Risk of fatty liver after long-term use of tamoxifen in patients with breast cancer

Jeong-Ju Yoo; Yong Seok Lim; Min Sung Kim; Bora Lee; Bo-Yeon Kim; Zisun Kim; Ji Eun Lee; Min Hee Lee; Sang Gyune Kim; Young Seok Kim

doi:10.1371/journal.pone.0236506

. 2020 Jul 30;15(7):e0236506. doi: 10.1371/journal.pone.0236506

Risk of fatty liver after long-term use of tamoxifen in patients with breast cancer

Jeong-Ju Yoo ^1,^#, Yong Seok Lim ^1,^#, Min Sung Kim ², Bora Lee ³, Bo-Yeon Kim ⁴, Zisun Kim ⁵, Ji Eun Lee ⁶, Min Hee Lee ⁶, Sang Gyune Kim ^1,^*, Young Seok Kim ¹

Editor: Hakan Buyukhatipoglu⁷

PMCID: PMC7392315 PMID: 32730287

Abstract

Background

Few studies report the effects of tamoxifen intake and the occurrence of de novo fatty liver and the deterioration of existing fatty liver. The aim of this study was to investigate the effects of tamoxifen on fatty change of liver over time and also the impact of fatty liver on the prognosis of patients with breast cancer.

Methods

This was a single-center, retrospective study of patients who were diagnosed with primary breast cancer from January 2007 to July 2017. 911 consecutive patients were classified into three groups according to treatment method: tamoxifen group, aromatase inhibitor (AI) group, and control group.

Results

Median treatment duration was 49 months (interquartile range, IQR; 32–58) and median observational period was 85 months (IQR; 50–118). Long-term use of tamoxifen significantly aggravated fatty liver status compared to AI or control groups [hazard ratio (HR): 1.598, 95% confidence interval (CI): 1.173–2.177, P = 0.003] after adjusting other factors. When analyzed separately depending on pre-existing fatty liver at baseline, tamoxifen was involved in the development of de novo fatty liver [HR: 1.519, 95% CI: 1.100–2.098, P = 0.011) and had greater effect on fatty liver worsening (HR: 2.103, 95% CI: 1.156–3.826, P = 0.015). However, the progression of fatty liver did not significantly affect the mortality of breast cancer patients.

Conclusions

Tamoxifen had a significant effect on the fatty liver status compared to other treatment modalities in breast cancer patients. Although fatty liver did not affect the prognosis of breast cancer, meticulous attention to cardiovascular disease or other metabolic disease should be paid when used for a long time.

Introduction

Breast cancer is the most common cancer in women, with an annual incidence of two million cases worldwide. Also, about 70% of breast cancer patients are hormone receptor positive.[1] Tamoxifen, a selective estrogen receptor modulator (SERM), is a well-known adjuvant endocrine treatment for estrogen receptor (ER)-positive breast cancer patients. Since tamoxifen can increase the rates of disease-free survival and overall survival of patients at all stages, and reduce the local recurrence rate, its usage in ER-positive patients is recommended for at least five years.[2, 3] However, side effects due to long-term use of tamoxifen such as vaginal bleeding, endometrial cancer, deep vein thrombosis, pulmonary embolism, and fatty liver have been reported.[4] Among these side effects, fatty liver is a serious complication because it can reduce drug compliance and increase the incidence of other metabolic diseases.[5, 6] In addition, it was reported that 43% of breast cancer patients treated with tamoxifen developed hepatic steatosis within the first two years.[7]

Aromatase inhibitor (AI) has the same mechanism as tamoxifen by inhibiting estrogen action. However, unlike tamoxifen, AI does not significantly increase the incidence of fatty liver. Recently, studies have reported the benefits of using tamoxifen for up to 10 years.[8] Thus, more attention should be paid to side effects of long-term use of tamoxifen. However, existing studies usually have short-term follow-up with the diagnosis of fatty liver based on elevated liver enzymes rather than imaging diagnosis.[9] In addition, reports on the use of tamoxifen in high risk groups of fatty liver are limited. Furthermore, the effect of fatty liver on the prognosis of breast cancer patients is not well known yet.

Thus, the purpose of this study was to investigate the effects of tamoxifen on the risk of fatty liver in comparison with other treatment modalities practicing long-term follow-ups and identify high risk groups. In addition, we investigated the effect of fatty liver caused by tamoxifen on the mortality of breast cancer patients.

Materials and methods

Patients and study design

This was a single-center, retrospective cohort study. We retrospectively reviewed data of patients who were first pathologically diagnosed with primary breast cancer and treated at a tertiary referral hospital from January 2007 to July 2017 (S1 Fig). Exclusion criteria were: (1) treatment period of less than two years, (2) evidence of viral hepatitis (e.g., hepatitis B surface antigen positive or hepatitis C antibody positive) or liver cirrhosis, (3) significant alcohol consumption, (4) no imaging study during the follow-up period, and (5) evidence of double primary cancer. Ongoing or recent alcohol consumption >21 standard drinks on average per week in men and >14 standard drinks on average per week in women was the criteria for significant alcohol consumption.[10]

911 patients were enrolled and classified into three groups according to treatment method: 1) tamoxifen group, patients taking tamoxifen for more than two years; 2) aromatase inhibitor group, patients taking anastrozole or letrozole for more than 2 years; and 3) control group, patients who had received treatment other than tamoxifen or AI (e.g., conventional chemotherapy, radiotherapy, or surgery alone). The chemotherapeutic agents of anticancer drugs were diverse, however, anthracycline and taxane-based chemotherapy was most widely used. Clinical, histological, imaging, and laboratory records of these patients were retrospectively reviewed. Patients were prescribed tamoxifen or AI every three months with laboratory tests at each regular visit. To monitor possible recurrences of breast cancer, follow-up computed tomography (CT) or ultrasonography (USG) were performed every 6months for patients with high risk of recurrence, and every 12months for others as recommended in the NCCN guideline.[11] If recurrence was not observed for five years, monitoring was carried out on a yearly basis.

Informed consent was waived because of the retrospective nature of the study and the analysis used anonymous clinical data. This study was approved by the Institutional Review Board of Soonchunhyang University Hospital, Bucheon, Korea (SCHBC-2018-12-002-001). The study protocol conformed to the ethical guidelines of the World Medical Association Declaration of Helsinki.

Diagnosis of fatty liver

The incidence or severity of fatty liver was assessed by non-contrast CT or abdominal USG. We used only one technique (among CT or USG) as a diagnostic tool to determine fatty liver throughout the follow-up period. All the images were evaluated by two experienced radiologists (LMH and LJE) who were blinded to the study aims and the administered drug. In USG examination, the severity of fatty liver was graded as normal, mild, moderate, or severe according to echogenicity of the liver parenchyma.[12] In non-contrast CT examination, hepatic steatosis was assessed based on Hounsfield unit (HU) hepatic attenuation using published method.[13, 14] Hepatic attenuation was measured as mean of three circular regions of interest (ROIs) on three transverse sections at different hepatic levels: confluence of right hepatic vein, umbilical portion of left portal vein, and posterior branch of the right portal vein. Mean splenic attenuation was also calculated for three random area ROI values of attenuation measurement at three different splenic levels. Fatty liver was defined when the ratio of mean hepatic attenuation to mean splenic attenuation was lower than 0.9.[13, 14]

Definition

Baseline was regarded as just before receiving hormonal therapy after breast cancer surgery and follow-up CT scan. The follow-up period was considered the period either during hormonal drug intake or until the time of loss or death. Patients were classified into the following four groups according to existence of fatty liver at baseline and the change of fatty liver status during follow-up period. No fatty liver group was defined as having a normal liver at baseline and remaining normal during follow-up period. De novo fatty liver group was defined as having a normal liver at baseline, but developing a new fatty liver. Stable fatty liver group was defined as having a fatty liver at baseline and no change of fatty liver severity during follow-up period. Worsened fatty liver group was defined as having a fatty liver at baseline and worsening of fatty liver status at any point during follow-up period (e.g., increased grade of fatty liver on abdominal USG or decreasing liver attenuation index value on non-contrast CT).[15, 16] These four groups mentioned above were also categorized based on aggravation of fatty liver. De novo fatty liver group and worsened fatty liver group were categorized as progression group while no fatty liver group and stable fatty liver group categorized as non-progression group.

Statistical analysis

Frequencies and percentages were used for descriptive statistics. Statistical differences between groups were investigated using one-way analysis of variance (ANOVA) or Student’s t-test for continuous variables and chi-squares test or Fisher’s exact test for categorical variables as appropriate. Kaplan-Meier survival analysis was used for survival rate and incidence of fatty liver. To identify predictive factors associated with development of fatty liver according to age, Cox proportional hazards (PH) regression analysis was used. Any variable showing a significance at 0.1 in the univariate model was selected as a candidate for the multivariable model.[17] The final multiple Cox PH regression model was chosen by the stepwise selection based on the Akaike information criterion (AIC).

