Real-world Effectiveness and Tolerability of Interferon-free Direct-acting Antiviral for 15,849 Patients with Chronic Hepatitis C: A Multinational Cohort Study

doi:10.14218/JCTH.2024.00089

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Real-world Effectiveness and Tolerability of Interferon-free Direct-acting Antiviral for 15,849 Patients with Chronic Hepatitis C: A Multinational Cohort Study

Fanpu Ji^1,#,
Sally Tran^2,#,
Eiichi Ogawa³,
Chung-Feng Huang^4,5,
Takanori Suzuki⁶,
Yu Jun Wong^7,8,
Hidenori Toyoda⁹,
Dae Won Jun^10,11,
Liu Li¹²,
Haruki Uojima¹³,
Akito Nozaki¹⁴,
Makoto Chuma¹⁴,
Cheng-Hao Tseng¹⁵,
Yao-Chun Hsu¹⁵,
Masatoshi Ishigami¹⁶,
Takashi Honda¹⁶,
Masanori Atsukawa¹⁷,
Hiroaki Haga¹⁸,
Masaru Enomoto¹⁹,
Huy Trinh²⁰,
Carmen Monica Preda²¹,
Phillip Vutien²²,
Charles Landis²²,
Dong Hyun Lee²³,
Tsunamasa Watanabe²⁴,
Hirokazu Takahashi^25,26,
Hiroshi Abe²⁷,
Akira Asai²⁸,
Yuichiro Eguchi^25,29,
Jie Li³⁰,
Xiaozhong Wang³¹,
Jia Li³²,
Junping Liu³³,
Jing Liang³⁴,
Carla Pui-Mei Lam³⁵,
Rui Huang³⁰,
Qing Ye³⁴,
Hongying Pan³⁶,
Jiajie Zhang³⁶,
Dachuan Cai³⁷,
Qi Wang³⁸,
Daniel Q. Huang^39,40,
Grace Wong^41,42,
Vincent Wai-Sun Wong⁴¹,
Junyi Li¹²,
Son Do⁴³,
Norihiro Furusyo⁴⁴,
Makoto Nakamuta⁴⁵,
Hideyuki Nomura⁴⁶,
Eiji Kajiwara⁴⁷,
Eileen L. Yoon^10,11,
Sang Bong Ahn⁴⁸,
Koichi Azuma⁴⁹,
Kazufumi Dohmen⁵⁰,
Jihyun An⁵¹,
Do Seon Song⁵²,
Hyun Chin Cho⁵³,
Akira Kawano⁵⁴,
Toshimasa Koyanagi⁵⁵,
Aritsune Ooho⁵⁶,
Takeaki Satoh⁵⁷,
Kazuhiro Takahashi⁵⁸,
Ming-Lun Yeh^4,5,
Pei-Chien Tsai^4,5,
Satoshi Yasuda⁹,
Yunyu Zhao¹,
Yishan Liu¹,
Tomomi Okubo⁵⁹,
Norio Itokawa¹⁷,
Mi Jung Jun²³,
Toru Ishikawa⁶⁰,
Koichi Takaguchi⁶¹,
Tomonori Senoh⁶¹,
Mingyuan Zhang⁶²,
Changqing Zhao⁶³,
Raluca Ioana Alecu²¹,
Wei Xuan Tay⁷,
Pooja Devan⁷,
Joanne Kimiko Liu²²,
Ritsuzo Kozuka⁶⁴,
Elena Vargas-Accarino⁶⁵,
Ai-Thien Do⁴³,
Mayumi Maeda²,
Wan-Long Chuang⁴,
Jee-Fu Huang^4,5,
Chia-Yen Dai^4,5,
Ramsey Cheung^2,66,
Maria Buti^65,67,
Junqi Niu⁶²,
Wen Xie³⁸,
Hong Ren³⁷,
Seng Gee Lim^39,40,
Chao Wu³⁰,
Man-Fung Yuen^35,68,
Jia Shang³³,
Qiang Zhu⁶⁹,
Yoshiyuki Ueno¹⁸,
Yasuhito Tanaka^6,70,
Jun Hayashi⁷¹,
Ming-Lung Yu^4,5,72 and
Mindie H. Nguyen^2,73,*

Journal of Clinical and Translational Hepatology 2024;12(7):646-658

doi: 10.14218/JCTH.2024.00089

Received: March 7, 2024

Revised: May 8, 2024

Accepted: May 22, 2024

Published online: June 17, 2024

Author information

1Department of Infectious Diseases, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China

2Division of Gastroenterology and Hepatology, Department of Medicine, Stanford University Medical Center, Palo Alto, CA, USA

3Department of General Internal Medicine, Kyushu University Hospital, Fukuoka, Japan

4Hepatobiliary Division, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung

5Hepatitis Research Center, College of Medicine and Center for Liquid Biopsy and Cohort Research, Kaohsiung Medical University, Kaohsiung

6Department of Gastroenterology and Metabolism, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan

7Gastroenterology & Hepatology, Changi General Hospital, Singhealth, Singapore

8Singhealth Duke-NUS Medicine Academic Clinical Program, Singapore

9Department of Gastroenterology, Ogaki Municipal Hospital, Ogaki, Japan

10Department of Internal Medicine, Hanyang University, College of Medicine, Seoul, Korea

11Hanyang Institute of Bioscience and Biotechnology, Hanyang University, Seoul, Korea

12Department of Hepatology, The Third People's Hospital of Kunming City, Kunming, Yunnan, China

13Department of Gastroenterology, Internal Medicine, Kitasato University School of Medicine, Sagamihara, Japan

14Gastroenterological Center, Yokohama City University Medical Center, Yokohama, Japan

15Division of Gastroenterology and Hepatology, Department of Internal Medicine, E-Da Cancer Hospital, Kaohsiung

16Department of Gastroenterology and Hepatology, Nagoya University Graduate School of Medicine, Nagoya, Japan

17Division of Gastroenterology and Hepatology, Nippon Medical School, Tokyo, Japan

18Department of Gastroenterology, Yamagata University Faculty of Medicine, Yamagata, Japan

19Department of Transfusion Medicine and Department of Hepatology, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan

20San Jose Gastroenterology, San Jose, CA, USA

21Gastroenterology & Hepatology Department, Clinic Fundeni Institute, Bucharest, Romania

22Division of Gastroenterology and Hepatology, University of Washington, Seattle, WA, USA

23Department of Gastroenterology, Good Gang-An Hospital, Busan, Korea

24Division of Gastroenterology and Hepatology, St. Marianna University School of Medicine, Kawasaki, Japan

25Liver Center, Saga University Hospital, Saga, Japan

26Division of Metabolism and Endocrinology, Saga University Faculty of Medicine, Saga, Japan

27Division of Gastroenterology and Hepatology, Shinmatsudo Central General Hospital, Chiba, Japan

282nd Department of Internal Medicine, Osaka Medical and Pharmaceutical University, Osaka, Japan

29Locomedical General Institute, Locomedical Eguchi Hospital, Saga, Japan

30Department of Infectious Diseases, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, China

31Affiliated Traditional Chinese Medicine Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China

32Department of Gastroenterology and Hepatology, The Second People's Hospital of Tianjin, Tianjin, China

33Department of Infectious Diseases, Henan Provincial People’s Hospital Affiliated to Zhengzhou University, Zhengzhou, Henan, China

34Department of Gastroenterology and Hepatology, The Third Central Hospital of Tianjin, Tianjin, China

35Department of Medicine, The University of Hong Kong, Hong Kong, China

36Department of Hepatology, Zhejiang Provincial People’s Hospital Affiliated to Zhejiang University, Hangzhou, Zhejiang, China

37Department of Infectious Diseases, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China

38Center of liver diseases, Beijing Ditan Hospital Affiliated to Capital Medical University, Beijing, China

39Division of Gastroenterology and Hepatology, National University Hospital, Singapore

40Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore

41Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China

42State Key Laboratory of Digestive Disease, The Chinese University of Hong Kong, Hong Kong, China

43Digestive Health Associates of Texas, Dallas, TX, USA

44Taihaku Avenue Clinic, Fukuoka, Japan

45Department of Gastroenterology, National Hospital Organization Kyushu Medical Center, Fukuoka, Japan

