, dialysis duration (months), current smoking, presence of residual urine production, and vitamin K antagonist use. Conventional hemodialysis was the reference group. Of note, the comparison of CAC progression in conventional hemodialysis and peritoneal dialysis is discussed elsewhere [19].

Regression coefficients are reported with 95% confidence intervals (95% CI). We considered p-values of ≤ 0.05 (two-tailed) statistically significant and used R 3.4.1 (R Foundation Statistical Computing) for all analyses.

Sensitivity analyses

To test the robustness of the associations, we repeated the analyses of treatment group with CAC progression using Agatston scores instead of volume scores.

Results

Study population

A total of 181 patients were included in the NOCTx study. For the current study, we excluded patients treated with peritoneal dialysis (n = 31) and patients that did not attend any follow-up exam (n = 36), leaving an analytical sample of 114 patients (Fig 1). The mean age of the study population (n = 114) was 53 ±13 years, 75 (66%) were male, dialysis duration (including historical dialysis duration of kidney transplant recipients) was median 28 (IQR 12–56) months, and 14 (12%) had diabetes mellitus (Table 1). There were 32 patients treated with conventional hemodialysis, 34 treated with nocturnal hemodialysis, and 48 kidney transplant recipients. Patients on nocturnal hemodialysis were enrolled after a training period of about 3 months. Kidney transplant patients were included about 3 months after transplantation, since many (25/48) received a deceased-donor transplant. Compared to patients on conventional hemodialysis, patients on nocturnal hemodialysis less often used vitamin D analogs (42% versus 84%) or calcium-containing phosphate binders (15% versus 50%). Also, patients on nocturnal hemodialysis had lower phosphate levels than patients on conventional hemodialysis (mean 1.2 versus 1.5 mmol/L), as did kidney transplant recipients (mean 0.9 mmol/L). These differences in phosphate levels subsisted during follow-up (S1 Fig).

Fig 1. Study flowchart.

Fig 1

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Table 1. Characteristics at enrollment of 114 patients with end-stage renal disease stratified by renal replacement therapy.

Conventional hemodialysis (n = 32) Nocturnal hemodialysis (n = 34) Kidney transplantation (n = 48) P value
Demographics and medical history
Age (years) 53 ±12 52 ±13 52 ±14 0.93
Male sex (%) 19 (59%) 20 (59%) 36 (75%) 0.21
Diabetes mellitus (%) 6 (19%) 5 (15%) 3 (6%) 0.22
Cardiovascular disease (%) 7 (22%) 9 (27%) 6 (13%) 0.26
Current smoker (%) 4 (13%) 6 (18%) 6 (13%) 0.77
History of kidney disease
Dialysis duration (months) 27 (11–58) 29 (16–56) 28 (12–51) 0.65
Cause of end-stage renal disease (%) 0.28
 • Cystic kidney disease 4 (13%) 6 (18%) 14 (29%)
 • Interstitial nephritis 2 (6%) 0 1 (2%)
 • Glomerulonephritis 8 (25%) 11 (32%) 9 (19%)
 • Vascular disease 8 (25%) 4 (12%) 10 (21%)
 • Diabetic nephropathy 5 (16%) 2 (6%) 2 (4%)
 • Other 3 (9%) 6 (18%) 5 (10%)
 • Unknown 2 (6%) 5 (15%) 7 (15%)
Dialysis therapy and kidney function
Dialysis therapy
 • Weekly dialysis sessions 2.9 ±0.4 5.2 ±0.8 -
 • Weekly dialysis hours 11.0 ±2.0 41.2 ±6.4 -
Kidney function
 • Residual urine production ≥100mL/24h (%) 19 (59%) 11 (32%) -
 • eGFR (mL/min) - - 57 ±20
Medication use
Vitamin K antagonists (%) 7 (22%) 5 (15%) 4 (8%) 0.23
Vitamin D analogs (%) 27 (84%) 14 (42%) 5 (10%) <0.01
Calcium-containing phosphate binder (%) 16 (50%) 5 (15%) - <0.01
Cinacalcet (%) 7 (22%) 9 (27%) 2 (4%) 0.07
Physical and laboratory parameters
Body mass index (kg/m2) 26.8 ±5.0 25.8 ±5.4 24.4 ±3.5 0.06
Systolic blood pressure (mmHg) 142 ±19 138 ±19 128 ±14 0.01
Diastolic blood pressure (mmHg) 79 ±11 77 ±11 77 ±9 0.80
Calcium (mmol/L) 2.3 ±0.1 2.3 ±0.2 2.4 ±0.1 0.02
Albumin (g/L) 40.8 ±3.1 41.7 ±3.6 39.9 ±3.4 0.07
Phosphate (mmol/L) 1.6 ±0.3 1.2 ±0.3 0.9 ±0.5 <0.01
Parathyroid hormone (pmol/L) 30 (17–48) 5 (3–14) 11 (7–21) <0.01
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Data are presented as mean ±standard deviation, median (interquartile range) or number (percentage).

Data of patients on nocturnal hemodialysis and kidney transplant recipients were measured at enrollment, i.e. about 3 months after initiating this treatment.

Abbreviations: eGFR: estimated glomerular filtration rate, calculated with the Chronic Kidney Disease-Epidemiology Collaboration equation 2009.

Patients that did not complete any follow-up exam (n = 36) had similar characteristics compared to the study population (S1 Table): they were on average 52 ±13 years old, 23 (64%) were male, dialysis duration was median 36 (IQR 18–66) months, and 10 (28%) had diabetes mellitus (all P>0.05 versus study population). Their median CAC score at enrollment was 323 (IQR 1–1181) (P = 0.18 versus study population).

During follow-up, 2 patients on conventional hemodialysis died (6%), as did 0 patient on nocturnal hemodialysis, and 2 kidney transplant recipients (4%). Cardiovascular events occurred in 2 patients on conventional hemodialysis (6%), in 5 patients on nocturnal hemodialysis (15%), and in 3 kidney transplant recipients (6%). Eleven patients on conventional hemodialysis received a kidney transplant (34%), as did 7 patients on nocturnal hemodialysis (21%).

Associations of renal replacement therapy with CAC progression

At enrollment, CAC scores were median 182 (IQR 3–835) in patients on conventional hemodialysis, 176 (IQR 16–501) in patients on nocturnal hemodialysis, and 110 (IQR 10–523) in kidney transplant recipients (P = 0.83 for difference). Eight patients on conventional hemodialysis had no calcification (25%), compared to 7 on nocturnal hemodialysis (21%) and 9 kidney transplant recipients (19%).