Propensity score (PS) matching analysis was conducted to minimize the probability of selection bias by pairing tamoxifen group and control group based on propensity scores. PS matching was generated by multiple logistic regressions. This model included all variables such as age, body mass index (BMI), breast cancer stage, diabetes, and hypertension that are likely to affect the process of fatty deposition in the liver. We used the nearest available matching (1:1) method for PS matching with the caliper of 0.05. For validation, we generated additional matched datasets using the caliper of 0.03 and 0.01.

All statistical analyses were performed using R (version 3.6.1, The R Foundation for Statistical Computing, Vienna, Austria) and SPSS software (version 21.0; SPSS Inc., Chicago, IL, USA). Statistical significance was defined at P < 0.05.

Results

Patients’ demographics at baseline

Baseline characteristics of 911 patients enrolled in this study are described in Table 1. Tamoxifen, prescribed to 416 (45.7%) patients, accounted for the highest proportion followed by a group of patients (296, 32.5%) who did not take any anti-estrogen hormonal treatment, and next by a group of patients (199, 21.8%) who were prescribed AI. Mean age and BMI were 50.13 ± 10.32 years and 24.17 ± 3.62, respectively. Median treatment duration was 49 months [interquartile range (IQR) 32–58)], and median observational period was 85 months (IQR 50–118). From the outset 260 (28.5%) of patients already had fatty liver. Seventy (7.7%) patients had diabetes and 176 (19.3%) had hypertension. Mean follicle stimulating hormone (FSH) level was 37.38 ± 30.15 IU/L. Breast cancer of stage I was most common (42.4%), followed by stage II (40.8%) and stage III (8.1%). Lymph node metastasis was found in 284 (31.2%) patients.

Table 1. Baseline characteristics of patients.

Variable	All	Control	Tamoxifen	Aromatase inhibitor	P-value
Variable	(N = 911)	(N = 296)	(N = 416)	(N = 199)	P-value
Age (year)	50.13 ± 10.32	49.78 ± 10.60	46.87 ± 9.43	57.46 ± 7.68	<0.001
Body mass index kg/m²)	24.17 ± 3.62	24.18 ± 3.78	23.67 ± 3.32	25.22 ± 3.76	<0.001
Diabetes mellitus	70 (7.68%)	21 (7.09%)	24 (5.77%)	25 (12.56%)	0.011
Hypertension	176 (19.32%)	49 (16.55%)	72 (17.31%)	55 (27.64%)	0.003
Treatment duration (month)	49.04 ± 21.85	50.88 ± 30.87	50.00 ± 17.07	44.30 ± 11.55	0.005
Cancer-related factor
Stage					<0.001
0	71 (7.79%)	19 (6.42%)	49 (11.78%)	3 (1.51%)
1	386 (42.37%)	129 (43.58%)	160 (38.46%)	97 (48.74%)
2	372 (40.83%)	120 (40.54%)	167 (40.14%)	85 (42.71%)
3	74 (8.12%)	22 (7.43%)	38 (9.13%)	14 (7.04%)
4	8 (0.88%)	6 (2.03%)	2 (0.48%)	0 (0%)
Pathology					0.007
Invasive ductal carcinoma	757 (83.10%)	248 (83.78%)	332 (79.81%)	177 (88.94%)
Ductal carcinoma in situ	73 (8.01%)	22 (7.43%)	48 (11.54%)	3 (1.51%)
Mucinous carcinoma	24 (2.63%)	4 (1.35%)	12 (2.88%)	8 (4.02%)
Infiltrating lobular carcinoma	27 (2.96%)	9 (3.04%)	12 (2.88%)	6 (3.02%)
Intraductal papilloma	13 (1.43%)	2 (0.68%)	6 (1.44%)	5 (2.51%)
Tubular carcinoma	2 (0.22%)	1 (0.34%)	1 (0.24%)	0 (0%)
Apocrine carcinoma	2 (0.22%)	1 (0.34%)	1 (0.24%)	0 (0%)
Squamous carcinoma	2 (0.22%)	1 (0.34%)	1 (0.24%)	0 (0%)
Medullary carcinoma	5 (0.55%)	3 (1.01%)	2 (0.48%)	0 (0%)
Others	6 (0.66%)	5 (1.69%)	1 (0.24%)	0 (0%)
Lymph node metastasis	284 (31.17%)	107 (36.15%)	115 (27.64%)	62 (31.16%)	0.054
ER (Intermediate or High)	614 (67.70%)	108 (36.49%)	328 (79.61%)	178 (89.45%)	<0.001
PR (Intermediate or High)	555 (61.19%)	102 (34.46%)	313 (75.97%)	140 (70.35%)	<0.001
HER2 (Intermediate or High)	340 (37.32%)	83 (28.04%)	167 (40.14%)	90 (45.23%)	<0.001
p53	328 (41.41%)	121 (49.79%)	152 (41.30%)	55 (30.39%)	<0.001
Ki67 (≥ 40%)	124 (15.31%)	77 (29.96%)	31 (8.36%)	16 (8.79%)	<0.001
Laboratory test
FSH (IU/L)	37.38 ± 30.15	30.37 ± 29.13	34.34 ± 29.78	55.55 ± 25.18	<0.001
Platelet (10³ mm³)	238.66 ± 72.70	247.55 ± 66.89	231.54 ± 74.33	240.35 ± 76.27	0.007
AST (U/L)	23.85 ± 13.53	21.28 ± 9.07	25.60 ± 15.42	24.03 ± 14.28	<0.001
ALT (U/L)	22.17 ± 16.86	19.35 ± 15.97	23.93 ± 18.43	22.67 ± 13.98	<0.001
Serum albumin (mg/dL)	4.20 ± 0.45	4.36 ± 0.45	4.11 ± 0.43	4.14 ± 0.43	<0.001
Total bilirubin (mg/dL)	0.59 ± 0.33	0.65 ± 0.42	0.55 ± 0.25	0.58 ± 0.31	<0.001
Total cholesterol (mg/dL)	185.16 ± 35.97	185.90 ± 36.59	181.12 ± 33.83	192.48 ± 38.28	0.118
Triglyceride (mg/dL)	132.95 ± 96.18	146.31 ± 110.62	124.34 ± 91.42	133.36 ± 82.19	0.060
HDL-cholesterol (mg/dL)	53.40 ± 13.41	52.29 ± 13.02	55.45 ± 13.92	51.18 ± 12.51	0.002
LDL-cholesterol (mg/dL)	107.32 ± 32.39	107.98 ± 31.99	104.32 ± 30.80	112.13 ± 35.42	0.096
Fasting blood glucose (mg/dL)	110.07 ± 28.42	106.83 ± 24.72	109.74 ± 28.28	115.60 ± 32.83	0.001

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computed by one-way ANOVA for continuous variables and chi-squares test for categorical variables.

Abbreviations: ER, estrogen receptor; PR, progesterone receptor; HER2, Human epidermal growth factor receptor 2; FSH, follicle stimulating hormone; AST, aspartate aminotransferase; ALT, alanine aminotransferase; HDL, high-density lipoprotein; LDL, low-density lipoprotein; NFS, nonalcoholic fatty liver disease fibrosis score; FIB-4, fibrosis-4; CT, computed tomography.

Changes in fatty liver status over time

There was no change of fatty liver status in 499 (54.8%) patients (non-progression group) while there was a deterioration of fatty liver status in 412 (45.2%) patients (progression group). Table 2 shows the baseline data according to the change of fatty liver status. BMI, aspartate aminotransferase (AST), alanine aminotransferase (ALT), and fasting blood glucose of patients in the progression group were significantly higher than those in the non-progression group. The worsened fatty liver group had the highest mean BMI, followed by stable fatty liver, de novo fatty liver, and no fatty liver groups. Levels of liver enzymes including AST, ALT, and other lipid profiles showed the same pattern. Of note, tamoxifen significantly increased fatty liver progression compared to AI or control over time (P < 0.001, Fig 1A). These differences were more pronounced in patients who had previously fatty liver (Fig 1B). In patients without basal fatty liver, tamoxifen also increased the incidence of de novo fatty liver more than control (Fig 1C).

Table 2. Clinical characteristics depending on the status of fatty liver.

