Neutrophil gelatinase-associated lipocalin partly reflects the dynamic changes of renal function among chronic hepatitis C patients receiving direct-acting antivirals.

BACKGROUND: Changes in renal function in chronic hepatitis C (CHC) patients receiving direct-acting antivirals (DAAs) are controversial. The evolution of neutrophil gelatinase-associated lipocalin (NGAL) in these patients remains unclear.
METHODS: A total of 232 CHC patients receiving DAA at Dalin Tzu Chi Hospital from May 2016 to February 2019, were enrolled in this retrospective study. Grade 2/3 renal function deterioration, defined as a decrease in eGFR between 10% and 50% from baseline (BL) to 12 weeks after the end of treatment (P12), was investigated for its association with BL characteristics. The changes in renal function and NGAL levels were also analyzed at the SOF-base or nonSOF-base DAA.
RESULTS: Sixty-two patients (26.7%) had grade 2/3 renal function deterioration at P12 after DAA therapy. Univariate analysis showed that it was associated with age (P = 0.038). Multivariate analysis indicated that age (OR = 1.033, 95% CI: 1.004-1.064, P = 0.027), sex (male; OR = 2.039, 95% CI: 1.093-3.804, P = 0.025), ACEI/ARB use (OR = 2.493, 95% CI: 1.016-6.119, P = 0.046), and BL NGAL (OR = 1.033, 95% CI: 1.001-1.067, P = 0.046) positively correlated with grade 2/3 renal function deterioration. Furthermore, eGFR was decreased (P = 0.009) and NGAL was increased (P = 0.004) from BL to P12 in CHC patients receiving SOF-based DAA.
CONCLUSIONS: Of the CHC patients receiving DAA therapy, 26.7% had grade 2/3 renal function deterioration at P12, and it was associated with older age, gender being male, ACEI/ARB use, and higher BL NGAL levels. In addition, NGAL might be a biomarker of nephrotoxicity at P12 in patients receiving SOF-based DAA.

1. Introduction

Chronic hepatitis C virus (HCV) infection may result in chronic kidney disease (CKD) and end-stage renal disease (ESRD) [1]. Currently, interferon-free direct-acting antivirals (DAAs) are the standard therapy for chronic hepatitis C (CHC) [2-4] and can improve some HCV-related extrahepatic outcomes [1]. However, the short-term effect of DAA on renal function is inconclusive [5,6]. Several studies have reported that the estimated glomerular filtration rate (eGFR) might be reduced during DAA therapy, especially sofosbuvir (SOF) -based regimens [7-13]. However, some studies have revealed that the eGFR change might be nonsignificant [10,11,13-16]. The metabolite of SOF is mainly cleared from the body via the kidney, but other kinds of DAAs are primarily metabolized and cleared by the liver [1], SOF-based DAA could be nephrotoxic.

The biomarker neutrophil gelatinase-associated lipocalin (NGAL) is a protein involved in complex biological activities such as bacteriostatic effects, cell proliferation and differentiation, and cellular apoptosis. The levels would markedly increase if renal tubular injury occurred [17]. NGAL has been found to be a useful tool to detect acute kidney injury (AKI) earlier than the traditional method estimated by creatinine in patients with drug-induced nephrotoxicity or those undergoing cardiac surgery and liver transplantation. It is also a predictor of delayed graft function after kidney transplantation [17-19]. In addition, the performance of urine or plasma/serum NGAL levels was comparable [19]. However, there is a paucity of studies investigating the relationship between renal function and NGAL in CHC patients treated with DAA, and the results are conflicting [20-22]. Strazzulla et al reported that NGAL levels increased at week 12 after DAA therapy, but the earlier generation of DAAs such as telaprevir was included in that study [20]. Regarding the relationship between NGAL and SOF-based DAA, some results are conflicting. Strazzulla et al. reported that NGAL levels would increase at the end of treatment (EOT) of DAA and at 12 weeks after EOT (P12) when compared with baseline (BL); however, Ali Nada et al. stated that NGAL would be decreased at EOT when compared with BL [21,22]. Furthermore, the relationship between nonSOF-based DAA, renal function, and NGAL is unknown; therefore, we conducted this study to investigate the changes in eGFR and the role of NGAL in CHC patients receiving DAA, including nonSOF- and SOF-based regimens.

2. Patients and methods

2.1 Patient selection

CHC patients who underwent DAA treatment between May 2016 and February 2019 from the Dalin Tzu Chi hospital were enrolled in this retrospective study. All patients were positive for anti-hepatitis C antibody for more than 6 months and had detectable serum HCV RNA at the time of enrollment. The treatment duration and regimens were based on the guidelines [3,4]. Patients with eGFR less than 30 ml/min/1.73 m2, active cancer status, hepatitis B virus co-infection, alcoholism, incomplete treatment course, incomplete medical records, died during the treatment course, missed post-treatment follow-up, or without sustained virologic response 12 (SVR12) were excluded. A total of 982 patients were screened, and 232 patients were enrolled in this study (Fig 1). The study protocol conformed to the ethical guidelines of the 1975 Declaration of Helsinki as reflected in a priori approval by the Ethics Committee of Dalin Tzu Chi Hospital (B10502022, B10704016). Written informed consent was obtained from all patients during enrollment.

Fig 1

Flowchart of patient selection.

2.2 Clinical and laboratory monitoring

According to the Division of AIDS (DAIDS) Table for Grading the Severity of Adult and Pediatric Adverse Events, grade 2 and 3 (grade 2/3) renal function deterioration were defined as a decrease of eGFR ≥ 10% but < 30% and ≥ 30% but < 50%, respectively, in our population [23]. Grade 4 renal function deterioration was defined as a ≥ 50% decrease from participant’s BL. The primary outcomes were BL factors associated with grade 2/3 and grade 4 renal function deterioration at P12 after DAA treatment. The secondary outcomes were the evolution of eGFR and NGAL in the different subgroups.

