Epidemiology,clinical,and laboratory profile of patients with hepatitis C: A prospective,observational study from north-eastern India

Abstract

Low and middle-income countries (LMICs) contribute to 80% of the global hepatitis C virus (HCV) infection burden. Intravenous drug use (IVDU) is not uncommon in Northeastern India, thus contributing to HCV. Its epidemiology, clinical, and laboratory profile were studied in a tertiary care centre in northeastern India.HCV patients (age >18) of either sex were prospectively assessed for demographic, virological, and genotype distributions. Most were male (M: F, 5.8:1) with a mean age of 37.1 ± 11.8 years. The most common risk factor was IVDU(77.69%), followed by concomitant alcohol use in 69.2%. Besides genotype 3 (59.2%), genotype 1 (26.1%) and genotype 6 were also common (14.6%). The demographics, liver disease severity, and biochemical parameters were similar across genotypes.

Keywords

hepatitis Asia diagnosis public health

Introduction

HCV infection continues to be a significant public health problem globally despite the introduction of new treatment based on a combination of direct-acting antiviral drugs (DAA). HCV infects 71.1 million people globally, approximately 1.0% of the world's population.¹ Oral DAA regimes administered for 8–12 weeks successfully eradicate HCV, with cure rates above 95%, prompting the World Health Organization (WHO) to propose nation-by-nation initiatives to eradicate this disease globally.^2,3

Although low and middle-income countries (LMICs) contribute to 80% of the global burden of HCV infection,⁴ the prevalence of HCV in India varies by geographical region, with a 2015 report estimating a disease burden of 6.2 million.^5,6 Intravenous drug use has become the leading cause worldwide, signaling a paradigm shift in HCV epidemiology.^7,8 In the northeast region of India there is rampant drug trafficking and IVDU.⁹ Recent literature evaluating HCV phylodynamics shows a link between HCV spread consistent with the drug trafficking route.¹⁰ Despite this important characteristics of the northeast region there has been little research on the epidemiology of HCV in the region.^9–12

Materials and methods

We conducted a single-centre, prospective, observational study on patients attending an outpatient clinic at the North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong, in India between July 2015 and December 2020. The institute's Ethics Committee approved the study protocol. Written informed consent was taken from all participants based on the tenets of the declaration of Helsinki (modified 1989). The guidelines laid by the Indian Council of Medical Research (2017) were adhered to for all patients in the study.

All patients >18 years old of either sex who were positive to an initial HCV antibody screening test (anti-HCV positive) were eligible for inclusion. Patients who had previously received or were currently receiving hepatitis C treatment, pregnant women,and those with double or triple infection with HIV and/or HBV were excluded.

Demographics and a detailed history of alcohol use, non-alcohol substance abuse, injection drug use, unsafe needle practices, and the need for renal replacement therapy were collected. The risk for alcohol use disorder (AUD) was defined according to the National Institute on Alcohol Abuse and Alcoholism.¹³ Height (cm), dry weight (kg), body mass index (kg/m2) and blood pressure were measured. Laboratory indices, liver and adrenal function tests, coagulation and lipid profile, and thyroid function tests. Cirrhosis was defined using clinical, biochemical, radiological (ultrasonography, CT or MRI scan), and liver biopsy findings.

Commercially available diagnostic kits were used to test for HCV (Erba Lisa HCV Gen3 v2, Transasia Bio-Medicals Ltd, Daman, India). Besides, the HCV RNA load estimation (COBAS^® AmpliPrep/COBAS^® TaqMan 48 HCV test) and HCV genotyping (nested reverse transcriptase-polymerase chain reaction) were also outsourced to SRL Diagnostics, Super Religare Laboratories Ltd, Mumbai, India. The approach used to detect HCV viral load had a lower limit of detection at 34 IU/ml.

Discrete categorical data were presented as n (%). Continuous data were reported as mean and standard deviation or in median and interquartile range. Kolmogorov-Smirnov tests of normality were used to ensure that quantitative data was normal. For statistical examination of two groups with normally distributed data, the t-test was used. For skewed data, non-parametric Mann-Whitney U-test was used. The Pearson Chi-square test or Fisher's exact test were used to test categorical data. The Kruskal-Wallis test was used to compare multiple groups with non-normally distributed data, while one-way analysis of variance (ANOVA) with post hoc analysis was used to compare multiple groups with normally distributed data. All the statistical tests were two-sided with a significance level of α = .05. Analysis was conducted using IBM SPSS (version 22.0 Chicago Illinois, USA).

