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PLOS One logoLink to PLOS One
. 2020 Jul 28;15(7):e0236274. doi: 10.1371/journal.pone.0236274

The risk factors associated with treatment-related mortality in 16,073 kidney transplantation—A nationwide cohort study

Hyunji Choi 1,#, Woonhyoung Lee 1,#, Ho Sup Lee 2, Seom Gim Kong 3, Da Jung Kim 2, Sangjin Lee 4, Haeun Oh 1, Ye Na Kim 5, Soyoung Ock 6, Taeyun Kim 6, Min-Jeong Park 7, Wonkeun Song 7, John Hoon Rim 8,9, Jong-Han Lee 10, Seri Jeong 7,*
Editor: Robert Jeenchen Chen11
PMCID: PMC7386583  PMID: 32722695

Abstract

Mortality at an early stage after kidney transplantation is a catastrophic event. Treatment-related mortality (TRM) within 1 or 3 months after kidney transplantation has been seldom reported. We designed a retrospective observational cohort study using a national population-based database, which included information about all kidney recipients between 2003 and 2016. A total of 16,073 patients who underwent kidney transplantation were included. The mortality rates 1 month (early TRM) and 3 months (TRM) after transplantation were 0.5% (n = 74) and 1.0% (n = 160), respectively. Based on a multivariate analysis, older age (hazard ratio [HR] = 1.06; P < 0.001), coronary artery disease (HR = 3.02; P = 0.002), and hemodialysis compared with pre-emptive kidney transplantation (HR = 2.53; P = 0.046) were the risk factors for early TRM. Older age (HR = 1.07; P < 0.001), coronary artery disease (HR = 2.88; P < 0.001), and hemodialysis (HR = 2.35; P = 0.004) were the common independent risk factors for TRM. In contrast, cardiac arrhythmia (HR = 1.98; P = 0.027) was associated only with early TRM, and fungal infection (HR = 2.61; P < 0.001), and epoch of transplantation (HR = 0.34; P < 0.001) were the factors associated with only TRM. The identified risk factors should be considered in patient counselling, selection, and management to prevent TRM.

Introduction

After kidney transplantation, patients with end-stage renal disease (ESRD) had better survival, improved cognition, and less economic burden than those who continued with dialysis [13]. Kidney transplantation has improved over the past decades [4]. However, some kidney recipients still die at an early stage after surgery, which is catastrophic for both the patient and medical staff.

Investigation of treatment-related mortality (TRM), which is a concept different from disease-related mortality, is important for improved survival after treatment. It provides information about factors that require intensive care and medical decisions during critical period [5,6]. In cardiovascular procedures or major abdominal surgery, 30-day mortality after surgery is considered TRM [79]. In addition, 90-day postoperative mortality is a legitimate measure of hepatobiliary–pancreatic surgery [10]. Furthermore, 90-day mortality rate is a good predictor of postoperative index in the field of hepatectomy, colectomy, and pneumonectomy [1013]. Data about 1-year mortality after kidney transplantation or long-term outcome were well reported [1417]. Most reports have shown the results of kidney transplantation after 1 [18], 5 [16], and greater than 10 years [19]; however, studies about 1- or 3-month mortality were extremely limited [20,21].

The present study was based on the use of a comprehensive database, which is operated by the National Health Insurance (NHI) of the Korean government. This database contains all the records of healthcare utilization among inpatients and outpatients particularly kidney recipients who were enrolled in the Rare Intractable Disease (RID) system and who received additional medical financial support. The registration is confirmed by a certified physician based on the RID criteria, which reflect international guidelines. Therefore, the use of this database was suitable for the investigation of TRM among kidney recipients.

Using this database, we performed a comprehensive population-based analysis to investigate the risk factors and causes of TRM after kidney transplantation. It would facilitate pre- and post-transplantation assessment and management, which contributed to the improvement of the survival of kidney recipients.

Materials and methods

Study design

This was a retrospective and observational cohort study that used prospectively registered national data sets for reimbursement purposes. All patients who underwent kidney transplantation procedures (Z94.0 code of the International Classification of Disease, 10th revision, Clinical Modification [ICD-10-CM]) at any Korean medical center from January 2003 to December 2016 were included. We defined death within 1 and 3 months after kidney transplantation as early TRM and TRM, respectively. We investigated the risk factors related to early TRM and TRM and the causes of death.

Ethics statement

This study was approved by the independent institutional review board of Kosin University Gospel Hospital (KUGH 2017-12-009) and was conducted in accordance with the Declaration of Helsinki. Moreover, the need for informed consent was waived because anonymity of personal information was maintained.

Study population (patient selection)

The study included all patients who have been listed for kidney transplantation from January 2003 to December 2016 in the Health Insurance Review and Assessment Service (HIRA). The patients were registered in the HIRA database after kidney transplantation, as defined by the ICD-10-CM code Z94.0. During this period, 18,822 patients were enrolled in the database. We excluded 2,726 patients who did not have complete demographic information and 59 patients who concurrently underwent other organ transplantations. The final cohort consisted of 16,037 patients. The records of medical visits, demographic characteristics, and death status were collected from the HIRA database for all kidney recipients.

Study variables

We collected the following demographic data and baseline characteristics of kidney recipients from the HIRA database: age, sex, medical comorbidities focusing on cardiac and cerebrovascular diseases reported to be important causes of early mortality [16], dialysis status, cytomegalovirus (CMV) and fungal infection, and year of transplantation (S1 Table). The induction regimens such as basiliximab, and anti-thymocyte globulin were also extracted. CMV infection included CMV diseases (mononucleosis, pneumonitis, and hepatitis) and the post-transplant administration of antiviral agent (ganciclovir or valganciclovir) [22]. The ICD-10-CM codes for CMV disease were B27.1, B25.0, B25.1, B25.8, and B25.9. Fungal infection encompassed candidiasis and aspergillosis and post-transplant administration of antifungal agents (amphotericin, caspofungin, itraconazole, voriconazole, fluconazole, posaconazole, anidulafungin, and micafungin) [23].

Data source

The data used in this study were obtained from the HIRA database, which is based on the NHI system operated by the Korean government. Healthcare institutions submit the medical data of all inpatients and outpatients in electronic format to the HIRA for reimbursement purposes. The claims data integrated by HIRA include all healthcare utilization information on inpatients and outpatients. Data about the demographic characteristics of the patients, principal diagnosis, comorbidities, prescription history, and performed procedures based on ICD-10-CM codes are included in this database. In this study, we obtained all data about kidney recipients from the RID program of the HIRA database registered between January 2003 and the end of December 2016. The Korean government assigned kidney transplantation to the RID system for reducing the payments of the patients. The diagnosis must be reviewed by the corresponding healthcare institution before submission to the NHI. Therefore, the data registered in the RID registry are verified and reliable.

The data for dialysis vintage, and donor state omitting in HIRA database were obtained from another database operated by the Korean Network for Organ Sharing system. In this database, the records of recipients who underwent kidney transplantation in 40 medical centers around the country were registered.

Statistical analysis

We evaluated the TRM, risk factors, and causes of death of kidney recipients in Korea from 2003 to 2016. Descriptive statistics were used for patient characteristics correlated to early TRM and TRM. Comparisons of nominal and continuous variables between groups were assessed using chi-square test and Mann–Whitney U test, respectively. The median and inter-quartile range were used for non-normally distributed variables. Multivariate Cox proportional-hazards regression models adjusting age, sex, cardiac and cerebrovascular diseases, hemodialysis, infection, and epoch of transplantation were used to examine the variables correlated to TRM.

Statistical analyses were performed using the R statistical software (version 3.4.4; R Foundation for Statistical Computing, Vienna, Austria) and SAS statistical analysis software (version 9.4; SAS Institute Inc., Cary, NC, the USA). The two-tailed P values less than 0.05 were considered statistically significant.

Results

Characteristics of patients

A total of 16,073 patients who underwent kidney transplantation between 2003 and 2016 were included in our study cohort. The baseline characteristics of these patients are presented in Table 1. The median age of the patients was 47.0 years (1st to 3rd quartile range: 38.0–55.0 years). Our cohort consisted of 9,495 men and 6,578 women. Most patients received kidney from living donor (62.2%), followed by deceased (37.5%) and non-heart beating (0.3%) donors. The most common underlying disease was coronary artery disease (CAD) or cardiac arrhythmia, present in 10.3% of included patients. Most of patients received kidney transplantation after hemodialysis (82.1%). Regarding to induction therapy, basiliximab, and anti-thymocyte globulin were administered to 79.0%, and 11.4% of recipients, respectively. Cytomegalovirus (CMV) and fungal infections were more commonly reported at 3-month than 1-month (4.3% to 12.1% for CMV; 4.0% to 7.7% for fungus). The number of transplantation cases more than doubled from 2003–2009 (4,661 transplantations, 29.0% of included patients) to 2010–2016 (11,412 transplantations, 71.0% of included patients).

Table 1. Comparison of the characteristics between living kidney recipients versus deceased ones at 1 and 3 months after transplantation.

Characteristicsa Early TRM TRM
Living at 1 month Death by 1 month P-valueb Living at 3 months Death by 3 months P-valueb
Number (%) 15,999 74 15,913 160
Age, years 47 (37–55) 56 (48.8–61) < 0.001 47 (37–55) 55.5 (48–61) < 0.001
    < 50 9,188 (57.4) 19 (25.7) < 0.001 9,163 (57.6) 44 (27.5) < 0.001
    50–59 4,830 (30.2) 32 (43.2) 4,792 (30.1) 70 (43.8)
    60–69 1,838 (11.5) 18 (24.3) 1,819 (11.4) 37 (23.1)
    70–79 143 (0.9) 5 (6.8) 139 (0.9) 9 (5.6)
Sex, male 9,451 (59.1) 44 (59.5) 0.946 9,403 (59.1) 92 (57.5) 0.684
Cause of ESRD
    Diabetes mellitus 3,501 (21.9) 19 (25.7) 0.431 3,479 (21.9) 41 (25.6) 0.252
    Hypertension 2,001 (12.5) 8 (10.8) 0.660 1,992 (12.5) 17 (10.6) 0.471
    Glomerulonephritis 2,850 (17.8) 11 (14.9) 0.508 2,840 (17.8) 21 (13.1) 0.120
    Cystic kidney disease 368 (2.3) 2 (2.7) 0.818 365 (2.3) 5 (3.1) 0.485
Underlying diseasec
    Cardiac disease
        Coronary artery disease 392 (2.5) 9 (12.2) < 0.001 384 (2.4) 17 (10.6) < 0.001
        Acute myocardial infarction 288 (1.8) 2 (2.7) 0.561 283 (1.8) 7 (4.4) 0.014
        Cardiac arrhythmia 1,240 (7.8) 13 (17.6) 0.002 1,230 (7.7) 23 (14.4) 0.002
        Cerebrovascular disease
        Cerebral hemorrhage 54 (0.3) 0 (0.0) 0.617 54 (0.3) 0 (0.0) 0.460
    Cerebral infarction 247 (1.5) 1 (1.4) 0.893 246 (1.5) 2 (1.3) 0.763
Hemodialysis 13,134 (82.1) 69 (93.2) 0.012 13,055 (82.0) 148 (92.5) 0.001
Dialysis vintage, monthsd 42.5 (29.5–62.8) 16.0 (9.5–24.5) 0.051 41.0 (29.0–63.5) 24.5 (12.8–39.0) 0.179
Before steroid usee 1,148 (7.2) 3 (4.1) 0.416 1,140 (7.2) 11 (6.9) 1.000
Induction therapy
    Basiliximab 12,637 (79.0) 55 (74.3) 0.402 12,569 (79.0) 123 (76.9) 0.579
    Anti-thymocyte globulin 1,818 (11.4) 22 (29.7) < 0.001 1,799 (11.3) 41 (25.6) < 0.001
Infection
    CMV infection 694 (4.3) 4 (5.4) 0.653 1,900 (11.9) 37 (23.1) < 0.001
    Fungal infection 639 (4.0) 2 (2.7) 0.571 1,205 (7.6) 37 (23.1) < 0.001
Epoch of transplantation
    2003–2009 4,634 (29.0) 27 (36.5) 0.155 4,594 (28.9) 67 (41.9) < 0.001
    2010–2016 11,365 (71.0) 47 (63.5) 11,319 (71.1) 93 (58.1)

a Data were expressed as number (%) or median (interquartile range).

b P value was calculated using chi-square test or Mann–Whitney U test.

c In case of the presence of underlying diseases, multiple diseases were designated to one patient.

d Data were obtained from the Korean Network for Organ Sharing system.

e The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.

Abbreviations: CMV, cytomegalovirus; ESRD, end-stage renal disease; TRM, treatment-related mortality.