Laboratory assessments (serum aspartate aminotransferase [AST], alanine aminotransferase [ALT], albumin, total bilirubin, hemoglobin, prothrombin time) and abdominal ultrasonography were performed at the BL, EOT, and P12. HCV RNA was quantified at the BL, EOT, and P12. The eGFR calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation [24] and NGAL were both obtained at the BL, EOT, and P12. According to the BL eGFR, patients’ renal function was classified as rank 1 (eGFR: > 90 ml/min/1.73 m2), rank 2 (eGFR: 60–90 ml/min/1.73 m2), and rank 3 (eGFR: 30–60 ml/min/1.73 m2). Fibrosis-4 (FIB-4) was used as a noninvasive test for liver fibrosis [25,26]. Advanced liver fibrosis was diagnosed by an FIB-4 score higher than 3.25 [25,26] or radiologic cirrhosis [27]. Radiologic cirrhosis was defined as coarse liver echotexture with nodularity and small liver size or the presence of features of portal hypertension (e.g., splenomegaly, ascites, or varices) noted on imaging. A diagnosis of fatty liver was based on findings from abdominal ultrasound, including the features of hepatorenal echogenicity contrast, liver brightness, deep attenuation, and vessel blurring [28]. Other clinical factors, including chronic hepatitis B, hyperlipidemia, diabetes mellitus (DM), hypertension (HTN), IFN-experienced, co-medications, hepatocellular carcinoma (HCC), and alcoholism, were recorded by chart review. Alcoholism was defined as alcohol consumption of more than 40 g/day [29]. HCC was diagnosed either by biopsy or by imaging in the setting of liver cirrhosis [30].

2.3 HCV quantification and genotyping

Serum HCV RNA was quantified at the BL, EOT, and P12 using the COBAS AmpliPrep/COBAS TaqMan HCV Test, v2.0 (Roche Diagnostics, Rotkreuz, Switzerland), with a lower limit of quantification of 15 IU/mL. HCV genotyping was performed using the COBAS HCV GT (Roche Diagnostics).

2.4 Neutrophil gelatinase‐associated lipocalin (NGAL) assay

NGAL was measured in serum samples using a sandwich enzyme-linked immunosorbent assay (ELISA; FineTest, Wuhan, China), following the manufacturer’s recommendations [31]. Samples were stored at −40°C until analysis. The lower detection limit of the NGAL assay was 0.19 ng/mL. The normal range is 0.313–20 ng/mL. Quality control samples were also included in each assay.

2.5 Statistical analysis

The commercial statistical software package (SPSS for Windows, version 22) was used for all statistical analyses. Variables were expressed as frequency count, percentage of total, and mean ± standard deviation. Basic comparisons of demographics and baseline clinical features between the groups with and without grade 2/3 renal function deterioration at P12 were firstly performed by univariate analyses by logistic regressions. In addition, multivariate logistic regression analysis was performed to evaluate the factors associated with renal function deterioration after DAA treatment, including those with P value < 0.1, after univariate analysis, and comorbidities [32,33] potentially making kidneys susceptible to injury. All statistical tests were two-tailed, with P < 0.05 considered as being significant.

3. Results

3.1 Baseline characteristics of CHC patients

A total of 232 patients were included in the analysis. The BL characteristics are listed in Table 1. This cohort included 83 men (35.8%) with a mean age of 64.0±10.7 years. Most patients were infected with HCV genotype 1 (n = 154, 66.4%). Of the patients in the cohort, 76 had BL eGFR > 90 ml/min/1.73 m2 (rank 1, 32.8%), 120 had BL eGFR between 60 and 90 ml/min/1.73 m2 (rank 2, 51.7%), and 36 had BL eGFR between 30 and 60 ml/min/1.73 m2 (rank 3, 15.5%). Forty-four patients had DM (19.0%); 50 had HTN (21.6%). Twenty-five patients were angiotensin-converting enzyme inhibitor (ACEI)/angiotensin receptor blocker (ARB) users (10.8%), 11 were diuretic users (4.7%), and 34 were nonsteroidal anti-inflammatory drug (NSAID) users (14.7%). Of these, 153 patients had advanced fibrosis (65.9%) and 37 had a history of HCC (15.9%). Paritaprevir/ritonavir/ombitasvir with dasabuvir (n = 71, 30.6%), sofosbuvir/ledipasvir (n = 55, 23.7%), sofosbuvir with ribavirin (n = 45, 19.4%), elbasvir/grazoprevir (n = 31, 13.4%), Glecaprevir/ Pibrentasvir (n = 18, 7.8%) and sofosbuvir/daclatasvir (n = 12, 5.2%) were the DAAs used in our studied population.

Table 1

Baseline characteristics of chronic hepatitis C patients receiving DAA with or without grade 2/3 renal function deterioration at P12.

Variable	All patients (n = 232)	With grade 2/3 deterioration (n = 62) (26.7%)	Without grade 2/3 deterioration (n = 170) (73.3%)	P-value#
Baseline clinical characteristics
Age (years)†	64.02 ± 10.65	66.44 ± 8.49	63.14 ± 11.23	0.038
Male (%)	83 (35.8%)	28 (45.2%)	55 (32.4%)	0.073
Fatty liver	75 (32.3%)	23 (37.1%)	52 (30.6%)	0.349
Hyperlipidemia	18 (7.8%)	8 (12.9%)	10 (5.9%)	0.084
Diabetes mellitus	44 (19.0%)	14 (22.6%)	30 (17.6%)	0.397
Hypertension	50 (21.6%)	16 (25.8%)	34 (20.0%)	0.342
eGFR ranks*				0.211
rank 1	76 (32.8%)	17 (27.4%)	59 (34.7%)
rank 2	120 (51.7%)	33 (53.2%)	87 (51.2%)
rank 3	36 (15.5%)	12 (19.4%)	24 (14.1%)
Baseline characteristics of HCV and liver-related conditions
Advanced fibrosis (%)‡	153 (65.9%)	45 (72.6%)	108 (63.5%)	0.200
HCC history (%)	37 (15.9%)	14 (22.6%)	23 (13.5%)	0.099
Splenomegaly (%)	71 (30.6%)	25 (40.3%)	46 (27.1%)	0.054
Ascites (%)	5 (2.2%)	2 (3.2%)	3 (1.8%)	0.504
Baseline HCV viral load (IU/mL)†	5.99Log ± 0.97Log	5.87Log ± 1.14Log	6.04Log ± 0.91Log	0.238
HCV genotype 1 (%)	154 (66.4%)	43 (69.4%)	111 (65.3%)	0.563
Sofosbuvir-based (%)	112 (48.3%)	33 (53.2%)	79 (46.5%)	0.363
Baseline medications associated with renal function
ACEI/ARB users	25 (10.8%)	11 (17.7%)	14 (8.2%)	0.043
Diuretics users	11 (4.7%)	4 (6.5%)	7 (4.1%)	0.463
NSAID users	34 (14.7%)	7 (11.3%)	27 (15.9%)	0.384
Baseline laboratory data
Baseline NGAL (ng/ml) †	16.10 ± 9.03	18.00 ± 10.00	15.40 ± 8.58	0.055
ALT (U/L)†	86.60 ± 75.20	93.08 ± 81.93	84.24 ± 72.69	0.430
AST (U/L)†	61.70 ± 55.22	69.68 ± 67.20	58.79 ± 50.07	0.194
Albumin (g/dl) †	4.20 ± 0.37	4.14 ± 0.39	4.22 ± 0.35	0.137
Total bilirubin (mg/dl) †	0.79 ± 0.40	0.83 ± 0.39	0.77 ± 0.41	0.349
eGFR (ml/min/1.73m2)†	78.94 ± 17.82	76.43 ± 17.04	79.86 ± 18.05	0.195
Hb (gm/dL) †	13.50 ± 1.62	13.48 ± 1.53	13.51 ± 1.66	0.916
Prothrombin time (INR)†	1.03 ± 0.07	1.04 ± 0.07	1.03 ± 0.07	0.094

