Background
The
β-thalassemias are among the most common genetic diseases and affect millions of children throughout the world [
1]. Around 1.5% (80–90 million people) of the worldwide population are carriers for
β-thalassemia, with 50,000–60,000 new
β-thalassemia cases being born each year [
2].
β-thalassemia is most prevalent in the populations of Asia, the Indian subcontinent, the Mediterranean countries, Africa and the Middle East [
3‐
5]. In Pakistan,
β-thalassemia is one of the commonest inherited disorders, with a carrier frequency of 5 to 7% of the Pakistani population [
2].
β-thalassemia patients are now surviving to older ages due to the availability of blood transfusion and iron chelation. There are around 100,000 patients registered currently but the burden of disease is increasing, with 5000 to 9000 children born with the disorder annually [
6].
Bloodborne infections are the second commonest reason of death in
β-thalassemia patients in Pakistan [
2]. Regular blood transfusions in
β-thalassemia patients expose them to a higher risk of contracting HCV viral infection, especially if adequate viral screening of blood donors has not been undertaken. The infection risk in β-thalassemia patients acts as a marker for the risk of transfusion-transmitted infections in the general population as their exposure to blood transfusions is high. If the infection rate is low in
β-thalassemia patients it implies that the risk for the general population will be minimal.
Hepatitis C infection is one of the most common bloodborne infections. More than 10 million individuals are living with HCV infection in Pakistan, and hence vulnerable to high morbidity and mortality [
7]. Pakistan is a developing country: according to the Human Development Index of the United Nations, it stands in 150th position out of 189 countries and territories [
8]. The health standard in Pakistan is well below the international standards to which all countries aspire. Therefore, contaminated blood transfusion is still a main risk factor for the spread of HCV. This is due to the lack of screening and the widespread use of paid blood donors [
9]. Several studies have been published on the prevalence of HCV in
β-thalassemia patients in Pakistan and there is considerable variation in the prevalence reported in the individually published studies. The purpose of this study is to investigate the pooled prevalence based on the available published studies conducted on the prevalence of HCV infection in
β-thalassemia patients, and to describe its associated risk factors in Pakistan. To our knowledge, this is the first systematic review and meta-analysis to investigate the pooled prevalence of HCV infection in
β-thalassemia patients in the country.
Methods
Search strategy
A systematic literature search on PubMed, EMBASE, the Cochrane Library, Web of Sciences, Directory of Open Access Journal and Pakistani Journals Online websites was conducted by two authors (J.A.N. and S.A.) to find studies performed on the prevalence of HCV infection in
β-thalassemia patients and published from January 1st, 1995 to May 31st 2019. Using MeSH headings, we searched for, the terms “prevalence”, “epidemiology”, “seroprevalence”, “hepatitis C Virus”, “HCV”, “hepacivirus”, “hep C,” “thalassemia”,”
β-thalassemia”, “thalassemia major”, “multitransfused blood transfusion”, “patients”, “Pakistan”, and “Pakistani”, as well as variations thereof. The results were defined using the Preferred Reporting Items for Systematic and Meta-analyses (PRISMA) statement (Table
1) [
10], and the PRISMA 2009 checklist is attached in supplementary file S1.