Treatment-related mortality

Of the 16,073 patients, 74 (0.5%) and 160 (1.0%) died within 1 and 3 months after kidney transplantation, respectively. The overall cumulative incidence of mortality is shown in Fig 1A. The characteristics of kidney recipients who died within 1 and 3 months were compared to those of living patients, and such characteristics are summarized in Table 1. Based on this comparative analysis, the values of both early TRM and TRM rates significantly increased as the age group increased. In particular, the number of patients who died 1 month (6.8%) and 3 months (5.6%) after transplantation was five times higher than that of living patients (0.9%) aged over 70 years. The rates of recipients who died 1 month (n = 1, 1.4% for living; n = 2, 2.7% for deceased; and n = 2, 2.7% for non-heart beating) and 3 months (n = 5, 3.1% for living; n = 9, 5.6% for deceased; and n = 5, 3.1% for non-heart beating) after transplantation showed significant difference according to the donor state (P < 0.001). The number of patients with a history of cardiac disease, including coronary artery disease (CAD) (P < 0.001) and cardiac arrhythmia (P = 0.002), was significantly higher in the TRM groups than in the non-TRM groups. The recipients with TRM more frequently had undergone hemodialysis (P = 0.012 for early TRM; P = 0.001 for TRM). Patients with anti-thymocyte globulin showed significant relation to TRM (P < 0.001), whereas those with basiliximab did not. CMV and fungal infections (P < 0.001) and the epoch of transplantation (P < 0.001), were associated with TRM at 3 months post-transplantation only.

Fig 1. Cumulative incidence of mortality according to common independent factors of both 1- and 3-month mortality after kidney transplantation.

Fig 1

(A) Total incidence. (B) Older age, (C) Coronary artery disease, and (D) Hemodialysis were associated with worse outcome.

Risk factors for early TRM and TRM

The risk factors of early TRM and TRM are shown in Tables 2 and 3, respectively. Based on the Cox multivariate analysis, older age (hazard ratio [HR] = 1.06; P < 0.001), CAD (HR = 3.02; P = 0.002), cardiac arrhythmia (HR = 1.98; P = 0.027), and hemodialysis compared to pre-emptive kidney transplant (HR = 2.53; P = 0.046) were independently associated with early TRM. Moreover, older age (HR = 1.07; P < 0.001), CAD (HR = 2.88, P = < 0.001), and hemodialysis (HR = 2.35, P = 0.004) were consistently independent risk factors of TRM at any time. However, fungal infection, (HR = 2.61; P < 0.001), and the epoch of transplantation (HR = 0.34 for 2010–2016; P < 0.001) were correlated to TRM only. Regarding to the epoch of transplantation, the aged between 50 and 59 years (HR = 0.37, P = 0.005 for early TRM; HR = 0.37, P < 0.001 for TRM), the patients receiving basiliximab as induction therapy (HR = 0.44, P = 0.002 for early TRM; HR = 0.40, P < 0.001 for TRM), and recipients with CMV infection (HR = 0.13, P = 0.040 for early TRM; HR = 0.39, P = 0.005 for TRM) presented better outcome in 2010–2016, when compared to 2003–2009.

Table 2. Univariate and multivariate analyses of 1-month mortality after kidney transplantation.

Variable Univariate Multivariate
HR (95% CI) P-value HR (95% CI) P-value
Age, yearsa 1.07 (1.05–1.10) < 0.001 1.06 (1.04–1.09) < 0.001
    < 50 Reference
    50–59 3.21 (1.82–5.66) < 0.001
    60–69 4.74 (2.49–9.03) < 0.001
    70–79 16.66 (6.22–44.62) < 0.001
Sex, male 0.98 (0.62–1.56) 0.944
Cause of ESRD
    Diabetes mellitus 1.22 (0.89–1.75) 0.451
    Hypertension 0.80 (0.58–1.12) 0.672
    Glomerulonephritis 0.93 (0.52–2.15) 0.591
    Cystic kidney disease 1.19 (0.78–2.32) 0.854
Underlying disease
    Cardiac disease
        Coronary artery disease 5.51 (2.74–11.06) < 0.001 3.02 (1.48–6.17) 0.002
        Acute myocardial infarction 1.51 (0.37–6.15) 0.566
        Cardiac arrhythmia 2.53 (1.39–4.60) 0.002 1.98 (1.08–3.62) 0.027
    Cerebrovascular disease
        Cerebral hemorrhage NA
        Cerebral infarction 0.87 (0.12–6.26) 0.890
Hemodialysis 3.00 (1.21–7.45) 0.018 2.53 (1.02–6.28) 0.046
Dialysis vintage, monthsc 0.918 (0.833–1.012) 0.086
Before steroid used 0.55 (0.17–1.74) 0.307
Induction therapy
    Basiliximab 0.77 (0.46–1.30) 0.326
    Anti-thymocyte globulin 3.31 (2.01–5.45) < 0.001 2.62 (1.59–4.32) < 0.001
Infection
    CMV infection 1.26 (0.46–3.45) 0.652
    Fungal infection 0.66 (0.16–2.71) 0.569
Epoch of transplantation, 2010–2016 0.72 (0.45–1.15) 0.168

a Variables less than 0.05 of P-values in univariate analysis were included in the multivariate analysis.

b NA is presented if the paucity of deceased or living patients exists for each variable 1 month after kidney transplantation.

c Data were obtained from the Korean Network for Organ Sharing system.

d The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.

Abbreviations: CI, confidence interval; CMV, cytomegalovirus; ESRD, end-stage renal disease; HR, hazard ratio; NA, not applicable.

Table 3. Univariate and multivariate analyses of 3-month mortality after kidney transplantation.

Variable Univariate Multivariate
HR (95% CI) P-value HR (95% CI) P-value
Age, yearsa 1.07 (1.05–1.09) < 0.001 1.07 (1.05–1.09) < 0.001
    < 50
    50–59 3.05 (2.09–4.44) < 0.001
    60–69 4.24 (2.74–6.57) < 0.001
    70–79 13.16 (6.43–26.96) < 0.001
Sex, female 1.07 (0.78–1.46) 0.690
Cause of ESRD
    Diabetes mellitus 1.25 (0.92–1.59) 0.273
    Hypertension 0.86 (0.68–1.10) 0.463
    Glomerulonephritis 0.91 (0.49–1.75) 0.385
    Cystic kidney disease 1.23 (0.87–2.41) 0.526
Underlying disease
    Cardiac disease
        Coronary artery disease 4.82 (2.92–7.97) < 0.001 2.88 (1.71–4.84) < 0.001
        Acute myocardial infarction 2.48 (1.16–5.29) 0.019 1.75 (0.81–3.80) 0.157
        Cardiac arrhythmia 1.99 (1.28–3.10) 0.002 1.40 (0.89–2.18) 0.145
    Cerebrovascular disease
        Cerebral hemorrhage NA
        Cerebral infarction 0.80 (0.20–3.23) 0.755
Hemodialysis 2.69 (1.49–4.85) 0.001 2.35 (1.30–4.25) 0.004
Dialysis vintage, monthsc 0.963 (0.911–1.017) 0.179
Before steroid used 0.95 (0.52–1.76) 0.882
Induction therapy
Basiliximab 0.88 (0.61–1.28) 0.514
Anti-thymocyte globulin 2.73 (1.92–3.90) < 0.001 2.38 (1.62–3.49) < 0.001
Infection
    CMV infection 2.19 (1.51–3.16) < 0.001 1.39 (0.93–2.08) 0.106
    Fungal infection 3.57 (2.47–5.15) < 0.001 2.61 (1.79–3.82) < 0.001
Epoch of transplantation, 2010–2016 0.58 (0.42–0.79) 0.001 0.34 (0.24–0.48) < 0.001

a Variables less than 0.05 of P-values in univariate analysis were included in the multivariate analysis.

b NA is presented if the paucity of deceased or living patients exists for each variable 3 months after kidney transplantation.

c Data were obtained from the Korean Network for Organ Sharing system.

d The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.

Abbreviations: CI, confidence interval; CMV, cytomegalovirus; ESRD, end-stage renal disease; HR, hazard ratio; NA, not applicable.

The effect of age on cumulative incidence of mortality is presented in Fig 1B. The older age group presented with higher HRs for both early TRM (50–59 years, 3.21; 60–69 years, 4.74; and 70–79 years, 16.66; P < 0.001) and TRM (50–59 years, 3.05; 60–69 years, 4.24; and 70–79 years, 13.16; P < 0.001). The effects of CAD and hemodialysis on cumulative incidences are shown in Fig 1C and 1D. In terms of early TRM, a significant difference was observed between patients with a history of cardiac arrhythmia and those without (Fig 2A). Fungal infection (Fig 2B) affected TRM (after early TRM). The protective effect of transplantation in 2010–2016 is illustrated in Fig 2C.

Fig 2. Cumulative incidence of mortality according to the factors associated 1- or 3-month mortality after kidney transplantation.

Fig 2

(A) Cardiac arrhythmia was related to a worse outcome 1 month after transplantation. (B) Fungal infection were a risk factor of 3-month mortality after transplantation. (C) Recent epoch of transplantation (2010–2016) was a protective factor of 3-month mortality compared to the treatment-related mortality of previous epoch (2003–2009).

Discussion

In the present study, a comprehensive analysis of 1- and 3-month mortality after kidney transplantation in Korea was conducted. Older age, CAD, cardiac arrhythmia, and hemodialysis were risk factors for early TRM. For TRM, older age, CAD, and hemodialysis were common independent risk factors observed in both early TRM and TRM. In contrast, cardiac arrhythmia is a risk factor that associated with early TRM only. Fungal infection and the epoch of transplantation were factors associated with TRM only.

Cardiovascular disease has been a well-known risk factor and cause of short- and long-term mortality after kidney transplantation [16,24]. Mortality from cardiovascular disease rather than infection has become a more predominant cause of death due to infection control [25]. Atheroma, left ventricular hypertrophy, and vascular calcification were the main mechanisms of cardiovascular disease after kidney transplantation [26]. Regarding CAD, coronary artery calcification was highly prevalent after kidney transplantation [27]. Coronary angiogram is recommended to individuals aged over 50 years who present with DM or previous cardiac events [28]. Cardiac arrhythmia occurred in 30–60% of ESRD patients and was affected by physiologic changes and hemodialysis [29,30]. The use of an implantable cardioverter defibrillator has been recommended if a life-threatening ventricular arrhythmia exists in a patient who is waiting for kidney transplantation [31]. According to a previous study, graft loss and mortality increased after 1 and 5 years of kidney transplantation in patients with cardiac arrhythmia [32]. Because of these risk factors of TRM, patients who have a history of CAD or cardiac arrhythmia should be counselled for additional work-up and proper management.

Patients without previous hemodialysis showed more favorable outcomes based on our study, despite of discrepancies in preemptive kidney transplantation suggested in previous reports [33,34]. Dialysis-associated comorbidities, decreased immune response, and cardiovascular complications might influence the outcome of non-preemptive kidney transplantation. Prolonged hemodialysis with long waiting times for transplantation has been consistently confirmed to be associated with worse outcomes [35]. The present study revealed that non-preemptive kidney transplantation is related to very short term mortality, such as early TRM and TRM. These findings support early access to transplantation whenever feasible.

The use of anti-thymocyte globulin has been greater in high-risk recipients such as highly sensitized patients, recipients from deceased donors, re-transplantations, and ABO incompatible transplants [36]. According to a prospective, randomized study, patients receiving anti-thymocyte globulin presented a greater incidence of infection (85.8%) compared to those with basiliximab (75.2%) at 12 months after transplantation [37]. However, there was no significant difference in patient survival, similar to the results of a recent study using a network meta-analysis [38]. In Korea, the one-year patient survival in the anti-thymocyte globulin group (89.4%) was compared to the basiliximab group (93.8%), and presented no significant difference [39]. Based on our data, the high-risk recipients receiving anti-thymocyte globulin were significantly associated with early mortality. Further studies for the premature mortality are necessary to validate our results, and intensive care for the high-risk patients receiving anti-thymocyte globulin is important for improving outcomes.

Fungal infections were not common (about 5%) [40] and usually detected after 90 days, however, most infections occurring within 90 days consisted of invasive candidiasis or aspergillosis [41]. Since invasive fungal infections have a mortality rate of 25–30%, these patients require careful management [42]. Obtaining a detailed history of the candidate’s risk, as posed by travel and residential exposures, is an important step for prevention and early diagnosis. The risk factors such as triple immunosuppression, broad spectrum antibiotics for more than 2 weeks, and diabetes mellitus should be also noted. Augmented screening, prophylaxis, and proper work-ups including culture, antigen-based immunoassay, chest radiography, and computed tomography, are all essential to improving the prognosis of kidney recipients [43].

Our risk analysis showed that age was a significant factor (P < 0.001) for both early TRM and TRM. The significant association between old age and poor outcome was persistently reported in previous studies [14,18,44], which have to be considered for patient counselling and selection.

Donor status has been a well-known important factor for short- and long-term mortality after kidney transplantation [15,45]. According to previous studies, kidney allograft recipients that died within the first year after transplantation were more likely to be recipients of deceased donor kidneys [18,44]. It was difficult to compare TRM of our cohort with those of other countries directly because of lack of available data. More intensive care for recipients from deceased donors at early point after transplantation is recommended.