During 3 years of follow-up, CAC progressed in most patients (Table 2 and Fig 2). In patients on conventional hemodialysis, ΔCAC SQRV was 1.37 per year (95% CI 0.81 to 1.93), while it was 1.29 per year in patients on nocturnal hemodialysis (95% CI 0.77 to 1.82) and 0.89 per year in kidney transplant recipients (95% CI 0.48 to 1.30). Patients on nocturnal hemodialysis and kidney transplant recipients did not have significantly less CAC progression compared to patients on conventional hemodialysis, with confidence intervals overlapping zero in both unadjusted and adjusted analyses (Table 3). CAC progression was also not significantly less in kidney transplant recipients when compared to patients on conventional and nocturnal hemodialysis combined (adjusted difference in ΔCAC SQRV -0.30, 95% CI -0.80 to 0.22). The above associations were similar when we used Agatston scores instead of volume scores (S2 and S3 Tables).

Table 2. Coronary calcium scores at annual follow-up exams in 114 patients with end-stage renal disease.

N* Enrollment N Year 1 N Year 2 N Year 3
Conventional hemodialysis 32 182 (3–835) 32 199 (27–1045) 21 106 (20–885) 11 334 (67–835)
Nocturnal hemodialysis 34 176 (16–501) 34 267 (20–583) 24 464 (46–743) 19 511 (107–799)
Kidney transplantation 48 103 (10–523) 48 154 (35–559) 44 144 (37–648) 42 194 (48–731)
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Coronary calcium scores in mm3 are presented as median (IQR).

*Patients without any follow-up exams were not included in the current analyses.

Fig 2. Progression of coronary artery calcification in 135 patients with end-stage renal disease stratified by renal replacement therapy.

Fig 2

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Two patients on conventional hemodialysis are off-scale, with CAC scores at enrollment/after 1 year of 5129/6793 and 5731/7424. Note that lines near zero can overlap.

Table 3. Longitudinal changes in calcium scores between annual follow-up exams in 114 patients with end-stage renal disease.

N Mean change per year Unadjusted difference Model 1* Model 2† Model 3‡
Conventional hemodialysis 32
 ΔCAC SQRV 1.37 (0.81 to 1.93) 0.0 (reference) 0.0 (reference) 0.0 (reference) 0.0 (reference)
Nocturnal hemodialysis 34
 ΔCAC SQRV 1.29 (0.77 to 1.82) -0.08 (-0.84 to 0.69) 0.04 (-0.65 to 0.74) 0.03 (-0.65 to 0.70) -0.10 (-0.77 to 0.57)
Kidney transplantation 48
 ΔCAC SQRV 0.89 (0.48 to 1.30) -0.48 (-1.17 to 0.22) -0.30 (-0.93 to 0.33) -0.28 (-0.90 to 0.33) -0.33 (-0.96 to 0.29)
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95% confidence intervals between brackets.

*Model 1 = Adjusted for CAC SQRV at enrollment.

†Model 2 = Model 1 + age and sex.

‡Model 3 = Model 2 + diabetes mellitus, dialysis duration, current smoking, presence of residual urine production, and vitamin K antagonist use.

Discussion

In this study, we investigated CAC progression measured annually among patients treated with conventional hemodialysis, nocturnal hemodialysis, and kidney transplant recipients, during up to 3 years of follow-up. Our study shows that nocturnal hemodialysis is not associated with less CAC progression compared to conventional hemodialysis. Furthermore, our study shows no significant difference in CAC progression between kidney transplant recipients and patients on conventional hemodialysis.

To our knowledge, this is the first study to compare CAC progression between conventional hemodialysis and nocturnal hemodialysis. Contrary to expected, we did not find less CAC progression in nocturnal hemodialysis or kidney transplantation compared to conventional hemodialysis, despite the fact that phosphate levels are substantially lower among patients on nocturnal hemodialysis [20] and kidney transplant recipients [21]. An interpretation could be that vascular calcification progresses regardless of the type of renal replacement therapy. This contrasts with the prevailing paradigm that kidney transplant recipients have lower cardiovascular morbidity and mortality in part due to mitigating effects of kidney transplantation on vascular calcification [22]. Rather, based on our current findings, one might also say that kidney transplant recipients have lower cardiovascular morbidity and mortality despite progressive vascular calcification. This suggests a discrepancy between progression of vascular calcification and hard endpoints.

Previously, others have also pointed out important discrepancies between the effects of several drugs on vascular calcification and mortality [23]. For example, several trials have demonstrated that drugs such as cinacalcet or sevelamer may slow down progression of coronary artery calcification [24, 25] but lack benefit on mortality [25, 26]. These discrepancies suggest that vascular calcification might only be a secondary phenomenon to vascular damage and may not be harmful in itself. We therefore believe future studies should use major adverse cardiovascular events or cardiovascular mortality instead of vascular calcification as primary outcome.

On the other hand, our data do not rule out that progression of vascular calcification is less after kidney transplantation compared to dialysis. The 95% confidence intervals of the effect estimates for kidney transplantation include a more than two thirds lower CAC progression rate (adjusted minimum of the 95% confidence interval -0.96), which we consider clinically meaningful. Furthermore, two previous studies reported statistically significant differences in CAC progression with far smaller samples. One study compared CAC progression between 41 kidney transplant recipients and 30 transplantation-eligible patients on hemodialysis during 2 years, and reported less frequent CAC progression among kidney transplant recipients [11]. Another earlier study also reported less frequent CAC progression in 23 kidney transplant recipients compared to 17 patients on hemodialysis during variable follow-up durations, although these patients were not matched on transplantation eligibility [10]. However, regardless of whether CAC progression is less after kidney transplantation, it is unclear to what extent CAC progression concerns progression of medial calcification, which is where an effect of kidney transplantation would be expected. Coronary artery calcification has been suggested to be predominantly intimal [18]. This is based on one post-mortem study in 23 patients on dialysis with known coronary artery disease, which showed that coronary artery calcification was mostly located in intimal plaques, although it also occurred in the media [27]. Moreover, intimal calcification has been suggested to stabilize atherosclerotic plaque [28], which further complicates the interpretation of CAC progression with regard to its potential cardiovascular consequences.