Table 1Description and list of characteristics of the included studies
| 1995 | NA | 35 | 21 | 60.00 | Urban | Khyber Pakhtunkhwa | Both | NA | 14.28 | 85.71 | 6.5 | ELISA | Medium |
| 2003 | Cross-sectional | 80 | 29 | 36.25 | Urban | Khyber Pakhtunkhwa | Both | Jul. 1999 to Mar. 2001 | NA | NA | 7.5 | ELISA | Medium |
| 2005 | Cross-sectional | 250 | 142 | 56.80 | Urban | Khyber Pakhtunkhwa | both | Jan. 2000 to Jan. 2001 | 72.00 | 28 | 10 | ELISA | Medium |
| 2008 | Cross-sectional | 180 | 75 | 41.67 | Urban | Khyber Pakhtunkhwa | Both | Jan. 2002 to Dec. 2003 | NA | NA | 6.8 | ELISA | Good |
| 2011 | NA | 167 | 26 | 15.57 | Urban | Khyber Pakhtunkhwa | Both | NA | 62.28 | 36.7 | NA | RNA | Medium |
| 2013 | NA | 170 | 37 | 21.67 | Urban | Khyber Pakhtunkhwa | both | Jan. 2012 to Dec. 2012 | 55.29 | 44.71 | 10 | ELISA | Medium |
| 2015 | Cross-sectional | 180 | 14 | 7.77 | Urban | Khyber Pakhtunkhwa | Both | Jun. 2013 to Jul. 2014 | 38.89 | 61.11 | NA | NA | Medium |
| 2018 | NA | 324 | 18 | 5.56 | Urban | Khyber Pakhtunkhwa | Both | Oct. 2013 to Mar. 2014 | 34.50 | 60.23 | 15.5 | RNA | Medium |
| 2004 | Cross-sectional | 75 | 32 | 42.00 | Urban | Punjab | Both | Jul. to Sep. 2003 | 64.00 | 36 | 6.5 | ELISA | Good |
| 2010 | NA | 141 | 50 | 35.46 | Urban | Punjab | Both | Sep. 2008 to Aug. 2009 | 58.20 | 41.8 | 8 | ELISA | Medium |
| 2011 | Cross-sectional | 300 | 195 | 65.00 | Urban | Punjab | Both | NA | 34.33 | 65.67 | 10 | NA | Medium |
| 2013 | Cross-sectional | 95 | 40 | 42.11 | Urban | Punjab | Both | Oct. 2009 Apr. 2010 | 60.00 | 40 | 9.2 | ELISA | Medium |
| 2014 | NA | 95 | 45 | 47.00 | Both | Punjab | Both | Jul. 2017 to Sept. 2017 | 56.84 | 53.68 | 7 | ELISA | Good |
| 2014 | NA | 200 | 82 | 41.00 | Urban | Punjab | Both | Jan. 2013 to May 2013 | 12.00 | 88 | 8.5 | ELISA | Medium |
| 2015 | Cross-sectional | 262 | 146 | 55.73 | Urban | Punjab | Both | Nov. 2011 to Apr. 2012 | 40.07 | 59.92 | 9.26 | ELISA | Medium |
| 2015 | Cross-sectional | 145 | 99 | 68.27 | Urban | Punjab | Both | Jan. 2009 to Dec. 2009 | 63.45 | 36.55 | 9 | ELISA | Medium |
| 2017 | Cross-sectional | 470 | 216 | 45.95 | Urban | Punjab | Both | Mar. 2014 to Sep. 2014 | 65.96 | 34.04 | 4.8 | ELISA | Medium |
| 2017 | Cross-sectional | 130 | 27 | 20.76 | Urban | Punjab | Both | Jan. 2014 to Jun. 2014 | 60.00 | 40 | 9.7 | ELISA | Medium |
| 2018 | Cross-sectional | 200 | 82 | 41.00 | Urban | Punjab | Both | Jan. 2015 to Dec. 2016 | 43.00 | 57 | 10.11 | ELISA | Good |
| 1997 | NA | 91 | 46 | 50.54 | Urban | Sindh | Both | NA | 39.56 | 60.43 | 13 | NA | Medium |
| 2002 | Cross-sectional | 341 | 70 | 20.50 | Urban | Sindh | Both | Jun-91 | NA | NA | 5 | RNA | Good |
| 2004 | NA | 86 | 38 | 44.20 | Urban | Sindh | Both | NA | 31.40 | 67.44 | 12 | ELISA | Medium |
| 2011 | Cross-sectional | 79 | 34 | 43.00 | Urban | Sindh | Both | Jul. 2009to Sep. 2009 | 41.77 | 58.23 | 12 | ELISA | Medium |
| 2012 | Cross-sectional | 160 | 21 | 13.10 | Urban | Sindh | Both | Jan. 2010 to Dec. 2010 | 49.38 | 50.63 | 8.5 | ELISA | Medium |
| 2016 | Cross-sectional | 100 | 27 | 27.00 | Urban | Sindh | Both | Jun. 2011 to Jun. 2014 | 54.00 | 46 | 15 | ELISA | Good |
| 2005 | NA | 180 | 75 | 41.67 | Urban | Punjab + Khyber Pakhtunkhwa | Both | Jan. 2002 to Dec. 2003 | NA | NA | 6 | ELISA | Medium |
| 2016 | Cross-sectional | 1253 | 273 | 21.71 | Urban | Punjab + Sindh | Both | Jul. 2015 to Dec. 2015 | 46.21 | 53.79 | 10.1 | NA | Medium |
Inclusion and exclusion criteria
Studies were included in this study if: (1) they were published in peer-reviewed journals; (2) they were conducted in Pakistan; (3) they reported on the prevalence HCV in thalassemia patients; (4) they were published in the English language.