46Department of Internal Medicine, Haradoi Hospital, Fukuoka, Japan

47Hepatology Clinic, Kajiwara Clinic, Kitakyushu, Japan

48Department of Internal Medicine, Nowon Eulji Medical Center, Eulji University College of Medicine, Seoul, Korea

49Department of Medicine, Kyushu Central Hospital, Fukuoka, Japan

50Department of Internal Medicine, Chihaya Hospital, Fukuoka, Japan

51Department of Internal Medicine, Hanyang University, College of Medicine, Guri Hospital, Guri, Korea

52Division of Hepatology, Department of Internal Medicine, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Suwon, Korea

53Departments of Internal Medicine, Gyeongsang National University Hospital, Jinju, Korea

54Department of Medicine, Kitakyushu Municipal Medical Center, Fukuoka, Japan

55Department of Medicine, Fukuoka City Hospital, Fukuoka, Japan

56Department of Hepatology, Steel Memorial Yawata Hospital, Kitakyushu, Japan

57Center for Liver Disease, National Hospital Organization Kokura Medical Center, Kitakyushu, Japan

58Department of Medicine, Hamanomachi Hospital, Fukuoka, Japan

59Division of Gastoroentelorogy, Nippon Medcal School Chiba Hokusoh Hospital, Chiba, Japan

60Department of Gastroenterology, Saiseikai Niigata Hospital, Niigata, Japan

61Department of Hepatology, Kagawa Prefectural Central Hospital, Kagawa, Japan

62Department of Hepatology, The First Hospital of Jilin University, Changchun, Jilin, China

63Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China

64Department of Hepatology, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan

65Liver Diseases Group, Vall d’Hebron Research Institute, Barcelona, Spain

66Division of Gastroenterology and Hepatology, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA

67Liver Unit, Department of Internal Medicine, Hospital Universitari Valle d’Hebron and Universitat Autònoma de Barcelona, Barcelona, Spain

68State Key Laboratory of Liver Research, The University of Hong Kong, Hong Kong, China

69Department of Gastroenterology, Shandong Provincial Hospital Affiliated to Shandong University, Ji’nan, Shandong, China

70Department of Gastroenterology and Hepatology, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan

71Kyushu General Internal Medicine Center, Haradoi Hospital, Fukuoka, Japan

72School of Medicine and Doctoral Program of Clinical and Experimental Medicine, College of Medicine and Center of Excellence for Metabolic Associated Fatty Liver Disease, National Sun Yat-sen University, Kaohsiung

73Department of Epidemiology and Population Health, Stanford University, Stanford, CA, USA

^#Contributed equally to this work.

*Correspondence to: Mindie H. Nguyen, MD, MAS, Professor of Medicine (Gastroenterology and Hepatology) and, by courtesy, of Epidemiology and Population Health, Stanford University Medical Center, 780 Welch Road, CJ250K, Palo Alto, CA 94304, USA. ORCID: https://orcid.org/0000-0002-6275-4989 . Tel: +1-650-498-6084, E-mail: [email protected].

Citation: Ji F, Tran S, Ogawa E, Huang CF, Suzuki T, Wong YJ, et al. Real-world Effectiveness and Tolerability of Interferon-free Direct-acting Antiviral for 15,849 Patients with Chronic Hepatitis C: A Multinational Cohort Study. J Clin Transl Hepatol. 2024;12(7):646-658. doi: 10.14218/JCTH.2024.00089.

Abstract

Background and Aims

As practice patterns and hepatitis C virus (HCV) genotypes (GT) vary geographically, a global real-world study from both East and West covering all GTs can help inform practice policy toward the 2030 HCV elimination goal. This study aimed to assess the effectiveness and tolerability of DAA treatment in routine clinical practice in a multinational cohort for patients infected with all HCV GTs, focusing on GT3 and GT6.

Methods

We analyzed the sustained virological response (SVR12) of 15,849 chronic hepatitis C patients from 39 Real-World Evidence from the Asia Liver Consortium for HCV clinical sites in Asia Pacific, North America, and Europe between 07/01/2014–07/01/2021.

Results

The mean age was 62±13 years, with 49.6% male. The demographic breakdown was 91.1% Asian (52.9% Japanese, 25.7% Chinese/Taiwanese, 5.4% Korean, 3.3% Malaysian, and 2.9% Vietnamese), 6.4% White, 1.3% Hispanic/Latino, and 1% Black/African-American. Additionally, 34.8% had cirrhosis, 8.6% had hepatocellular carcinoma (HCC), and 24.9% were treatment-experienced (20.7% with interferon, 4.3% with direct-acting antivirals). The largest group was GT1 (10,246 [64.6%]), followed by GT2 (3,686 [23.2%]), GT3 (1,151 [7.2%]), GT6 (457 [2.8%]), GT4 (47 [0.3%]), GT5 (1 [0.006%]), and untyped GTs (261 [1.6%]). The overall SVR12 was 96.9%, with rates over 95% for GT1/2/3/6 but 91.5% for GT4. SVR12 for GT3 was 95.1% overall, 98.2% for GT3a, and 94.0% for GT3b. SVR12 was 98.3% overall for GT6, lower for patients with cirrhosis and treatment-experienced (TE) (93.8%) but ≥97.5% for treatment-naive patients regardless of cirrhosis status. On multivariable analysis, advanced age, prior treatment failure, cirrhosis, active HCC, and GT3/4 were independent predictors of lower SVR12, while being Asian was a significant predictor of achieving SVR12.

Conclusions

In this diverse multinational real-world cohort of patients with various GTs, the overall cure rate was 96.9%, despite large numbers of patients with cirrhosis, HCC, TE, and GT3/6. SVR12 for GT3/6 with cirrhosis and TE was lower but still excellent (>91%).

Graphical Abstract

Keywords

Hepatitis C virus, Liver cirrhosis, Hepatocellular carcinoma, Genotype, DAA, REAL-C

Introduction

Hepatitis C virus (HCV) infection is a significant global health problem. Chronic hepatitis C (CHC) can result in the progression of liver disease, including liver cirrhosis, hepatocellular carcinoma (HCC), and liver-related mortality.¹ As of 2020, an estimated 56.8 million individuals worldwide are affected by chronic HCV infection, indicating a decrease from the 71 million estimated in 2015.² However, despite this decline, the goal of globally eliminating HCV by 2030 remains distant. The advent of direct-acting antiviral (DAA) medications has revolutionized the treatment of HCV infection by allowing shorter treatment durations and enhancing the efficiency of sustained virological response (SVR). Achieving SVR improves patient outcomes by reducing the risk of liver disease progression and its associated complications.^3–6

Globally, HCV genotypes (GTs) 1, 2, 3, 4, and 6 are the most prevalent. HCV GTs can play a crucial role in predicting the risk of disease progression and the response to treatment. For example, GT3 has been associated with an increased risk of treatment failure and the emergence of resistance-associated substitutions.^7,8 HCV GT distribution also varies geographically, with GT1 accounting for the highest proportion of HCV cases globally (46.2%) and being the predominant GT in most Western countries. GT3 is the second most common genotype (30.1%) and is more prevalent in South Asia and Western China. Other GTs, including GT2 (9.1%), GT4 (8.3%), and GT6 (5.4%), are more common in East and Southeast Asia, North Africa, and the Middle East.^9–11 Geographical variations in HCV GT distribution, access to healthcare, and the availability of effective treatment options all contribute to the complexity of treatment outcomes. Consequently, conducting a global real-world HCV study encompassing data from both East and West is important and can guide medical practice and public health policy to achieve the 2030 HCV elimination goal.

In this study, using a large cohort of patients with CHC derived from the Real-World Evidence from the Asia Liver Consortium for HCV (REAL-C) database, we aimed to assess the effectiveness and tolerability of DAA treatment in routine clinical practice for patients infected with all HCV GTs. Since GT3 is still more difficult to treat, especially for patients with GT3b and cirrhosis, and there are still conflicting data on low SVR rates for GT6,^7,8,12–14 this study focused on SVR outcomes and factors associated with lower treatment response for patients with GT3 and GT6 infections.