e-GFR, estimated glomerular filtration rate; HCC, hepatocellular carcinoma; HCV, hepatitis C virus; ACEI, angiotensin-converting enzyme inhibitor; ARB, angiotensin receptor blocker; NSAID, nonsteroidal anti-inflammatory drugs; NGAL, neutrophil gelatinase-associated lipocalin; ALT, alanine aminotransferase; AST, aspartate aminotransferase; INR, international normalized ratio.

*rank 1: > 90 ml/min/1.73 m2, rank 2: 60–90 ml/min/1.73 m2, rank 3: 30–60 ml/min/1.73 m2

†Data are expressed as mean±SD

#the P-value here was calculated by univariate logistic regression analysis

‡Advanced liver fibrosis was diagnosed by an FIB-4 ≧ 3.25 or radiologic cirrhosis. Radiologic cirrhosis was defined as coarse liver echotexture with nodularity and small liver size or the presence of features of portal hypertension (e.g., splenomegaly, ascites, or varices) noted on imaging.

3.2 Baseline factors associated with renal function deterioration

The BL characteristics of patients with and without grade 2/3 renal function deterioration are shown in Table 1. None of the patients had grade 4 renal function deterioration according to the DAIDS table. Sixty-two patients (26.7%) had grade 2/3 renal function deterioration at P12 after DAA therapy, and such deterioration was only associated with age (P = 0.028) on univariate analysis. Other factors, including hyperlipidemia, DM, HTN, different BL eGFR ranks, liver function tests, BL HCV viral load, previous HCC history, and SOF-based DAA regimens were not significantly different between the two groups. The percentage of users of commonly used medications that may affect eGFR, such as ACEI, ARB, diuretics, and NSAIDs, was not significantly different between those with or without grade 2/3 renal function deterioration on univariate analysis. In multivariate analysis, age (OR = 1.033, 95% CI: 1.004–1.064, P = 0.028), gender (male) (OR = 2.021, 95% CI: 1.083–3.771, P = 0.027), ACEI/ARB use (OR = 2.476, 95% CI: 1.009–6.075, P = 0.048), and BL NGAL (OR = 1.033, 95% CI: 1.001–1.067, P = 0.045) were positively correlated with grade 2/3 renal function deterioration (Table 2).

Table 2

Factors associated with grade 2/3 renal function deterioration in chronic hepatitis C patients receiving DAA at P12^.

	Odds Ratio (95% CI)	P
Age	1.033 (1.004–1.064)	0.027
Sex
Female	1.000	0.025
Male	2.039 (1.093–3.804)
ACEI/ARB
Non-user	1.000	0.046
User	2.493 (1.016–6.119)
BL NGAL	1.033 (1.001–1.067)	0.046

^Adjusted for age, sex, variables with P < 0.1 from Table 1: hyperlipidemia, splenomegaly, HCC history, ACEI/ARB users, BL NGAL and PT INR; factors reported to be associated with renal injury: baseline renal disease, DM, HTN, liver disease (advanced fibrosis), diuretics users, NSAID users, and SOF users.

3.3 Serial changes of eGFR and NGAL in overall patients, patients receiving nonSOF- or SOF-based DAA regimens, and different BL eGFR ranks

The serial changes in eGFR from the BL to P12 in all patients are shown in Fig 2A. The mean eGFR was 78.94±17.82 ml/min/1.73 m2 at the BL and decreased to 76.41±18.25 ml/min/1.73 m2 and 77.32±18.48 ml/min/1.73 m2 at EOT and P12, respectively (EOT vs. BL, P < 0.001; P12 vs. BL, P = 0.005). The overall NGAL at the BL, EOT and P12 (Fig 2B) were 16.10±9.03 ng/ml, 16.13±8.54 ng/ml and 16.50±8.60 ng/ml, respectively (BL vs EOT, P = 0.274; BL vs P12, P = 0.056; EOT vs P12, P = 0.159).

Fig 2

Overall eGFR and NGAL changes from the BL, EOT to P12 in CHC patients receiving DAA therapy.

a. eGFR; b. NGAL.

The eGFRs in patients receiving nonSOF-based DAA were significantly decreased from the BL to EOT (BL vs. EOT, P = 0.007). However, the eGFR did not significantly decrease from the BL to P12 (BL vs. P12, P = 0.173) (Fig 3A). The eGFRs in patients receiving SOF-based DAA were significantly decreased from the BL to EOT and from the BL to P12 (BL vs. EOT, P = 0.001; BL vs. P12, P = 0.009) (Fig 3A). The eGFR at the BL, EOT, and P12 were not significantly different between the non-SOF-based and SOF-based groups (P = 0.131, 0.141, and 0.077, respectively). For nonSOF-based DAA users, the NGAL levels at the BL, EOT, and P12 were not significantly different from each other (BL vs. EOT, P = 0.986; BL vs. P12, P = 0.937; EOT vs. P12, P = 0.428) (Fig 3B). For SOF-based DAA users, the NGAL levels at the BL, EOT, and P12 were mildly increased, with a significant difference between the BL and P12 (BL vs. EOT, P = 0.112; BL vs. P12, P = 0.004; EOT vs. P12, P = 0.236) (Fig 3B). The levels of NGAL at the BL, EOT, and P12 were all significantly different between nonSOF- and SOF-based DAA users (P = 0.011, 0.024, and 0.037, respectively) (Fig 3B). Further subgroup analysis showed predictive factors associated with grade 2/3 renal function deterioration were different between nonSOF- and SOF-based users (n = 120 and n = 112, respectively) (S1–S3 Tables). The predictive factors of nonSOF users (n = 120) were gender (OR:3.161; CI: 1.150–8.686; P = 0.026), fatty liver (OR: 4.684; CI: 1.689–12.990; P = 0.003), and hyperlipidemia (OR:9.401; CI: 2.268–38.959; P = 0.002). The BL NGAL has the trend associated with the grade 2/3 renal function deterioration (P = 0.05). The ACEI/ARB use (OR:3.276; CI: 1.008–10.647; P = 0.049) was the only predictive factor for SOF users.