Variable	All	No fatty liver	De novo fatty liver	Stable fatty liver	Worsened fatty liver	P	Fatty liver progression^* (-)	Fatty liver progression^* (+)	P
	(N = 911)	(N = 364)	(N = 287)	(N = 135)	(N = 125)		Fatty liver progression^* (-)	Fatty liver progression^* (+)
	(N = 911)	(N = 364)	(N = 287)	(N = 135)	(N = 125)		(N = 499)	(N = 412)
Treatment modality						<0.001			<0.001
Control	296	159 (53.72%)	67 (22.64%)	52 (17.57%)	18 (6.07%)		211 (71.29%)	85 (28.71%)
Aromatase inhibitor	199	73 (36.68%)	55 (27.64%)	41 (20.60%)	30 (15.08%)		114 (57.28%)	85 (42.72%)
Tamoxifen	416	132 (31.73%)	165 (39.66%)	42 (10.10%)	77 (18.51%)		174 (41.83%)	242 (58.17%)
Age (year)	50.13 ± 10.32	49.65 ± 10.69	49.70 ± 10.40	52.58 ± 10.30	49.84 ± 8.64	0.018	50.44 ± 10.66	49.75 ± 9.89	0.306
Body mass index (kg/m²)	24.17 ± 3.62	23.03 ± 3.15	24.06 ± 3.25	25.38 ± 3.92	26.47 ± 3.93	<0.001	23.67 ± 3.53	24.79 ± 3.64	<0.001
Diabetes mellitus	70 (7.68%)	18 (4.95%)	18 (6.27%)	18 (13.33%)	16 (12.80%)	0.002	36 (7.21%)	34 (8.25%)	0.645
Hypertension	176 (19.32%)	55 (15.11%)	52 (18.12%)	33 (24.44%)	36 (28.80%)	0.003	88 (17.64%)	88 (21.36%)	0.183
Treatment duration (month)	49.04 ± 21.85	44.48 ± 20.83	48.57 ± 18.57	60.01 ± 28.09	51.55 ± 19.64	<0.001	48.68 ± 24.01	49.48 ± 18.92	0.075
Cancer-related factor
Stage						0.460			0.062^a
0	71 (7.79%)	26 (7.14%)	27 (9.41%)	5 (3.70%)	13 (10.40%)		31 (6.21%)	40 (9.71%)
1	386 (42.37%)	171 (46.98%)	110 (38.33%)	60 (44.44%)	45 (36.00%)		231 (46.29%)	155 (37.62%)
2	372 (40.83%)	138 (37.91%)	121 (42.16%)	57 (42.22%)	56 (44.80%)		195 (39.08%)	177 (42.96%)
3	74 (8.12%)	26 (7.14%)	26 (9.06%)	12 (8.89%)	10 (8.00%)		38 (7.62%)	36 (8.74%)
4	8 (0.88%)	3 (0.82%)	3 (1.05%)	1 (0.74%)	1 (0.80%)		4 (0.80%)	4 (0.97%)
Pathology						0.099
Invasive ductal carcinoma	757 (83.10%)	312 (85.71%)	229 (79.79%)	117 (86.67%)	99 (79.20%)				0.101
Ductal carcinoma in situ	73 (8.01%)	27 (7.42%)	26 (9.06%)	6 (4.44%)	14 (11.20%)		429 (85.97%)	328 (79.61%)
Mucinous carcinoma	24 (2.63%)	6 (1.65%)	11 (3.83%)	4 (2.96%)	3 (2.40%)		33 (6.61%)	40 (9.71%)
Infiltrating lobular carcinoma	27 (2.96%)	13 (3.57%)	11 (3.83%)	3 (2.22%)	0 (0%)		10 (2.00%)	14 (3.40%)
Intraductal papilloma	13 (1.43%)	1 (0.27%)	7 (2.44%)	1 (0.74%)	4 (3.20%)		16 (3.21%)	11 (2.67%)
Tubular carcinoma	2 (0.22%)	1 (0.27%)	0 (0%)	0 (0%)	1 (0.80%)		2 (0.40%)	11 (2.67%)
Apocrine carcinoma	2 (0.22%)	1 (0.27%)	0 (0%)	0 (0%)	1 (0.80%)		1 (0.20%)	1 (0.24%)
Squamous carcinoma	2 (0.22%)	0 (0%)	1 (0.35%)	1 (0.74%)	0 (0%)		1 (0.20%)	1 (0.24%)
Medullary carcinoma	5 (0.55%)	1 (0.27%)	2 (0.70%)	1 (0.74%)	1 (0.80%)		1 (0.20%)	1 (0.24%)
Others	6 (0.66%)	2 (0.55%)	0 (0%)	2 (1.48%)	2 (1.60%)		2 (0.40%)	3 (0.73%)
Lymph node metastasis	284 (31.17%)	104 (28.57%)	96 (33.45%)	47 (34.81%)	37 (29.60%)	0.420	151 (30.26%)	133 (32.28%)	0.559
ER (Intermediate or High)	614 (67.70%)	230 (63.19%)	208 (73.24%)	82 (61.19%)	94 (75.20%)	0.004	312 (62.65%)	302 (73.84%)	<0.001
PR (Intermediate or High)	555 (61.19%)	200 (54.95%)	192 (67.61%)	70 (52.24%)	93 (74.40%)	<0.001	270 (54.22%)	285 (69.68%)	<0.001
HER2 (Intermediate or High)	340 (37.32%)	134 (36.81%)	111 (38.68%)	39 (28.89%)	56 (44.80%)	0.061	173 (34.67%)	167 (40.53%)	0.080
p53	328 (41.41%)	135 (42.86%)	97 (39.75%)	55 (45.08%)	41 (36.94%)	0.544	190 (43.48%)	138 (38.87%)	0.216
Ki67 (≥ 40%)	124 (15.31%)	58 (17.85%)	33 (13.10%)	22 (18.03%)	11 (9.91%)	0.124	80 (17.90%)	44 (12.12%)	0.030
Laboratory test
Initial
FSH (IU/L)	37.38 ± 30.15	37.01 ± 31.61	33.93 ± 28.73	43.40 ± 29.05	39.98 ± 28.98	0.048	38.65 ± 31.07	35.74 ± 28.89	0.416
Platelet (10³ mm³)	238.66 ± 72.70	237.47 ± 73.38	241.26 ± 74.23	233.10 ± 71.58	242.18 ± 68.66	0.562	236.29 ± 72.85	241.54 ± 72.51	0.216
AST (U/L)	23.85 ± 13.53	21.79 ± 9.42	22.43 ± 9.37	26.08 ± 17.47	30.73 ± 21.92	<0.001	22.95 ± 12.27	24.95 ± 14.86	0.033
ALT (U/L)	22.17 ± 16.86	18.39 ± 13.70	20.43 ± 12.38	27.13 ± 21.14	31.80 ± 23.05	<0.001	20.75 ± 16.49	23.88 ± 17.16	<0.001
Serum albumin (mg/dL)	4.20 ± 0.45	4.22 ± 0.46	4.14 ± 0.47	4.23 ± 0.44	4.23 ± 0.38	0.092	4.22 ± 0.45	4.17 ± 0.45	0.040
Total bilirubin (mg/dL)	0.59 ± 0.33	0.60 ± 0.27	0.56 ± 0.27	0.64 ± 0.57	0.58 ± 0.25	0.081	0.61 ± 0.38	0.56 ± 0.26	0.024
Total cholesterol (mg/dL)	185.16 ± 35.97	182.03 ± 37.16	183.82 ± 34.51	193.00 ± 36.18	188.87 ± 34.33	0.006	185.00 ± 37.18	185.35 ± 34.50	0.884
Triglyceride (mg/dL)	132.95 ± 96.18	109.55 ± 64.12	132.42 ± 90.74	144.71 ± 82.52	185.90 ± 156.16	<0.001	119.58 ± 71.52	148.85 ± 117.20	<0.001
HDL-cholesterol (mg/dL)	53.40 ± 13.41	54.86 ± 13.91	54.02 ± 13.85	52.64 ± 12.87	48.47 ± 9.98	<0.001	54.30 ± 13.67	52.36 ± 13.05	0.059
LDL-cholesterol (mg/dL)	107.32 ± 32.39	105.79 ± 31.31	104.31 ± 30.29	113.44 ± 34.13	113.38 ± 37.54	0.039	107.68 ± 32.16	106.89 ± 32.72	0.743
Fasting blood glucose (mg/dL)	110.07 ± 28.42	107.40 ± 25.31	109.61 ± 30.42	112.27 ± 31.95	116.58 ± 27.28	0.001	108.72 ± 27.32	111.72 ± 29.64	0.043
BARD	1.95 ± 0.77	1.96 ± 0.62	1.95 ± 0.74	1.93 ± 0.94	1.95 ± 1.01	0.930	1.95 ± 0.72	1.95 ± 0.83	0.984
NFS	-1.04 ± 1.31	-1.05 ± 1.30	-1.06 ± 1.35	-0.93 ± 1.30	-1.10 ± 1.25	0.589	-1.01 ± 1.30	-1.07 ± 1.32	0.393
FIB-4	1.27 ± 1.03	1.26 ± 0.72	1.24 ± 1.23	1.38 ± 1.43	1.26 ± 0.82	0.332	1.29 ± 0.96	1.25 ± 1.12	0.083
ALT elevation						<0.001			0.461
No	524 (57.52%)	224 (61.54%)	187 (65.16%)	69 (51.11%)	44 (35.20%)		293 (58.72%)	231 (56.07%)
Yes	387 (42.48%)	140 (38.46%)	100 (34.84%)	66 (48.89%)	81 (64.80%)		206 (41.28%)	181 (43.93%)

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Data are reported as means and standard deviation (SD) (mean ± SD) for continuous variables and frequency (percentage) for categorical variables. Proportions are presented as percentages for categorical variables. P-values were computed by one-way ANOVA or Student’s t-test for continuous variables and chi-squares test or Fisher’s exact test for categorical variables as appropriate (^a, computed by Fisher’s exact test).

* Definition of fatty liver progression is increased grade of fatty liver according to abdominal ultrasound or decreasing liver attenuation index value on non-contrast computed tomography.

Fig 1 — (A) All patients (N = 911), (B) Patients with initial fatty liver (N = 260), (C) Patients without initial fatty liver (N = 651).