Although our data may be inconclusive regarding the effect of kidney transplantation on CAC progression, they clearly do not suggest less CAC progression in nocturnal hemodialysis compared to conventional hemodialysis despite the lower phosphate levels in nocturnal hemodialysis. The effect estimates for nocturnal hemodialysis were close to zero and do not indicate an undetected difference. Only one previous study reported CAC progression in patients on nocturnal hemodialysis but had no control group [29]. An explanation for similar CAC progression in nocturnal hemodialysis and conventional hemodialysis may be that longer and more frequent hemodialysis could also increase clearance of certain water-soluble calcification inhibitors. These include pyrophosphate [30, 31] and magnesium [32, 33], which have been shown to be lost during hemodialysis. Whether nocturnal hemodialysis indeed results in lower serum levels of pyrophosphate or magnesium needs further study.

This study should be viewed within the context of some limitations. There was significant loss to follow-up, especially among patients on conventional hemodialysis (25 out of 57 enrolled patients). This could have led to survivor bias. Nevertheless, many patients were lost to follow-up due to kidney transplantation (7/25) or switch to nocturnal hemodialysis (5/25). Therefore, we do not believe that the high rate of loss to follow-up in this group led to a selection of healthier patients. Another limitation is that we could not measure serum levels of certain calcification inhibitors or serum calcification propensity. This could have provided additional information. Furthermore, although this study was the first to compare CAC progression between different dialysis modalities and kidney transplantation with up to 3 years follow-up, sufficiently long to detect CAC progression [34], our sample size was limited and our study was not powered to investigate cardiovascular events or mortality. Finally, our study was observational, which could potentially lead to selection bias. For example, we did not know the reasons for individual patients to opt for nocturnal hemodialysis. On the other hand, we used treatment adherence as an inclusion criterion in order to enroll patients on conventional hemodialysis that were somewhat similar in this respect to patients on nocturnal hemodialysis, who are generally more likely to adhere to treatment. Furthermore, we only enrolled patients on dialysis who were transplantation-eligible and kidney transplant recipients that had been on dialysis before transplantation. Although there may have been unmeasured confounders, patient on dialysis versus kidney transplant recipients were as a result comparable in terms of baseline variables, notably age and dialysis duration.

In conclusion, nocturnal hemodialysis and kidney transplantation are not associated with significantly less CAC progression compared to conventional hemodialysis during up to 3 years follow-up. Further studies are needed to confirm these findings, to determine which type of calcification is measured with CAC in end-stage renal disease, and whether that reflects cardiovascular risk.

Supporting information

S1 Table. Characteristics at enrollment of 114 patients who completed at least one follow-up visit and of 36 patients who did not.

(DOCX)

Click here for additional data file. (16.6KB, docx)
S2 Table. Agatston scores at annual follow-up exams in 114 patients with end-stage renal disease.

(DOCX)

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S3 Table. Longitudinal changes in Agatston scores between annual follow-up exams in 114 patients with end-stage renal disease.

(DOCX)

Click here for additional data file. (14.5KB, docx)
S1 Dataset

(CSV)

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S1 Fig

(DOCX)

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S1 File

(PDF)

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S1 Checklist

(DOC)

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Data Availability

The data are contained in the Supporting information files (S1 Dataset).

Funding Statement

The NOCTx study was supported by unrestricted grants from Amgen, Baxter, Fresenius Medical Care, Novartis, Roche and Shire Pharmaceuticals. T.T. Jansz was supported financially by a grant from the Wellerdieck de Goede Foundation with mediation from Friends of UMC Utrecht. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Decision Letter 0

Ping-Hsun Wu

31 Jan 2020

PONE-D-19-32023

Progression of coronary artery calcification in conventional hemodialysis, nocturnal hemodialysis, and kidney transplantation

PLOS ONE

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It is important to include baseline serum calcium, serum phosphorus, plasma PTH levels as covariables in multivariate linear regression. A characteristics comparison between enrolled and non-enrolled cases could be considered to reflect the generalizzbility. The lost follow-up is an important issue in this study that the author need to address this issue.

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Reviewer #1: This article entitled “Progression of coronary artery calcification in conventional hemodialysis, nocturnal hemodialysis, and kidney transplantation” by Jansz TT et al investigated progression of CAC between patients treated with different dialysis modality. They concluded that nocturnal hemodialysis and kidney transplantation are not associated with significantly less CAC progression compared to conventional hemodialysis during up to 3 years follow-up. I have several comments as follows.

1. This study takes much time and efforts to answer whether nocturnal HD or kidney transplantation decreases vascular calcifications. However, I think that its clinical significance and merit are limited because vascular calcification is not a good surrogate marker (Ref 1 and 2). A good surrogate marker should accurately reflect the clinical event they are supposed to surrogate. However, meta-analysis and randomized controlled studies did not show vascular calcifications reflecting the underlying risk for death in HD patients.

2. The authors mentioned “kidney transplantation is associated with less CAC progression compared to PD” in Discussion. However, I did not find any data in the article supporting this conclusion. Please shows the data or cite the references if available, otherwise please revise this sentence.

3. Because vascular calcification is just a surrogate marker for cardiovascular diseases or related mortality, the authors should explain why this study aims to investigate vascular calcification rather than major adverse cardiovascular events (MACE) or CV-related mortality as the primary outcome.

4. The article is not well organized, especially in Introduction and Discussion. I suggest rewrite some paragraphs to highlight the importance of your study. In addition, the repetition of several sentences is found in Discussion. Please revise them.

5. The authors should include baseline serum calcium, serum phosphorus, plasma PTH levels in as covariables in multivariate linear regression. These covariables for vascular calcification are more important compared to residual renal function or Vitamin K antagonists.

Ref 1: Con: Vascular calcification is a surrogate marker, but not the cause of ongoing vascular disease and it is not a treatment target in chronic kidney disease. Carmine Zoccali and Gerard London. Nephrol Dial Transplant (2015) 30: 352–357

Ref 2: Annual Progression of Coronary Calcification in Trials of Preventive Therapies

A Systematic Review. Peter A. McCullough and Kavitha M. Chinnaiyan. Arch Intern Med. 2009 Dec 14;169(22):2064-70.