Fig 3

The eGFR and NGAL changes from the BL, EOT to P12 in nonSOF-based or SOF-based DAA subgroups.

a. eGFR; b. NGAL.

As shown in Fig 4A, among patients with BL eGFR rank 1, the eGFR was significantly reduced from the BL to EOT and from the BL to P12, but not from EOT to P12 (BL vs. EOT, P < 0.001; BL vs. P12, P < 0.001; EOT vs. P12, P = 0.680). Among patients with BL eGFR rank 2, the eGFR was significantly decreased from the BL to EOT but not significantly different between BL and P12 and between EOT and P12 (BL vs. EOT, P = 0.004; BL vs. P12, P = 0.225; EOT vs. P12, P = 0.086). Among patients with BL eGFR rank 3, the eGFR was not significantly different between the two groups (BL vs. EOT, P = 0.423; BL vs. P12, P = 0.477; EOT vs. P12, P = 0.910). As shown in Fig 4B, among patients with BL eGFR rank 1, 2, or 3, the NGAL levels at the BL, EOT, and P12 were not significantly different from each other (for rank 1: BL vs. EOT, P = 0.755; BL vs. P12, P = 0.626; EOT vs. P12, P = 0.396; for rank 2: BL vs. EOT, P = 0.935; BL vs. P12, P = 0.152; EOT vs. P12, P = 0.105; for rank 3: BL vs EOT, P = 0.313; BL vs P12, P = 0.337; EOT vs. P12, P = 0.864). The levels of NGAL at the BL, EOT, and P12 were not significantly different between BL eGFR ranks 1, 2, and 3 (P = 0.831, 0.613, and 0.646, respectively).

Fig 4

The eGFR and NGAL changes from the BL, EOT to P12 in different BL eGFR ranks in CHC patients receiving DAA therapy.

a. eGFR; b. NGAL.

4. Discussion

This study showed that older patients, males, ACEI/ARB users, and those with higher BL NGAL levels were associated with grade 2/3 renal function deterioration at P12 (Table 2). Moreover, the serial changes in eGFR from both nonSOF- and SOF-based DAA users were significantly decreased from the BL to EOT, and this decrease was only persistent at P12 in SOF-based users. The serum levels of NGAL were significantly increased at P12 from the BL for SOF-based DAA users but were similar among the BL, EOT, and P12 for non-SOF-based DAA users.

The overall eGFR (Fig 2A) of DAA-treated CHC patients decreased from the BL to EOT and P12 after DAA treatment. Several studies have revealed similar phenomena [9,11,13]. However, a decreased eGFR may not reflect true renal injury. A previous study reported that the first-generation DAA, telaprevir, was found to affect creatinine transporters, and therefore, the values of eGFR [34]. Hence, the level of creatinine and eGFR would not fully show the true renal function in such circumstances. The overall levels of NGAL (Fig 2B) did not change significantly during this period when eGFR was reduced. This result could only show that it is less likely to have tubular injury, but other possibilities such as glomerular damage could not be ruled out.

Grade 2/3 renal function deterioration was observed in 26.7% of patients at P12. Multivariate analyses (Table 2) revealed that older age, gender (male), ACEI/ARB use, and higher levels of BL NGAL were independent risk factors. Older age has also been reported as a factor for renal function deterioration after short-term follow-up in patients with DAA-treated CHC patients [11,13]. Patients older than 60 years are at a highest risk of drug-induced nephrotoxicity [35]. In this study, we also showed a positive association between male sex and renal function deterioration after DAA treatment, which has not been reported in other studies. The most likely reasons could be that the definition of renal injury, the follow-up period, and the confounding factors for multivariate analysis were different in these studies. In fact, there are conflicting reports about the influence of gender on the development of AKI [35]. ACEI/ARB users may have decreased eGFR due to the adverse effects of these medications, which might be exacerbated by drug-drug interactions from DAA with ACEI/ARB. Patients with any of these risk factors, especially those who have more than one risk factor (e.g., an old male patient), should be closely monitored for changes in renal function when a nephrotoxic medication is added or the dosage is increased. To our knowledge, this is the first report to describe the positive association between BL NGAL levels and renal function deterioration at P12 during DAA therapy. The exact mechanism was unclear in our study. It is also difficult to hypothesize due to the complex activities of NGAL, which are related to antimicrobial effects, cell differentiation, acute-phase response, and renal tubular injury [36]. The role of NGAL in the early detection of drug-induced nephrotoxicity (such as cisplatin, aminoglycosides, or amphotericin B) has been investigated in animal and human studies. However, more human studies involving urine or serum NGAL levels, are necessary [18].

Since SOF might be related to renal injury via drug-induced tubulointerstitial nephritis [12], we further subdivided our population into nonSOF-based and SOF-based DAA users for comparison. As shown in Fig 3A, the eGFRs at EOT were significantly decreased in both subgroups (nonSOF-based, P = 0.007; SOF-based, P = 0.001) when compared with the BL. This eGFR decrease at P12 was still significant for SOF-based users (P = 0.009) but became nonsignificant for nonSOF-based users when compared with the BL. This phenomenon might indirectly show nephrotoxicity from sofosbuvir during treatment, and this decrease persisted up to P12. Another study also demonstrated that the SOF-related eGFR decline was more prominent during the on-treatment period, but the eGFR decline improved after the off-treatment period [12]. The study indicated that the renal toxicity of sofosbuvir may be reversible after long-term follow-up. We further found that NGAL was significantly increased at P12 (P = 0.004) when compared with the BL in SOF-based DAA users, but the levels of NGAL between the BL, EOT, and P12 showed no significant changes in nonSOF-based DAA users. Our results are similar to those of a previous study by Strazzulla et al. [21] Strazzulla et al. showed that NGAL was significantly increased at P12 when compared with the BL, but the eGFR was not. However, another study by Ali Nada et al. reported that NGAL levels decreased after SOF-based therapy at EOT [22]. These conflicting results may be due to differences in ethnicity (Taiwanese in our study; Italian and Egyptian in the other two studies, respectively), or different HCV genotypes (mainly genotype 1b in our and Strazzulla et al study, but mainly genotype 4 in Ali Nada et al study). In addition, Ali Nada et al. did not check NGAL at P12; therefore, we could not directly compare these studies. Although we found that an increase in NGAL was significant at P12 by SOF-based DAA, the values were still within the normal range (normal range is 0.313–20 ng/ml). Finally, we performed univariate and multivariate analyses again for nonSOF and SOF-based DAA users separately (S1–S3 Tables). Interestingly, the predictive factors of grade 2/3 renal function deterioration among these two subgroups were different. The possible mechanisms are unclear. Hence, further prospective studies with larger populations and different HCV genotypes are required to clarify the evolutions of renal function and NGAL during nonSOF- or SOF-based DAA therapy.