The recent year of transplantation was a protective factor for TRM, which is similar to previous studies [4,24,26,46]. This improvement was based on improvements in surgical and anesthesia techniques and methods for immunologic barriers; the development of chemical and biological immunosuppressive drugs, including cyclosporine, mycophenolate mofetil, and tacrolimus [36]; and infection control and appropriate patient selection. The risk of mortality has decreased over the years in most of the categories of patients [26], which is consistent with our results. Even diabetic and old-aged recipients had better outcome. In particular, relatively low- or intermediate-risk patients such as aged 50 to 59 years, and patients receiving basiliximab were influence by the improved protocols, and showed better outcome than high-risk recipients (aged over 60 years, and recipients with anti-thymocyte globulin). Further, more aggressive and sophisticated infection controls on CMV such as monitoring quantitative levels, and high dose of antiviral therapy [47] may protect more recipients in 2010–2016 than those in 2003–2009. However, patients with cardiovascular disease, particularly CAD, should be counselled because their outcome has not improved based on our study and previous reports [26,48].

This study had several limitations. The lack of detailed clinical information, such as donor’s characteristics and laboratory data (immunologic antibody profiles, and serology for CMV and fungus), led to restrictions on the analysis of wider variables for TRM. Moreover, classification bias could exist because we used registry data based on physicians’ diagnoses. Despite these limitations, the strength of this study includes the use of a nationwide population database of recent kidney recipients. To the best of our knowledge, no other study has reported about TRM and the causes of death using a nationwide data source, particularly in Asia. The relatively large sample size covering the entire national population and unbiased measures used in this study could provide reliable information about kidney recipients.

In conclusion, our study characterized risk factors and causes of 1- and 3-month mortality after kidney transplantation. Old age, particularly greater than 70 years, CAD, and hemodialysis prior to transplant were common risk factors of both early TRM and TRM. By contrast, cardiac arrhythmia was a risk factors for early TRM only, and fungal infection, and epoch of transplantation were important risk factors associated with TRM only. The most common causes of death were chronic kidney disease, cardiovascular disease, and type 2 DM, which require intensive management immediately after transplantation. The risk factors we have identified should be considered when counselling and selecting patients to prevent catastrophic TRM.

Supporting information

S1 Table. Data set of recipients with TRM after kidney transplantation.

(XLSX)

Acknowledgments

The authors acknowledge the efforts of the staff of the HIRA database, which is supported by the NHI system of Korea, for the maintenance and extraction of data about precise kidney transplantation as a research resource. We also thank Hyun Jung Kim and Hyeong Sik Ahn and the staff of the Department of Preventive Medicine, College of Medicine, Korea University, for their assistance in preparing this article.

Abbreviations

CAD

coronary artery disease

CI

confidence interval

CMV

cytomegalovirus

ESRD

end-stage renal disease

HIRA

Health Insurance Review and Assessment Service

HR

hazard ratio

ICD-10-CM

International Classification of Disease, 10th revision, Clinical Modification

NA

not applicable

NHI

National Health Insurance

RID

Rare Intractable Disease

TRM

treatment-related mortality

Data Availability

The repository data for public release is not available because of the personally identifiable information. The full dataset includes clinic centers in which they attend, insurance conditions. Therefore, concerning privacy risks, the data is managed by authorized executive supervisor. If one researcher asks to access data, the person in charge releases data with blind identification for the discrete requirements and the data should be analyzed only in permitted rooms in centers of National Health Insurance Service. Subsets of data limited to anonymisable information obtained and analyzed during this study are included in this article (tables, figures, and supporting information). Contact information for a data access committee is listed as follows: National Health Insurance Sharing Service, Tel: 82-33-736-2432; Official internet site: https://nhiss.nhis.or.kr/bd/ay/bdaya001iv.do. Other researchers can access these data in the same manner as the authors and the authors did not have any special access privileges.

Funding Statement

This work was supported by the National Research Foundation of Korea (NRF) grant, funded by the Korean government (Ministry of Science and ICT) [NRF-2017R1C1B2004597] (to SJ). URL: http://www.nrf.re.kr/index The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

  • 1.Harciarek M, Biedunkiewicz B, Lichodziejewska-Niemierko M, Debska-Slizien A, Rutkowski B. Continuous cognitive improvement 1 year following successful kidney transplant. Kidney Int. 2011;79: 1353–1360. 10.1038/ki.2011.40 [DOI] [PubMed] [Google Scholar]
  • 2.Tonelli M, Wiebe N, Knoll G, Bello A, Browne S, Jadhav D, et al. Systematic review: kidney transplantation compared with dialysis in clinically relevant outcomes. Am J Transplant. 2011;11: 2093–2109. 10.1111/j.1600-6143.2011.03686.x [DOI] [PubMed] [Google Scholar]
  • 3.Yildirim A. The importance of patient satisfaction and health-related quality of life after renal transplantation. Transplant Proc. 2006;38: 2831–2834. 10.1016/j.transproceed.2006.08.162 [DOI] [PubMed] [Google Scholar]
  • 4.Hariharan S, Johnson CP, Bresnahan BA, Taranto SE, McIntosh MJ, Stablein D. Improved graft survival after renal transplantation in the United States, 1988 to 1996. N Engl J Med. 2000;342: 605–612. 10.1056/NEJM200003023420901 [DOI] [PubMed] [Google Scholar]
  • 5.Ethier MC, Blanco E, Lehrnbecher T, Sung L. Lack of clarity in the definition of treatment-related mortality: pediatric acute leukemia and adult acute promyelocytic leukemia as examples. Blood. 2011;118: 5080–5083. 10.1182/blood-2011-07-363333 [DOI] [PubMed] [Google Scholar]
  • 6.Santori G, Andorno E, Morelli N, Antonucci A, Bottino G, Mondello R, et al. MELD score versus conventional UNOS status in predicting short-term mortality after liver transplantation. Transpl Int. 2005;18: 65–72. 10.1111/j.1432-2277.2004.00024.x [DOI] [PubMed] [Google Scholar]
  • 7.Finlayson EV, Birkmeyer JD. Operative mortality with elective surgery in older adults. Eff Clin Pract. 2001;4: 172–177. [PubMed] [Google Scholar]
  • 8.Welch HG, Black WC. Are deaths within 1 month of cancer-directed surgery attributed to cancer? J Natl Cancer Inst. 2002;94: 1066–1070. 10.1093/jnci/94.14.1066 [DOI] [PubMed] [Google Scholar]
  • 9.Begg CB, Cramer LD, Hoskins WJ, Brennan MF. Impact of hospital volume on operative mortality for major cancer surgery. Jama. 1998;280: 1747–1751. 10.1001/jama.280.20.1747 [DOI] [PubMed] [Google Scholar]
  • 10.Mise Y, Vauthey JN, Zimmitti G, Parker NH, Conrad C, Aloia TA, et al. Ninety-day Postoperative Mortality Is a Legitimate Measure of Hepatopancreatobiliary Surgical Quality. Ann Surg. 2015;262: 1071–1078. 10.1097/SLA.0000000000001048 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Hu Y, McMurry TL, Wells KM, Isbell JM, Stukenborg GJ, Kozower BD. Postoperative mortality is an inadequate quality indicator for lung cancer resection. Ann Thorac Surg. 2014;97: 973–979; discussion 978–979. 10.1016/j.athoracsur.2013.12.016 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Visser BC, Keegan H, Martin M, Wren SM. Death after colectomy: it's later than we think. Arch Surg. 2009;144: 1021–1027. 10.1001/archsurg.2009.197 [DOI] [PubMed] [Google Scholar]
  • 13.Mayo SC, Shore AD, Nathan H, Edil BH, Hirose K, Anders RA, et al. Refining the definition of perioperative mortality following hepatectomy using death within 90 days as the standard criterion. HPB (Oxford). 2011;13: 473–482. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Arend SM, Mallat MJ, Westendorp RJ, van der Woude FJ, van Es LA. Patient survival after renal transplantation; more than 25 years follow-up. Nephrol Dial Transplant. 1997;12: 1672–1679. 10.1093/ndt/12.8.1672 [DOI] [PubMed] [Google Scholar]
  • 15.Wang JH, Skeans MA, Israni AK. Current Status of Kidney Transplant Outcomes: Dying to Survive. Adv Chronic Kidney Dis. 2016;23: 281–286. 10.1053/j.ackd.2016.07.001 [DOI] [PubMed] [Google Scholar]
  • 16.Morales JM, Marcen R, del Castillo D, Andres A, Gonzalez-Molina M, Oppenheimer F, et al. Risk factors for graft loss and mortality after renal transplantation according to recipient age: a prospective multicentre study. Nephrol Dial Transplant. 2012;27 Suppl 4: iv39–46. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Chapter 5: Mortality. American Journal of Kidney Diseases. 2018;71: S337–S350. [Google Scholar]
  • 18.Gill JS, Pereira BJ. Death in the first year after kidney transplantation: implications for patients on the transplant waiting list. Transplantation. 2003;75: 113–117. 10.1097/00007890-200301150-00021 [DOI] [PubMed] [Google Scholar]
  • 19.Howard RJ, Patton PR, Reed AI, Hemming AW, Van der Werf WJ, Pfaff WW, et al. The changing causes of graft loss and death after kidney transplantation. Transplantation. 2002;73: 1923–1928. 10.1097/00007890-200206270-00013 [DOI] [PubMed] [Google Scholar]
  • 20.Port FK, Wolfe RA, Mauger EA, Berling DP, Jiang K. Comparison of survival probabilities for dialysis patients vs cadaveric renal transplant recipients. JAMA. 1993;270: 1339–1343. [PubMed] [Google Scholar]
  • 21.Tahir S, Gillott H, Jackson-Spence F, Nath J, Mytton J, Evison F, et al. Do outcomes after kidney transplantation differ for black patients in England versus New York State? A comparative, population-cohort analysis. BMJ Open. 2017;7: e014069 10.1136/bmjopen-2016-014069 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Azevedo LS, Pierrotti LC, Abdala E, Costa SF, Strabelli TM, Campos SV, et al. Cytomegalovirus infection in transplant recipients. Clinics (Sao Paulo). 2015;70: 515–523. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Husain S, Sole A, Alexander BD, Aslam S, Avery R, Benden C, et al. The 2015 International Society for Heart and Lung Transplantation Guidelines for the management of fungal infections in mechanical circulatory support and cardiothoracic organ transplant recipients: Executive summary. J Heart Lung Transplant. 2016;35: 261–282. 10.1016/j.healun.2016.01.007 [DOI] [PubMed] [Google Scholar]
  • 24.Diethelm AG, Deierhoi MH, Hudson SL, Laskow DA, Julian BA, Gaston RS, et al. Progress in renal transplantation. A single center study of 3359 patients over 25 years. Ann Surg. 1995;221: 446–457; discussion 457–448. 10.1097/00000658-199505000-00002 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Matas AJ, Payne WD, Sutherland DE, Humar A, Gruessner RW, Kandaswamy R, et al. 2,500 living donor kidney transplants: a single-center experience. Annals of surgery. 2001;234: 149–164. 10.1097/00000658-200108000-00004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Briggs JD. Causes of death after renal transplantation. Nephrology Dialysis Transplantation. 2001;16: 1545–1549. [DOI] [PubMed] [Google Scholar]
  • 27.Paizis IA, Mantzouratou PD, Tzanis GS, Melexopoulou CA, Darema MN, Boletis JN, et al. Coronary artery disease in renal transplant recipients: an angiographic study. Hellenic J Cardiol. 2018. 2018/07/10. 10.1016/j.hjc.2018.07.002 [DOI] [PubMed] [Google Scholar]
  • 28.Aalten J, Peeters SA, van der Vlugt MJ, Hoitsma AJ. Is standardized cardiac assessment of asymptomatic high-risk renal transplant candidates beneficial? Nephrol Dial Transplant. 2011;26: 3006–3012. 10.1093/ndt/gfq822 [DOI] [PubMed] [Google Scholar]
  • 29.Roy-Chaudhury P, Tumlin JA, Koplan BA, Costea AI, Kher V, Williamson D, et al. Primary outcomes of the Monitoring in Dialysis Study indicate that clinically significant arrhythmias are common in hemodialysis patients and related to dialytic cycle. Kidney International. 2018;93: 941–951. 10.1016/j.kint.2017.11.019 [DOI] [PubMed] [Google Scholar]
  • 30.Roberts PR, Zachariah D, Morgan JM, Yue AM, Greenwood EF, Phillips PC, et al. Monitoring of arrhythmia and sudden death in a hemodialysis population: The CRASH-ILR Study. PLoS One. 2017;12: e0188713 10.1371/journal.pone.0188713 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Fuster V, Rydén LE, Cannom DS, Crijns HJ, Curtis AB, Ellenbogen KA, et al. ACC/AHA/ESC 2006 guidelines for the management of patients with atrial fibrillation: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines and the European Society of Cardiology Committee for Practice Guidelines (Writing Committee to Revise the 2001 guidelines for the management of patients with atrial fibrillation) developed in collaboration with the European Heart Rhythm Association and the Heart Rhythm Society. Journal of the American College of Cardiology. 2006;48: e149–e246. [Google Scholar]
  • 32.Lenihan CR, Montez-Rath ME, Scandling JD, Turakhia MP, Winkelmayer WC. Outcomes After Kidney Transplantation of Patients Previously Diagnosed With Atrial Fibrillation. American Journal of Transplantation. 2013;13: 1566–1575. 10.1111/ajt.12197 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Haller MC, Kainz A, Baer H, Oberbauer R. Dialysis Vintage and Outcomes after Kidney Transplantation: A Retrospective Cohort Study. Clin J Am Soc Nephrol. 2017;12: 122–130. 10.2215/CJN.04120416 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Sayin B, Colak T, Tutal E, Sezer S. Comparison of preemptive kidney transplant recipients with nonpreemptive kidney recipients in single center: 5 years of follow-up. Int J Nephrol Renovasc Dis. 2013;6: 95–99. 10.2147/IJNRD.S42042 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Lee S, Yoo KD, An JN, Oh YK, Lim CS, Kim YS, et al. Factors affecting mortality during the waiting time for kidney transplantation: A nationwide population-based cohort study using the Korean Network for Organ Sharing (KONOS) database. PLoS One. 2019;14: e0212748 10.1371/journal.pone.0212748 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Chang JY, Yu J, Chung BH, Yang J, Kim SJ, Kim CD, et al. Immunosuppressant prescription pattern and trend in kidney transplantation: A multicenter study in Korea. PLoS One. 2017;12: e0183826 10.1371/journal.pone.0183826 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Brennan DC, Daller JA, Lake KD, Cibrik D, Del Castillo D, Thymoglobulin Induction Study G. Rabbit antithymocyte globulin versus basiliximab in renal transplantation. N Engl J Med. 2006;355: 1967–1977. 10.1056/NEJMoa060068 [DOI] [PubMed] [Google Scholar]
  • 38.Shao M, Tian T, Zhu X, Ming Y, Iwakiri Y, Ye S, et al. Comparative efficacy and safety of antibody induction therapy for the treatment of kidney: a network meta-analysis. Oncotarget. 2017;8: 66426–66437. 10.18632/oncotarget.19815 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Cheon SU, Moon JI, Choi IS, Yoon SH, Hwang WM, Yun SR. Comparison of the Clinical Outcomes between Anti-thymocyte Globulin and Basiliximab Induction Therapy in Deceased Donor Kidney Transplantation: Single Center Experience. J Korean Soc Transplant. 2015;29: 61–67. [Google Scholar]
  • 40.Eswarappa M, Varma PV, Madhyastha R, Reddy S, Gireesh MS, Gurudev KC, et al. Unusual Fungal Infections in Renal Transplant Recipients. Case Reports in Transplantation. 2015;2015: 4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Pappas PG, Alexander BD, Andes DR, Hadley S, Kauffman CA, Freifeld A, et al. Invasive Fungal Infections among Organ Transplant Recipients: Results of the Transplant-Associated Infection Surveillance Network (TRANSNET). Clinical Infectious Diseases. 2010;50: 1101–1111. 10.1086/651262 [DOI] [PubMed] [Google Scholar]
  • 42.Patel MH, Patel RD, Vanikar AV, Kanodia KV, Suthar KS, Nigam LK, et al. Invasive fungal infections in renal transplant patients: a single center study. Renal failure. 2017;39: 294–298. 10.1080/0886022X.2016.1268537 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Miller R, Assi M, the ASTIDCoP. Endemic fungal infections in solid organ transplant recipients—Guidelines from the American Society of Transplantation Infectious Diseases Community of Practice. Clinical Transplantation. 2019;33: e13553 10.1111/ctr.13553 [DOI] [PubMed] [Google Scholar]
  • 44.Farrugia D, Cheshire J, Begaj I, Khosla S, Ray D, Sharif A. Death within the first year after kidney transplantation—an observational cohort study. Transpl Int. 2014;27: 262–270. 10.1111/tri.12218 [DOI] [PubMed] [Google Scholar]
  • 45.Jehn U, Schutte-Nutgen K, Bautz J, Pavenstadt H, Suwelack B, Tholking G, et al. Cytomegalovirus Viremia after Living and Deceased Donation in Kidney Transplantation. J Clin Med. 2020;9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Chapman JR. Progress in Transplantation: Will It Be Achieved in Big Steps or by Marginal Gains? Am J Kidney Dis. 2017;69: 287–295. 10.1053/j.ajkd.2016.08.024 [DOI] [PubMed] [Google Scholar]
  • 47.Selvey LA, Lim WH, Boan P, Swaminathan R, Slimings C, Harrison AE, et al. Cytomegalovirus viraemia and mortality in renal transplant recipients in the era of antiviral prophylaxis. Lessons from the western Australian experience. BMC Infectious Diseases. 2017;17: 501 10.1186/s12879-017-2599-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Schweitzer EJ, Matas AJ, Gillingham KJ, Payne WD, Gores PF, Dunn DL, et al. Causes of renal allograft loss. Progress in the 1980s, challenges for the 1990s. Ann Surg. 1991;214: 679–688. 10.1097/00000658-199112000-00007 [DOI] [PMC free article] [PubMed] [Google Scholar]