Methods

Study design and study patients

This multinational, non-interventional study extracted patient data from the REAL-C database using a standardized case report form and unified variable definitions at each study center. REAL-C is an international consortium comprising 39 study centers from North America, Europe, and the Asia-Pacific region. Details of this registry have been described previously and include CHC patients monitored and treated in routine practice.¹⁵ The study was conducted by the Declaration of Helsinki and approved by the Institutional Review Board at Stanford University, Stanford, CA, USA, and at each participating study center.

Patients were included if they were adults (18 years or older), received any interferon (IFN)-free DAA regimen for the treatment of CHC of any GT between July 1, 2014, and July 1, 2021, regardless of a history of cirrhosis or HCC, prior treatment, and had adequate medical records for the primary endpoint assessment. Patients with a prognosis of < 12 months were excluded.

Study assessment

Patient demographic information, clinical characteristics, and laboratory data were collected at baseline. The demographic information included age, gender, and race/ethnicity. The clinical characteristics included the presence of cirrhosis, active/inactive HCC, co-infection with HBV/HIV, comorbidities, treatment history, and the specific DAA treatment regimens administered. Patients with inactive HCC were defined as those who had undergone local ablation (such as alcohol injection, radiofrequency ablation, or microwave ablation), surgical resection, or liver transplantation and had no evidence of HCC recurrence on imaging within the three months preceding the initiation of DAA treatment. The choice of antiviral therapy was solely determined by the treating physician, taking into consideration factors such as HCV GTs, local preferences, insurance coverage, prior treatment history, and the presence of cirrhosis.

The baseline laboratory data included HCV GT, platelet count, total bilirubin, alanine aminotransferase, aspartate aminotransferase, albumin, creatinine, estimated glomerular filtration rate, fibrosis-4 index, and aspartate aminotransferase to platelet ratio index. The HCV RNA viral load was determined both at the time of DAA initiation and 12 weeks after the end of treatment using a real-time reverse transcriptase polymerase chain reaction assay.

The primary endpoint was the achievement of SVR12, defined as an undetectable HCV RNA level (with a detection threshold of 25 IU/mL or lower) at 12 weeks after the completion of treatment. The secondary endpoint was the assessment of tolerability, including treatment-related adverse events (AEs), treatment discontinuation, and death.

Statistical analysis

Categorical variables were expressed as numbers (percentages) and evaluated by χ² or Fisher’s exact test as appropriate. Continuous variables were expressed as mean±standard deviation and evaluated by Student’s t-test for normally distributed data or Mann-Whitney U-tests if not. Logistic regression analysis was used to identify any independent baseline factors influencing treatment response. We estimated the odds ratio (OR) associated with achieving SVR12 in each subgroup and its 95% confidence intervals (95% CI). Factors included in the logistic regression models were chosen based on prior knowledge, and those with an univariable OR value of p < 0.1 were considered for inclusion in the multivariable model. A two-tailed p < 0.05 was considered statistically significant. All statistical analyses were performed using STATA version 17.0 (StataCorp LLC, USA).

Results

Patient characteristics and treatment regimens

Our study analyzed a total of 15,849 patients treated with IFN-free DAA in routine practice from 39 centers across North America, Europe, and the Asia-Pacific region. As shown in Table 1, the mean age of the cohort was 62±13 years, 49.6% were male, and most were Asian (91.1%: 52.9% Japanese, 25.7% Chinese and Taiwanese, 5.4% Korean, 3.3% Malaysian, and 2.9% Vietnamese), followed by White (6.4%), Hispanic/Latino (1.3%), Black/African-American (1.0%), American Indian/Alaska Native (0.1%), and others (0.3%). In this study, 24.9% were treatment-experienced (TE: 20.7% with IFN regimens and 4.3% with DAA), 34.8% had cirrhosis (10.7% of these with decompensated cirrhosis, classified as CTP class B in 9.1% and CTP class C in 1.6%), 8.6% had preexisting HCC (78.6% inactive, 21.4% active), and 3.0% and 1.7% were co-infected with HBV or HIV, respectively. In addition, common comorbidities included hypertension (37.6%), diabetes (18.9%), dyslipidemia (8.8%), and cardiovascular disease (6.7%) (Table 1).