Reviewer #2: The study enrolled 114 patients on dialysis and divided them into three groups: conventional hemodialysis, nocturnal hemodialysis, and kidney transplantation. The differences of changes of coronary artery calcification (CAC) with three-year period were evaluated using mixed-effect models for these groups. The author concluded that there is no significant difference of CAC progression in the group of kidney transplantation, and nocturnal hemodialysis compared to that in the group of conventional hemodialysis. The advantages of this study include well study design, transparent process in information collection, and correct statistical analysis. However, a main shortage of the study, insufficient sample size, may result in incorrect inference and misguide future research.

In addition, several comments were provided for improvement of this article.

1. I suggest the authors perform post-hoc power analysis. It can estimate type 2 error which represents the probability of false negative conclusion.

2. What are the indications for patients switching therapeutic model from conventional to nocturnal hemodialysis? If the indications are also related to CAC progression, the authors should probably consider to adjust when modeling.

3. Please compare patient characteristics between enrolled and not enrolled cases, which may possibly reflect the limits of generalization.

4. Line 89, Page 4: The sentence, “Patients left the study if they switched renal replacement therapy…” is ambiguous. Dose it also contain that patients switching therapeutic model from conventional to nocturnal hemodialysis? please modify it.

5. I also concern that the lack consistent patient numbers of peritoneal dialysis (n=31) with those (n=40) on previous published on Am J Nephrol 2018;48:369–377 because both number are from NOCTx study. Please explain it.

6. On Page 5, I am not sure whether the description, “dialysis duration defined from the first day to inclusion, minus the time with a functioning kidney transplantation” is correct or not. What does the word “inclusion” mean? Kidney translation should be after the time of inclusion, right?

7. Sum of not enrolled cases in the fig 1 is incorrect, please confirm it.

8. Is there any possible follow-up bias existing in your observation? The lost follow-up rate seems to be higher at 3rd year in the group of conventional hemodialysis than those in the other groups.

9. Does the discrepancies of cardiovascular disease / mortality risk between patients treated with conventional, nocturnal hemodialysis, or kidney transplant recipients probably contributed by the different CAC which reflects potential patient selection at baseline in this study? The author should discuss it.

**********

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Reviewer #1: Yes: CHIH-CHIA LIANG

Reviewer #2: No

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PLoS One. 2020 Dec 30;15(12):e0244639. doi: 10.1371/journal.pone.0244639.r002

Author response to Decision Letter 0

20 Mar 2020

Thank you for the opportunity to submit a revised version of our manuscript. Please find our responses to the comments below.

Editor:

It is important to include baseline serum calcium, serum phosphorus, plasma PTH levels as covariables in multivariate linear regression.

We agree with the Editor and Reviewer #2 that it could be valuable to examine the associations of serum and plasma markers of mineral metabolism with CAC progression. However, we should not adjust for these variables when examining the association of renal replacement therapy with CAC progression. The reason is that in the case of renal replacement therapy, these variables are not confounders but mediators; i.e., kidney transplantation and nocturnal hemodialysis could have an effect on CAC progression by changing serum calcium, phosphorus, or plasma PTH[1]. Adjusting for these variables in multivariate regression models would lead to biased estimates instead of removing bias by confounding[2].

A characteristics comparison between enrolled and non-enrolled cases could be considered to reflect the generalizability.

We agree with the Editor and Reviewer #2 that it would be valuable to compare characteristics of patients that were enrolled in the NOCTx study (n=181) with those who were not (n=148). However, as the patients that were not enrolled did not give informed consent for study participation, we could not collect any data on their characteristics. On the other hand, we do compare patient characteristics between enrolled patients that completed follow-up (n=114) and those that did not (n=36) in the Results section, page 11, lines 184-189:

“Patients that were excluded from the current analyses as they did not complete any follow-up exam (n=36) had similar characteristics compared to the study population: they were on average 52 ±13 years old, 23 (64%) were male, dialysis duration was median 36 (IQR 18–66) months, and 10 (28%) had diabetes mellitus (all P>0.05 versus study population). Their median CAC score at inclusion was 323 (IQR 1–1181) (P=0.18 versus study population).”

Also, we have now added a S1 Table comparing further characteristics between enrolled patients that completed follow-up and those that did not.

The lost follow-up is an important issue in this study that the author need to address this issue.

The Editor is right to point out that there was significant loss to follow-up in our study. Specifically, only 32 out of 57 enrolled patients on conventional hemodialysis completed the first follow-up visit. This could have led to survivor bias. However, only 2 of these 25 patients had died, whereas 4 had withdrawn consent, 7 were lost to follow-up, 7 had received a kidney transplant, and 5 had switched to nocturnal hemodialysis, leaving the study as a result. Therefore, we believe that the high rate of loss to follow-up in this group did not necessarily lead to a selection of healthier patients. We now address this issue in the Discussion section, page 18:

“There was significant loss to follow-up, especially among patients on conventional hemodialysis (25 out of 57 enrolled patients). This could have led to survivor bias, although many patients were also lost to follow-up due to kidney transplantation (7/25) or switched to nocturnal hemodialysis (5/25).”

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

Reviewer #1:

This article entitled “Progression of coronary artery calcification in conventional hemodialysis, nocturnal hemodialysis, and kidney transplantation” by Jansz TT et al investigated progression of CAC between patients treated with different dialysis modality. They concluded that nocturnal hemodialysis and kidney transplantation are not associated with significantly less CAC progression compared to conventional hemodialysis during up to 3 years follow-up. I have several comments as follows.

1. This study takes much time and efforts to answer whether nocturnal HD or kidney transplantation decreases vascular calcifications. However, I think that its clinical significance and merit are limited because vascular calcification is not a good surrogate marker (Ref 1 and 2). A good surrogate marker should accurately reflect the clinical event they are supposed to surrogate. However, meta-analysis and randomized controlled studies did not show vascular calcifications reflecting the underlying risk for death in HD patients.

3. Because vascular calcification is just a surrogate marker for cardiovascular diseases or related mortality, the authors should explain why this study aims to investigate vascular calcification rather than major adverse cardiovascular events (MACE) or CV-related mortality as the primary outcome.

Thank you for pointing out this major controversy in the field of cardiovascular disease in end-stage renal disease. We fully agree with the reviewer that it is debatable whether vascular calcification is an adequate surrogate marker for cardiovascular disease. Even more, we believe our data support that vascular calcification may not be an adequate surrogate outcome. As we point out in the Discussion section, there is a discrepancy between our data not showing less vascular calcification progression among kidney transplant recipients, and the fact that kidney transplant recipients have significantly less cardiovascular morbidity and mortality.