Decision Letter 0

Robert Jeenchen Chen

24 Mar 2020

PONE-D-20-03919

The risk factors associated with treatment-related mortality in 16,073 kidney transplantation - A nationwide cohort study

PLOS ONE

Dear Dr. Seri Jeong,

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Reviewer #1: Partly

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

Reviewer #1: Yes

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Reviewer #1: Yes

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Reviewer #1: In this paper submitted by Jeong et al, an investigation about the risk factors causes of TRM after kidney transplantation, focusing on vascular diseases was presented.

The paper is written in a correct and fluent English, and statistical analyses are correctly described and presented by the authors.

Nevertheless, the paper presents several limitations, apart the retrospective design, which make oit unsuitable for the publication in this form. First of all, several important data are missing and in my opinion crucial for the aim of the study: dialysis vintage, prevalence of deceased/living donor (if not considered explain why), basic nephropathy, and steroid therapy before therapy, donor characteristics. All those factors might impact also on the global results of the study that at the moment does not add any novel knowledge on the problem.

In addition many topics need a better clarification and explanation: definition of CMD disease, prevalence of CMV serum-negativity. The cause of death classification is absolutely unreasonable, - “chronic kidney disease was the main cause of both early TRM and TRM, followed cystic kidney disease” ??????

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PLoS One. 2020 Jul 28;15(7):e0236274. doi: 10.1371/journal.pone.0236274.r002

Author response to Decision Letter 0


3 May 2020

1. Thank you for providing the following Data Availability Statement:

The repository data for public release is not available because of the personally dentifiable information. The full dataset includes clinic centers in which they attend, insurance conditions. Therefore, concerning privacy risks, the data is managed by authorized executive supervisor. If one researcher asks to access data, the person in charge releases data with blind identification for the discrete requirements and the data should be analyzed only in permitted rooms in centers of National Health Insurance Service. Subsets of data limited to anonymisable information obtained and analyzed during this study are included in this article (tables, figures, and supporting information). Contact information for a data access committee is listed as follows: National Health Insurance Sharing Service, Tel: 82-33-736-2432; Official internet site: https://nhiss.nhis.or.kr/bd/ay/bdaya001iv.do."

Before we proceed, please confirm the following:

1) Please give the full name of the organization that has imposed the data restictions (e.g., a Research Ethics Committee or Institutional Review Board, etc.).

� We submitted the security memorandum and pledge to the Institutional Review Board of National Health Insurance Sharing Service when we access these data. The original files of security memorandum and pledge have been uploaded for this revision. The translated contents include “Any data obtained from National Health Insurance Sharing Service will not be taken out externally or used for any other purpose. I pledge to take any civil and criminal penalties.”. Your kind consideration for this security situation would be greatly appreciated. We have inserted additional explanation in to the revised Data Availability Statement (page 20, lines 11 to 13) as follows.

“If one researcher asks to access data, the researcher should submit the security memorandum and pledge to the Institutional Review Board of National Health Insurance Sharing Service. After approval, the person in charge releases data with blind identification for the discrete requirements and the data should be analyzed only in permitted rooms in centers of National Health Insurance Service.”

2) Please confirm that others would be able to access these data in the same manner as the authors. Please also confirm that the authors did not have any special access privileges that others would not have.

� We confirmed that others could access these data in the same manner as the authors and the authors did not have any special access privileges. We also have added these statement to the revised Data Availability Statement (page 20, lines 15 to 16) as follows.

“The other researchers could access these data in the same manner as the authors and the authors did not have any special access privileges.”

3) Please confirm that the data that researchers can access fits our definition of "minimal data set" as outlined here: https://journals.plos.org/plosone/s/data-availability#loc-minimal-data-set-definition

� We have provided maximally permitted data for meeting the requirements of “minimal data set”. Although entire data sets of kidney recipients were not permitted, the anonymisable data for recipients with treatment-related mortality focused on this manuscript and used for tables and graphs were provided in S1 Table.

Journal requirements:

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at http://www.plosone.org/attachments/PLOSOne_formatting_sample_main_body.pdf and http://www.plosone.org/attachments/PLOSOne_formatting_sample_title_authors_affiliations.pdf

� We have checked the PLOS ONE style templates and corrected the location of References section. The revised References section has been listed after the main text, before the supporting information. The file naming also checked and corrected.

2. We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions.

In your revised cover letter, please address the following prompts:

a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially identifying or sensitive patient information) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent.

b) If there are no restrictions, please upload the minimal anonymized data set necessary to replicate your study findings as either Supporting Information files or to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. Please see http://www.bmj.com/content/340/bmj.c181.long for guidelines on how to de-identify and prepare clinical data for publication. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories.

We will update your Data Availability statement on your behalf to reflect the information you provide.

� We provided the minimal data set, which had anonymisable information in S1 Table. Therefore, we have corrected the sentence from “Subsets of data limited to anonymisable information obtained and analyzed during this study are included in this article (tables, figures, and supporting information) and are available from the corresponding author upon reasonable request.” to “Subsets of data limited to anonymisable information obtained and analyzed during this study are included in this article (tables, figures, and supporting information).” in the revised Data accessibility statement section (page 20, lines 14 to 16). Because National Health Insurance Sharing Service restricts to share full dataset concerning privacy risks, minimal anonymized data set focusing on recipients with treatment-related mortality after kidney transplantation was provided. Contact information for a data access committee and the way for obtaining the data were described in the Data accessibility statement section. We have added these statement to the revised cover letter.

Response to the reviewer’s comments

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

Reviewer #1: Partly

� We have corrected and checked that the revised manuscript described a technically sound piece of scientific research and that the data supported the conclusions. We also responded to the reviewer #1’s comments sincerely.

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

Reviewer #1: Yes

� We have checked that the statistical analysis has been conducted appropriately and rigorously.

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

Reviewer #1: Yes

� According to the journal requirements, we provided the minimal data set focusing on recipients with treatment-related mortality after kidney transplantation. Contact information for a data access committee and the way for obtaining the data were described in the Data accessibility statement section. We have added these statement to the revised cover letter.

“We collected the following demographic data and baseline characteristics of kidney recipients from the HIRA database: age, sex, medical comorbidities focusing on cardiac and cerebrovascular diseases reported to be important causes of early mortality [16], dialysis status, cytomegalovirus (CMV) and fungal infection, and year of transplantation (S1 Table).”

S1 Table. Data set of recipients with TRM after kidney transplantation.

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

Reviewer #1: Yes

� We used manuscript editing service before submission.

5. Review Comments to the Author

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Response to reviewer #1’s comments

Comment 1: In this paper submitted by Jeong et al, an investigation about the risk factors causes of TRM after kidney transplantation, focusing on vascular diseases was presented.

The paper is written in a correct and fluent English, and statistical analyses are correctly described and presented by the authors.

Nevertheless, the paper presents several limitations, apart the retrospective design, which make oit unsuitable for the publication in this form. First of all, several important data are missing and in my opinion crucial for the aim of the study: dialysis vintage, prevalence of deceased/living donor (if not considered explain why), basic nephropathy, and steroid therapy before therapy, donor characteristics. All those factors might impact also on the global results of the study that at the moment does not add any novel knowledge on the problem.

� Response 1: As indicated by reviewer, we have provided available information in the revised manuscript.

Dialysis vintage:

We have requested additional data from another database operated by the Korean Network for Organ Sharing system in order to analyze dialysis vintage. In this database, the records of recipients who underwent kidney transplantation in 40 medical centers around the country have been registered. We have provided the results of dialysis vintage, time from dialysis to transplantation, in the revised Tables 1-3 as follows. The source of data was also described in revised Materials and Methods section as follows.

Results

Table 1. Comparison of the characteristics between living kidney recipients versus deceased ones at 1 and 3 months after transplantation.