Table 1

Baseline characteristics of patients who initiated antiviral therapy

Characteristics	All Genotypes (n=15,849)	Genotype 1 (n=10,246)	Genotype 2 (n=3,686)	Genotype 3 (n=1,151)	Genotype 4 (n=47)	Genotype 5 (n=1)	Genotype 6 (n=457)	Untyped GTs (n=261)
Age, year	62±13	64±13	61±13	50±10	58±11	48	60±13	54±13
Male, n (%)	7,866 (49.6)	4,803 (46.9)	1,696 (46.0)	921 (80.0)	28 (59.6)	1 (100)	244 (53.4)	173 (66.3)
Ethnicity, n (%) (n=15,663)
Asian	14,263 (91.1)	9,110 (89.5)	3,602 (97.9)	951 (83.3)	16 (35.6)	–	454 (99.3)	130 (80.3)
White	995 (6.4)	763 (7.5)	54 (1.5)	150 (13.1)	9 (20.0)		0	19 (11.7)
Black/African-American	149 (1.0)	125 (1.2)	5 (0.1)	3 (0.3)	13 (28.9)		0	3 (1.9)
Hispanic/Latino	197 (1.3)	135 (1.3)	16 (0.4)	31 (2.7)	6 (13.3)		0	9 (5.6)
American Indian/Alaska Native	9 (0.1)	8 (0.1)	0	1 (0.1)	0		0	0
Others	50 (0.3)	37 (0.4)	2 (0.1)	6 (0.5)	1 (2.2)		3 (0.7)	1 (0.6)
Treatment experienced, n (%) (n=15,725)	3,922 (24.9)	2,995 (29.5)	691 (18.9)	99 (8.6)	13 (28.3)	0	76 (16.7)	48 (19.2)
Interferon regimens	3,249 (20.7)	2,455 (24.2)	614 (16.8)	65 (5.7)	11 (23.9)	0	67 (14.8)	37 (14.8)
DAA regimens	699 (4.3)	537 (5.3)	77 (2.1)	34 (3.0)	2 (4.4)	0	8 (1.8)	11 (4.4)
HBV co-infection, n (%) (n=11,835)	353 (3.0)	218 (2.9)	73 (2.7)	29 (2.7)	1 (3.2)	–	22 (5.7)	10 (7.4)
HIV co-infection, n (%) (n=7,363)	124 (1.7)	32 (0.8)	11 (0.7)	49 (4.7)	1 (3.9)	–	6 (1.7)	25 (12.6)
HCC, n (%) (n=15,811)	1,352 (8.6)	992 (9.7)	242 (6.6)	72 (6.3)	2 (4.3)	–	18 (3.9)	26 (10.0)
HCC status, n (%) (n=1,312)
Inactive	1,031 (78.6)	778 (80.2)	176 (76.2)	42 (60.0)	2 (100)	–	13 (72.2)	20 (95.2)
Active	281 (21.4)	192 (19.8)	55 (23.8)	28 (40.0)	0	–	5 (27.8)	1 (4.8)
Cirrhosis, n (%)	5,502 (34.8)	3,748 (34.6)	1,007 (27.3)	468 (40.8)	21 (44.7)	–	156 (34.2)	102 (39.2)
Cirrhosis stages, n (%) (n=3297)
CTP A	2,947 (89.4)	2,091 (89.7)	583 (92.7)	202 (80.2)	10 (90.9)		38 (90.5)	23 (69.7)
CTP B	299 (9.1)	207 (8.9)	41 (6.5)	40 (15.9)	1 (9.1)		3 (7.1)	7 (21.2)
CTP C	51 (1.6)	32 (1.4)	5 (0.8)	10 (4.0)	0		1 (2.4)	3 (9.1)
AST, IU/L	45 (30–70)	45 (31–69)	41 (27–72)	52 (35–80)	34 (24–72)	30	44 (29–72)	45 (29–74)
ALT, IU/L	43 (27–77)	43 (27–72)	40 (23–79)	58 (34–96)	40 (25–90)	35	53 (29–90)	66 (40–99)
Platelet count, ×10³ U/L	164±70	159±68	172±69	175±78	181±74	–	179±70	181±80
Albumin, g/dL	4.1±0.5	4.0±0.5	4.1±0.5	4.1±0.7	4.0±0.5	–	4.1±0.5	4.1±0.7
Total bilirubin, mg/dL	0.7 (0.6–1)	0.7 (0.6–1)	0.7 (0.5–1)	0.8 (0.5–1.1)	0.6 (0.4–0.8)	–	0.7 (0.5–1)	0.7 (0.5–1)
FIB–4	2.8 (1.7–4.9)	3.1 (1.9–5.2)	2.5 (1.5–4.4)	2.0 (1.2–4.0)	2.4 (1.2–3.3)	–	2.0 (1.4–3.9)	2.0 (1.1–3.7)
APRI	0.7 (0.4–1.5)	0.8 (0.4–1.5)	0.6 (0.3–1.4)	0.8 (0.5–1.6)	0.6 (0.3–1.3)	–	0.6 (0.4–1.3)	0.6 (0.4–1.5)
Creatinine, mg/dL	0.8 (0.6–0.9)	0.8 (0.6–0.9)	0.7 (0.6–0.9)	0.9 (0.7–1.0)	0.8 (0.6–1.0)	–	0.8 (0.7–1.0)	0.8 (0.6–1.0)
eGFR, mL/m/1.73 m²	88±22	86±22	89±23	93±20	95±23	–	85±23	92±26
HCV RNA, log10 IU/mL	6.0±0.8	6.0±0.8	5.9±1.0	6.0±0.9	5.8±0.8	6.9	6.3±0.9	6.1±0.9
>800,000 IU/mL	9,758 (63.2)	6,438 (64.2)	2,076 (57.5)	745 (68.7)	24 (53.3)	1 (100)	309 (72.0)	165 (66.5)
Comorbidity, n (%)						–
Diabetes (n=14,674)	2,772 (18.9)	1,898 (20.1)	660 (19.1)	89 (8.4)	10 (23.3)		73 (17.0)	42 (17.0)
Hypertension (n=11,674)	4,387 (37.6)	2,991 (39.2)	1,043 (37.1)	125 (23.0)	20 (51.3)		146 (34.3)	62 (27.9)
Dyslipidemia (n=11,630)	1,026 (8.8)	656 (8.7)	254 (8.9)	45 (8.5)	5 (13.2)		49 (11.5)	17 (7.8)
Cardiovascular disease (n=9,491)	636 (6.7)	443 (7.3)	146 (6.6)	27 (5.1)	1 (2.8)		11 (2.6)	8 (3.7)
DAA treatment regimens						–
DCV/ASV	2,357 (14.9)	2,351 (23.0)	5 (0.1)	1 (0.1)	0		0	0
PrOD±RBV	1,603 (10.1)	1,527 (14.9)	75 (2.0)	0	0		0	1 (0.4)
EBR/GZR	847 (5.3)	825 (8.1)	3 (0.1)	0	6 (12.8)		2 (0.4)	11 (4.2)
SOF/LDV±RBV	4,856 (30.6)	4,375 (42.7)	132 (3.6)	24 (2.1)	25 (53.2)	1 (100)	219 (47.9)	80 (30.7)
SOF/RBV	2,785 (17.6)	74 (0.7)	2,593 (70.4)	82 (7.1)	2 (4.3)		22 (4.8)	12 (4.6)
SOF/DCV±RBV	382 (2.4)	96 (0.9)	149 (4.0)	102 (8.9)	0		16 (3.5)	19 (7.3)
GLE/PIB	1,219 (7.7)	530 (5.2)	494 (13.4)	68 (5.9)	5 (10.6)		70 (15.3)	52 (19.9)
SOF/VEL±RBV	1,640 (10.4)	381 (3.7)	205 (5.6)	851 (73.9)	8 (17.0)		122 (26.7)	73 (28.0)
Others	160 (1.0)	87 (0.9)	30 (0.8)	23 (2.0)	1 (2.1)		6 (1.3)	13 (5.0)

HCC, Hepatocellular carcinoma; HCV, Hepatitis C virus; HBV, Hepatitis B virus; HIV, Human immunodeficiency virus; DAA, Direct-acting antiviral; ALT, Alanine aminotransferase; AST, Aspartate aminotransferase; FIB-4, Fibrosis-4 index; APRI, AST to platelet ratio index; CTP, Child-Turcotte-Pugh; eGFR, Estimated glomerular filtration rate; SOF, Sofosbuvir; VEL, Velpatasvir; RBV, Ribavirin; DCV, Daclatasvir; ASV, Asunaprevir; LDV, Ledipasvir; PrOD, Paritaprevir/ritonavir, ombitasvir + dasabuvir; EBR, Elbasvir; GZR, Grazoprevir; GLE, Glecaprevir; PIB, Pibrentasvir.

Patients were primarily infected with HCV GT1 (10,246 [64.6%]), followed by GT2 (3,686 [23.2%]), GT3 (1,151 [7.2%]), GT6 (457 [2.8%]), GT4 (47 [0.3%]), untyped GTs (261 [1.6%]), and there was only 1 case of GT5 (1 [0.006%]). Prescribed DAA regimens were also diverse, with the most commonly used being sofosbuvir/ledipasvir (SOF/LDV)±ribavirin (RBV) (30.6%), followed by SOF + RBV (17.6%), daclatasvir + asunaprevir (DCV/ASV) (14.9%), SOF/velpatasvir (VEL)±RBV (10.4%), paritaprevir/ritonavir, ombitasvir + dasabuvir (PrOD)±RBV (10.1%), glecaprevir/pibrentasvir (GLE/PIB) (7.7%), elbasvir/grazoprevir (EBR/GZR) (5.3%), SOF + DCV±RBV (2.4%), and others (1.0%).

SVR12 outcomes

Overall, SVR12 was achieved in 96.9% (95% CI: 96.6–97.1%, all DAA-based regimens and all GTs combined). Figure 1 displayed the SVR12 outcomes by demographic characteristics and DAA regimens. The SVR12 rates were generally comparable for both males (96.6%) and females (97.0%). By age group, patients older than 60 years had a slightly lower SVR12 rate (96.4%) compared to those younger than 60 years (97.4%) (p=0.001). By GTs, SVR12 was >95% for GT1/2/3/6, while it was 91.5% for GT4 (p < 0.001). Moreover, cirrhosis (94.8% vs. 97.9% without cirrhosis; p < 0.001), history of HCC (94.0% vs. 97.1% without HCC; p < 0.001), especially for active HCC (91.5% vs. 95.0% inactive HCC; p < 0.001), prior treatment failure (95.4% vs. 97.3% with treatment-naive; p < 0.001), as well as renal dysfunction (95.5% vs. 96.9% without renal dysfunction; p=0.003), all had negative impacts on SVR12 rates, though the incremental differences were not large.

Fig. 1 Sustained virologic response at week 12 after end-of-treatment (SVR12) rates for patients with chronic hepatitis C.

Renal dysfunction was defined as an estimated glomerular filtration rate (eGFR) less than 60 (mL/m/1.73 m²). HCC, Hepatocellular carcinoma; CH, Chronic hepatitis; LC, Liver cirrhosis; GT, Genotype; SOF, Sofosbuvir; VEL, Velpatasvir; RBV, Ribavirin; DCV, Daclatasvir; ASV, Asunaprevir; LDV, Ledipasvir; PrOD, Paritaprevir/ritonavir, ombitasvir + dasabuvir; EBR, Elbasvir; GZR, Grazoprevir; GLE, Glecaprevir; PIB, Pibrentasvir; CI, Confidence interval.