Next, we investigated factors affecting fatty liver progression by Cox proportional hazard regression analyses. Table 3 shows that tamoxifen significantly contributed to the progression of fatty liver [hazard ratio (HR): 1.598, 95% confidence interval (CI): 1.173–2.177, P = 0.003] as compared with other treatments modality after adjusting for BMI, progesterone receptor (PR), and FSH. This effect of tamoxifen on fatty liver was consistently meaningful whether or not fatty liver was present at baseline (S1 Table).

Table 3. Multivariable analysis for the risk factors associated with fatty liver progression.

Variable	Univariable		Multivariable
Variable	HR (95% CI)	P-value	HR (95% CI)	P-value
Treatment modality
Control	1 (Reference)		1 (Reference)
Aromatase inhibitor	1.331 (0.985–1.798)	0.063	1.230 (0.839–1.803)	0.289
Tamoxifen	1.744 (1.361–2.234)	<0.001	1.598 (1.173–2.177)	0.003
Age (year)	1.002 (0.993–1.012)	0.618
BMI (kg/m²)	1.061 (1.036–1.087)	<0.001	1.083 (1.052–1.114)	<0.001
Diabetes	1.197 (0.843–1.701)	0.315
Hypertension	1.214 (0.959–1.537)	0.107
Cancer stage
≤1	1 (Reference)
2	1.230 (1.003–1.507)	0.047
≥3	1.204 (0.857–1.693)	0.284
Pathology
Invasive ductal carcinoma	1 (Reference)
Ductal carcinoma in situ	1.271 (0.915–1.764)	0.153
Mucinous carcinoma	1.300 (0.761–2.22)	0.337
Infiltrating lobular carcinoma	1.051 (0.576–1.917)	0.871
Intraductal papilloma	2.187 (1.199–3.991)	0.011
Tubular carcinoma	0.878 (0.123–6.252)	0.896
Apocrine carcinoma	0.923 (0.13–6.574)	0.936
Squamous carcinoma	1.005 (0.141–7.16)	0.996
Medullary carcinoma	0.900 (0.289–2.807)	0.856
Others	0.820 (0.204–3.294)	0.780
Lymph node metastasis	1.115 (0.907–1.37)	0.303
ER (Intermediate or High)	1.459 (1.17–1.82)	0.001
PR (Intermediate or High)	1.621 (1.312–2.002)	<0.001	1.395 (1.049–1.857)	0.022
HER2 (Intermediate or High)	1.215 (0.998–1.479)	0.052
Chemotherapy	0.827 (0.664–1.029)	0.089
Radiotherapy	1.092 (0.9–1.326)	0.372
FSH	0.995 (0.991–0.999)	0.012	0.995 (0.991–0.999)	0.024
Platelet	1.002 (1.001–1.003)	0.004	1.002 (1.001–1.004)	0.004
AST	1.004 (0.998–1.011)	0.207
ALT	1.004 (0.999–1.009)	0.115
Serum albumin	0.902 (0.729–1.115)	0.339
Total bilirubin	0.620 (0.419–0.917)	0.017
Total cholesterol	0.999 (0.997–1.002)	0.668
Triglyceride	1.001 (1–1.002)	0.002
HDL-cholesterol	0.983 (0.975–0.992)	<0.001
LDL-cholesterol	1 (0.996–1.003)	0.972
Fasting blood glucose	1.003 (1–1.006)	0.088
BARD	1.044 (0.921–1.184)	0.503
NFS	0.947 (0.876–1.024)	0.170
FIB-4	0.937 (0.83–1.056)	0.287

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Abbreviations: HR, hazard ratio; CI, confidence interval; ER, estrogen receptor; PR, progesterone receptor; HER2, Human epidermal growth factor receptor 2; FSH, follicle stimulating hormone; AST, aspartate aminotransferase; ALT, alanine aminotransferase; HDL, high-density lipoprotein; LDL, low-density lipoprotein; NFS, nonalcoholic fatty liver disease fibrosis score; FIB-4, fibrosis-4.

Propensity score matching analysis

We performed PS matching in these patients (S2 Table). After PS matching, factors that might affect the development of fatty liver such as age, BMI, cancer stage, diabetes, and hypertension were well-balanced (S2 Fig). In the matched cohort, tamoxifen significantly increased the incidence of fatty liver progression compared with the control group (P<0.001, Fig 2A). And this phenomenon was observed in the same manner regardless of fatty liver status at baseline (Fig 2B and 2C). Univariate (S3 Table) and multivariate analyses (Table 4) according to baseline fatty liver status were also performed for the matched cohort, showing similar results with non-matched cohort. Overall, tamoxifen increased the risk of fatty liver by 1.385 times (95% CI: 1.019–1.883, P = 0.037) compared to control after adjusting for BMI and PR status. The effect of tamoxifen on fatty liver progression was also confirmed to the same degree and significance in other matched datasets (HR: 1.4, 95% CI: 1.018–1.927 in dataset with caliper 0.3; HR: 1.452, 95% CI: 1.021–2.065 in dataset with caliper 0.1) (S5 and S6 Tables).

Fig 2 — (A) All patients (N = 512), (B) Patients with initial fatty liver (N = 124), (C) Patients without initial fatty liver (N = 388).

Table 4. Propensity score matching analysis for risk factors associated with fatty liver progression.

Variable	Multivariable
Variable	HR (95% CI)	P-value
All (N = 512)
Treatment modality
Control	1 (Reference)
Tamoxifen	1.385 (1.019–1.883)	0.037
Body mass index (kg/m²)	1.069 (1.032–1.107)	<0.001
PR (Intermediate or High)	1.607 (1.186–2.178)	0.002
Fatty liver (-) at baseline (N = 388)
Treatment modality
Control	1 (Reference)
Tamoxifen	2.214 (1.416–3.464)	<0.001
Body mass index (kg/m²)	1.067 (1.014–1.122)	0.013
Triglyceride	1.005 (1.002–1.007)	<0.001
Fatty liver (+) at baseline (N = 124)
Treatment modality
Control	1 (Reference)
Tamoxifen	2.103 (1.156–3.826)	0.015
Body mass index (kg/m²)	1.049 (1.005–1.096)	0.029
HER2 (Intermediate + High)	1.804 (1.06–3.071)	0.030
Radiotherapy	2.081 (1.217–3.56)	0.007
Total cholesterol	0.988 (0.981–0.996)	0.002

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Abbreviations: HR, hazard ratio; CI, confidence interval.

Prediction model associated with fatty liver progression

Apart from multivariate analysis, we have made prediction models 1, 2, 3, and 4, incorporating various confounding factors to re-confirm the causal relationship between tamoxifen use and fatty liver progression. As shown in Table 5, tamoxifen was significantly associated with progression of fatty liver regardless of all these factors. After adjusting for age, BMI, diabetes, hypertension, menopausal status, cancer-related factors and other laboratory findings, tamoxifen was independently associated with increased risk of fatty liver (before matching, HR: 2.998, 95% CI: 1.646–5.462, P < 0.001; after matching, HR: 2.907, 95% CI: 1.451–5.821, P = 0.003).

Table 5. Prediction model related to fatty liver progression.

Variable		N	Model 1 ^*		Model 2 ^†		Model 3 ^§		Model 4 ^¶
Variable		N	HR (95% CI)	P	HR (95% CI)	P	HR (95% CI)	P	HR (95% CI)	P
Before matching	All
	Control	296	1 (Reference)		1 (Reference)		1 (Reference)		1 (Reference)
	Aromatase inhibitor	199	1.331 (0.985–1.798)	0.063	1.232 (0.902–1.682)	0.190	1.191 (0.858–1.654)	0.295	1.381 (0.806–2.367)	0.239
	Tamoxifen	416	1.744 (1.361–2.234)	<0.001	1.882 (1.461–2.424)	<0.001	1.860 (1.416–2.444)	<0.001	1.859 (1.167–2.96)	0.009
	Fatty liver (-) at baseline
	Control	226	1 (Reference)		1 (Reference)		1 (Reference)		1 (Reference)
	Aromatase inhibitor	128	1.389 (0.971–1.985)	0.072	1.231 (0.848–1.788)	0.274	1.100 (0.742–1.631)	0.634	1.135 (0.597–2.156)	0.699
	Tamoxifen	297	1.467 (1.103–1.952)	0.009	1.665 (1.244–2.227)	0.001	1.612 (1.172–2.217)	0.003	1.511 (0.843–2.708)	0.165
	Fatty liver (+) at baseline
	Control	70	1 (Reference)		1 (Reference)		1 (Reference)		1 (Reference)
	Aromatase inhibitor	71	1.514 (0.844–2.718)	0.164	1.581 (0.87–2.871)	0.133	1.749 (0.898–3.405)	0.100	2.410 (0.666–8.722)	0.180
	Tamoxifen	119	2.691 (1.61–4.497)	<0.001	2.672 (1.575–4.534)	<0.001	2.998 (1.646–5.462)	<0.001	3.668 (1.232–10.925)	0.020
After matching	All
	Control	256	1 (Reference)		1 (Reference)		1 (Reference)		1 (Reference)
	Tamoxifen	256	1.636 (1.237–2.165)	0.001	1.714 (1.293–2.271)	<0.001	1.773 (1.294–2.43)	<0.001	1.716 (0.98–3.005)	0.059
	Fatty liver (-) at baseline
	Control	202	1 (Reference)		1 (Reference)		1 (Reference)		1 (Reference)
	Tamoxifen	186	1.481 (1.075–2.042)	0.016	1.612 (1.166–2.23)	0.004	1.590 (1.092–2.314)	0.016	1.497 (0.745–3.007)	0.257
	Fatty liver (+) at baseline
	Control	54	1 (Reference)		1 (Reference)		1 (Reference)		1 (Reference)
	Tamoxifen	70	2.241 (1.244–4.038)	0.007	2.219 (1.226–4.015)	0.008	2.907 (1.451–5.821)	0.003	279.154 (2.887–26992.851)	0.016

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Abbreviations: HR, hazard ratio; CI, confidence interval.