Characteristicsa Early TRM TRM

Living at 1 month Death by 1 month P-valueb Living at 3 months Death by 3 months P-valueb

Number (%) 15,999 74   15,913 160  

Age, years 47 (37-55) 56 (48.8-61) < 0.001 47 (37-55) 55.5 (48-61) < 0.001

< 50 9,188 (57.4) 19 (25.7) < 0.001 9,163 (57.6) 44 (27.5) < 0.001

50–59 4,830 (30.2) 32 (43.2)   4,792 (30.1) 70 (43.8)  

60–69 1,838 (11.5) 18 (24.3)   1,819 (11.4) 37 (23.1)  

70–79 143 (0.9) 5 (6.8)   139 (0.9) 9 (5.6)  

Sex, male 9,451 (59.1) 44 (59.5) 0.946 9,403 (59.1) 92 (57.5) 0.684

Cause of ESRD

Diabetes mellitus 3,501 (21.9) 19 (25.7) 0.431 3,479 (21.9) 41 (25.6) 0.252

Hypertension 2,001 (12.5) 8 (10.8) 0.660 1,992 (12.5) 17 (10.6) 0.471

Glomerulonephritis 2,850 (17.8) 11 (14.9) 0.508 2,840 (17.8) 21 (13.1) 0.120

Cystic kidney disease 368 (2.3) 2 (2.7) 0.818 365 (2.3) 5 (3.1) 0.485

Underlying diseasec            

Cardiac disease            

Coronary artery disease 392 (2.5) 9 (12.2) < 0.001 384 (2.4) 17 (10.6) < 0.001

Acute myocardial infarction 288 (1.8) 2 (2.7) 0.561 283 (1.8) 7 (4.4) 0.014

Cardiac arrhythmia 1,240 (7.8) 13 (17.6) 0.002 1,230 (7.7) 23 (14.4) 0.002

Cerebrovascular disease            

Cerebral hemorrhage 54 (0.3) 0 (0.0) 0.617 54 (0.3) 0 (0.0) 0.460

Cerebral infarction 247 (1.5) 1 (1.4) 0.893 246 (1.5) 2 (1.3) 0.763

Hemodialysis 13,134 (82.1) 69 (93.2) 0.012 13,055 (82.0) 148 (92.5) 0.001

Dialysis vintage, monthsd 42.5 (29.5-62.8) 16.0 (9.5-24.5) 0.051 41.0 (29.0-63.5) 24.5 (12.8-39.0) 0.179

Before steroid usee 1,148 (7.2) 3 (4.1) 0.416 1,140 (7.2) 11 (6.9) 1.000

Infection            

CMV infection 694 (4.3) 4 (5.4) 0.653 1,900 (11.9) 37 (23.1) < 0.001

Fungal infection 639 (4.0) 2 (2.7) 0.571 1,205 (7.6) 37 (23.1) < 0.001

Epoch of transplantation            

2003–2009 4,634 (29.0) 27 (36.5) 0.155 4,594 (28.9) 67 (41.9) < 0.001

2010–2016 11,365 (71.0) 47 (63.5)   11,319 (71.1) 93 (58.1)  

a Data were expressed as number (%) or median (interquartile range).

b P value was calculated using chi-square test or Mann–Whitney U test.

c In case of the presence of underlying diseases, multiple diseases were designated to one patient.

d Data were obtained from the Korean Network for Organ Sharing system.

e The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.

Abbreviations: CMV, cytomegalovirus; ESRD, end-stage renal disease; TRM, treatment-related mortality.

Table 2. Univariate and multivariate analyses of 1-month mortality after kidney transplantation.

Variable Univariate Multivariate

HR (95% CI) P-value HR (95% CI) P-value

Age, yearsa 1.07 (1.05–1.10) < 0.001 1.07 (1.05-1.10) < 0.001

< 50 Reference      

50–59 3.21 (1.82-5.66) < 0.001    

60–69 4.74 (2.49-9.03) < 0.001    

70–79 16.66 (6.22-44.62) < 0.001    

Sex, male 0.98 (0.62-1.56) 0.944    

Cause of ESRD

Diabetes mellitus 1.22 (0.89-1.75) 0.451

Hypertension 0.80 (0.58-1.12) 0.672

Glomerulonephritis 0.93 (0.52-2.15) 0.591

Cystic kidney disease 1.19 (0.78-2.32) 0.854

Underlying disease        

Cardiac disease        

Coronary artery disease 5.51 (2.74-11.06) < 0.001 2.81 (1.37-5.78) 0.005

Acute myocardial infarction 1.51 (0.37-6.15) 0.566    

Cardiac arrhythmia 2.53 (1.39-4.60) 0.002 1.99 (1.09-3.64) 0.025

Cerebrovascular disease        

Cerebral hemorrhage NA      

Cerebral infarction 0.87 (0.12-6.26) 0.890    

Hemodialysis 3.00 (1.21-7.45) 0.018 2.58 (1.04-6.42) 0.041

Dialysis vintage, monthsc 0.918 (0.833-1.012) 0.086

Before steroid used 0.55 (0.17-1.74) 0.307

Infection        

CMV infection 1.26 (0.46-3.45) 0.652    

Fungal infection 0.66 (0.16-2.71) 0.569    

Epoch of transplantation, 2010–2016 0.72 (0.45-1.15) 0.168    

a Variables less than 0.05 of P-values in univariate analysis were included in the multivariate analysis.

b NA is presented if the paucity of deceased or living patients exists for each variable 1 month after kidney transplantation.

c Data were obtained from the Korean Network for Organ Sharing system.

d The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.Abbreviations: CI, confidence interval; CMV, cytomegalovirus; ESRD, end-stage renal disease; HR, hazard ratio; NA, not applicable.

Table 3. Univariate and multivariate analyses of 3-month mortality after kidney transplantation.

Variable Univariate Multivariate

HR (95% CI) P-value HR (95% CI) P-value

Age, yearsa 1.07 (1.05–1.09) < 0.001 1.08 (1.06-1.09) < 0.001

< 50        

50–59 3.05 (2.09-4.44) < 0.001    

60–69 4.24 (2.74-6.57) < 0.001    

70–79 13.16 (6.43-26.96) < 0.001    

Sex, female 1.07 (0.78-1.46) 0.690    

Cause of ESRD

Diabetes mellitus 1.25 (0.92-1.59) 0.273

Hypertension 0.86 (0.68-1.10) 0.463

Glomerulonephritis 0.91 (0.49-1.75) 0.385

Cystic kidney disease 1.23 (0.87-2.41) 0.526

Underlying disease        

Cardiac disease        

Coronary artery disease 4.82 (2.92-7.97) < 0.001 2.53 (1.49-4.31) 0.001

Acute myocardial infarction 2.48 (1.16-5.29) 0.019 1.70 (0.78-3.69) 0.183

Cardiac arrhythmia 1.99 (1.28-3.10) 0.002 1.43 (0.91-2.24) 0.117

Cerebrovascular disease        

Cerebral hemorrhage NA      

Cerebral infarction 0.80 (0.20-3.23) 0.755    

Hemodialysis 2.69 (1.49-4.85) 0.001 2.32 (1.28-4.19) 0.005

Dialysis vintage, monthsc 0.963 (0.911-1.017) 0.179

Before steroid used 0.95 (0.52-1.76) 0.882

Infection        

CMV infection 2.19 (1.51-3.16) < 0.001 1.65 (1.12-2.42) 0.012

Fungal infection 3.57 (2.47-5.15) < 0.001 2.48 (1.69-3.65) < 0.001

Epoch of transplantation, 2010–2016 0.58 (0.42-0.79) 0.001 0.43 (0.31-0.60) < 0.001

a Variables less than 0.05 of P-values in univariate analysis were included in the multivariate analysis.

b NA is presented if the paucity of deceased or living patients exists for each variable 3 months after kidney transplantation.

c Data were obtained from the Korean Network for Organ Sharing system.

d The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.

Abbreviations: CI, confidence interval; CMV, cytomegalovirus; ESRD, end-stage renal disease; HR, hazard ratio; NA, not applicable.

Materials and Methods section (page 7, lines 11 to 14)

The data for dialysis vintage, and donor state omitting in HIRA database were obtained from another database operated by the Korean Network for Organ Sharing system. In this database, the records of recipients who underwent kidney transplantation in 40 medical centers around the country were registered.

Prevalence of deceased/living donor (if not considered explain why):

We have also requested data of donor state from the Korean Network for Organ Sharing system since donor information was not included in the Health Insurance Review and Assessment Service (HIRA). The results of living, deceased, and non-heart beating donors are presented in the revised Results section as follows. These variables did not insert into the Tables because the direct combination of data was not available for the multivariate analyses.

Results

Characteristics of patients (page 8, lines 11 to 13)

“Most patients received kidney from living donor (62.2%), followed by deceased (37.5%) and non-heart beating (0.3%) donors.”

Treatment-related mortality (page 11, lines 9 to 12)

“The rates of recipients who died 1 month (1.2% for living, 2.4% for deceased, and 3.3% for non-heart beating) and 3 months (3.2% for living, 5.5% for deceased, and 3.3% for non-heart beating) after transplantation showed significant difference according to the donor state (P < 0.001).”

Discussion (page 17, lines 22 to page 18 lines 3)

“Donor status has been a well-known important factor for short- and long-term mortality after kidney transplantation [15,21]. According to previous studies, kidney allograft recipients that died within the first year after transplantation were more likely to be recipients of deceased donor kidneys [18,20]. It was difficult to compare TRM of our cohort with those of other countries directly because of lack of available data. More intensive care for recipients from deceased donors at early point after transplantation is recommended.”

Basic nephropathy:

We have added the results of basic nephropathy including diabetes mellitus, hypertension, glomerulonephritis, and cystic kidney disease to the revised Tables 1-3 as follows.

Table 1. Comparison of the characteristics between living kidney recipients versus deceased ones at 1 and 3 months after transplantation.

Characteristicsa Early TRM TRM

Living at 1 month Death by 1 month P-valueb Living at 3 months Death by 3 months P-valueb

Number (%) 15,999 74   15,913 160  

Age, years 47 (37-55) 56 (48.8-61) < 0.001 47 (37-55) 55.5 (48-61) < 0.001

< 50 9,188 (57.4) 19 (25.7) < 0.001 9,163 (57.6) 44 (27.5) < 0.001

50–59 4,830 (30.2) 32 (43.2)   4,792 (30.1) 70 (43.8)  

60–69 1,838 (11.5) 18 (24.3)   1,819 (11.4) 37 (23.1)  

70–79 143 (0.9) 5 (6.8)   139 (0.9) 9 (5.6)  

Sex, male 9,451 (59.1) 44 (59.5) 0.946 9,403 (59.1) 92 (57.5) 0.684

Cause of ESRD

Diabetes mellitus 3,501 (21.9) 19 (25.7) 0.431 3,479 (21.9) 41 (25.6) 0.252

Hypertension 2,001 (12.5) 8 (10.8) 0.660 1,992 (12.5) 17 (10.6) 0.471

Glomerulonephritis 2,850 (17.8) 11 (14.9) 0.508 2,840 (17.8) 21 (13.1) 0.120

Cystic kidney disease 368 (2.3) 2 (2.7) 0.818 365 (2.3) 5 (3.1) 0.485

Underlying diseasec            

Cardiac disease            

Coronary artery disease 392 (2.5) 9 (12.2) < 0.001 384 (2.4) 17 (10.6) < 0.001

Acute myocardial infarction 288 (1.8) 2 (2.7) 0.561 283 (1.8) 7 (4.4) 0.014

Cardiac arrhythmia 1,240 (7.8) 13 (17.6) 0.002 1,230 (7.7) 23 (14.4) 0.002

Cerebrovascular disease            

Cerebral hemorrhage 54 (0.3) 0 (0.0) 0.617 54 (0.3) 0 (0.0) 0.460

Cerebral infarction 247 (1.5) 1 (1.4) 0.893 246 (1.5) 2 (1.3) 0.763

Hemodialysis 13,134 (82.1) 69 (93.2) 0.012 13,055 (82.0) 148 (92.5) 0.001

Dialysis vintage, monthsd 42.5 (29.5-62.8) 16.0 (9.5-24.5) 0.051 41.0 (29.0-63.5) 24.5 (12.8-39.0) 0.179

Before steroid usee 1,148 (7.2) 3 (4.1) 0.416 1,140 (7.2) 11 (6.9) 1.000

Infection            

CMV infection 694 (4.3) 4 (5.4) 0.653 1,900 (11.9) 37 (23.1) < 0.001

Fungal infection 639 (4.0) 2 (2.7) 0.571 1,205 (7.6) 37 (23.1) < 0.001

Epoch of transplantation            

2003–2009 4,634 (29.0) 27 (36.5) 0.155 4,594 (28.9) 67 (41.9) < 0.001

2010–2016 11,365 (71.0) 47 (63.5)   11,319 (71.1) 93 (58.1)  

a Data were expressed as number (%) or median (interquartile range).

b P value was calculated using chi-square test or Mann–Whitney U test.

c In case of the presence of underlying diseases, multiple diseases were designated to one patient.

d Data were obtained from the Korean Network for Organ Sharing system.

e The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.

Abbreviations: CMV, cytomegalovirus; ESRD, end-stage renal disease; TRM, treatment-related mortality.

Table 2. Univariate and multivariate analyses of 1-month mortality after kidney transplantation.