Figure 2 displayed SVR12 outcomes for patients stratified by GTs, liver cirrhosis, and prior treatment history. Overall, patients with TE cirrhosis had the lowest SVR12 (93.2%, 95% CI: 91.9–94.3%), compared with treatment-naive cirrhotic (95.6%, 95% CI: 94.9–96.2%), TE non-cirrhotic (97.1%, 95% CI: 96.3–97.8%), and treatment-naive non-cirrhotic (98.1%, 95% CI: 97.8–98.4%) (p < 0.001). Among GT3-infected patients, although the overall SVR12 was 95.1% (1,095/1,151, 95% CI: 93.7–96.3%), significantly lower SVR12 was observed in TE patients, regardless of cirrhosis status (85.7–89.1%). Notably, GT3b patients had lower SVR12 than those with GT3a (94.0% vs. 98.2%; p < 0.001). For GT3b-infected, TE patients had significantly lower SVR12 (10/13, 76.9%, 95% CI: 46.2–95.0%) compared to treatment-naive patients (224/236, 94.9%, 95% CI: 91.3–97.4%). However, for GT3a-infected, the lowest SVR12 was observed in patients with TE CHC while it was still over 92%. Among GT6-infected patients, the overall SVR12 rate was 98.3% (449/457, 95% CI: 96.6–99.2%) (Fig. 1), with slightly lower response at 93.8% (95% CI: 79.2–99.2%) among those with TE cirrhosis, while SVR12 for all treatment-naive patients was 97.5% regardless of cirrhosis status. Additionally, among patients with GT1 or GT2 infection, significantly lower treatment responses were observed in patients with TE cirrhosis, though still over 90%.

Sustained virologic response at week 12 after end-of-treatment (SVR12) rates for patients with chronic hepatitis C virus stratified by genotypes (GTs), liver fibrosis stage, and prior treatment.

Fig. 2 Sustained virologic response at week 12 after end-of-treatment (SVR12) rates for patients with chronic hepatitis C virus stratified by genotypes (GTs), liver fibrosis stage, and prior treatment.

CH, Chronic hepatitis; LC, Liver cirrhosis; TE, Treatment-experienced; TN, Treatment-naive; CI, Confidence interval.

The treatment responses in patients stratified by GT3 or GT6 and different regimens were shown in Supplementary Table 1. Among patients with GT3 infection, the best SVR12 was 96.2% with SOF/VEL±RBV (95% CI: 94.7–97.4%), followed by 95.8% with SOF/LDV±RBV (95% CI: 78.9–99.9%), 94.1% with GLE/PIB (95% CI: 85.6–98.4%), 91.5% with SOF + RBV (95% CI: 83.2–96.5%), and 88.2% with SOF + DCV±RBV (95% CI: 80.4–93.8%). Among patients with GT6 infection, the SVR12 rates were ≥ 97.5% with SOF-based regimens and 100% with GLE/PIB.

Factors associated with treatment response

Using a multivariable logistic regression analysis, significant independent factors associated with lower SVR12 included age over 60 years (adjusted odds ratio [aOR], 0.74; p=0.01), prior treatment failure (aOR, 0.64; p < 0.001), cirrhosis (compensated: aOR, 0.55; p < 0.001; decompensated: aOR, 0.20; p<0.001), active HCC (aOR, 0.58; p=0.03, compared with non-HCC), and HCV GT3 and GT4 (aOR, 0.48; p=0.01 and aOR, 0.30; p=0.04; compared with GT1). However, being Asian (aOR, 1.81; p < 0.001) compared to non-Asian was a significant independent predictor for achieving SVR12, and there was no significant difference between inactive HCC and non-HCC (aOR, 0.86 [0.62–1.18]; p=0.34) (Table 2).

Table 2

Univariate and multivariate analyses of baseline factors associated with SVR12 in patients with HCV infection (all GTs)^§

Factors	Category	Univariate Analysis		Multivariate Analysis
Factors	Category	Odds Ratio (95% CI)	p-Value	Odds Ratio (95% CI)	p-Value
Age, years	≤60	1 (Referent)		1 (Referent)
	>60	0.72 (0.60–0.87)	0.001	0.74 (0.59–0.92)	0.01
Sex	Female	1 (Referent)		1 (Referent)
	Male	0.88 (0.73–1.05)	0.15	0.91 (0.74–1.11)	0.33
Ethnicity	Non-Asian	1 (Referent)		1 (Referent)
	Asian	1.94 (1.51–2.49)	< 0.001	1.81 (1.30–2.53)	< 0.001
Prior treatment	No	1 (Referent)		1 (Referent)
	Yes	0.57 (0.47–0.69)	< 0.001	0.64 (0.52–0.78)	< 0.001
Liver fibrosis	Non-cirrhosis	1 (Referent)		1 (Referent)
	Compensated cirrhosis	0.45 (0.37–0.55)	< 0.001	0.55 (0.44–0.68)	< 0.001
	Decompensated cirrhosis	0.18 (0.13–0.24)	< 0.001	0.20 (0.14–0.29)	< 0.001
HCC	Non-HCC	1 (Referent)		1 (Referent)
	Ablated HCC	0.56 (0.42–0.75)	< 0.001	0.86 (0.62–1.18)	0.35
	Active HCC	0.32 (0.21–0.49)	< 0.001	0.58 (0.36–0.94)	0.03
CKD, eGFR < 60	No	1 (Referent)		1 (Referent)
	Yes	0.67 (0.52–0.87)	0.003	0.85 (0.63–1.13)	0.26
HBV co-infection	No	1 (Referent)
	Yes	1.54 (0.72–3.27)	0.27	–	–
HIV co-infection	No	1 (Referent)
	Yes	4.25 (0.59–30.6)	0.15	–	–
HCV RNA, IU/mL	≤800,000	1 (Referent)		1 (Referent)
	>800,000	1.17 (0.97–1.41)	0.10	1.01 (0.83–1.24)	0.91
Genotypes	GT1	1 (Referent)		1 (Referent)
	GT2	0.89 (0.72–1.11)	0.30	0.68 (0.42–1.09)	0.11
	GT3	0.60 (0.47–0.80)	0.001	0.48 (0.29–0.81)	0.01
	GT4	0.33 (0.12–0.92)	0.03	0.30 (0.09–0.94)	0.04
	GT6	1.72 (0.85–3.48)	0.14	0.96 (0.43–2.18)	0.93
DAA regimens	DCV/ASV	1 (Referent)		1 (Referent)
	PrOD±RBV	2.41 (1.69–3.43)	< 0.001	2.96 (2.00–4.36)	< 0.001
	EBR/GZR	3.50 (2.04–6.00)	< 0.001	3.73 (1.95–7.11)	< 0.001
	SOF/LDV±RBV	3.20 (2.45–4.17)	< 0.001	3.54 (2.63–4.76)	< 0.001
	SOF/RBV	1.61 (1.24–2.09)	< 0.001	1.96 (1.15–3.35)	0.01
	SOF/DCV±RBV	1.44 (0.85–2.45)	0.17	2.55 (1.27–5.12)	0.01
	GLE/PIB	2.79 (1.84–4.23)	< 0.001	3.29 (1.95–5.57)	< 0.001
	SOF/VEL±RBV	1.79 (1.30–2.45)	< 0.001	3.07 (1.79–5.27)	< 0.001
	Others	1.62 (0.70–3.73)	0.26	3.46 (1.34–8.93)	0.01

^§5,995 patients with data for all variables, and 13,971 of 15,849 (88.2%) patients were included in the multivariable model, which does not include HBV and HIV. HBV and HIV were not used in the multivariable models since they were not significant predictors in the univariable analysis. HCV, Hepatitis C virus; HBV, Hepatitis B virus; HIV, Human immunodeficiency virus; CKD, Chronic kidney disease; eGFR, Estimated glomerular filtration rate; HCC, Hepatocellular carcinoma; GT, Genotype; SVR, Sustained virological response; DAA, Direct-acting antiviral; SOF, Sofosbuvir; VEL, Velpatasvir; RBV, Ribavirin; DCV, Daclatasvir; ASV, Asunaprevir; LDV, Ledipasvir; PrOD, Paritaprevir/ritonavir, ombitasvir + dasabuvir; EBR, Elbasvir; GZR, Grazoprevir; GLE, Glecaprevir; PIB, Pibrentasvir; CI, Confidence interval.