Unfortunately, our study was designed in 2008 before these discrepancies came to light. Therefore, our study was designed with CAC progression as primary outcome and was as such not powered for major adverse cardiovascular events or cardiovascular mortality as primary outcome. Nevertheless, we believe that future studies should use major adverse cardiovascular events or cardiovascular mortality instead of vascular calcification as an primary outcome, which we also state in the Discussion section, page 18:

“Previously, others have also pointed out important discrepancies between the effects of several drugs on vascular calcification and mortality[23]. For example, several trials have demonstrated that drugs such as cinacalcet or sevelamer may slow down progression of coronary artery calcification[24, 25] but lack benefit on mortality[25, 26]. These discrepancies suggest that vascular calcification might only be a secondary phenomenon to vascular damage and may not be harmful in itself. We therefore believe future studies should use major adverse cardiovascular events or cardiovascular mortality instead of vascular calcification as primary outcome.”

2. The authors mentioned “kidney transplantation is associated with less CAC progression compared to PD” in Discussion. However, I did not find any data in the article supporting this conclusion. Please shows the data or cite the references if available, otherwise please revise this sentence.

Please accept our apologies for this error. This sentence should have been deleted after a recent redrafting of this manuscript. We have now deleted this sentence accordingly.

4. The article is not well organized, especially in Introduction and Discussion. I suggest rewrite some paragraphs to highlight the importance of your study. In addition, the repetition of several sentences is found in Discussion. Please revise them.

As recommended by the reviewer, we revised several paragraphs in the Introduction and Discussion section.

5. The authors should include baseline serum calcium, serum phosphorus, plasma PTH levels in as covariables in multivariate linear regression. These covariables for vascular calcification are more important compared to residual renal function or Vitamin K antagonists.

We agree with the Editor and Reviewer #2 that it could be valuable to examine the associations of serum and plasma markers of mineral metabolism with CAC progression. However, we should not adjust for these variables when examining the association of renal replacement therapy with CAC progression. The reason is that in the case of renal replacement therapy, these variables are not confounders but mediators; i.e., kidney transplantation and nocturnal hemodialysis could have an effect on CAC progression by changing serum calcium, phosphorus, or plasma PTH[1]. Adjusting for these variables in multivariate regression models would lead to biased estimates instead of removing bias by confounding[2].

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

Reviewer #2: The study enrolled 114 patients on dialysis and divided them into three groups: conventional hemodialysis, nocturnal hemodialysis, and kidney transplantation. The differences of changes of coronary artery calcification (CAC) with three-year period were evaluated using mixed-effect models for these groups. The author concluded that there is no significant difference of CAC progression in the group of kidney transplantation, and nocturnal hemodialysis compared to that in the group of conventional hemodialysis. The advantages of this study include well study design, transparent process in information collection, and correct statistical analysis. However, a main shortage of the study, insufficient sample size, may result in incorrect inference and misguide future research.

In addition, several comments were provided for improvement of this article.

1. I suggest the authors perform post-hoc power analysis. It can estimate type 2 error which represents the probability of false negative conclusion.

As suggested by the reviewer, we performed a post-hoc power analysis. We calculated the sample size needed to detect an effect of the magnitude suggested for kidney transplantation compared to conventional hemodialysis after a 1-year interval by our data, with 80% power and a significance level of 0.05. This yielded a sample size of 359 per group. We now address this issue in the Discussion section, page 18:

“We performed a post-hoc power analysis, revealing that over 350 patients per group would be needed to detect the difference currently observed between kidney transplant recipients and patients on conventional hemodialysis in a one-year interval with 80% power at a 0.05 significance level.”

2. What are the indications for patients switching therapeutic model from conventional to nocturnal hemodialysis? If the indications are also related to CAC progression, the authors should probably consider to adjust when modeling.

There are various reasons why patients wanted to switch to nocturnal hemodialysis from conventional hemodialysis. Important advantages of nocturnal hemodialysis include more free time during the day and less dietary restrictions. As a result, patients initiating nocturnal hemodialysis in general are often younger, healthier, more motivated, and more likely to adhere to treatment. Although we did not know the reasons of individual patients to switch to nocturnal hemodialysis, we did adjust for variables that may reflect overall health and thus could influence choice of renal replacement therapy as well as CAC progression (e.g. age, diabetes, and vitamin K antagonist use).

3. Please compare patient characteristics between enrolled and not enrolled cases, which may possibly reflect the limits of generalization.

We agree with the Editor and Reviewer #2 that it would be valuable to compare characteristics of patients that were enrolled in the NOCTx study (n=181) with those who were not (n=148). However, as the patients that were not enrolled did not give informed consent for study participation, we could not save any data on their characteristics. On the other hand, we do compare patient characteristics between enrolled patients that completed follow-up (n=114) and those that did not (n=36) in the Results section, page 11, lines 184-189:

“Patients that were excluded from the current analyses as they did not complete any follow-up exam (n=36) had similar characteristics compared to the study population: they were on average 52 ±13 years old, 23 (64%) were male, dialysis duration was median 36 (IQR 18–66) months, and 10 (28%) had diabetes mellitus (all P>0.05 versus study population). Their median CAC score at inclusion was 323 (IQR 1–1181) (P=0.18 versus study population).”

Also, we have now added a S1 Table comparing further characteristics between enrolled patients that completed follow-up and those that did not.

4. Line 89, Page 4: The sentence, “Patients left the study if they switched renal replacement therapy…” is ambiguous. Dose it also contain that patients switching therapeutic model from conventional to nocturnal hemodialysis? please modify it.

We apologize for the confusion arising from our wording. Patients in the nocturnal hemodialysis group switched to nocturnal hemodialysis shortly before enrollment. Indeed, if patients switched renal replacement therapy after enrollment (for example from conventional hemodialysis to nocturnal hemodialysis), they left the study. For clarity, we added “after enrollment” to the sentence:

“Patients left the study if they switched renal replacement therapy after enrollment”

5. I also concern that the lack consistent patient numbers of peritoneal dialysis (n=31) with those (n=40) on previous published on Am J Nephrol 2018;48:369–377 because both number are from NOCTx study. Please explain it.