Many studies have shown that a lower BL eGFR was associated with eGFR improvement post-DAA treatment [9,11,13,14,16,37]. Therefore, we stratified patients with BL eGFR into ranks 1, 2, and 3 (Table 1) and assessed the changes in eGFR at the BL, EOT, and P12 (Fig 4A). The changes in eGFR from the BL to EOT and P12 in different BL eGFR subgroups demonstrated that eGFR would be significantly decreased at EOT and P12 in those with higher BL eGFR (rank 1) but significantly decreased only at EOT in those with BL eGFR between 60 and 90 ml/min/1.73 m2 (rank 2). These findings have also been reported in other studies [11,13]. In those studies, a better BL eGFR was associated with a reduced eGFR at P12. One study even found that DAA treatment for CHC patients would be helpful in improving eGFR decline only among those with baseline eGFR less than 60 ml/min/1.73 m2 [16]. The authors thought that some CHC patients with HCV-induced glomerular disease are more likely to have renal function improvement after HCV eradication by DAA. Another study [9] reported that more patients experienced a decrease in eGFR by >10 ml/min/1.73 m2 in those with BL eGFR > 60 ml/min/1.73 m2. Taken together, it seems that patients with a higher BL eGFR are more likely to have decreased eGFR after DAA therapy and the exact mechanism remains unclear. However, BL eGFR was not an independent predictor of renal function deterioration after multivariate analysis in our study. Moreover, NGAL was not correlated with eGFR changes in the different BL eGFR subgroups.

There are some limitations in our study. First, the choice of the DAA regimen was not randomized. Therefore, selection bias may exist. For example, some physicians would choose SOF-based DAA for patients with more advanced liver disease or a history of decompensation. However, we know that protease inhibitors containing DAAs are not suitable for decompensated cirrhosis. Therefore, randomization is not ethical. Second, we did not check other biomarkers of acute renal damage, such as cystatin C or kidney injury molecule 1, which may be helpful in combination with NGAL as NGAL is mainly a biomarker for detecting tubular damage. However, renal injury may occur in the glomeruli, proximal and distal tubules, or loops of Henle [38,39]. NGAL is also produced by immune cells and the liver [36]. Therefore, once the injury caused by DAAs is mild, or when we consider other sources of NGAL, the role of NGAL might not be prominent. Third, we did not check these patients’ urinalyses or their albuminuria levels, which is also suggestive of renal injury. Fourth, renal biopsy was not performed during or after DAA therapy. The histological findings may provide us with more information about DAA-related kidney injury and the possible underlying mechanisms. However, renal biopsy is risky, especially when only a relative minority of patients experience more than grade 2 renal function deterioration, and most deteriorations are reversible after long-term follow-up [12]. Hence, it is less meaningful to perform a renal biopsy under such circumstances. In addition, regardless of the adverse renal effect of DAA, we should closely follow up renal function in CHC patients with CKD even after HCV eradication by DAA therapy because of their fragile renal function.

5. Conclusion

A total of 26.7% of CHC patients receiving DAA therapy had a decreased eGFR of more than 10% during short-term follow-up, especially in older patients, males, ACEI/ARB users, and those with higher BL NGAL levels. In addition, NGAL might be a biomarker of nephrotoxicity at P12 in patients receiving SOF-based DAA.

Baseline characteristics of chronic hepatitis C patients receiving DAA with or without grade 2/3 renal function deterioration at P12 in nonSOF users.

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Baseline characteristics of chronic hepatitis C patients receiving DAA with or without grade 2/3 renal function deterioration at P12 in SOF users.

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Patient factors associated with grade 2/3 renal function deterioration in chronic hepatitis C patients receiving DAA at P12^ for nonSOF and SOF-based DAA users.

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1 Jun 2021

PONE-D-21-15486

Neutrophil gelatinase-associated lipocalin partly reflects the dynamic changes of renal function among chronic hepatitis C patients receiving direct-acting antivirals

PLOS ONE

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Reviewer #1: Authors proposed neutrophil gelatinase-associated lipocalin partly reflects the dynamic changes of renal function among CHC patients receiving DAA. It would give another point of view for clinical daily practice. I have several questions as below.

1. In table 1, authors showed baseline characteristics of subgroup with or without grade 2/3 renal function deterioration at P12. I was confused that the P-value here (in this table) was calculated by the Student's t-test and the Mann-Whitney U test for continuous variables/the chi-square test or Fisher's exact test for categorical data to check baseline difference between subgroups; "Or" by univariate logistic regression analysis? I suggest that authors should show another table for data of univariate logistic regression analysis for each predictive factors and then recheck multivariate logistic regression analysis.

2. In table 1, because many patients usually has abnormal liver function before treatment, FIB-4 might be influenced by hepatitis. I suggest "advanced liver fibrosis" might be replaced by "FIB-4 score higher than 3.25".

3. In table 1, HCC history means curative or inactive or stable status of HCC. Maybe authors exclude these patients to avoid some confounding effects.

4. In table 2, the odds ratio (OR) of ACEI/ARB was 2.476 (P=0.048) and the OR of BL NGAL was just 1.033 (P=0.045). ACEI/ARB had the higher weight for grade 2/3 renal function deterioration. If possible, authors could exclude patients using the medications associated with renal function (in table 1, ACEI/ARB, diuretics, NSAID) to clarify the effect of BL NGAL.

5. In Figure 3 & 4, the dynamic change of NGAL might be negatively associated with the dynamic change of eGFR from BL to P12, for patients with eGFR rank 1 and 2. This phenomenon was also found while focusing on SOF user. Therefore, these findings demonstrated the dynamic change of NGAL might reflect the dynamic changes of renal function. Maybe, authors could add the dynamic change of NGAL as one of predictive factors for analysis. As for BL NGAL, it should recheck by univariate/multivariate logistic regression analysis.

Reviewer #2: This retrospective study was aimed to investigate the changes in eGFR and the role of neutrophil gelatinase-associated lipocalin (NGAL) in CHC patients receiving DAA, including nonSOF- and SOF-based regimens. Although it is interesting, some concerns are needed to be clarified.

1. Since SOF might be related to renal injury via drug-induced tubulointerstitial nephritis, the proportion of SOF-based DAA users should be added in Table 1.

2. Factors associated with grade 2/3 renal function deterioration in CHC patients receiving DAA at P12 in nonSOF-based and SOF-based DAA users may be analyzed in another two tables, respectively. The cut -off of variables, including age, BL NGAL, should be offered in Table 2.