* Model 1: unadjusted.

† Model 2: adjusted for age, BMI, and underlying disease (diabetes, hypertension).

§ Model 3: Model 2 plus cancer-related factors (stage, pathology, lymph node metastasis).

¶ Model 4: Model 3 plus initial laboratory factors (FSH, platelet, AST, ALT, total bilirubin, total cholesterol, triglyceride, fasting blood glucose).

Next, we performed a subgroup analysis in the tamoxifen group to find any correlations between the degree of hepatic steatosis with drug duration or changes in liver enzymes. However, we discovered no significant or clinically meaningful correlations when using the spearman’s correlation coefficient (data not shown).

Effect of fatty liver progression on mortality

In addition, we analyzed the effect of fatty liver on the prognosis of breast cancer patients. When patients were classified into two groups according to progression of fatty liver, there was no significant difference in long-term mortality between the two groups (before matching, P = 0.928, S3A Fig; after matching, P = 0.471, S3B Fig). Given the follow-up period with our cohort, cardiovascular risk possibly caused by tamoxifen was not fully assessed. In univariate (S4 Table) and multivariate analyses (Table 6), progression of fatty liver did not significantly affect mortality of breast cancer patients (HR: 0.753, 95% CI: 0.380–1.493, P = 0.417), although cancer stage and age were associated with mortality.

Table 6. Multivariable Cox proportional hazards regression for death.

Variable	Multivariable
Variable	HR (95% CI)	P-value
All (N = 911)
Fatty liver progression
No	1 (Reference)
Yes	0.753 (0.380–1.493)	0.417
Age (year)	1.041 (1.014–1.068)	0.003
ER (Intermediate or High)	0.314 (0.164–0.599)	<0.001
Cancer stage
≤1	1 (Reference)
2	1.647 (0.795–3.412)	0.180
≥3	3.789 (1.587–9.045)	0.003

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Abbreviations: ER, estrogen receptor; HR, hazard ratio; CI, confidence interval.

Discussion

Recent studies have shown that 10 years of adjuvant treatment of tamoxifen is superior to 5 years of tamoxifen use in reducing the risk of breast cancer recurrence or death.[8, 18] Since then, extended adjuvant tamoxifen (10 years) is recommended for selected high risk groups. However, there are still few studies considering the effect of tamoxifen on the incidence of fatty liver from a large population. Since the use of tamoxifen has been extended to be 10 years, its side effect such as fatty liver is expected to increase even more.

The largest study of tamoxifen-induced fatty liver was conducted in 2005 enrolling 5,408 patients in Italy.[9] However, the major disadvantage of that study was that the occurrence of fatty liver was not evaluated by imaging study, but by an increase in liver enzyme. In addition, patients included in that study were not breast cancer patients, but healthy women who underwent hysterectomy. Thereafter, although several studies were reported, the patient group was so heterogeneous as to come to a solid conclusion, and factors that could affect fatty liver development were not adjusted.[19, 20] In this study, we presented the risk of tamoxifen versus control or AI accurately using PS matching and multiple Cox regression analysis with a large cohort of patients. Tamoxifen had a great effect both on the development of de novo fatty liver and fatty liver worsening than other treatment modalities. In addition, there was a steady increase in fatty liver incidence in proportion to the cumulative dose as seen on the Kaplan-Meier curve.

The mechanism of how tamoxifen causes fatty liver is not well understood yet. The most representative hypothesis is the “multiple hit” hypothesis which suggests that fat accumulation would make liver vulnerable to oxidants, and then second hits (e.g., tamoxifen) could promote progress to steatohepatitis.[9] In this process, production of large amounts of reactive oxygen species, decreased mitochondrial β-oxidation, and increased TNF-α is known to play a major role in drug-induced steatohepatitis.[21] Our study supported this hypothesis with the fact that tamoxifen was more associated with deterioration of fatty liver in patients with pre-existing fatty liver than in those without.

The second hypothesis is that tamoxifen decreases lipid metabolism by inhibiting estrogen. Estrogen can regulate hepatic lipid metabolism through ERα, ERβ or GPER with regard to the extent of liver gene expression.[22] Indeed, the incidence of fatty liver gradually increases after menopause. It can be interpreted that with greater estrogen inhibition, more fatty liver will occur. Tamoxifen is known to cause higher levels of estrogen deprivation than AI. While AI blocks estrogen production in menopausal women who have already shown decreased estrogen production, tamoxifen blocks estrogen by binding to its receptor in the premenopausal status.[23, 24] Our study also demonstrated that the incidence of fatty liver was proportional to the degree of estrogen deprivation, which was highest in the tamoxifen group followed by the aromatase inhibitor and control group.

Because tamoxifen can induce or aggravate fatty liver mainly in susceptible patients, it is important to do close surveillance in advance, especially in high risk groups such as those with high BMI or presence of basal fatty liver. However, whether tamoxifen should be discontinued after the development of fatty liver is currently unclear. In our study, the occurrence of fatty liver did not affect the prognosis of breast cancer. Thus, we are not certain of the benefits and harms of suspending tamoxifen intake because it is difficult to adequately reflect the risk of cardiovascular disease during the five-year follow-up period. The guideline recommends weight reduction by 10%, rather than stopping the drug immediately.[21] Also, there was a report showing that moderate-intensity exercise of more than 150-minutes a week could reduce the risk of fatty liver development.[25] If fatty liver does not improve using this method, suspending tamoxifen or changing it to AI may be considered.

Our study has several limitations. First, the main limitation is predominant from its retrospective nature. The patients were not randomly assigned to the modalities which meant that the choice of modalities might have been biased. Also, there were some subjects who had no imaging study during the follow-up period which resulted in missing data. Along with the above drawbacks, this study has been designed for bias-reduction by propensity score matching. This result can be used to implement further prospective cohort study. Second, the quantification of steatosis was evaluated by either USG or CT. For the diagnostic ability of non-enhanced CT for fatty liver, sensitivity of macrovesicular steatosis of 30% or greater was 0.991 (95% CI: 0.960–0.999), and specificity was 1.0 (95% CI: 0.97, 1.00).[26, 27] In general, diagnostic performance of non-enhanced CT is comparable to USG and MR-PDFF.[28] Considering accessibility and price, it has slight advantages over MRI, and the inter-reader and intra-reader accordance is superior to ultrasound. In addition, recent studies by Artz et al.[29] and Luca et al.[15] suggested that simple ROI-based mean attenuation measurement with CT has an inverse linear relationship with fat content measured by MR spectroscopy. These studies imply that CT may be used as a quantitative imaging biomarker for both detection and quantification of liver fat content. Third, we did not evaluate whether fatty liver was improved after discontinuation of tamoxifen because of the relatively short follow–up period. It would ascertain the causal relationship between tamoxifen use and fatty liver progression. Lastly, studies on Asians may not be applicable to all other races.

In conclusion, tamoxifen may be an important risk factor in the incidence and progression of fatty liver. Close follow-up and screening are necessary for high risk patients. Also, multidisciplinary approach with hepatologists should be considered for these populations. In the future, studies using accurate steatosis quantification (e.g., transient elastography, MR-based technique) may be needed with a large, prospective cohort.

Supporting information

S1 Fig. The flow chart of patients assessed for eligibility.

(DOCX)

Click here for additional data file.^{(69.9KB, docx)}

S2 Fig. Distribution of propensity score for balance between groups and covariance balance plot.

(DOCX)

Click here for additional data file.^{(73.7KB, docx)}

S3 Fig. Difference in survival rate according to aggravation of fatty liver.

(A) Before matching, (B) After matching.

(DOCX)

Click here for additional data file.^{(352.2KB, docx)}

S1 Table. Multivariable Cox proportional hazards regression for fatty liver aggravation (Before matching).

(DOCX)

Click here for additional data file.^{(34.1KB, docx)}

S2 Table. Propensity score matching analysis.

(DOCX)

Click here for additional data file.^{(40.4KB, docx)}

S3 Table. Univariable proportional hazards regression for fatty liver progression (After matching).

(DOCX)

Click here for additional data file.^{(45.4KB, docx)}

S4 Table. Univariable proportional hazards regression for death.