Among GT3-infected patients, significant factors independently associated with lower SVR12 included decompensated cirrhosis, with patients being 81% less likely to achieve SVR12 compared to those without cirrhosis (aOR, 0.19; p < 0.001), while Asians were significant independent predictors for achieving SVR12 (aOR, 4.05; p=0.01) (Table 3). For patients with GT3b, TE (OR 0.12, 95% CI 0.03–0.57; p=0.01) and HCV RNA >800,000 IU/mL (OR 3.94, 95% CI 1.14–13.61; p=0.03) were associated with treatment failure (Table 4). Among GT6-infected patients, active HCC was the strongest independent predictor for treatment failure (OR 0.01, 95% CI 0.0002–0.36; p=0.01), but this was not true for inactive HCC (p=0.62). Moreover, TE patients were 83% less likely to achieve SVR than treatment-naive patients (OR, 0.17; p=0.03) (Table 5).

Table 3

Univariate and multivariate analysis of baseline factors associated with SVR12 in patients with HCV GT3^§

Factors	Category	Univariate analysis		Multivariate analysis
Factors	Category	Odds Ratio (95% CI)	p-Value	Odds Ratio (95% CI)	p-Value
Age, years	≤60	1 (Referent)		1 (Referent)
	>60	0.48 (0.26–0.90)	0.02	1.16 (0.52–2.62)	0.71
Sex	Female	1 (Referent)		1 (Referent)
	Male	0.86 (0.43–1.74)	0.68	0.72 (0.31–1.64)	0.43
Ethnicity	Non-Asian	1 (Referent)		1 (Referent)
	Asian	5.19 (2.98–9.03)	< 0.001	4.05 (1.43–11.5)	0.01
Prior treatment	No	1 (Referent)		1 (Referent)
	Yes	0.32 (0.16–0.62)	0.001	0.49 (0.20–1.19)	0.12
Liver fibrosis	Non cirrhosis	1 (Referent)		1 (Referent)
	Compensated cirrhosis	0.40 (0.20–0.81)	0.01	0.49 (0.22–1.10)	0.08
	Decompensated cirrhosis	0.10 (0.05–0.21)	< 0.001	0.19 (0.08–0.46)	< 0.001
HCC	Non-HCC	1 (Referent)		1 (Referent)
	Ablated HCC	0.29 (0.11–0.75)	0.01	0.81 (0.25–2.58)	0.72
	Active HCC	0.18 (0.07–0.49)	0.001	0.37 (0.20–1.37)	0.14
CKD, eGFR < 60	No	1 (Referent)
	Yes	0.54 (0.21–1.35)	0.18	–	–
HBV co-infection	No	1 (Referent)
	Yes	2.98 (0.18–49.5)	0.45	–	–
HIV co-infection	No	1 (Referent)
	Yes	1.57 (0.30–8.20)	0.59	–	–
HCV RNA, IU/mL	≤800,000	1 (Referent)		1 (Referent)
	>800,000	2.04 (1.17–3.55)	0.01	1.02 (0.52–2.03)	0.95
Genotypes	GT3a	1 (Referent)		1 (Referent)
	GT3b	0.29 (0.13–0.65)	0.003	0.55 (0.19–1.58)	0.27
	GT3 unspecified	0.19 (0.10–0.39)	< 0.001	0.59 (0.21–1.62)	0.30
DAA regimens	SOF/DCV±RBV	1 (Referent)		1 (Referent)
	SOF/RBV	1.39 (0.53–3.61)	0.50	0.93 (0.29–2.91)	0.90
	GLE/PIB	1.98 (0.64–6.09)	0.23	1.68 (0.43–6.56)	0.45
	SOF/VEL±RBV	3.48 (1.75–6.92)	< 0.001	1.32 (0.49–3.60)	0.59
	SOF/LDV	2.16 (0.37–12.5)	0.39	2.54 (0.36–17.7)	0.35

^§861 patients with data for all variables, and 1,001 of 1,151 (87.0%) patients were included in the multivariable model, which does not include HBV and HIV. HBV and HIV were not used in the multivariable models since they were not significant predictors in the univariable analysis. HCV, Hepatitis C virus; HBV, Hepatitis B virus; HIV, Human immunodeficiency virus; CKD, Chronic kidney disease; eGFR, Estimated glomerular filtration rate; HCC, Hepatocellular carcinoma; GT, Genotype; SVR, Sustained virological response; DAA, Direct-acting antiviral; SOF, Sofosbuvir; VEL, Velpatasvir; RBV, Ribavirin; DCV, Daclatasvir; LDV, Ledipasvir; GLE, Glecaprevir; PIB, Pibrentasvir; CI, Confidence interval.

Table 4

Univariate and multivariate analysis of baseline factors associated with SVR12 in patients with HCV GT3b^§

Factors	Category	Univariate analysis		Multivariate analysis
Factors	Category	Odds Ratio (95% CI)	p-Value	Odds Ratio (95% CI)	p-Value
Age, years	≤60	1 (Referent)		1 (Referent)
	>60	0.64 (0.13–3.02)	0.57	0.49 (0.10–2.48)	0.39
Sex	Female	1 (Referent)		1 (Referent)
	Male	1.34 (0.44–4.06)	0.61	1.09 (0.30–3.96)	0.90
Prior treatment	No	1 (Referent)		1 (Referent)
	Yes	0.18 (0.04–0.73)	0.02	0.12 (0.03–0.57)	0.01
Liver fibrosis	Non cirrhosis	1 (Referent)		–	–
	Compensated cirrhosis	0.82 (0.15–4.64)	0.83	–	–
	Decompensated cirrhosis	0.40 (0.07–2.33)	0.31	–	–
HCC	No	1 (Referent)		–	–
	Yes	0.60 (0.13–2.87)	0.53	–	–
CKD, eGFR < 60	No	1 (Referent)
	Yes	1.24 (0.15–9.99)	0.84	–	–
HIV co-infection	No	1 (Referent)
	Yes	1.84 (0.23–14.6)	0.56	–	–
HCV RNA, IU/mL	≤800,000	1 (Referent)		1 (Referent)
	>800,000	3.87 (1.16–13.0)	0.03	3.94 (1.14–13.61)	0.03
DAA regimens	SOF/VEL±RBV	1 (Referent)		–	–
	Others	1.37 (0.42–4.43)	0.60	–	–

^§167 patients with data for all variables, and 236 of 249 (94.8%) patients were included in the multivariable model, which does not include HIV. There are not enough patients for variables of HBV and active/ablated HCC. HCV, Hepatitis C virus; HBV, Hepatitis B virus; HIV, Human immunodeficiency virus; CKD, Chronic kidney disease; eGFR, Estimated glomerular filtration rate; HCC, Hepatocellular carcinoma; GT, Genotype; SVR, Sustained virological response; DAA, Direct-acting antiviral; SOF, Sofosbuvir; VEL, Velpatasvir; RBV, Ribavirin; DCV, Daclatasvir; LDV, Ledipasvir; GLE, Glecaprevir; PIB, Pibrentasvir; CI, Confidence interval.

Table 5

Univariate and multivariate analysis of baseline factors associated with SVR12 in patients with HCV GT6^§

Factors	Category	Univariate analysis		Multivariate analysis
Factors	Category	Odds Ratio (95% CI)	p-Value	Odds Ratio (95% CI)	p-Value
Age, years	≤60	1 (Referent)		1 (Referent)
	>60	1.02 (0.27–3.83)	0.97	1.35 (0.26–7.14)	0.73
Sex	Female	1 (Referent)		1 (Referent)
	Male	0.43 (0.10–1.89)	0.27	0.56 (0.11–2.91)	0.50
Ethnicity	Non-Asian	1 (Referent)
	Asian	7.54 (0.36–156.86)	0.19	–	–
Prior treatment	No	1 (Referent)		1 (Referent)
	Yes	0.19 (0.05–0.73)	0.02	0.17 (0.03–0.87)	0.03
Liver fibrosis	Non cirrhosis	1 (Referent)		1 (Referent)
	Compensated cirrhosis	0.30 (0.07–1.23)	0.09	0.64 (0.12–3.36)	0.60
	Decompensated cirrhosis	0.48 (0.02–9.66)	0.63	1.86 (0.03–117.17)	0.77
HCC	Non-HCC	1 (Referent)		1 (Referent)
	Ablated HCC	0.12 (0.02–0.80)	0.03	0.45 (0.02–10.6)	0.62
	Active HCC	0.04 (0.01–0.33)	0.002	0.01 (0.0002–0.36)	0.01
CKD, eGFR < 60	No	1 (Referent)
	Yes	0.77 (0.13–4.52)	0.77	–	–
HBV co-infection	No	1 (Referent)
	Yes	0.26 (0.04–1.60)	0.15	–	–
HIV co-infection	No	1 (Referent)
	Yes	0.29 (0.02–5.68)	0.42	–	–
HCV RNA, IU/mL	≤800,000	1 (Referent)
	>800,000	1.17 (0.26–5.29)	0.84	–	–
DAA regimens	SOF/DCV±RBV	1 (Referent)		1 (Referent)
	SOF/LDV±RBV	1.45 (0.07–28.1)	0.81	2.41 (0.09–62.5)	0.60
	SOF/VEL±RBV	1.03 (0.05–20.9)	0.98	2.44 (0.07–83.7)	0.62