3. Page 16, line 3, “The levels of NGAL at the BL, EOT, and P12 were all significantly different between nonSOF- and SOF-based DAA users (P = 0.011, 0.024, and 0.037, respectively). Please add a figure.

4. Page 21, line 6, “Although we found that an increase in NGAL was significant at P12 by SOF-based DAA, the values were still within the normal range”. What is the normal range of NGAL?

5. Page 22, “Fig 4. The eGFR and NGAL changes from the BL, EOT to P12 in different BL eGFR ranks in CHC patients receiving DAA therapy. a. eGFR; b. NGAL” should be in “3. Results”.

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20 Jul 2021

Reviewer #1: Authors proposed neutrophil gelatinase-associated lipocalin partly reflects the dynamic changes of renal function among CHC patients receiving DAA. It would give another point of view for clinical daily practice. I have several questions as below.

1. In table 1, authors showed baseline characteristics of subgroup with or without grade 2/3 renal function deterioration at P12. I was confused that the P-value here (in this table) was calculated by the Student's t-test and the Mann-Whitney U test for continuous variables/the chi-square test or Fisher's exact test for categorical data to check baseline difference between subgroups; "Or" by univariate logistic regression analysis? I suggest that authors should show another table for data of univariate logistic regression analysis for each predictive factors and then recheck multivariate logistic regression analysis.

Response:

1. As we mentioned in the method, the P value in Table 1 was calculated by using the Student’s t-test and the Mann-Whitney U test for continuous variables and the chi-square test or Fisher’s exact test for categorical data, as appropriate.

2. In order to avoid the confusion about the statistical method, we decided to use the univariate logistic regression analysis according to your suggestion (Table 1, Page 11-13, Line 194-196). We also revised the method (Page 10, Line 168-171). Abstract was also revised (Page 3, Line 42-46).

3. The final multivariate logistic regession showed the same results (Table 2, Page 15, Line 224-230). The predictive factors were age, gender, ACEI/ARB use and BL NGAL.

2. In table 1, because many patients usually has abnormal liver function before treatment, FIB-4 might be influenced by hepatitis. I suggest "advanced liver fibrosis" might be replaced by "FIB-4 score higher than 3.25".

Response:

Thank you for your comment.

In this study, the advanced liver fibrosis was diagnosed by an FIB-4 score higher than 3.25 or radiologic cirrhosis. The cutoff value of 3.25 was based on the metaanlysis study and total 2,297 HCV-positive paitinets regarding the liver function were included. (Chou R, Wasson N. Blood tests to diagnose fibrosis or cirrhosis in patients with chronic hepatitis C virus infection: a systematic review. Ann Intern Med 2013;158:807–820.) The sensertivity was 55% and sepecificity was 92%. Besides, according to EASL recommendations on treatment of hepatitis C, FIB-4 is generally available, simple and inexpensive, and reliable non-invasive method to assess liver disease severity prior to therapy. [J Hepatol. 2020;73(5):1170-218]. We marked the definition of advanced liver fibrosis in footnote of the Table 1 (Page 13-14, Line 203-206).

3. In table 1, HCC history means curative or inactive or stable status of HCC. Maybe authors exclude these patients to avoid some confounding effects.

Response:

1. Thank you for your comment. We tried to exclude patients with HCC history (n=37, 16% ) and analyzed their variables. After univariate logistic regression and multivariate analyses, baseline NGAL (OR: 1.054; CI: 1.017–1.092; P= 0.004) was still predictive factor for grade 2/3 renal funtion deterioration.

2. In the logistic regression analysis, the more variables we put in our model, the greater the sample size must be. The sample size was markedly decreased after we exlcued those paitnets with HCC history (n=37, 16%) and it casues some factors become nonsignificant. Hence, we wanted to maintain original analyses and keep HCC history as one of variables.

4. In table 2, the odds ratio (OR) of ACEI/ARB was 2.476 (P=0.048) and the OR of BL NGAL was just 1.033 (P=0.045). ACEI/ARB had the higher weight for grade 2/3 renal function deterioration. If possible, authors could exclude patients using the medications associated with renal function (in table 1, ACEI/ARB, diuretics, NSAID) to clarify the effect of BL NGAL.

Response:

1. It’s another good point to remove the effect of nephrotoxic medications by excluding these variables from original analysis. After we excluded patients taking nephrotoxic agents (n= 63, 27%), multivariate analyses revealed age (OR: 1.049; CI: 1.012–1.087; P= 0.010) and gender (OR: 2.363; CI: 1.144–4.877; P= 0.020) were predictive factors for grade 2/3 renal funtion deterioration. The decrease of sample size cause the baseline NGAL become nonsignificant factor.

2. Subgroup analysis may be interesting if the study included more patient number. If the number is limited, it seems reasonable to adjust those factors in multivariate analyses. As previous reason, we thought the role of baseline NGAL may be better understood under larger sample size. Furthermore, to have these variables (ACEI/ARB, diuretics, NSAID) in our investigation may be helpful in realizing the roles of thses nephrotoxic medications in the renal function of CHC patients using DAA therapy. Thank you very much.

5. In Figure 3 & 4, the dynamic change of NGAL might be negatively associated with the dynamic change of eGFR from BL to P12, for patients with eGFR rank 1 and 2. This phenomenon was also found while focusing on SOF user. Therefore, these findings demonstrated the dynamic change of NGAL might reflect the dynamic changes of renal function. Maybe, authors could add the dynamic change of NGAL as one of predictive factors for analysis. As for BL NGAL, it should recheck by

univariate/multivariate logistic regression analysis.

Response:

Thank you for your reminder.

1. Althrough the decrease of eGFR was noted in paitnets with eGFR rank 1 and 2, the serum level of NGAL showed no significant differences from BL to P12 (Figure 4). The dynamic changes of NGAL were not negatively associated with the dynamic change of eGFR from BL to P12 for the patients with baseline rank 1 and 2 renal function. We think the values of eGFR and NGAL were not clearly demonstrated under previous versions of figure due to smaller font size. Hence, we provided newer figures in order to improve the legibility.

2. For the SOF user, the dynamic change of NGAL might be negatively associated with the dynamic change of eGFR from BL to P12 (Figure 3). But the associations between eGFR and NGAL changes were not statistically significant and they were shown in the following table.