There is indeed a discrepancy in these numbers. The explanation is that a total of 4 patients were enrolled while on peritoneal dialysis (n=2) and conventional hemodialysis (n=2), but received a kidney transplantation >6 months after enrollment. These patients therefore had to leave the study, but requested re-enrollment. They were subsequently re-enrolled as kidney transplant recipients. For this paper, we used the data of those 4 patients after kidney transplantation, whereas in the paper Am J Nephrol 2018;48:369–377 we used data of these patients before kidney transplantation. Hence, there is a discrepancy of 2 patients in the peritoneal dialysis group (21 vs 23) and 2 patients in the conventional hemodialysis group (32 vs 34) between this paper and Am J Nephrol 2018;48:369–377.

6. On Page 5, I am not sure whether the description, “dialysis duration defined from the first day to inclusion, minus the time with a functioning kidney transplantation” is correct or not. What does the word “inclusion” mean? Kidney translation should be after the time of inclusion, right?

We apologize for the confusion arising from our wording. Patients that were enrolled as kidney transplant recipients had received a kidney transplant shortly before enrollment. We added this to the Methods section, page 4, lines 88-89:

“NOCTx included [..] patients on dialysis who received a kidney transplant 2-3 months before enrollment.”

Furthermore, some patients had had kidney transplants longer before but were again on dialysis at time of enrollment. Their time with a kidney transplant was not counted towards dialysis duration. When mentioning inclusion in this context, we meant enrollment. For clarity, we replaced the word inclusion with enrollment throughout the manuscript.

7. Sum of not enrolled cases in the fig 1 is incorrect, please confirm it.

Please accept our apologizes for this error. The number of patients with “other reasons” should be 57 instead of 56. We have amended the figure accordingly.

8. Is there any possible follow-up bias existing in your observation? The lost follow-up rate seems to be higher at 3rd year in the group of conventional hemodialysis than those in the other groups.

Thank you for addressing this issue. Indeed, the rate of loss to follow-up was higher in the conventional hemodialysis group than in the nocturnal hemodialysis or kidney transplantation group. Notably, more than a third of the patients on conventional hemodialysis (34%) were lost to follow-up because they received a kidney transplant, which we mention in the Results section, page 11. We now also acknowledge this issue in the Discussion section, page 18:

“There was significant loss to follow-up, especially among patients on conventional hemodialysis”

9. Does the discrepancies of cardiovascular disease / mortality risk between patients treated with conventional, nocturnal hemodialysis, or kidney transplant recipients probably contributed by the different CAC which reflects potential patient selection at baseline in this study? The author should discuss it.

We thank the reviewer for addressing the issue of potential selection bias. Our study is observational and as such cannot fully eliminate potential selection bias. We attempted to minimize this by only enrolling patients on dialysis that were eligible for kidney transplantation and kidney transplant recipients that had been on dialysis. As a result, the patient groups were similar e.g. in terms of age and dialysis duration, although diabetes mellitus was somewhat more frequent in patients on conventional hemodialysis versus kidney transplant recipients (6/32 versus 3/48, P=0.22), which we adjusted for in our statistical analyses. We now discuss this issue in the limitations paragraph of the Discussion:

“Finally, our study was observational, which could potentially lead to selection bias. To minimize this, we only enrolled patients on dialysis who were transplantation-eligible and kidney transplant recipients that had been on dialysis before transplantation. The patient groups were comparable as a result”

References:

1. Rocco MV, Lockridge RS Jr, Beck GJ, Eggers PW, Gassman JJ, Greene T, Larive B, Chan CT, Chertow GM, Copland M, Hoy CD, Lindsay RM, Levin NW, Ornt DB, Pierratos A, Pipkin MF, Rajagopalan S, Stokes JB, Unruh ML, Star RA, Kliger AS; Frequent Hemodialysis Network (FHN) Trial Group, Kliger A, Eggers P, Briggs J, Hostetter T, Narva A, Star R, Augustine B, Mohr P, Beck G, Fu Z, Gassman J, Greene T, Daugirdas J, Hunsicker L, Larive B, Li M, Mackrell J, Wiggins K, Sherer S, Weiss B, Rajagopalan S, Sanz J, Dellagrottaglie S, Kariisa M, Tran T, West J, Unruh M, Keene R, Schlarb J, Chan C, McGrath-Chong M, Frome R, Higgins H, Ke S, Mandaci O, Owens C, Snell C, Eknoyan G, Appel L, Cheung A, Derse A, Kramer C, Geller N, Grimm R, Henderson L, Prichard S, Roecker E, Rocco M, Miller B, Riley J, Schuessler R, Lockridge R, Pipkin M, Peterson C, Hoy C, Fensterer A, Steigerwald D, Stokes J, Somers D, Hilkin A, Lilli K, Wallace W, Franzwa B, Waterman E, Chan C, McGrath-Chong M, Copland M, Levin A, Sioson L, Cabezon E, Kwan S, Roger D, Lindsay R, Suri R, Champagne J, Bullas R, Garg A, Mazzorato A, Spanner E, Rocco M, Burkart J, Moossavi S, Mauck V, Kaufman T, Pierratos A, Chan W, Regozo K, Kwok S. The effects of frequent nocturnal home hemodialysis: the Frequent Hemodialysis Network Nocturnal Trial. Kidney Int. 2011 Nov;80(10):1080-91.

2. Jager KJ, Zoccali C, MacLeod A, Dekker FW. Confounding: what is it and how to deal with it. Kidney Int 2008 Feb;73(3):256-60.

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Decision Letter 1

Ping-Hsun Wu

22 Apr 2020

PONE-D-19-32023R1

Progression of coronary artery calcification in conventional hemodialysis, nocturnal hemodialysis, and kidney transplantation

PLOS ONE

Dear Dr. Thijs T Jansz,

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

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Ping-Hsun Wu, M.D.

Academic Editor

PLOS ONE

Additional Editor Comments (if provided):

A new statistician was invited to review this study. Confounding factors and selection bias may still persist to compare therapeutic approaches. Please response the comments from reviewer 3.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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Reviewer #1: (No Response)

Reviewer #2: All comments have been addressed

Reviewer #3: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: (No Response)

Reviewer #2: Yes

Reviewer #3: Partly

**********

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

Reviewer #1: (No Response)

Reviewer #2: Yes

Reviewer #3: No

**********

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Reviewer #1: (No Response)

Reviewer #2: Yes

Reviewer #3: Yes

**********

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Reviewer #2: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

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Reviewer #1: (No Response)

Reviewer #2: The authors have satisfactorily responded to all my listed questions. Therefore, I have no further questions.

Reviewer #3: I come to this revised paper as a new reviewer.