(DOCX)

Click here for additional data file.^{(36KB, docx)}

S5 Table. Propensity score matching analysis for the risk factors associated with fatty liver progression (caliper 0.3).

(DOCX)

Click here for additional data file.^{(33.3KB, docx)}

S6 Table. Propensity score matching analysis for the risk factors associated with fatty liver progression (caliper 0.1).

(DOCX)

Click here for additional data file.^{(33.5KB, docx)}

Acknowledgments

We thank Eun-Ae Jung (Librarian, Medical Library, Soonchunhyang University Bucheon Hospital) for carefully proofreading the manuscript.

List of abbreviations

AI: aromatase inhibitor
ALT: alanine aminotransferase
ANOVA: analysis of variance
AST: aspartate aminotransferase
BMI: body mass index
CI: confidence interval
CT: computed tomography
ER: estrogen receptor
HR: hazard ratio
HU: hounsfield unit
MR: magnetic resonance
PR: progesterone receptor
PS: propensity score
ROI: regions of interest
SERM: selective estrogen receptor modulator
USG: ultrasonography

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

The author(s) received no specific funding for this work.

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PLoS One. doi: 10.1371/journal.pone.0236506.r001

Decision Letter 0

Hakan Buyukhatipoglu

22 May 2020

PONE-D-20-05309

Risk of fatty liver after long-term use of tamoxifen in patients with breast cancer

PLOS ONE

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PLOS ONE

Additional Editor Comments:

Authors spent a lot effort in this study and worths publishing. However it needs several improvements. Firstly please closely address the reviewers' suggestions. Additionally:

1) what kind of retrospective study is this) (ie. case-control, cohort etc.) You should include that. Which anova test did you use, one-way anova?

2) It seemed that a level of p<0.10 was used for selection of variables in order to include cox-regression analysis. You should explain about why you chose this significance level?

3) which model did you use for cox-regression (forward, enter, etc)?

4) Flow of discussion is not well. Especially first two paragraphs are not necessary looks like introduction. Please fully revise the discussion and discuss and focus on your objectives and results. Unnecessary review of tamoxifen is not appropriate.

5) Retrospective nature of this study is the main shortage of this study you should emphasize that in the limitations.

6) Please specifically address the statistical concerns of reviewer 2.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. 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: Partly

Reviewer #3: Partly

**********

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

Reviewer #1: Yes

Reviewer #2: I Don't Know

Reviewer #3: No

**********

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

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

Reviewer #1: No

Reviewer #2: No

Reviewer #3: Yes

**********

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

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Review Comments to the Author

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

Reviewer #1: This topic is of interest. The usage of tamoxifen is common in clinical work, therefore it is urgent to analyze the effect of tamoxifen on life quality and clinical prognosis in patients with breast cancer. In this retrospective study, the authors found that tamoxifen had a significant effect on the deterioration of fatty liver status compared to other treatment modalities in breast cancer patients. But fatty liver progression did not affect the prognosis of breast cancer patients and further follow-up might be needed and the effect of tamoxifen on cardiovascular disease needs further exploration. Here I have only several minor comments.

1.Statistical proper nouns such as 95%CI, IQR and HR should be expressed in italic form. The authors should check the manuscript and correct some erros.

2.The cross tab analysis was perfomed to compare the basline information between groups. However, some data meet the criteria for Fisher exact test in Table 1. The authors might check the data and methods and marked out the groups with Fisher exact test.

3.The list of abbreviations in page 2 was not in alphabetical order. I would suggest the author to rearrange in alphabetical order for reading convenience.

4.There are some typos and grammatical mistakes in this manuscript. But I believe that the author will check and correct in the revision.

Reviewer #2: It was interesting to read the paper ‘Risk of fatty liver after long-term use of tamoxifen in patients with breast cancer” by Yoo et al. where the authors highlight the aggravation of fatty liver disease by long term use of Tamoxifen by patients for breast cancer. It was a single-centred retrospective study.

The paper is well written but have raised a number if question which need further explanation. On balance, I feel that some of the important questions need explanation before considering this manuscript for publication. I have listed my comments as follows with my queries:

1- It’s a retrospective study which mean that the data collection was predominantly depended upon what was available from resources. This is a main drawback of most retrospective studies which result in difficulty of drawing any meaningful conclusion.

2- Ultrasonography is widely used for assessment and follow up of fatty liver disease however there are number of studies reporting significant interobserver and intra-observer variability in reporting the degree of fatty liver disease even by experienced radiologists. Such variabilities were also reported in term of CT scan evaluation of fatty liver disease. In this study, baseline assessment of fatty liver disease was done by ultrasonography and CT scan. The author stated that all UDSG and CT images were reported by two radiologists who were blinded to the study aims and drugs but the Autor didn’t explain whether all patients have ultrasound scans as well as CT or some have USG while others have CT? Also it is important to explain whether follow up assessment was done by the same mode of imaging as base line? Nevertheless, there remains a significant weakness in this study due to interobserver / intraobserver variability leading to lack of solid conclusion on progression of fatty liver disease. Some of the related referenced are as follows.

Ref:

Cengiz, Mustafa et al. “Sonographic assessment of fatty liver: intraobserver and interobserver variability.” International journal of clinical and experimental medicine vol. 7,12 5453-60. 15 Dec. 2014

Hamer OW, Aguirre DA, Casola G, Lavine JE, Woenckhaus M, Sirlin CB. Fatty liver: imaging patterns and pitfalls. Radiographics. 2006;26:1637–53.

3- The author didn’t explain whether the baseline assessment of fatty liver disease was done at the same post-operative intervals in all groups as there are studies reporting the presence of some degree of fatty changes in the liver post-operatively which improve with times.

4- It would be important to know the dietary habits of these patient as there are studies reporting association of fatty liver disease with diet.

5- Similarly, a detailed drug history is also important as patients in this study had underlying Diabetes and Hypertension but it is important to know the type of antihypertensive and diabetic medication in each group

6- It is also important to know whether any patient was taken off Tamoxifen during the follow up period and any subsequent improvement in the hepatic steatosis.

7- In discussion section, it should be mentioned about any correlation between degree of hepatic steatosis with drug dosage or duration. Also whether the changes in liver enzymes were in line with worsening of hepatic steatosis ?

Once authors have explained this queries , the manuscript can be resubmitted for further review .

Reviewer #3: A well-done, medium-volume, retrospective study. But no new data. My comments to the authors were as follow:

1- What is meant by “significant alcohol consumption” term at the exclusion criteria?

2- When you look at the values given at the table I; the difference between the groups for “age, BMI, platelets, AST, ALT, albümin, bilirubin, fasting blood glucose” looks too small. So p values seem to be wrong. Please check.

3- I cannot judge about the accuracy of propensity score matching analysis. I recommend an extra evaluation by a qualified statistician.

4- At table I what is meant by “treatment duration”; follow-up time?, chemotherapy?, tamoxifen. What is the treatment of control group?

5- No data was given about the chemotherapy? Chemotherapeutic agents can also cause fatty liver.

6- Along with ultrasonography, fibroscan can be a more valuable method of monitoring.

7- Some current and valuable articles are not referenced. Below you can fınd two sample:

a) Lee B, Jung EA, Yoo JJ, Kim SG, Lee CB, Kim YS, Jeong SW, Jang JY, Lee SH, Kim HS, Jun BG, Kim YD, Cheon GJ. Prevalence, incidence and risk factors of tamoxifen-related non-alcoholic fatty liver disease: A systematic review and meta-analysis. Liver Int. 2020 Mar 14. doi: 10.1111/liv.14434.

b) Hong N, Yoon HG, Seo DH, Park S, Kim SI, Sohn JH, Rhee Y. Different patterns in the risk of newly developed fatty liver and lipid changes with tamoxifen versus aromatase inhibitors in postmenopausal women with early breast cancer: A propensity score-matched cohort study. Eur J Cancer. 2017 Sep;82:103-114. doi: 10.1016/j.ejca.2017.05.002.

**********

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: Yes: Huseyin Alkim

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

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PLoS One. 2020 Jul 30;15(7):e0236506. doi: 10.1371/journal.pone.0236506.r002

Author response to Decision Letter 0

4 Jul 2020

Response to the Associate Editor’s and Reviewers’ Comments

3 July, 2020

Dear reviewers and editorial staffs at Plos One,

We are sincerely grateful for your thorough consideration and review of our manuscript, “Risk of Fatty Liver after Long-Term Use of Tamoxifen in Patients with Breast Cancer”, control number PONE-D-20-05309. Thanks to the accurate comments made by the reviewers, we could better understand the critical issues in this paper. We have modified the manuscript according to the reviewer’s suggestions. We hope that our revised manuscript will be considered and accepted for publication in Plos One. We acknowledge that the scientific and clinical quality of our manuscript has been improved with the guidance of the reviewers and editors.

The changes within the revised manuscript were highlighted (underlined and in blue). Point-by-point responses to the reviewers’ comments are provided below.

Editor:

1) Editor’s comment: What kind of retrospective study is this? (i.e. case-control, cohort etc.) You should include that. Which anova test did you use, one-way anova?