P12-BL EOT-BL P12-EOT

eGFR (mean±SD) -2.02±10.44 -2.52±9.87 0.49±9.33

NGAL (mean±SD) 0.73±2.99 0.29±2.47 0.44±3.36

Linear correlation R = -0.144 , P =0.131 R = 0.007 , P =0.939 R = -0.052 , P =0.585

3. As to the dynamic change of NGAL as possible predictive factor, we tried to analyze the difference between NGAL (EOT) and NGAL (BL) as a variable for those with or without grade 2/3 renal function deterioration in the following table. We found the dynamic change between EOT and BL or P12 and BL would not become a significant predictive factor after univariate logistic regression analyses. Hence, it seemed that the dynamic change of NGAL plays no role in predicting the renal function change.

Variable All patients

(n = 232) With grade 2/3 deterioration

(n = 62) (26.7%) Without grade 2/3 deterioration

(n = 170) (73.3%) P-value#

Difference between NGAL (EOT) and NGAL (BL) 0.04±2.91 -0.26±2.37 0.14±3.08 0.346

Difference between NGAL (P12) and NGAL (BL) 0.39±3.41 0.29±3.74 0.43±3.29 0.772

Reviewer #2: This retrospective study was aimed to investigate the changes in eGFR and the role of neutrophil gelatinase-associated lipocalin (NGAL) in CHC patients receiving DAA, including nonSOF- and SOF-based regimens. Although it is interesting, some concerns are needed to be clarified.

1. Since SOF might be related to renal injury via drug-induced tubulointerstitial nephritis, the proportion of SOF-based DAA users should be added in Table 1.

Response:

The proportion of nonSOF-based and SOF-based users were shown in table 1 (Page 12, table 1, the variable “Sofosbuvir-based”). There was a total of 112 (48.3%) SOF users. Of these patients, 33 (53.2%) were in grade 2/3 renal function deterioration group and 79 (46.5%) were in the group without grade 2/3 deterioration (P=0.363). Thank you very much.

2. Factors associated with grade 2/3 renal function deterioration in CHC patients receiving DAA at P12 in nonSOF-based and SOF-based DAA users may be analyzed in another two tables, respectively. The cut -off of variables, including age, BL NGAL, should be offered in Table 2.

Response:

1. Factors associated with grade 2/3 renal function deterioration were different in nonSOF and SOF-based users. Therefore, we showed the new tables in supplement materials to demonstrate the difference between nonSOF (n= 120) and SOF-based (n=112) DAA users. The predictive factors of nonSOF users (n= 120) were gender (OR:3.161; CI: 1.150–8.686; P=0.026), fatty liver (OR: 4.684; CI: 1.689–12.990; P=0.003), and hyperlipidemia (OR:9.401; CI:1.106-7.333; P=0.002). The basline NGAL has the trend associated with the grade 2/3 renal function deterioration (P=0.05). The ACEI/ARB users (OR:3.276; CI: 1.008–10.647;P=0.049) was the only predective factor for SOF users (n=112). The possible mechanisms to explain different predictive factors of grade 2/3 renal function deterioration in nonSOF and SOF DAA users are unclear and require further study to clarify it. We added this in the our result (Page 16-17, Line 257-265) and discussion (Page 21-22, Line 356-360). These tables are displayed as supplementary materials.

2. We analyzed age and BL NGAL as continuous variables in the multivariate logistic regession. Therefore, we don’t show the cut-off values in table 2.

Supplement table 1. Baseline characteristics of chronic hepatitis C patients receiving DAA with or without grade 2/3 renal function deterioration at P12 in nonSOF users.

Variable All patients

(n = 120) With grade 2/3 deterioration

(n = 29) (26.7%) Without grade 2/3 deterioration

(n = 91) (73.3%) P value

Baseline clinical characteristics

Age (years)† 64.06 ± 10.22 67.15 ± 6.30 63.10 ± 11.03 0.043

Male (%) 41 (34.2%) 14 (48.3%) 27 (29.7%) 0.076

Fatty liver 38 (31.7%) 15 (51.7%) 23 (25.3%) 0.011

Hyperlipidemia 12 (10.0%) 7 (24.1%) 5 (5.5%) 0.008

Diabetes mellitus 26 (21.7%) 9 (31.0%) 17 (18.7%) 0.196

Hypertension 26 (21.7%) 9 (31.0%) 17 (18.7%) 0.196

eGFR ranks* 0.428

rank 1 38 (31.7%) 7 (24.1%) 31 (34.1%)

rank 2 70 (58.3%) 19 (65.5%) 51 (56.0%)

rank 3 12 (10.0%) 3 (10.3%) 9 (9.9%)

Baseline characteristics of HCV and liver-related conditions

Advanced fibrosis (%) 70 (58.3%) 19 (65.5%) 51 (56.0%) 0.396

HCC history (%) 20 (16.7%) 6 (20.7%) 14 (15.4%) 0.569

Splenomegaly (%) 37 (30.8%) 13 (44.8%) 24 (26.4%) 0.069

Ascites (%) 1 (0.8%) 0 (0.0%) 1 (1.1 %) 1.000

Baseline HCV viral load (IU/mL)† 6.10Log ± 0.86Log 5.86Log ± 1.20Log 6.17Log ± 0.71Log 0.512

HCV genotype 1 (%) 110 (91.7%) 26 (89.7%) 84 (92.3%) 0.703

Baseline medications associated with renal function

ACEI/ARB users 12 (10.0%) 4 (13.8%) 8 (8.8%) 0.481

Diuretics users 2 (1.7%) 0 (0.0%) 2 (2.2%) 1.000

NSAID users 21 (17.5%) 5 (17.2%) 16 (17.6%) 1.000

Baseline laboratory data

Baseline NGAL (ng/ml) † 17.55 ± 9.55 20.59 ± 10.32 16.58 ± 9.14 0.042

ALT(U/L)† 83.63 ± 72.30 99.21 ± 99.57 78.66 ± 61.02 0.498

AST(U/L)† 60.55 ± 62.40 73.79 ± 86.03 56.33 ± 52.65 0.406

Albumin (g/dl) † 4.27 ± 0.30 4.22 ± 0.29 4.29 ± 0.30 0.222

Total bilirubin (mg/dl) † 0.73 ± 0.30 0.78 ± 0.32 0.71 ± 0.29 0.399

eGFR (ml/min/1.73m2)† 80.66 ± 15.93 78.72 ± 13.99 81.28 ± 16.52 0.274

Hb† (gm/dL) 13.67 ± 1.48 13.71 ± 1.54 13.65 ± 1.46 0.688

Prothrombin time (INR)† 1.02 ± 0.05 1.04 ± 0.06 1.01 ± 0.05 0.078

*rank 1: > 90 ml/min/1.73 m2, rank 2: 60-90 ml/min/1.73 m2, rank 3: 30-60 ml/min/1.73 m2; †Data are expressed as mean±SD.