I must respectfully disagree with reviewer 2 who talks of post hoc power. Power is an estimate used in planning. The data are what they are, and the actual power is either zero or 1 because the effect is either significant or not. I can wholeheartedly recommend the paper "The Abuse of Power" by Hoenig et al in The American Statistician.

The issue of whether there is absence of evidence or evidence of absence is based upon the confidence intervals. The issue in interpretation is whether the extremes of the CI represent something worth knowing about. If, for example, 0.96 is worth knowing about then one cannot rule out a clinically meaningful benefit and the conclusion must be that the study is inconclusive.

The paper as it stands doesn't adequately explain how people entered one or other group for comparison.What were the selection factors? Clearly there must have been some choice made here and groups cannot be entirely comparable. Not can those differences be measured exclusively in the variables collected here. Table 1 needs tests for confounding here, and the reason for dialysis vs transplantation in particular is needed.

Please explain the differences in missing data rates in Table 2 - there is potential for bias if these are outcome related.

**********

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Reviewer #1: Yes: CHIH-CHIA LIANG

Reviewer #2: Yes: Ming-Yen Lin

Reviewer #3: No

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PLoS One. 2020 Dec 30;15(12):e0244639. doi: 10.1371/journal.pone.0244639.r004

Author response to Decision Letter 1

5 Jun 2020

Thank you for the opportunity to submit a revised version of our manuscript. Please find our responses to the comments below.

Reviewer 3.

1. I must respectfully disagree with reviewer 2 who talks of post hoc power. Power is an estimate used in planning. The data are what they are, and the actual power is either zero or 1 because the effect is either significant or not. I can wholeheartedly recommend the paper "The Abuse of Power" by Hoenig et al in The American Statistician.

The issue of whether there is absence of evidence or evidence of absence is based upon the confidence intervals. The issue in interpretation is whether the extremes of the CI represent something worth knowing about. If, for example, 0.96 is worth knowing about then one cannot rule out a clinically meaningful benefit and the conclusion must be that the study is inconclusive.

Thank you for pointing this out. We have replaced the paragraph about post-hoc power in the Discussion with a paragraph in which we address that the confidence intervals include a possible clinically meaningful benefit:

“The 95% confidence intervals of the effect estimates for kidney transplantation include a more than two thirds lower CAC progression rate (adjusted minimum of the 95% confidence interval -0.96), which we consider clinically meaningful.”

2. The paper as it stands doesn't adequately explain how people entered one or other group for comparison. What were the selection factors? Clearly there must have been some choice made here and groups cannot be entirely comparable. Nor can those differences be measured exclusively in the variables collected here. Table 1 needs tests for confounding here, and the reason for dialysis vs transplantation in particular is needed.

The reviewer rightfully addresses the issue of how participants ended up in one treatment group or another, and whether there may be confounder bias beyond the variables presented in Table 1.

In this study, there was no choice made for dialysis versus transplantation. As stated in the Methods and Discussion sections, all patients on dialysis were eligible for transplantation. Hence, the patients on dialysis had not received a kidney transplant, simply because they did not have the luck to receive one yet. Notably, 18 patients on dialysis did have the luck to receive a kidney transplant during study participation.

As for conventional hemodialysis versus nocturnal hemodialysis, there are various reasons why patients opted for nocturnal hemodialysis versus conventional hemodialysis. Important advantages of nocturnal hemodialysis include more free time during the day and less dietary restrictions. As a result, patients opting for nocturnal hemodialysis are often younger, healthier, more motivated, and more likely to adhere to treatment. Although we did not know the reasons of individual patients to opt for nocturnal hemodialysis (which we now acknowledge in the Limitations paragraph of the Discussion), we did adjust for variables that may reflect overall health and thus could influence choice of renal replacement therapy as well as CAC progression (e.g. age, diabetes, and vitamin K antagonist use).

“For example, we did not know the reasons of individual patients to opt for nocturnal hemodialysis.”

Following the reviewer’s recommendation, we added significance tests to Table 1. Of note, there were no significant differences in demographics, medical history, and vitamin K antagonist use between treatment groups. There were significant differences in medication use and physical/laboratory parameters, expectedly due to the treatments received. However, we agree with the reviewer that there may be confounding beyond the variables measured in this study. Therefore, we added the following line to the Limitations paragraph of the Discussion:

“Although there may have been unmeasured confounders, patient groups on dialysis versus kidney transplant recipients were comparable in terms of the measured variables as a result.”

3. Please explain the differences in missing data rates in Table 2 - there is potential for bias if these are outcome related.

The reviewer is right to point out that there were differences in loss to follow-up in our study. Specifically, only 32 out of 57 enrolled patients on conventional hemodialysis completed the first follow-up visit. This could have led to survivor bias. However, only 2 of these 25 patients had died, whereas 4 had withdrawn consent, 7 were lost to follow-up, 7 had received a kidney transplant, and 5 had switched to nocturnal hemodialysis, leaving the study as a result. Therefore, we believe that the high rate of loss to follow-up in this group did not necessarily lead to a selection of healthier patients. We address this issue in the Discussion section, page 18:

“There was significant loss to follow-up, especially among patients on conventional hemodialysis (25 out of 57 enrolled patients). This could have led to survivor bias. Nevertheless, many patients were lost to follow-up due to kidney transplantation (7/25) or switch to nocturnal hemodialysis (5/25). Therefore, we do not believe that the high rate of loss to follow-up in this group led to a selection of healthier patients.”

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Decision Letter 2

Ping-Hsun Wu

18 Sep 2020

PONE-D-19-32023R2

Progression of coronary artery calcification in conventional hemodialysis, nocturnal hemodialysis, and kidney transplantation

PLOS ONE

Dear Dr. Thijs T Jansz,

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

Please submit your revised manuscript by Nov 02 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

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We look forward to receiving your revised manuscript.

Kind regards,

Ping-Hsun Wu, M.D.

Academic Editor

PLOS ONE

Additional Editor Comments (if provided):

Most of the comments had been well response by the author. However, Reviewer 3 still have some comment on the patient selection in the different groups. Please clarify accordingly.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

Reviewer #3: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: (No Response)

**********

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

Reviewer #1: I Don't Know

Reviewer #2: Yes

Reviewer #3: (No Response)

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: (No Response)

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: (No Response)

**********

6. Review Comments to the Author

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

Reviewer #1: (No Response)

Reviewer #2: (No Response)

Reviewer #3: Thank you for your clarification of the design of the study. As I understand it patients will naturally change groups - what is unclear is why patients are excluded for compliance, as this leads to differently selected patients in the different groups, and why patients leave the study on switching therapy as opposed to changing group.