Variable Univariate Multivariate

HR (95% CI) P-value HR (95% CI) P-value

Age, yearsa 1.07 (1.05–1.10) < 0.001 1.07 (1.05-1.10) < 0.001

< 50 Reference      

50–59 3.21 (1.82-5.66) < 0.001    

60–69 4.74 (2.49-9.03) < 0.001    

70–79 16.66 (6.22-44.62) < 0.001    

Sex, male 0.98 (0.62-1.56) 0.944    

Cause of ESRD

Diabetes mellitus 1.22 (0.89-1.75) 0.451

Hypertension 0.80 (0.58-1.12) 0.672

Glomerulonephritis 0.93 (0.52-2.15) 0.591

Cystic kidney disease 1.19 (0.78-2.32) 0.854

Underlying disease        

Cardiac disease        

Coronary artery disease 5.51 (2.74-11.06) < 0.001 2.81 (1.37-5.78) 0.005

Acute myocardial infarction 1.51 (0.37-6.15) 0.566    

Cardiac arrhythmia 2.53 (1.39-4.60) 0.002 1.99 (1.09-3.64) 0.025

Cerebrovascular disease        

Cerebral hemorrhage NA      

Cerebral infarction 0.87 (0.12-6.26) 0.890    

Hemodialysis 3.00 (1.21-7.45) 0.018 2.58 (1.04-6.42) 0.041

Dialysis vintage, monthsc 0.918 (0.833-1.012) 0.086

Before steroid used 0.55 (0.17-1.74) 0.307

Infection        

CMV infection 1.26 (0.46-3.45) 0.652    

Fungal infection 0.66 (0.16-2.71) 0.569    

Epoch of transplantation, 2010–2016 0.72 (0.45-1.15) 0.168    

a Variables less than 0.05 of P-values in univariate analysis were included in the multivariate analysis.

b NA is presented if the paucity of deceased or living patients exists for each variable 1 month after kidney transplantation.

c Data were obtained from the Korean Network for Organ Sharing system.

d The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.Abbreviations: CI, confidence interval; CMV, cytomegalovirus; ESRD, end-stage renal disease; HR, hazard ratio; NA, not applicable.

Table 3. Univariate and multivariate analyses of 3-month mortality after kidney transplantation.

Variable Univariate Multivariate

HR (95% CI) P-value HR (95% CI) P-value

Age, yearsa 1.07 (1.05–1.09) < 0.001 1.08 (1.06-1.09) < 0.001

< 50        

50–59 3.05 (2.09-4.44) < 0.001    

60–69 4.24 (2.74-6.57) < 0.001    

70–79 13.16 (6.43-26.96) < 0.001    

Sex, female 1.07 (0.78-1.46) 0.690    

Cause of ESRD

Diabetes mellitus 1.25 (0.92-1.59) 0.273

Hypertension 0.86 (0.68-1.10) 0.463

Glomerulonephritis 0.91 (0.49-1.75) 0.385

Cystic kidney disease 1.23 (0.87-2.41) 0.526

Underlying disease        

Cardiac disease        

Coronary artery disease 4.82 (2.92-7.97) < 0.001 2.53 (1.49-4.31) 0.001

Acute myocardial infarction 2.48 (1.16-5.29) 0.019 1.70 (0.78-3.69) 0.183

Cardiac arrhythmia 1.99 (1.28-3.10) 0.002 1.43 (0.91-2.24) 0.117

Cerebrovascular disease        

Cerebral hemorrhage NA      

Cerebral infarction 0.80 (0.20-3.23) 0.755    

Hemodialysis 2.69 (1.49-4.85) 0.001 2.32 (1.28-4.19) 0.005

Dialysis vintage, monthsc 0.963 (0.911-1.017) 0.179

Before steroid used 0.95 (0.52-1.76) 0.882

Infection        

CMV infection 2.19 (1.51-3.16) < 0.001 1.65 (1.12-2.42) 0.012

Fungal infection 3.57 (2.47-5.15) < 0.001 2.48 (1.69-3.65) < 0.001

Epoch of transplantation, 2010–2016 0.58 (0.42-0.79) 0.001 0.43 (0.31-0.60) < 0.001

a Variables less than 0.05 of P-values in univariate analysis were included in the multivariate analysis.

b NA is presented if the paucity of deceased or living patients exists for each variable 3 months after kidney transplantation.

c Data were obtained from the Korean Network for Organ Sharing system.

d The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.

Abbreviations: CI, confidence interval; CMV, cytomegalovirus; ESRD, end-stage renal disease; HR, hazard ratio; NA, not applicable.

Steroid therapy before therapy:

We have inserted the results of steroid therapy before transplantation into the revised Tables 1-3 as follows. The recipients with the use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation were designated and described in the revised footnotes of Tables.

Table 1. Comparison of the characteristics between living kidney recipients versus deceased ones at 1 and 3 months after transplantation.

Characteristicsa Early TRM TRM

Living at 1 month Death by 1 month P-valueb Living at 3 months Death by 3 months P-valueb

Number (%) 15,999 74   15,913 160  

Age, years 47 (37-55) 56 (48.8-61) < 0.001 47 (37-55) 55.5 (48-61) < 0.001

< 50 9,188 (57.4) 19 (25.7) < 0.001 9,163 (57.6) 44 (27.5) < 0.001

50–59 4,830 (30.2) 32 (43.2)   4,792 (30.1) 70 (43.8)  

60–69 1,838 (11.5) 18 (24.3)   1,819 (11.4) 37 (23.1)  

70–79 143 (0.9) 5 (6.8)   139 (0.9) 9 (5.6)  

Sex, male 9,451 (59.1) 44 (59.5) 0.946 9,403 (59.1) 92 (57.5) 0.684

Cause of ESRD

Diabetes mellitus 3,501 (21.9) 19 (25.7) 0.431 3,479 (21.9) 41 (25.6) 0.252

Hypertension 2,001 (12.5) 8 (10.8) 0.660 1,992 (12.5) 17 (10.6) 0.471

Glomerulonephritis 2,850 (17.8) 11 (14.9) 0.508 2,840 (17.8) 21 (13.1) 0.120

Cystic kidney disease 368 (2.3) 2 (2.7) 0.818 365 (2.3) 5 (3.1) 0.485

Underlying diseasec            

Cardiac disease            

Coronary artery disease 392 (2.5) 9 (12.2) < 0.001 384 (2.4) 17 (10.6) < 0.001

Acute myocardial infarction 288 (1.8) 2 (2.7) 0.561 283 (1.8) 7 (4.4) 0.014

Cardiac arrhythmia 1,240 (7.8) 13 (17.6) 0.002 1,230 (7.7) 23 (14.4) 0.002

Cerebrovascular disease            

Cerebral hemorrhage 54 (0.3) 0 (0.0) 0.617 54 (0.3) 0 (0.0) 0.460

Cerebral infarction 247 (1.5) 1 (1.4) 0.893 246 (1.5) 2 (1.3) 0.763

Hemodialysis 13,134 (82.1) 69 (93.2) 0.012 13,055 (82.0) 148 (92.5) 0.001

Dialysis vintage, monthsd 42.5 (29.5-62.8) 16.0 (9.5-24.5) 0.051 41.0 (29.0-63.5) 24.5 (12.8-39.0) 0.179

Before steroid usee 1,148 (7.2) 3 (4.1) 0.416 1,140 (7.2) 11 (6.9) 1.000

Infection            

CMV infection 694 (4.3) 4 (5.4) 0.653 1,900 (11.9) 37 (23.1) < 0.001

Fungal infection 639 (4.0) 2 (2.7) 0.571 1,205 (7.6) 37 (23.1) < 0.001

Epoch of transplantation            

2003–2009 4,634 (29.0) 27 (36.5) 0.155 4,594 (28.9) 67 (41.9) < 0.001

2010–2016 11,365 (71.0) 47 (63.5)   11,319 (71.1) 93 (58.1)  

a Data were expressed as number (%) or median (interquartile range).

b P value was calculated using chi-square test or Mann–Whitney U test.

c In case of the presence of underlying diseases, multiple diseases were designated to one patient.

d Data were obtained from the Korean Network for Organ Sharing system.

e The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.

Abbreviations: CMV, cytomegalovirus; ESRD, end-stage renal disease; TRM, treatment-related mortality.

Table 2. Univariate and multivariate analyses of 1-month mortality after kidney transplantation.

Variable Univariate Multivariate

HR (95% CI) P-value HR (95% CI) P-value

Age, yearsa 1.07 (1.05–1.10) < 0.001 1.07 (1.05-1.10) < 0.001

< 50 Reference      

50–59 3.21 (1.82-5.66) < 0.001    

60–69 4.74 (2.49-9.03) < 0.001    

70–79 16.66 (6.22-44.62) < 0.001    

Sex, male 0.98 (0.62-1.56) 0.944    

Cause of ESRD

Diabetes mellitus 1.22 (0.89-1.75) 0.451

Hypertension 0.80 (0.58-1.12) 0.672

Glomerulonephritis 0.93 (0.52-2.15) 0.591

Cystic kidney disease 1.19 (0.78-2.32) 0.854

Underlying disease        

Cardiac disease        

Coronary artery disease 5.51 (2.74-11.06) < 0.001 2.81 (1.37-5.78) 0.005

Acute myocardial infarction 1.51 (0.37-6.15) 0.566    

Cardiac arrhythmia 2.53 (1.39-4.60) 0.002 1.99 (1.09-3.64) 0.025

Cerebrovascular disease        

Cerebral hemorrhage NA      

Cerebral infarction 0.87 (0.12-6.26) 0.890    

Hemodialysis 3.00 (1.21-7.45) 0.018 2.58 (1.04-6.42) 0.041

Dialysis vintage, monthsc 0.918 (0.833-1.012) 0.086

Before steroid used 0.55 (0.17-1.74) 0.307

Infection        

CMV infection 1.26 (0.46-3.45) 0.652    

Fungal infection 0.66 (0.16-2.71) 0.569    

Epoch of transplantation, 2010–2016 0.72 (0.45-1.15) 0.168    

a Variables less than 0.05 of P-values in univariate analysis were included in the multivariate analysis.

b NA is presented if the paucity of deceased or living patients exists for each variable 1 month after kidney transplantation.

c Data were obtained from the Korean Network for Organ Sharing system.

d The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.Abbreviations: CI, confidence interval; CMV, cytomegalovirus; ESRD, end-stage renal disease; HR, hazard ratio; NA, not applicable.

Table 3. Univariate and multivariate analyses of 3-month mortality after kidney transplantation.

Variable Univariate Multivariate

HR (95% CI) P-value HR (95% CI) P-value

Age, yearsa 1.07 (1.05–1.09) < 0.001 1.08 (1.06-1.09) < 0.001

< 50        

50–59 3.05 (2.09-4.44) < 0.001    

60–69 4.24 (2.74-6.57) < 0.001    

70–79 13.16 (6.43-26.96) < 0.001    

Sex, female 1.07 (0.78-1.46) 0.690    

Cause of ESRD

Diabetes mellitus 1.25 (0.92-1.59) 0.273

Hypertension 0.86 (0.68-1.10) 0.463

Glomerulonephritis 0.91 (0.49-1.75) 0.385

Cystic kidney disease 1.23 (0.87-2.41) 0.526

Underlying disease        

Cardiac disease        

Coronary artery disease 4.82 (2.92-7.97) < 0.001 2.53 (1.49-4.31) 0.001

Acute myocardial infarction 2.48 (1.16-5.29) 0.019 1.70 (0.78-3.69) 0.183

Cardiac arrhythmia 1.99 (1.28-3.10) 0.002 1.43 (0.91-2.24) 0.117

Cerebrovascular disease        

Cerebral hemorrhage NA      

Cerebral infarction 0.80 (0.20-3.23) 0.755    

Hemodialysis 2.69 (1.49-4.85) 0.001 2.32 (1.28-4.19) 0.005

Dialysis vintage, monthsc 0.963 (0.911-1.017) 0.179

Before steroid used 0.95 (0.52-1.76) 0.882

Infection        

CMV infection 2.19 (1.51-3.16) < 0.001 1.65 (1.12-2.42) 0.012

Fungal infection 3.57 (2.47-5.15) < 0.001 2.48 (1.69-3.65) < 0.001

Epoch of transplantation, 2010–2016 0.58 (0.42-0.79) 0.001 0.43 (0.31-0.60) < 0.001

a Variables less than 0.05 of P-values in univariate analysis were included in the multivariate analysis.

b NA is presented if the paucity of deceased or living patients exists for each variable 3 months after kidney transplantation.

c Data were obtained from the Korean Network for Organ Sharing system.

d The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.

Abbreviations: CI, confidence interval; CMV, cytomegalovirus; ESRD, end-stage renal disease; HR, hazard ratio; NA, not applicable.

Donor characteristics:

Unfortunately, the donor characteristics were not provided by National Health Insurance Sharing Service. We have described this limitation in the revised Discussion section (page 18, lines 14 to 15) as follows.

“This study had several limitations. The lack of detailed clinical information, such as donor’s characteristics and laboratory data (immunologic antibody profiles, and serology for CMV and fungus), led to restrictions on the analysis of wider variables for TRM.”

Comment 2: In addition many topics need a better clarification and explanation: definition of CMD disease, prevalence of CMV serum-negativity. The cause of death classification is absolutely unreasonable, - “chronic kidney disease was the main cause of both early TRM and TRM, followed cystic kidney disease” ??????

� Response 2: We have added explanation for the definition of CMV disease to the revised Materials Methods section (page 6, lines 16 to 17) as follows.

“The ICD-10-CM codes for CMV disease were B27.1, B25.0, B25.1, B25.8, and B25.9.”

The prevalence of CMV serum-negativity could not be provided because laboratory values for CMV infection were not included in the datasets provided by National Health Insurance Sharing Service. We have described this limitation in the revised Discussion section (page 18, lines 14 to 15) as follows.