Supplement table 2. Baseline characteristics of chronic hepatitis C patients receiving DAA with or without grade 2/3 renal function deterioration at P12 for SOF users.

Variable All patients

(n = 112) With grade 2/3 deterioration

(n = 33) (26.7%) Without grade 2/3 deterioration

(n = 79) (73.3%) P value

Baseline clinical characteristics

Age (years)† 63.98 ± 11.14 65.82 ± 10.09 63.21 ± 11.52 0.255

Male (%) 42 (37.5%) 14 (42.4%) 28 (35.4%) 0.525

Fatty liver 37 (33.0%) 8 (24.2%) 29 (36.7%) 0.271

Hyperlipidemia 6 (5.4%) 1 (3.0%) 5 (6.3%) 0.668

Diabetes mellitus 18 (16.1%) 5 (15.2%) 13 (16.5%) 1.000

Hypertension 24 (21.4%) 7 (21.2%) 17 (21.5%) 1.000

eGFR ranks* 0.382

rank 1 38 (33.9%) 10 (30.3%) 28 (35.4%)

rank 2 50 (44.6%) 14 (42.4%) 36 (45.6%)

rank 3 24 (21.4%) 9 (27.3%) 15 (19.0%)

Baseline characteristics of HCV and liver-related conditions

Advanced fibrosis (%) 83 (74.1%) 26 (78.8%) 57 (72.2%) 0.637

HCC history (%) 17 (15.2%) 8 (24.2%) 9 (11.4%) 0.146

Splenomegaly (%) 34 (30.4%) 12 (36.4%) 22 (27.8%) 0.377

Ascites (%) 4 (3.6%) 2 (6.1%) 2 (2.5 %) 0.580

Baseline HCV viral load (IU/mL)† 5.88Log ± 1.08Log 5.87Log ± 1.10Log 5.88Log ± 1.08Log 0.924

HCV genotype 1 (%) 44 (39.3%) 17 (51.5%) 27 (34.2%) 0.095

Baseline medications associated with renal function

ACEI/ARB users 13 (11.6%) 7 (21.2%) 6 (7.6%) 0.054

Diuretics users 9 (8.0%) 4 (12.1%) 5 (6.3%) 0.445

NSAID users 13 (11.6%) 2 (6.1%) 11 (13.9%) 0.339

Baseline laboratory data

Baseline NGAL (ng/ml) † 14.54 ± 8.20 15.73 ± 9.27 14.05 ± 7.72 0.612

ALT(U/L)† 89.80 ± 78.38 87.70 ± 63.70 90.67 ± 84.11 0.532

AST(U/L)† 62.93 ± 46.57 66.06 ± 45.85 61.62 ± 47.10 0.491

Albumin (g/dl) † 4.12 ± 0.41 4.07 ± 0.45 4.14 ± 0.39 0.650

Total bilirubin (mg/dl) † 0.85 ± 0.48 0.87 ± 0.44 0.84 ± 0.50 0.559

eGFR (ml/min/1.73m2)† 77.10 ± 19.54 74.41 ± 19.31 78.22 ± 19.65 0.330

Hb† (gm/dL) 13.32 ± 1.75 13.28 ± 1.52 13.34 ± 1.85 0.959

Prothrombin time (INR)† 1.04 ± 0.08 1.05 ± 0.08 1.04 ± 0.08 0.529

*rank 1: > 90 ml/min/1.73 m2, rank 2: 60-90 ml/min/1.73 m2, rank 3: 30-60 ml/min/1.73 m2; †Data are expressed as mean±SD.

Supplement table 3. Patient factors associated with grade 2/3 renal function deterioration in chronic hepatitis C patients receiving DAA at P12^ for nonSOF and SOF-based DAA users.

Odds Ratio (95% CI) P value

NonSOF-based DAA users

Sex

Female

Male

1.000

3.161 (1.150–8.686)

0.026

Fatty liver

No

Yes

1.000

4.684 (1.689–12.990)

0.003

Hyperlipidemia

No

Yes

1.000

9.401 (2.268–38.959)

0.002

BL NGAL 1.051 (1.000–1.104) 0.05

SOF-based DAA users

ACEI/ARB users

No

Yes

1.000

3.276 (1.008–10.647)

0.049

^Adjusted for age, sex, variables with P < 0.1 from supplement table 1: fatty liver, hyperlipidemia, splenomegaly, BL NGAL and PT INR and from supplement table 2: GT1 and ACEI/ARB users for nonSOF users and SOF users, respectively ; factors reported to be associated with renal injury: baseline renal disease, DM, HTN, liver disease (advanced fibrosis), ACEI/ARB users, diuretics users, and NSAID users were also considered in multivariate analysis.

3. Page 16, line 3, “The levels of NGAL at the BL, EOT, and P12 were all significantly different between nonSOF- and SOF-based DAA users (P = 0.011, 0.024, and 0.037, respectively). Please add a figure.

Response:

Thank you for your commnet. The figure has been revealed as figure 3b. We also provided new figures for better legibility and added the footnote after this sentence (Page 16, line 257).

4. Page 21, line 6, “Although we found that an increase in NGAL was significant at P12 by SOF-based DAA, the values were still within the normal range”. What is the normal range of NGAL?

Response:

Thank you for your reminder. We showed the normal range of NGAL in the page 9, method paragraph 2.4 and line 163-164. We added this normal range again in Page 21, line 356 for better readability.

5. Page 22, “Fig 4. The eGFR and NGAL changes from the BL, EOT to P12 in different BL eGFR ranks in CHC patients receiving DAA therapy. a. eGFR; b. NGAL” should be in “3. Results”.

Response:

Thank you for your reminder. We have corrected it (Page 18, line 286-287). Thank you very much.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

9 Aug 2021

Neutrophil gelatinase-associated lipocalin partly reflects the dynamic changes of renal function among chronic hepatitis C patients receiving direct-acting antivirals

PONE-D-21-15486R1

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Reviewer #2: All comments have been addressed

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

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

Reviewer #1: Yes

Reviewer #2: Yes

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

Reviewer #1: Yes

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 #1: Yes

Reviewer #2: Yes

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

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Reviewer #1: Yes

Reviewer #2: Yes

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6. Review Comments to the Author

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Reviewer #1: The authors answered and revised the manuscript according to my suggestions. I endorse publication of the manuscript.

Reviewer #2: (No Response)

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Reviewer #1: No

Reviewer #2: Yes: Wei-Yu Kao

18 Aug 2021

PONE-D-21-15486R1

Neutrophil gelatinase-associated lipocalin partly reflects the dynamic changes of renal function among chronic hepatitis C patients receiving direct-acting antivirals

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