The analysis of this sort of study would appear to be the same as one would use for any other transplantation study. It is unclear why Mantel-Byar or equivalent analyses were not used for time to event outcomes and equivalent methodology for multiperiod crossover trials for the other measures. As it stands the different groups appear to enter the study post diagnosis, or time from starting dialysis - how is this allowed for in the analyses as the patients entering after a long period on dialysis are clearly more compliant and have disease that has not led to death (ie could be considered to be more indolent). As it stands the data aren't really interpretable since we are not looking at similar times.

**********

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Reviewer #1: No

Reviewer #2: Yes: Ming-Yen Lin

Reviewer #3: No

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PLoS One. 2020 Dec 30;15(12):e0244639. doi: 10.1371/journal.pone.0244639.r006

Author response to Decision Letter 2

5 Oct 2020

Thank you for the opportunity to revise our manuscript. Please find our responses to the queries raised by Reviewer #3 below.

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

Reviewer #3:

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

Thank you for your clarification of the design of the study. As I understand it patients will naturally change groups - what is unclear is why patients are excluded for compliance, as this leads to differently selected patients in the different groups.

We appreciate your concern as to why patients were excluded from the study if they were non-compliant, i.e. non-adherent to dialysis regimes. This was a deliberate choice when we designed the study, for the following. Often, patients initiating nocturnal hemodialysis are younger, healthier, more motivated, and more likely to adhere to treatment compared to the general dialysis population. We therefore sought to minimize these differences by selecting patients on conventional hemodialysis that were somewhat similar in this respect to patients on nocturnal hemodialysis, using treatment adherence as inclusion criterion. Without this criterion, patients on conventional hemodialysis could overall have been less compliant, which theoretically could have led to poorer phosphate control and hence more CAC progression in that group. We therefore believe that rather than introducing bias, this exclusion criterion contributed to reducing bias in our study.

To clarify this, we added the following explanation to the Discussion:

“On the other hand, we used treatment adherence as an inclusion criterion in order to enroll patients on conventional hemodialysis that were somewhat similar in this respect to patients on nocturnal hemodialysis, who are generally more likely to adhere to treatment”

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

[What is unclear is] why patients leave the study on switching therapy as opposed to changing group. The analysis of this sort of study would appear to be the same as one would use for any other transplantation study. It is unclear why Mantel-Byar or equivalent analyses were not used for time to event outcomes and equivalent methodology for multiperiod crossover trials for the other measures.

We agree with the reviewer that ideally patients would change group rather than leave the study upon switching therapy during study participation, especially in a study with survival as primary endpoint. However, our study did not investigate survival, but had CAC progression as primary endpoint. As a result, it was not feasible for patients to change groups during study participation for the following reasons. First, a switch in therapy would not coincide with the annual follow-up visits during which we measured CAC. Had we decided to allow patients to continue study participation after switching therapy, we would have been left with CAC progression measurements that had been influenced by multiple therapies, which would be difficult if not impossible to interpret. Second, patients would often switch to a hemodialysis therapy that did not match the hemodialysis categories defined in our study (3x4hrs/week or 4-6x8hrs/week). Many would switch to hemodialysis 3x8hrs/week, 4-6x2-4hrs/week, or anything in between. This also precluded continued participation after switching therapy.

For the above reasons, our study did not allow continued participation after switching therapy, and cannot be analyzed as a multiperiod crossover trial. We note that our study did not investigate time-to-event outcomes.

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

As it stands the different groups appear to enter the study post diagnosis, or time from starting dialysis - how is this allowed for in the analyses as the patients entering after a long period on dialysis are clearly more compliant and have disease that has not led to death (ie could be considered to be more indolent). As it stands the data aren't really interpretable since we are not looking at similar times.

Thank you for pointing out the issue of patients who have had a long period of dialysis (i.e. dialysis duration or vintage). Patients with a longer dialysis duration are a selected group: mortality has been shown to be the highest in the first 120 days after hemodialysis initiation[Robinson, 2014]. One could thus regard patients with a longer dialysis duration as the “survivors” of the dialysis population – this goes particularly for patients on nocturnal hemodialysis, who generally have had 1-2 years of dialysis before switching to this therapy. This is why we aimed to recruit patients on conventional hemodialysis and kidney transplant recipients who were somewhat similar to patients on nocturnal hemodialysis, using inclusion criteria such as treatment adherence, transplantation eligibility, and a period of dialysis for kidney transplant recipients. Notably, if we look at Table 1, we can appreciate that there were no significant differences in demographics or medical history between the groups, and that dialysis duration was actually quite similar in these three groups (median 27 months in conventional hemodialysis, 29 months in nocturnal hemodialysis, and 28 months in kidney transplant recipients). Thus, patients entered our study after a long period of dialysis, but this was similar for all three therapies. Moreover, we accounted for dialysis duration in our statistical analyses. We therefore do not believe that differences in dialysis duration would have biased our findings with regards to CAC progression.

We now state that the treatment groups were comparable in terms of dialysis duration in the Discussion:

“[..]We used treatment adherence as an inclusion criterion [and] only enrolled patients on dialysis who were transplantation-eligible [or] kidney transplant recipients that had been on dialysis before transplantation. Although there may have been unmeasured confounders, patient on dialysis versus kidney transplant recipients were [..] comparable in terms of baseline variables, notably age and dialysis duration”

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

References:

Robinson BM, Zhang J, Morgenstern H, et al. Worldwide, mortality risk is high soon after initiation of hemodialysis. Kidney Int. 2014;85(1):158-165. doi:10

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Decision Letter 3

Ping-Hsun Wu

15 Dec 2020

Progression of coronary artery calcification in conventional hemodialysis, nocturnal hemodialysis, and kidney transplantation

PONE-D-19-32023R3

Dear Dr. Thijs T Jansz,

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

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Kind regards,

Ping-Hsun Wu, M.D.

Academic Editor

PLOS ONE

Acceptance letter

Ping-Hsun Wu

18 Dec 2020

PONE-D-19-32023R3

Progression of coronary artery calcification in conventional hemodialysis, nocturnal hemodialysis, and kidney transplantation

Dear Dr. Jansz:

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

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on behalf of

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Academic Editor

PLOS ONE

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