“This study had several limitations. The lack of detailed clinical information, such as donor’s characteristics and laboratory data (immunologic antibody profiles, and serology for CMV and fungus), led to restrictions on the analysis of wider variables for TRM.”

We have eliminated the contents for the cause of death throughout the revised manuscript (Abstract, Materials and Methods, Results [Table 4, and S2 Table], and Discussion sections).

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

� We have uploaded our figure files (Fig 1.tif, and Fig 2.tif) to the PACE digital diagnostic tool to meet PLOS requirements. The preview files (Preview_20200420051917202.pdf, and Preview_20200420052011519.pdf) were generated and checked.

Attachment

Submitted filename: Response to Reviewers.doc

Decision Letter 1

Robert Jeenchen Chen

25 May 2020

PONE-D-20-03919R1

The risk factors associated with treatment-related mortality in 16,073 kidney transplantation - A nationwide cohort study

PLOS ONE

Dear Dr. Jeong,

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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We look forward to receiving your revised manuscript.

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Academic Editor

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

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Reviewer #2: Yes

**********

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Reviewer #2: Yes

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Reviewer #2: No

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Reviewer #1: I thank the authors to have addressed all my recommendations. At the moment the paper is suitable for publication.

Reviewer #2: Treatment-related mortality (TRM) after renal transplantation is a concept different from disease-related mortality and appeared to be a very prevalent entity.

This article would be a valuable contribution to the medical literature to encourage further discussion on this entity.

The writing is clear and easily understandable.

The Authors have worked hard to improve this article, and they have met all criticisms raised by referees

Strengths:

- There are scarce data in scientific literature about TRM within 1 or 3 months after kidney transplantation.

- Authors collected an important amount of data from a very large cohort of patients using a national population based database, which included information about a total of 16,073 kidney recipients.

Specific comments:

- Abstract. Authors should clearly explain the following sentence: “Based on a multivariate analysis, older age (hazard ratio [HR] = 1.07; P < 0.001), coronary artery disease (HR = 2.81; P = 0.005), and hemodialysis (HR = 2.58; P = 0.041) were the risk factors for early TRM.” What do you mean with hemodialysis as a risk factor for early TRM? Patients who underwent to hemodialysis immediately after renal transplant for a DGF, o hemodialysis compared with peritoneal dialysis or pre-emptive renal transplant? This is not clear.

- Introduction, page 4, line 16. Supporting references at the end of the following sentence are needed: “however, studies about 1- or 3-month mortality were extremely limited.”

- Introduction, page 5, line 2. Authors should clearly explain the following sentence: “… to investigate the risk factors and causes of TRM after kidney transplantation focusing on vascular diseases.” Are Authors focused on vascular diseases in this analysis?

- Methods. Authors collected data of the post-transplant administration of antiviral agent, but there is no mention to induction (basiliximab vs thymoglobuline) immunosuppressive therapy, that is supposed to strongly impact on treatment related mortality. This is an important point that Authors should add into the analysis. Otherwise this will represent an important limitation.

- Results. A sub-analysis might be performed distinguishing TRM analysis between transplantation cases performed in different epoch (2003-2009 vs 2010-2016). This might be interesting even if this factor did not reach statistical significance at univariate analysis. In fact, “Epoch of transplantation 2010–2016” showed a trend towards statistical significance.

- Results. In the following sentence, Authors should specify the number of recipients who died among the total number of recipients for each type of transplantation, and only after the percentage value in parentheses: “The rates of recipients who died 1 month (1.2% for living, 2.4% for deceased, and

3.3% for non-heart beating) and 3 months (3.2% for living, 5.5% for deceased, and

3.3% for non-heart beating) after transplantation showed significant difference

according to the donor state (P < 0.001).”

**********

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2020 Jul 28;15(7):e0236274. doi: 10.1371/journal.pone.0236274.r004

Author response to Decision Letter 1


23 Jun 2020

Response to the reviewer’s comments

Response to reviewer #1’s comments

1. I thank the authors to have addressed all my recommendations. At the moment the paper is suitable for publication.

� We thank the reviewer for the constructive review of our manuscript.

Response to reviewer #2’s comments

Treatment-related mortality (TRM) after renal transplantation is a concept different from disease-related mortality and appeared to be a very prevalent entity.

This article would be a valuable contribution to the medical literature to encourage further discussion on this entity.

The writing is clear and easily understandable.

The Authors have worked hard to improve this article, and they have met all criticisms raised by referees

Strengths:

- There are scarce data in scientific literature about TRM within 1 or 3 months after kidney transplantation.

- Authors collected an important amount of data from a very large cohort of patients using a national population based database, which included information about a total of 16,073 kidney recipients.

Specific comments:

1. Abstract. Authors should clearly explain the following sentence: “Based on a multivariate analysis, older age (hazard ratio [HR] = 1.07; P < 0.001), coronary artery disease (HR = 2.81; P = 0.005), and hemodialysis (HR = 2.58; P = 0.041) were the risk factors for early TRM.” What do you mean with hemodialysis as a risk factor for early TRM? Patients who underwent to hemodialysis immediately after renal transplant for a DGF, o hemodialysis compared with peritoneal dialysis or pre-emptive renal transplant? This is not clear.

� We have provided detailed description of hemodialysis in the revised Abstract section as follows for clarification. In addition, we have also inserted this description into the revised Results section as follows.

Abstract section (page 3, lines 8 to 11)

“Based on a multivariate analysis, older age (hazard ratio [HR] = 1.06; P < 0.001), coronary artery disease (HR = 3.02; P = 0.002), and hemodialysis compared with pre-emptive kidney transplantation (HR = 2.53; P = 0.046) were the risk factors for early TRM.”

Results section (page 11, lines 22 to page 12, lines 2)

“Based on the Cox multivariate analysis, older age (hazard ratio [HR] = 1.06; P < 0.001), CAD (HR = 3.02; P = 0.002), cardiac arrhythmia (HR = 1.98; P = 0.027), and hemodialysis compared to pre-emptive kidney transplant (HR = 2.53; P = 0.046) were independently associated with early TRM.”

2. Introduction, page 4, line 16. Supporting references at the end of the following sentence are needed: “however, studies about 1- or 3-month mortality were extremely limited.”

� To the best of our knowledge, mortality after kidney transplantation within 1- or 3- months has been seldom reported. There was one report comparing mortality risk between deceased-donor kidney allograft recipients and wait-listed transplant candidates from time of listing published in 1993. Relative risk of mortality within the first 30 days, days 31-365 and more than 365-days post transplantation were 2.43, 0.96 and 0.36, respectively. Another report recently published was dealt with 30-day mortality and compared mostly the ethnic difference of England, and New York State. We have cited these two articles at the end of the sentence in the revised Introduction section as follows. These articles have been presented in the revised Reference section as follows.

Introducton section (page 4, lines 15 to 17)

“Most reports have shown the results of kidney transplantation after 1 [18], 5 [16], and greater than 10 years [19]; however, studies about 1- or 3-month mortality were extremely limited [20,21].”

Reference section (page 23, lines 20 to page 24, lines 1)

“20. Port FK, Wolfe RA, Mauger EA, Berling DP, Jiang K. Comparison of survival probabilities for dialysis patients vs cadaveric renal transplant recipients. JAMA. 1993;270: 1339-1343.

21. Tahir S, Gillott H, Jackson-Spence F, Nath J, Mytton J, Evison F, et al. Do outcomes after kidney transplantation differ for black patients in England versus New York State? A comparative, population-cohort analysis. BMJ Open. 2017;7: e014069.”

3. Introduction, page 5, line 2. Authors should clearly explain the following sentence: “… to investigate the risk factors and causes of TRM after kidney transplantation focusing on vascular diseases.” Are Authors focused on vascular diseases in this analysis?

� As indicated by the reviewer, various risk factors related to treatment-related mortality (TRM) were identified in our manuscript. Therefore, we have eliminated “focusing on vascular diseases” in the revised Introduction section (page 5, lines 1 to 2) as follows.

“Using this database, we performed a comprehensive population-based analysis to investigate the risk factors and causes of TRM after kidney transplantation.”

4. Methods. Authors collected data of the post-transplant administration of antiviral agent, but there is no mention to induction (basiliximab vs thymoglobuline) immunosuppressive therapy, that is supposed to strongly impact on treatment related mortality. This is an important point that Authors should add into the analysis. Otherwise this will represent an important limitation.

� As suggested by the reviewer, we have extracted the information about induction regimens and provided the results, and discussion in the revised manuscript. Because the recipients receiving anti-thymocyte globulin were significantly associated with 1- and 3-month mortalities in the multivariate analyses, the results of other variables such as age, coronary artery disease, cardiac arrhythmia, and hemodialysis in the early TRM, and age, coronary artery disease, acute myocardial infarction, cardiac arrhythmia, hemodialysis, and cytomegalovirus and fungal infections in TRM were also revised throughout the manuscript. In particular, the contents for CMV infection related to TRM including Fig 2B were eliminated because the P value was changed from 0.012 to 0.106 in the revised manuscript.

Abstract section (page 3, lines 8 to 15)

“Based on a multivariate analysis, older age (hazard ratio [HR] = 1.06; P < 0.001), coronary artery disease (HR = 3.02; P = 0.002), and hemodialysis compared with pre-emptive kidney transplantation (HR = 2.53; P = 0.046) were the risk factors for early TRM. Older age (HR = 1.07; P < 0.001), coronary artery disease (HR = 2.88; P < 0.001), and hemodialysis (HR = 2.35; P = 0.004) were the common independent risk factors for TRM. In contrast, cardiac arrhythmia (HR = 1.98; P = 0.027) was associated only with early TRM, and fungal infection (HR = 2.61; P < 0.001), and epoch of transplantation (HR = 0.34; P < 0.001) were the factors associated with only TRM.”

Materials and Methods section (page 6, line 15)

“The induction regimens such as basiliximab, and anti-thymocyte globulin were also extracted.”

Results section (page 8, lines 16 to 17)

“Regarding to induction therapy, basiliximab, and anti-thymocyte globulin were administered to 79.0%, and 11.4% of recipients, respectively.”

Results section (page 11, lines 16 to 18)

“Patients with anti-thymocyte globulin showed significant relation to TRM (P < 0.001), whereas those with basiliximab did not.”

Results section (page 11, lines 22 to page 12, lines 5)

“The risk factors of early TRM and TRM are shown in Tables 2 and 3, respectively. Based on the Cox multivariate analysis, older age (hazard ratio [HR] = 1.06; P < 0.001), CAD (HR = 3.02; P = 0.002), cardiac arrhythmia (HR = 1.98; P = 0.027), and hemodialysis compared to pre-emptive kidney transplant (HR = 2.53; P = 0.046) were independently associated with early TRM. Moreover, older age (HR = 1.07; P < 0.001), CAD (HR = 2.88, P = < 0.001), and hemodialysis (HR = 2.35, P = 0.004) were consistently independent risk factors of TRM at any time. However, fungal infection, (HR = 2.61; P < 0.001), and the epoch of transplantation (HR = 0.34 for 2010–2016; P < 0.001) were correlated to TRM only.”

Results section (page 15, lines 10 to 11)

“Fungal infection (Fig 2B) affected TRM (after early TRM). The protective effect of transplantation in 2010–2016 is illustrated in Fig 2C.”

Discussion section (page 17, lines 8 to 19)

“The use of anti-thymocyte globulin has been greater in high-risk recipients such as highly sensitized patients, recipients from deceased donors, re-transplantations, and ABO incompatible transplants [36]. According to a prospective, randomized study, patients receiving anti-thymocyte globulin presented a greater incidence of infection (85.8%) compared to those with basiliximab (75.2%) at 12 months after transplantation [37]. However, there was no significant difference in patient survival, similar to the results of a recent study using a network meta-analysis [38]. In Korea, the one-year patient survival in the anti-thymocyte globulin group (89.4%) was compared to the basiliximab group (93.8%), and presented no significant difference [39]. Based on our data, the high-risk recipients receiving anti-thymocyte globulin were significantly associated with early mortality. Further studies for the premature mortality are necessary to validate our results, and intensive care for the high-risk patients receiving anti-thymocyte globulin is important for improving outcomes.”

Figure (page 15, lines 18 to 23)

Fig 2. Cumulative incidence of mortality according to the factors associated 1- or 3-month mortality after kidney transplantation.

(A) Cardiac arrhythmia was related to a worse outcome 1 month after transplantation. (B) Fungal infection were a risk factor of 3-month mortality after transplantation. (C) Recent epoch of transplantation (2010–2016) was a protective factor of 3-month mortality compared to the treatment-related mortality of previous epoch (2003–2009).

Table 1. Comparison of the characteristics between living kidney recipients versus deceased ones at 1 and 3 months after transplantation.