Author’s response: Thank you for the valuable advice. This study was a retrospective cohort study. We added this information to the Method section according to the editor’s recommendation. Regarding the anove test, we used one-way ANOVA test. We also added this information to the Method section. The Method of the manuscript was revised as follows:

“This was a single-center, retrospective cohort study.” (page 12, lines 14 –page 13, lines 2)

“Statistical differences between groups were investigated using one-way analysis of variance (ANOVA) or Student’s t-test for continuous variables and chi-squares test or Fisher’s exact test for categorical variables as appropriate.” (page 12, lines 14 –page 13, lines 2)

2) Editor’s comment: It seemed that a level of p<0.10 was used for selection of variables in order to include cox-regression analysis. You should explain about why you chose this significance level?

Author’s response: Thank you for the valuable advice. It is difficult to include all the variables into the multiple regression model due to limited number of events according to the practical thumb of rule, which is based on the following reference. Thus, we chose the criterion of 0.1 in our study. We described this fact in statistical analysis and added the reference. The Method section of the manuscript was revised as follows:

“Any variable showing a significance at 0.1 in the univariate model was selected as a candidate for the multivariable model [17].” (page 12, lines 14 –page 13, lines 2)

“(Reference) 17. Hosmer Jr, D. W., Lemeshow, S., & May, S. (2011). Applied survival analysis: regression modeling of time-to-event data (Vol. 618). John Wiley & Sons.” (page 12, lines 14 –page 13, lines 2)

3) Editor’s comment: Which model did you use for cox-regression (forward, enter, etc)?

Author’s response: Thank you for the valuable advice. We used the step-wise selection for the final multiple model. We added this method in the statistical analysis. The Method section of the manuscript was revised as follows:

“The final multiple Cox PH regression model was chosen by the stepwise selection based on the Akaike information criterion (AIC).” (page 12, lines 14 –page 13, lines 2)

4) Editor’s comment: Flow of discussion is not well. Especially the first two paragraphs do not necessary look like the introduction. Please fully revise the discussion and discuss and focus on your objectives and results. Unnecessary review of tamoxifen is not appropriate.

Author’s response: Thank you for the valuable advice. As recommended, the two unnecessary paragraphs of the discussion were deleted, and the other paragraph of the discussion was modified.

5) Editor’s comment: Retrospective nature of this study is the main shortage of this study you should emphasize that in the limitations.

Author’s response: Thank you for the valuable advice. For limitations arising from retrospective research, content was added to the discussion as recommended. The discussion of the manuscript was revised as follows:

“Our study has several limitations. First, the main limitation is predominant from its retrospective nature. The patients were not randomly assigned to the modalities which meant that the choice of modalities might have been biased.” (page 12, lines 14 –page 13, lines 2)

6) Editor’s comment: Please specifically address the statistical concerns of reviewer 2.

Author’s response: Thank you for the advice. The detailed answers to reviewer 2's questions are listed below.

Reviewer #1 :

1) Reviewer’s comment: Statistical proper nouns such as 95%CI, IQR and HR should be expressed in italic form. The authors should check the manuscript and correct some errors.

Author’s response: Thank you for the valuable advice. We corrected the above terms in italic form as recommended.

2) Reviewer’s comment: The cross tab analysis was performed to compare the baseline information between groups. However, some data meet the criteria for Fisher exact test in Table 1. The authors might check the data and methods and marked out the groups with Fisher exact test.

Author’s response: Thank you for the valuable advice. We additionally indicated items using the Fisher exact test. We added a footnote on Table 2 and described the method in statistical analysis. It is worth noting that stage and pathology variables received warnings from the chi-squares test due to the low expected frequency, however the numerous cells of these variables prevented testings by the Fisher’s exact test. Thus, we used the chi-squares test in those cases. The Method section of the manuscript was revised as follows:

3) Reviewer’s comment: The list of abbreviations in page 2 was not in alphabetical order. I would suggest the author to rearrange in alphabetical order for reading convenience.

Author’s response: Thank you for the valuable advice. We rearranged the abbreviations in alphabetical order.

4) Reviewer’s comment: There are some typos and grammatical mistakes in this manuscript. But I believe that the author will check and correct in the revision.

Author’s response: Thank you for the valuable advice. We received English proofreading once more and made the corrections.

Reviewer #2 :

1) Reviewer’s comment: It’s a retrospective study which mean that the data collection was predominantly depended upon what was available from resources. This is a main drawback of most retrospective studies which result in difficulty of drawing any meaningful conclusion.

Author’s response: Thank you for the valuable advice. For limitations arising from retrospective research, content was added to the Discussion section as recommended. The Discussion section of the manuscript was revised as follows:

“First, the main limitation is predominant from its retrospective nature. The patients were not randomly assigned to the modalities which meant that the choice of treatment might have been biased. Also, there were some subjects who had no imaging study during the follow-up period which resulted in missing data. Along with the above drawbacks, this study has been designed for bias-reduction by propensity score matching. This result can be used to implement further prospective cohort study.” (page 15, lines 13 –17)

2) Reviewer’s comment: Ultrasonography is widely used for assessment and follow up of fatty liver disease however there are number of studies reporting significant interobserver and intra-observer variability in reporting the degree of fatty liver disease even by experienced radiologists. Such variabilities were also reported in term of CT scan evaluation of fatty liver disease. In this study, baseline assessment of fatty liver disease was done by ultrasonography and CT scan. The author stated that all UDSG and CT images were reported by two radiologists who were blinded to the study aims and drugs but the Author didn’t explain whether all patients have ultrasound scans as well as CT or some have USG while others have CT? Also it is important to explain whether follow up assessment was done by the same mode of imaging as base line? Nevertheless, there remains a significant weakness in this study due to interobserver / intraobserver variability leading to lack of solid conclusion on progression of fatty liver disease. Some of the related referenced are as follows.

Ref:

Hamer OW, Aguirre DA, Casola G, Lavine JE, Woenckhaus M, Sirlin CB. Fatty liver: imaging patterns and pitfalls. Radiographics. 2006;26:1637–53.

Author’s response: Thank you for the valuable advice. We used only one technique (among CT or USG) in a patient as a diagnostic tool to determine fatty liver thoughout the follow-up period. For example, if a patient was first diagnosed fatty liver by ultrasound, the change of fatty liver was then determined by ultrasound. We added this information in the Method section as follows:

“We used only one technique (among CT or USG) as a diagnostic tool to determine fatty liver thoughout the follow-up period.” (page 15, lines 8 –9)

We acknowledge that what Reviewer #2’s pointed out is the main limitation of our research. CT and USG are most common modalities used for follow-up of breast cancer, as is recommended in the NCCN guideline.1. For the diagnostic ability of non-enhanced CT for fatty liver, sensivitiy of macrovesicular steatosis of 30% or greater was 0.991 (95% confidence interval: 0.960, 0.999), and specificity was 100% (95%CI: 97-100).2,3 In general, diagnostic performance of non-enhanced CT is comparable to USG and MR-PDFF.4. However, considering accessibility and price, it has advantages over MRI, and the inter-reader and intra-reader accordance is superior to ultrasound. In addition, recent studies by Artz et al.5 and Luca et al.6 suggested that simple ROI-based mean attenuation measurement with CT has an inverse linear relationship with fat content measured by MR spectroscopy. These studies imply that CT may be used as a quantitative imaging biomarker for both detection and quantification of liver fat content. We added this infomation in the Discussion section. The Discussion of the manuscript was revised as follows:

“Second, the quantification of steatosis was evaluated by either USG or CT. For the diagnostic ability of non-enhanced CT for fatty liver, sensitivity of macrovesicular steatosis of 30% or greater was 0.991 (95% CI: 0.960-0.999), and specificity was 1.0 (95% CI: 0.97, 1.00). In general, diagnostic performance of non-enhanced CT is comparable to USG and MR-PDFF. Considering accessibility and price, it has slight advantages over MRI, and the inter-reader and intra-reader accordance is superior to ultrasound. In addition, recent studies by Artz et al. and Luca et al. suggested that simple ROI-based mean attenuation measurement with CT has an inverse linear relationship with fat content measured by MR spectroscopy. These studies imply that CT may be used as a quantitative imaging biomarker for both detection and quantification of liver fat content.” (page 15, lines 8 –9)

3) Reviewer’s comment: The author didn’t explain whether the baseline assessment of fatty liver disease was done at the same post-operative intervals in all groups as there are studies reporting the presence of some degree of fatty changes in the liver post-operatively which improve with time.

Author’s response: Thank you for the valuable advice. Follow-up CT and ultrasound were performed every 6months for patients with high risk of recurrence, and every 12months for other patients, as recommended in the NCCN guideline.1. We added this infomation in the Method section which was revised as follows:

“To monitor possible recurrences of breast cancer, follow-up computed tomography (CT) or ultrasonography (USG) were performed every 6months for patients with high risk of recurrence, and every 12months for others as recommended in the NCCN guideline.” (page 12, lines 14 –page 13, lines 2)

4) Reviewer’s comment: It would be important to know the dietary habits of these patient as there are studies reporting association of fatty liver disease with diet.

Author’s response: Thank you for the valuable advice. In this study, the data of dietary habits were insufficient in the medical charts and could not be investigated. We are currently planning a prospective study and will definitely consider this point in the next one.