Results

Of the 148 patients testing positive for anti-HCV, 130 (male: female ratio 5.8:1) with a mean age of 37.1 ± 11.8 years were included. Eighteen patients were excluded.

The patients hailed from several north-eastern states, with the majority from Meghalaya 68/130 (52.31%), Manipur 10/130 (7.69%), Nagaland 14/130 (10.78%), Mizoram 29/130 (22.31%), Assam 7/130 (5.38%), Tripura 2/130 (1.53%).

The overall group's median HCV RNA was 1 × 106(1.3 × 10⁵-3.8 × 10⁶). The most common genotypes observed were genotype 3 (77/130, 59.23%) followed by genotype 1 (34/130, 26.15%) and genotype 6 (19/130, 14.62%). One quarter had underlying cirrhosis (33/120, 25%), while only 2/130 (1.5%) had evidence of hepatocellular carcinoma. (Table 1)

Table 1.

Baseline characteristics of patients with hepatitis c.

Variable	Number of patients (%)
Age (years)	37.1 ± 11.8*
Sex (Male)	101(85.3)
Alcohol use disorder (AUD)	104(80)
Intravenous drug use (IVDU)	101(77.6)
Genotype
1	34(26.1)
3	77(59.2)
6	19(14.6)
Liver disease status
Cirrhosis	33(25%)
Body mass index (Kg/m²)	22.1 ± 2.7
Hepatitis C Virus RNA	1 × 10⁶(1.3 × 10⁵-3.8 × 10⁶)^**
Haemoglobin(g/L)	138 ± 21
Total leucocyte count (x10⁹/L)	6.6(4.9-7.8)
Platelet Count (x10⁹/L)	200(165-245)
Bilirubin (umol/L)	0.01(0.01-0.02)
Aspartate transaminase (µkat/L)	0.97 (0.58-1.66)
Alanine transaminase (µkat/L)	1.06 (0.56-2.04)
International normalized ratio	1.2 ± 0.2
High density lipoprotein(mmol/L)	0.95 ± 0.27
Low density lipoprotein(mmol/L)	1.98 (1.51-2.27)
Serum Triglyceride(mmol/L)	1.09 (0.79-1.51)
Thyroid stimulating hormone (mIU/L)	1.7(0.8-3.3)

*Data expressed as Mean ± Standard Deviation “Data expressed as Median (Interquartile range); RNA- Ribonucleic acid.

Some 92.3% of respondents reported multiple possible HCV exposures, while only 7.69% identified no risk factor. IVDU was found in 101/130 (77.69%), and blood transfusion 3/130 (2.31%), haemodialysis 8/130 (6.15%), tattooing 3/130 (2.31%), and multiple sexual partners 5/130(3.84%) responsible in others. A significant number, 104/130 (80%), reported concomitant alcohol use equal to AUD of whom 90/130 (69.2%) admitted AUD. Genotype 3 was the most common 61/101 (60.3%) genotype among patients with IVDU.

Sex distribution (P = 0.9), alcohol use (P = 0.6), IDU status (P = 0.7), and liver disease severity (P = 0.5) were similar across genotypes. No significant differences in virological (HCV RNA) and laboratory parameters were found when the three genotypes were compared. (Table 2)

Table 2.

Showing variations in parameters in according to different genotypes of hepatitis c virus .