Characteristicsa Early TRM TRM

Living at 1 month Death by 1 month P-valueb Living at 3 months Death by 3 months P-valueb

Number (%) 15,999 74   15,913 160  

Age, years 47 (37-55) 56 (48.8-61) < 0.001 47 (37-55) 55.5 (48-61) < 0.001

< 50 9,188 (57.4) 19 (25.7) < 0.001 9,163 (57.6) 44 (27.5) < 0.001

50–59 4,830 (30.2) 32 (43.2)   4,792 (30.1) 70 (43.8)  

60–69 1,838 (11.5) 18 (24.3)   1,819 (11.4) 37 (23.1)  

70–79 143 (0.9) 5 (6.8)   139 (0.9) 9 (5.6)  

Sex, male 9,451 (59.1) 44 (59.5) 0.946 9,403 (59.1) 92 (57.5) 0.684

Cause of ESRD

Diabetes mellitus 3,501 (21.9) 19 (25.7) 0.431 3,479 (21.9) 41 (25.6) 0.252

Hypertension 2,001 (12.5) 8 (10.8) 0.660 1,992 (12.5) 17 (10.6) 0.471

Glomerulonephritis 2,850 (17.8) 11 (14.9) 0.508 2,840 (17.8) 21 (13.1) 0.120

Cystic kidney disease 368 (2.3) 2 (2.7) 0.818 365 (2.3) 5 (3.1) 0.485

Underlying diseasec            

Cardiac disease            

Coronary artery disease 392 (2.5) 9 (12.2) < 0.001 384 (2.4) 17 (10.6) < 0.001

Acute myocardial infarction 288 (1.8) 2 (2.7) 0.561 283 (1.8) 7 (4.4) 0.014

Cardiac arrhythmia 1,240 (7.8) 13 (17.6) 0.002 1,230 (7.7) 23 (14.4) 0.002

Cerebrovascular disease            

Cerebral hemorrhage 54 (0.3) 0 (0.0) 0.617 54 (0.3) 0 (0.0) 0.460

Cerebral infarction 247 (1.5) 1 (1.4) 0.893 246 (1.5) 2 (1.3) 0.763

Hemodialysis 13,134 (82.1) 69 (93.2) 0.012 13,055 (82.0) 148 (92.5) 0.001

Dialysis vintage, monthsd 42.5 (29.5-62.8) 16.0 (9.5-24.5) 0.051 41.0 (29.0-63.5) 24.5 (12.8-39.0) 0.179

Before steroid usee 1,148 (7.2) 3 (4.1) 0.416 1,140 (7.2) 11 (6.9) 1.000

Induction therapy

Basiliximab 12,637 (79.0) 55 (74.3) 0.402 12,569 (79.0) 123 (76.9) 0.579

Anti-thymocyte globulin 1,818 (11.4) 22 (29.7) < 0.001 1,799 (11.3) 41 (25.6) < 0.001

Infection            

CMV infection 694 (4.3) 4 (5.4) 0.653 1,900 (11.9) 37 (23.1) < 0.001

Fungal infection 639 (4.0) 2 (2.7) 0.571 1,205 (7.6) 37 (23.1) < 0.001

Epoch of transplantation            

2003–2009 4,634 (29.0) 27 (36.5) 0.155 4,594 (28.9) 67 (41.9) < 0.001

2010–2016 11,365 (71.0) 47 (63.5)   11,319 (71.1) 93 (58.1)  

a Data were expressed as number (%) or median (interquartile range).

b P value was calculated using chi-square test or Mann–Whitney U test.

c In case of the presence of underlying diseases, multiple diseases were designated to one patient.

d Data were obtained from the Korean Network for Organ Sharing system.

e The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.

Abbreviations: CMV, cytomegalovirus; ESRD, end-stage renal disease; TRM, treatment-related mortality.

Table 2. Univariate and multivariate analyses of 1-month mortality after kidney transplantation.

Variable Univariate Multivariate

HR (95% CI) P-value HR (95% CI) P-value

Age, yearsa 1.07 (1.05–1.10) < 0.001 1.06 (1.04-1.09) < 0.001

< 50 Reference      

50–59 3.21 (1.82-5.66) < 0.001    

60–69 4.74 (2.49-9.03) < 0.001    

70–79 16.66 (6.22-44.62) < 0.001    

Sex, male 0.98 (0.62-1.56) 0.944    

Cause of ESRD

Diabetes mellitus 1.22 (0.89-1.75) 0.451

Hypertension 0.80 (0.58-1.12) 0.672

Glomerulonephritis 0.93 (0.52-2.15) 0.591

Cystic kidney disease 1.19 (0.78-2.32) 0.854

Underlying disease        

Cardiac disease        

Coronary artery disease 5.51 (2.74-11.06) < 0.001 3.02 (1.48-6.17) 0.002

Acute myocardial infarction 1.51 (0.37-6.15) 0.566    

Cardiac arrhythmia 2.53 (1.39-4.60) 0.002 1.98 (1.08-3.62) 0.027

Cerebrovascular disease        

Cerebral hemorrhage NA      

Cerebral infarction 0.87 (0.12-6.26) 0.890    

Hemodialysis 3.00 (1.21-7.45) 0.018 2.53 (1.02-6.28) 0.046

Dialysis vintage, monthsc 0.918 (0.833-1.012) 0.086

Before steroid used 0.55 (0.17-1.74) 0.307

Induction therapy

Basiliximab 0.77 (0.46-1.30) 0.326

Anti-thymocyte globulin 3.31 (2.01-5.45) < 0.001 2.62 (1.59-4.32) < 0.001

Infection        

CMV infection 1.26 (0.46-3.45) 0.652    

Fungal infection 0.66 (0.16-2.71) 0.569    

Epoch of transplantation, 2010–2016 0.72 (0.45-1.15) 0.168    

a Variables less than 0.05 of P-values in univariate analysis were included in the multivariate analysis.

b NA is presented if the paucity of deceased or living patients exists for each variable 1 month after kidney transplantation.

c Data were obtained from the Korean Network for Organ Sharing system.

d The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.

Abbreviations: CI, confidence interval; CMV, cytomegalovirus; ESRD, end-stage renal disease; HR, hazard ratio; NA, not applicable.

Table 3. Univariate and multivariate analyses of 3-month mortality after kidney transplantation.

Variable Univariate Multivariate

HR (95% CI) P-value HR (95% CI) P-value

Age, yearsa 1.07 (1.05–1.09) < 0.001 1.07 (1.05-1.09) < 0.001

< 50        

50–59 3.05 (2.09-4.44) < 0.001    

60–69 4.24 (2.74-6.57) < 0.001    

70–79 13.16 (6.43-26.96) < 0.001    

Sex, female 1.07 (0.78-1.46) 0.690    

Cause of ESRD

Diabetes mellitus 1.25 (0.92-1.59) 0.273

Hypertension 0.86 (0.68-1.10) 0.463

Glomerulonephritis 0.91 (0.49-1.75) 0.385

Cystic kidney disease 1.23 (0.87-2.41) 0.526

Underlying disease        

Cardiac disease        

Coronary artery disease 4.82 (2.92-7.97) < 0.001 2.88 (1.71-4.84) < 0.001

Acute myocardial infarction 2.48 (1.16-5.29) 0.019 1.75 (0.81-3.80) 0.157

Cardiac arrhythmia 1.99 (1.28-3.10) 0.002 1.40 (0.89-2.18) 0.145

Cerebrovascular disease        

Cerebral hemorrhage NA      

Cerebral infarction 0.80 (0.20-3.23) 0.755    

Hemodialysis 2.69 (1.49-4.85) 0.001 2.35 (1.30-4.25) 0.004

Dialysis vintage, monthsc 0.963 (0.911-1.017) 0.179

Before steroid used 0.95 (0.52-1.76) 0.882

Induction therapy

Basiliximab 0.88 (0.61-1.28) 0.514

Anti-thymocyte globulin 2.73 (1.92-3.90) < 0.001 2.38 (1.62-3.49) < 0.001

Infection        

CMV infection 2.19 (1.51-3.16) < 0.001 1.39 (0.93-2.08) 0.106

Fungal infection 3.57 (2.47-5.15) < 0.001 2.61 (1.79-3.82) < 0.001

Epoch of transplantation, 2010–2016 0.58 (0.42-0.79) 0.001 0.34 (0.24-0.48) < 0.001

a Variables less than 0.05 of P-values in univariate analysis were included in the multivariate analysis.

b NA is presented if the paucity of deceased or living patients exists for each variable 3 months after kidney transplantation.

c Data were obtained from the Korean Network for Organ Sharing system.

d The use of intravenous steroids such as dexamethasone, and prednisolone within 6 months before transplantation.

Abbreviations: CI, confidence interval; CMV, cytomegalovirus; ESRD, end-stage renal disease; HR, hazard ratio; NA, not applicable.

5. Results. A sub-analysis might be performed distinguishing TRM analysis between transplantation cases performed in different epoch (2003-2009 vs 2010-2016). This might be interesting even if this factor did not reach statistical significance at univariate analysis. In fact, “Epoch of transplantation 2010–2016” showed a trend towards statistical significance.

� We have conducted the sub-analysis for the two epoch of transplantation and added the results to the revised Results and Discussion sections as follows.

Results section (page 12, lines 6 to 10)

“Regarding to the epoch of transplantation, the aged between 50 and 59 years (HR = 0.37, P = 0.005 for early TRM; HR = 0.37, P < 0.001 for TRM), the patients receiving basiliximab as induction therapy (HR = 0.44, P = 0.002 for early TRM; HR = 0.40, P < 0.001 for TRM), and recipients with CMV infection (HR = 0.13, P = 0.040 for early TRM; HR = 0.39, P = 0.005 for TRM) presented better outcome in 2010-2016, when compared to 2003-2009.”

Discussion section (page 18, lines 22 to page 19, lines 4)

“In particular, relatively low- or intermediate-risk patients such as aged 50 to 59 years, and patients receiving basiliximab were influence by the improved protocols, and showed better outcome than high-risk recipients (aged over 60 years, and recipients with anti-thymocyte globulin). Further, more aggressive and sophisticated infection controls on CMV such as monitoring quantitative levels, and high dose of antiviral therapy [47] may protect more recipients in 2010-2016 than those in 2003-2009.”

6. Results. In the following sentence, Authors should specify the number of recipients who died among the total number of recipients for each type of transplantation, and only after the percentage value in parentheses: “The rates of recipients who died 1 month (1.2% for living, 2.4% for deceased, and

3.3% for non-heart beating) and 3 months (3.2% for living, 5.5% for deceased, and 3.3% for non-heart beating) after transplantation showed significant difference according to the donor state (P < 0.001).”

� We have applied these results to our cohort and presented the number of recipients in the revised Results section (page 11, lines 9 to 12) as follows. The calculation errors were also corrected.

“The rates of recipients who died 1 month (n = 1, 1.4% for living; n= 2, 2.7% for deceased; and n = 2, 2.7% for non-heart beating) and 3 months (n = 5, 3.1% for living; n = 9, 5.6% for deceased; and n = 5, 3.1% for non-heart beating) after transplantation showed significant difference according to the donor state (P < 0.001).”

Response to the editor’s comment

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Decision Letter 2

Robert Jeenchen Chen

6 Jul 2020

The risk factors associated with treatment-related mortality in 16,073 kidney transplantation - A nationwide cohort study

PONE-D-20-03919R2

Dear Dr. Jeong,

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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Academic Editor

PLOS ONE

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Reviewer #2: All comments have been addressed

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #2: Yes

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

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Reviewer #2: Yes

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Reviewer #1: I thank the authors to have addressed all my recommendations. At the moment the

paper is suitable for publication

Reviewer #2: Treatment-related mortality (TRM) after renal transplantation is a concept different from disease-related mortality and appeared to be a very prevalent entity.

Strengths:

- There are scarce data in scientific literature about TRM within 1 or 3 months after kidney transplantation.

- Authors collected an important amount of data from a very large cohort of patients using a national population based database, which included information about a total of 16,073 kidney recipients.

This article would be a valuable contribution to the medical literature to encourage further discussion on this entity.

The writing is clear and easily understandable.

The Authors have worked hard to improve this article, and they have met all criticisms raised by referees.

I feel the manuscript is now suitable for publication in Plos One.

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Reviewer #1: No

Reviewer #2: No

Acceptance letter

Robert Jeenchen Chen

9 Jul 2020

PONE-D-20-03919R2

The risk factors associated with treatment-related mortality in 16,073 kidney transplantation - A nationwide cohort study

Dear Dr. Jeong:

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.

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

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Kind regards,

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on behalf of

Dr. Robert Jeenchen Chen

Academic Editor

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Associated Data

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

    Supplementary Materials

    S1 Table. Data set of recipients with TRM after kidney transplantation.

    (XLSX)

    Attachment

    Submitted filename: Response to Reviewers.doc

    Attachment

    Submitted filename: Response to Reviewers.doc

    Data Availability Statement

    The repository data for public release is not available because of the personally identifiable information. The full dataset includes clinic centers in which they attend, insurance conditions. Therefore, concerning privacy risks, the data is managed by authorized executive supervisor. If one researcher asks to access data, the person in charge releases data with blind identification for the discrete requirements and the data should be analyzed only in permitted rooms in centers of National Health Insurance Service. Subsets of data limited to anonymisable information obtained and analyzed during this study are included in this article (tables, figures, and supporting information). Contact information for a data access committee is listed as follows: National Health Insurance Sharing Service, Tel: 82-33-736-2432; Official internet site: https://nhiss.nhis.or.kr/bd/ay/bdaya001iv.do. Other researchers can access these data in the same manner as the authors and the authors did not have any special access privileges.


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