^§260 patients with data for all variables, and 338 of 457 (74.0%) patients were included in the multivariable model, which does not include HBV and HIV. HBV and HIV were not used in the multivariable models since they were not significant predictors in the univariable analysis. HCV, Hepatitis C virus; HBV, Hepatitis B virus; HIV, Human immunodeficiency virus; CKD, Chronic kidney disease; eGFR, Estimated glomerular filtration rate; HCC, Hepatocellular carcinoma; GT, Genotype; SVR, Sustained virological response; DAA, Direct-acting antiviral; SOF, Sofosbuvir; VEL, Velpatasvir; RBV, Ribavirin; DCV, Daclatasvir; LDV, Ledipasvir; CI, Confidence interval.

Among GT1-infected patients, significant factors independently associated with lower SVR12 were age over 60 years (aOR, 0.69; p=0.01), prior treatment failure (aOR, 0.64; p < 0.001), decompensated and compensated cirrhosis (aOR, 0.19; p < 0.001 and aOR, 0.56; p < 0.001; respectively) (Supplementary Table 2). Among GT2-infected patients, decompensated cirrhosis (OR, 0.27; p=0.003) and compensated cirrhosis (OR, 0.47; p < 0.001) were significant factors independently associated with lower SVR12 (Supplementary Table 3).

Treatment tolerability

Supplementary Table 4 displayed the safety profile for patients stratified by different regimens. The overall incidence of AEs was low, with the most common AEs being fatigue (5.5%), pruritus (2.7%), insomnia (1.9%), headache (1.8%), and nausea (1.5%). AEs by DAA regimens are shown in Supplementary Table 4. Additionally, 319 patients (2.18%) discontinued treatment prematurely. The most common causes for early discontinuation were liver injury (0.3%), non-compliance (0.2%), and viral breakthrough (0.2%), with other reasons including patient choice, loss to follow-up, HCC diagnosis/recurrence, and other AEs such as fever, nausea, vomiting, and pruritus. Higher rates of treatment interruption were seen in patients receiving DCV/ASV (6.4%, 144/2,249), PrOD±RBV (3.2%, 43/1,346), and GLE/PIB (2.2%, 24/1,115), while it was less than 1.3% for other regimens. Serious adverse events (SAEs) occurred in 90 patients (0.6%), with the most common SAEs being decompensation (0.06%), HCC progression (0.03%), renal events (0.02%), cerebral hemorrhage (0.02%), and anemia (0.02%).

Discussion

The emergence of DAAs has dramatically transformed the HCV treatment landscape, but clinical practice patterns and HCV GT distribution vary by geographic region. We presented a large, multinational study including patients infected with HCV GTs 1–6 who received DAAs in a "real-world" setting. Overall, the SVR12 rate was 96.9%, with rates exceeding 90% in almost all subgroups, including patients with advanced age, renal dysfunction, prior treatment failure, cirrhosis, and HCC. Among the GTs, the cure rates were 97.0% for GT1, 96.7% for GT2, 95.1% for GT3, 91.5% for GT4, and 98.3% for GT6 (Fig. 1). The single patient with GT5 was treatment-naive, noncirrhotic, and was cured with SOF/LDV. Independent predictors of lower SVR12 included age over 60 years, prior treatment failure, cirrhosis, active HCC, and GT3 or GT4. Conversely, being Asian was a significant predictor of achieving SVR12, and there was no significant difference in SVR12 between patients with non-HCC and inactive HCC. The study also found that the overall incidence of AEs was low, with common AEs including fatigue, pruritus, insomnia, headache, and nausea. SAEs were rare (0.6%), and none led to death. Early treatment discontinuation was also uncommon in this large cohort (2.2%).

GT3 is the second most common HCV GT worldwide, and patients infected with GT3, especially the 3b subtype, remain a difficult-to-cure population.^12,13 Our results showed an overall high SVR12 rate of 95.1% for GT3 patients, but a lower SVR12 in TE patients with or without cirrhosis (85.7–89.1%), largely due to TE patients infected with GT3b (75–77%). Moreover, decompensated cirrhosis, rather than compensated cirrhosis, was an independent predictor of treatment failure in GT3 patients, and a high HCV viral load increased the risk of treatment failure by 3.9 times compared to patients with a low HCV RNA. A large cohort study from Thailand showed an overall SVR12 of 96.7% in HCV GT3 patients who received SOF-based±RBV regimens, but it was 88.4% in patients with decompensated cirrhosis, and 57.1% for TE decompensated cirrhotic patients with GT3b.¹² A multicenter phase 3 clinical trial in Asia showed an overall SVR12 of 86% in GT3 patients treated with SOF/VEL, while it was only 50% in GT3b patients with cirrhosis.¹³

On the other hand, our study found that SOF-based±RBV regimens were highly efficacious in HCV GT3-infected patients, with the highest SVR12 of 96.2% achieved by SOF/VEL±RBV (98.1% for GT3a and 93.4% for GT3b) (Supplementary Table 1). This supports the current recommendation for GT3 treatment with an IIB evidence grade by the 2023 HCV guidelines of the American Association for the Study of Liver Diseases and the Infectious Disease Society of America.¹⁶ SOF/VEL, as a protease inhibitor-free regimen, was recommended for treatment-naive or non-cirrhotic TE patients with GT3 infection for 12 weeks, or in combination with RBV for decompensated cirrhosis for 12/24 weeks.^16,17 A multicenter phase 2 clinical study across Australia, New Zealand, and the United States found that SOF/VEL combination therapy for TE GT3 patients was highly effective, with an SVR12 of 88% without RBV and 96% with RBV.¹⁸ A phase 2 clinical study from Spain showed an SVR12 of 91% with SOF/VEL and 96% with SOF/VEL+RBV in GT3 patients with compensated cirrhosis.¹⁹ Furthermore, a phase 3 clinical study in the United States showed that 12-week SOF/VEL, 24-week SOF/VEL, or 12-week SOF/VEL + RBV in GT3 patients with decompensated cirrhosis achieved SVR12 rates of 50%, 50%, and 85%, respectively.²⁰ Notably, SOF/VEL + RBV treatment of refractory GT3 patients can still achieve a high SVR12 rate, including patients with GT3b (93.4% in our study). High SVR12 rates among GT3 patients have been shown in real-world settings using SOF/VEL; however, few patients with GT3b were included.²¹ In settings where the cost and availability of HCV genotyping may be limited (e.g., HCV microelimination through outreach programs) and the prevalence of GT3b is low, pangenotypic SOF-based DAA regimens could be a reasonable and cost-effective approach. However, the efficacy of this regimen in GT3b patients with treatment experience or cirrhosis needs further evaluation. Therefore, despite the relatively high SVR12 based on DAA achieved in patients with GT3, the treatment of HCV 3b subtype infection remains a clinical challenge, especially when combined with cirrhosis and/or prior treatment failure, as well as high HCV viral load.