Parameter	HCV Genotype 1 (Mean ± SD)^a	HCV Genotype 3 (Mean ± SD)^b	HCV Genotype 6 (Mean ± SD)^c	P-Value^a−b	P-Value^a−c	Pvalue^b−c	P-value^a−b−c
Age (years)	37.5 ± 14.1	36.5 ± 10.9	38.6 ± 10.9	0.9	0.9	0.7	0.7
Body mass index (Kg/m²)	22.28 ± 2.67*	22.1 ± 2.83	22.49 ± 2.87	0.7	0.8	0.6	0.8
Hepatitis C Virus RNA	1.3 × 10⁶(2.4 × 10⁵-4.4 × 10⁶)**	6.5 × 10⁵(1.1 × 10⁵-2.5 × 10⁶)	1.8 × 10⁶(2.4 × 10⁵-8.4 × 10⁶)	0.4	0.2	0.3	0.15
Haemoglobin(g/L)	134 ± 22	134 ± 21	135 ± 25	0.9	0.9	0.8	0.9
Total leucocyte count (x10⁹/L)	6.2(4.8-7.8)	6.5(4.8-7.8)	8(5-8.7)	0.2	0.07	0.1	0.2
Platelet Count (x10⁹/L)	200(165-240)	200(165-235)	230(191.1-278.5)	0.6	0.4	0.3	0.2
Bilirubin (umol/L)	15.39 (11.97-20.52)	18.81 (13.68-27.36)	23.94 (11.97-29.07)	0.1	0.4	0.8	0.4
Aspartate transaminase (µkat/L)	0.83(0.55-1.4)	1(0.75-1.7)	0.93(0.63-1.6)	0.2	0.2	0.6	0.4
Alanine transaminase (µkat/L)	0.8(0.4-1.6)	1.1(0.61-2.1)	0.9(0.5-1.8)	0.1	0.8	0.2	0.3
International normalized ratio	1.1 ± 0.19	1.2 ± 0.2	1.2 ± 0.3	0.9	0.3	0.9	0.3
High density lipoprotein (mmol/dl)	0.92 ± 0.26	0.96 ± 0.27	0.96 ± 0.26	0.7	0.5	0.9	0.7
Low density lipoprotein (mmol/dl)	1.92 (1.63-2.33)	2.02 (1.53-2.31)	1.89 (1.3-2.15)	0.4	0.3	0.6	0.8
Serum Triglyceride(mmol/dl)	1.17 (0.75-1.65)	1.08 (0.85-1.45)	0.96 (0.67-1.48)	0.2	0.1	0.3	0.4
Thyroid stimulating hormone (mIU/L)	2.6(0.8-3.5)	1.7(0.9-3.2)	1.0(0.6-2.5)	0.3	0.3	0.4	0.5

*Data expressed as Mean ± SD (Standard Deviation).

^**

Data expressed as Median (Interquartile range); RNA, Ribonucleic acid.

Discussion

IVDU was identified as a major risk factor and this group now forms the primary risk group for the propagation of HCV infection and must be so recognized. Although simplified decentralized routines with pan-genotypic drugs are becoming the norm for HCV care, IVDU access to these systems is still limited. Thus, incorporating the IVDU population into universal HCV care programmes should be a priority for achieving the HCV elimination goal.

Most of the HCV-infected patients in our study were genotype 3 (59%), in contrast with global data, where genotype 1 is most commonly found. Ours is not the only study indicating a higher prevalence of genotype 3.^14,15 We also found a high prevalence of genotype 6, also previously noted in the north-eastern region of India, but not as high. A study in 2012 of a predominantly tribal population in this region peculiarly found genotype 4 to be most common HCV though we found no case of genotype 4 at all.¹⁶

Information about the distribution of HCV genotypes is useful for epidemiological purposes, as transmission routes and changes in distribution pattern can be monitored thereby. Compared to the other genotypes, there is a dearth of literature on genotype 6. Historically this genotype is reported more commonly with IVDU;¹⁷ the northeast region's proximity to Asia in this regard is probably relevant.^18–20

While genotype 3 has traditionally been regarded as difficult-to-treat, genotype 1b has been linked to severe liver disease and a more aggressive course.^21,22 However, recent research has found that genotypes have no bearing on illness severity or progression.^17,23 Although the importance of genotype analysis has waned with the emergence of successful pan-genotypic regimens, our findings imply that resistance-associated substitutions and variations still play a role in genotype 3, the most frequent genotype in our region.²⁴ In cases with low viral loads, classification of genotype may be difficult, though we did not have this problem.

Our study has the limitation of being from a single tertiary care referral centre; some referral bias influencing disease distributions may therefore occur. Also, we excluded those with HIV co-infection, an important subgroup of IVDU patients. Finally, because prior anti-HCV reports within the last six months were not available, acute seroconversion could not be documented. However, we found no patients with negative anti-HCV and positive HCV RNA, nor with very low levels of HCV RNA load, nor with high ALT or fluctuating RNA values (>1log10 IU /ml).^25–27

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Bhupen Barman

Akash Roy

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