5) Reviewer’s comment: Similarly, a detailed drug history is also important as patients in this study had underlying Diabetes and Hypertension but it is important to know the type of antihypertensive and diabetic medication in each group.

Author’s response: Thank you for the valuable advice. In this study, medication intake was investigated by group, but information on individual drugs was insufficient and could not be investigated. We will definitely consider this in the subsequent study.

6) Reviewer’s comment: It is also important to know whether any patient was taken off Tamoxifen during the follow up period and any subsequent improvement in the hepatic steatosis.

Author’s response: Thank you for the valuable advice. The study did not include patients who discontinued tamoxifen. We agree that in the long run, changes after tamoxifen discontinuation are also essential. We added this limitation in the Discussion section.

“Third, we did not evaluate whether fatty liver was improved after discontinuation of tamoxifen because of the relatively short follow–up period. It would ascertain the causal relationship between tamoxifen use and fatty liver progression.” (page 12, lines 14 –page 13, lines 2)

7) Reviewer’s comment: In discussion section, it should be mentioned about any correlation between degree of hepatic steatosis with drug dosage or duration. Also whether the changes in liver enzymes were in line with worsening of hepatic steatosis?

Author’s response: Thank you for the valuable advice. We analyzed the association between the severity of fatty liver at baseline with the drug duration and ALT at baseline using the spearman’s correlation coefficient. They have no significant or clinically meaningful correlation as shown in following figures. We added this information in the Result section.

“Next, we performed a subgroup analysis in the tamoxifen group to find any correlations between the degree of hepatic steatosis with drug duration or changes in liver enzymes. However, we discovered no significant or clinically meaningful correlations when using the spearman’s correlation coefficient.” (page 12, lines 14 –page 13, lines 2)

Reviewer #3 :

1) Reviewer’s comment: What is meant by “significant alcohol consumption” term at the exclusion criteria?

Author’s response: Thank you for the valuable advice. We used the AASLD guideline and criteria. Ongoing or recent alcohol consumption >21 standard drinks on average per week in men and >14 standard drinks on average per week in women is used as a reasonable threshold for significant alcohol consumption. We added this information to the Method section which was revised as follows:

“Ongoing or recent alcohol consumption >21 standard drinks on average per week in men and >14 standard drinks on average per week in women was the criteria for significant alcohol consumption.” (page 15, lines 13 –17)

2) Reviewer’s comment: When you look at the values given at the table I; the difference between the groups for “age, BMI, platelets, AST, ALT, albümin, bilirubin, fasting blood glucose” looks too small. So p values seem to be wrong. Please check.

Author’s response: According to your considerable comment, we checked all the statistical results including Table 1, and they turned out to be identical to the previous ones. The difference of age, BMI, platelets, AST, ALT, albumin, bilirubin and fasting blood glucose seem to be small, but the large sample size might be beneficial to show the statistical significance since they have the small standard errors.

3) Reviewer’s comment: I cannot judge about the accuracy of propensity score matching analysis. I recommend an extra evaluation by a qualified statistician.

Author’s response: Thank you for the considerable comment. The caliper of 0.05 was applied in this study, but we generated two more matched sets assuming the narrower caliper, 0.03 and 0.01 for validation of propensity score matching. From those sets, we obtained the similar pattern of results related to the fatty liver progression of tamoxifen and added the supplementary tables 5 and 6. Also, we described the additional analysis for this validation in statistical analysis and result. The Method and Result section of the manuscript was revised as follows:

“We used the nearest available matching (1:1) method for PS matching with the caliper of 0.05. For validation , we generated additional matched datasets using the caliper of 0.03 and 0.01.” (page 15, lines 13 –17)

“The effect of tamoxifen on fatty liver progression was also confirmed to the same degree and significance in other matched datasets (HR: 1.4, 95% CI: 1.018-1.927 in dataset with caliper 0.3; HR: 1.452, 95% CI: 1.021-2.065 in dataset with caliper 0.1) (Supplementary Table 5 and 6).” (page 15, lines 13 –17)

4) Reviewer’s comment: At table I what is meant by “treatment duration”; follow-up time?, chemotherapy?, tamoxifen. What is the treatment of control group?

Author’s response: The definition of "treatment duration" is the duration of taking tamoxifen or aromatase inhibitor, respectively, in the tamoxifen or AI groups. In the case of the control group, it means the period of receiving chemotherapy or other conservative management.

5) Reviewer’s comment: No data was given about the chemotherapy? Chemotherapeutic agents can also cause fatty liver.

Author’s response: The chemotherapeutic agents of anticancer drugs are so diverse that they could not be described individually, but mostly anthracycline and taxane agents were used. In the case of the anti-cancer agent described above, there were no reports of significant fatty liver. The Method section of the manuscript was revised as follows:

“The chemotherapeutic agents of anticancer drugs were diverse, however, anthracycline and taxane-based chemotherapy was most widely used. ” (page 15, lines 13 –17)

6) Reviewer’s comment: Along with ultrasonography, fibroscan can be a more valuable method of monitoring.

Author’s response: Thank you for the valuable advice. We totally agree with the reviewer’s opinion. The proportion of patients who received fibroscan was small and could not be analyzed in this study. We are currently planning a prospective study and will definitely consider it in the next one.

7) Reviewer’s comment: Some current and valuable articles are not referenced. Below you can fınd two samples:

Author’s response: Thank you for the valuable advice. In the case of the first paper, it is a paper written by our group. We are honored to have it recommended and added it directly to the list of references.

Attachment

Submitted filename: Response_to_Reviewers_Yoo_et_al_20200703.docx

Click here for additional data file.^{(163.1KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0236506.r003

Decision Letter 1

Hakan Buyukhatipoglu

9 Jul 2020

Risk of fatty liver after long-term use of tamoxifen in patients with breast cancer

PONE-D-20-05309R1

Dear Dr. Kim,

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.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. 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.

Kind regards,

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0236506.r004

Acceptance letter

Hakan Buyukhatipoglu

15 Jul 2020

PONE-D-20-05309R1

Risk of fatty liver after long-term use of tamoxifen in patients with breast cancer

Dear Dr. Kim:

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.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Hakan Buyukhatipoglu

Academic Editor

PLOS ONE

Associated Data

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

Supplementary Materials

S1 Fig. The flow chart of patients assessed for eligibility.

(DOCX)

Click here for additional data file.^{(69.9KB, docx)}

S2 Fig. Distribution of propensity score for balance between groups and covariance balance plot.

(DOCX)

Click here for additional data file.^{(73.7KB, docx)}

S3 Fig. Difference in survival rate according to aggravation of fatty liver.

(A) Before matching, (B) After matching.

(DOCX)

Click here for additional data file.^{(352.2KB, docx)}

S1 Table. Multivariable Cox proportional hazards regression for fatty liver aggravation (Before matching).

(DOCX)

Click here for additional data file.^{(34.1KB, docx)}

S2 Table. Propensity score matching analysis.

(DOCX)

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S3 Table. Univariable proportional hazards regression for fatty liver progression (After matching).

(DOCX)

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S4 Table. Univariable proportional hazards regression for death.

(DOCX)

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S5 Table. Propensity score matching analysis for the risk factors associated with fatty liver progression (caliper 0.3).

(DOCX)

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S6 Table. Propensity score matching analysis for the risk factors associated with fatty liver progression (caliper 0.1).

(DOCX)

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Attachment

Submitted filename: Response_to_Reviewers_Yoo_et_al_20200703.docx

Click here for additional data file.^{(163.1KB, docx)}

Data Availability Statement

All relevant data are within the manuscript and its Supporting Information files.

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PERMALINK

Risk of fatty liver after long-term use of tamoxifen in patients with breast cancer

Jeong-Ju Yoo

Yong Seok Lim

Min Sung Kim

Bora Lee

Bo-Yeon Kim

Zisun Kim

Ji Eun Lee

Min Hee Lee

Sang Gyune Kim

Young Seok Kim

Roles

Abstract

Background

Methods

Results

Conclusions

Introduction

Materials and methods

Patients and study design

Diagnosis of fatty liver

Definition

Statistical analysis

Results

Patients’ demographics at baseline

Table 1. Baseline characteristics of patients.

Changes in fatty liver status over time

Table 2. Clinical characteristics depending on the status of fatty liver.

Fig 1. Cumulative incidence of fatty liver progression before propensity score matching.

Table 3. Multivariable analysis for the risk factors associated with fatty liver progression.

Propensity score matching analysis

Fig 2. Cumulative incidence of fatty liver progression after propensity score matching.

Table 4. Propensity score matching analysis for risk factors associated with fatty liver progression.

Prediction model associated with fatty liver progression

Table 5. Prediction model related to fatty liver progression.

Effect of fatty liver progression on mortality

Table 6. Multivariable Cox proportional hazards regression for death.

Discussion

Supporting information

Acknowledgments

List of abbreviations

Data Availability

Funding Statement

References

Decision Letter 0

Hakan Buyukhatipoglu

Roles

Author response to Decision Letter 0

Decision Letter 1

Hakan Buyukhatipoglu

Roles

Acceptance letter

Hakan Buyukhatipoglu

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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