Our study of over 15,000 diverse patients, including 1,352 HCC patients (281 with active HCC) from both the East and the West, confirmed an important finding: inactive HCC was not associated with a lower SVR12 compared to non-HCC patients. Thus, the presence of HCC should not discourage providers from treating viremic HCV patients with DAAs though treatment should generally be delayed until HCC has been adequately treated since active HCC was associated with lower SVR, consistent with prior reports.^22,23 The current study expanded on prior knowledge of the interaction between HCC and DAA treatment, including findings from an earlier study from REAL-C that included only patients from Asia which compared SVR12 rates of 436 pairs of matched patients with HCV/HCC and HCV/non-HCC patients and found that SVR12 for active HCC was significantly lower than that with inactive HCC (85.5% vs. 93.7%; p=0.03). However, there was no statistically significant difference between HCC (92.7%) and non-HCC (95.0%) groups.²⁴ It should also be noted that the SVR12 for active HCC in our study was still fairly high at 91.5% (Fig.1), supporting prior suggestions that HCV-related HCC should be treated with DAAs based on a risk-benefit evaluation.^25,26 However, DAA-based treatment recommendations for patients with HCV-related HCC have not been well-established across guidelines,^16,17 despite increasing evidence that HCV-cured HCC patients have significantly improved overall and liver-related survival compared to those without SVR12.^27,28 Therefore, additional patient and provider education and clearer guideline recommendations are needed. This is especially important given the dismally poor median 20-month overall survival for HCV-HCC patients. Those who received DAA treatment had a higher five-year survival rate compared to those untreated (47.2% vs. 35.2%). Additionally, the DAA utilization rate was low at 23.5% in a nationwide cohort of 3,922 U.S. patients with private insurance.^29,30

Globally, data regarding the clinical features and treatment of HCV GT6 are limited. In this multicenter cohort, our study included 457 patients with HCV GT6, 99% of whom were from Asia (59.5% Vietnamese and 37.4% Chinese). Our study reported an excellent SVR12 rate of 98.3% among patients with GT6 infection, including those with TE cirrhosis (93.8%). HCV GT6 is mostly found in Southern China and Southeast Asia and has a higher prevalence in certain populations, such as intravenous drug users.³¹ A study from Hong Kong showed that the proportion of HCV GT6 infection among intravenous drug users was approximately 58%, significantly higher than among non-intravenous drug users (23%).³² Given the high cure rate of HCV GT6 patients receiving DAA treatment, including those with TE cirrhosis, it is recommended that people at high risk of HCV GT6 infection, especially intravenous drug users, should be screened and treated early to achieve the 2030 hepatitis C elimination target.

There were some limitations in our study. Firstly, this study is a real-world investigation, and patients were not randomly assigned to a specific DAA regimen. Instead, DAA treatment options were chosen based on the availability of DAAs in different regions at the time and the judgment of clinicians. Despite this, our overall SVR12 remained high. Secondly, although we performed multivariable regression analyses to adjust for potential confounders, residual confounding effects may remain, and not all patients had detailed records of important factors such as co-infection with HBV or HIV.

Conclusion

This large international multicenter observational study of patients with diverse GTs showed an overall SVR12 rate of 96.9%, despite including many patients with cirrhosis, HCC, prior treatment failure, and the use of older DAAs. Our study demonstrates that for refractory GT3 patients, including those with TE cirrhosis, SOF/VEL plus RBV can achieve high cure rates, lending further support to recent practice guideline recommendations. However, the efficacy of this regimen for the GT3b subtype with prior treatment failure or cirrhosis and high HCV viral load remains to be evaluated. Meanwhile, the study observed a high overall SVR12 for GT6, a prevalent GT among injection drug users who should be screened and promptly treated. Our study also confirmed high SVR12 rates for patients with HCC, though slightly lower for those with active HCC, underscoring the need for additional guideline recommendations to increase DAA utilization in this population.

Supporting information

Supplementary Table S1

SVR12 rates (95% CI) in patients infected with HCV GT3 and GT6 among different DAA regimens.

(DOCX)

Click here for additional data file.

Supplementary Table S2

Univariate and multivariate analyses of baseline factors associated with SVR12 in patients with HCV GT1.

(DOCX)

Click here for additional data file.

Supplementary Table S3

Univariate and multivariate analyses of baseline factors associated with SVR12 in patients with HCV GT2.

(DOCX)

Click here for additional data file.

Supplementary Table S4

The AEs in different regimens.

(DOCX)

Click here for additional data file.

Declarations

Ethical statement

The study was conducted according to the Helsinki Declaration of 1975, as revised in 2008, and was approved by the Institutional Review Board at Stanford University, Stanford, California, USA (No. 40878, No. 13927), and participating study centers. The written informed consent was obtained from the patients.

Data sharing statement

Due to privacy policy, data are not publicly available.

Funding

This study is partially supported by an investigator-initiated research grant (IN-US-334-4309) from Gilead Sciences to Stanford University. The authors independently collected the data, designed and performed all study analyses, and drafted the manuscript. The funding source had no role in the study design, data collection, data analysis or interpretation, report writing, or the decision to submit the paper for publication.

Conflict of interest

FJ: Speaker fees: Gilead Sciences, MSD, and Ascletis. Consultancy: Gilead Sciences, MSD. FJ has been an Editorial Board Member of Journal of Clinical and Translational Hepatology since 2023. YJW: Speaker fees: Gilead Science, AbbVie. Research Grant: Medicine Academic Clinical Program, SingHealth, Singapore. YJW has been an Editorial Board Member of Journal of Clinical and Translational Hepatology since 2020. HT: Speaker fees: Gilead Science, AbbVie, Eisai, Fujifilm WAKO, Takeda, Kowa, Terumo, Astra Zeneca. VWSW: Consultancy: AbbVie, Boehringer Ingelheim, Echosens, Gilead Sciences, Intercept, Inventiva, Novo Nordisk, Pfizer, Sagimet Biosciences, TARGET PharmaSolutions, Visirna. Speaker fees: Abbott, AbbVie, Gilead Sciences, Novo Nordisk, Unilab. Research grants: Gilead Sciences. Stock: Co-founder of Illuminatio Medical Technology Limited. MA: Speakers’ fees: AbbVie, Gilead Sciences. SD: Speakers fees: Gilead Sciences. MFY: Speakers’ fees: Fujirebio Incorporation, Gilead Sciences, Roche, Sysmex Corporation. Consulting or advisory board: AbbVie, Abbott Diagnostics, Aligos Therapeutics, AiCuris, Antios Therapeutics, Arbutus Biopharma, Arrowhead Pharmaceuticals, Assembly Biosciences, Clear B Therapeutics, Dicerna Pharmaceuticals, Finch Therapeutics, Fujirebio Incorporation, GlaxoSmithKline, Gilead Sciences, Immunocore, Janssen, Precision BioSciences, Roche, Sysmex Corporation, Tune Therapeutics, Vir Biotechnology and Visirna Therapeutics. Research grant: AbbVie, Assembly Biosciences, Arrowhead Pharmaceuticals, Fujirebio Incorporation, Gilead Sciences, Immunocore, Sysmex Corporation and Roche. MFY has been an Associate Editor of Journal of Clinical and Translational Hepatology since 2021. CW: Research grant: Gilead Sciences. MLYu: Research support (grant) from Abbvie, BMS, Gilead, Merck, and Roche diagnostics. Consultant of Abbvie, BMS, Gilead, Roche, and Roche diagnostics. Speaker of Abbvie, BMS, Eisai, Gilead, Roche, and Roche diagnostics. MLYu has been an Associate Editor of Journal of Clinical and Translational Hepatology since 2023. MHN: Research grants via institution: Pfizer, Enanta, Astra Zeneca, GSK, Delfi, Innogen, Exact Science, CurveBio, Gilead, Vir Biotech, Helio Health, National Cancer Institute, Glycotest. Consulting/Advisory board: Intercept, Exact Science, Gilead, GSK. JL, MLYe, WLC and JFH have been Editorial Board Members of Journal of Clinical and Translational Hepatology since 2022. HR has been an Editor-in-Chief of Journal of Clinical and Translational Hepatology since 2013. The other authors have no conflict of interests related to this publication.

Authors’ contributions

Guarantor of the article: MHN. Specific author contributions: study design: FJ, ST, and MHN. Data collection: all the authors. Data analysis: ST, FJ and MHN. Data interpretation: all the authors. Drafting of the article: FJ, ST and MHN. Study concept and study supervision: MHN.

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