Studies were excluded if: (1) they were in languages other than English; (2) they were case series, reviews, letters, and editorials or commentaries; (3) they did not allow the calculation of the prevalence of HCV; (4) they were duplicates (using the same data), in which case the more recently published version only was considered; (5) they related to the Pakistani community living outside Pakistan.
After choosing the relevant articles, two reviewers (J.A.N. and S.A.) independently screened the titles and abstracts to identify articles for full-text read. The data was then extracted using a standardised data extraction template of Microsoft Office Excel 2013. Information extracted included: surname of first author, year of study, year of publication, geographic region (province), gender, study design, study setting (rural, urban or both), sample size and average age of β-thalassemia patients. Any disagreement regarding the extracted information was resolved by discussion and mutual consensus.
Evaluating the quality of the included studies
Two authors (J.A.N. and S.A.) also independently judged the methodological quality of each included study using Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies [
11]. Any disagreement on the quality assessment check list was resolved by discussion and consensus. We categorized the quality of each included study as ‘good’ if its scored at least 70% of the points available, ‘medium’ if it scored 50–69%, and ‘poor’ if its scored less than 50%.
Statistical analysis
Statistical analyses were conducted by the software R, version 3.5.3 [
12], using two packages: ‘meta’ and ‘metafor’. Random effects (DerSimonian-Laird) models were used to make point estimates and their 95% confidence intervals (95% CIs), as well as to estimate the pooled prevalence of HCV among the
β-thalassemia patients. A process for combining prevalence in the meta-analysis of multiple studies was used and the results presented in a forest plot. The Random effect models are more conservative than fixed effect models, and have better statistical properties in the presence of heterogeneity, as the random effects model allows both within-study and between-study variances [
13,
14]. The Freeman–Tukey Double Arcsine transformation was used to stabilise the variance prior to the calculation of the pooled estimates [
15]. Heterogeneity among the eligible articles was investigated with the
I2 index [
16]. For the
I2-index, values of 75, 50, and 25% were considered high, moderate, and low levels of heterogeneity, respectively. To determine the possible reasons for substantial heterogeneity, univariate meta-regression and sub group analyses were conducted by geographical location, sample size, year of study, year of publication, gender and average age of the
β-thalassemia patients. The presence of publication bias was evaluated by visually inspecting a funnel plot and test using Egger test [
17], with
p-value less than 0.05 indicating significant publication bias.
Discussion
The aim of this study was to summarise the available literature on the prevalence of hepatitis C virus infection in
β-thalassemia patients and its correlated risk factors in Pakistan. The result of this meta-analysis showed that the pooled prevalence based on 27 studies was 36.21%. More than one in every three
β-thalassemia patients in Pakistan have already been exposed to HCV infection. The pooled prevalence of HCV in
β-thalassemia patients, as showed by this study is six times higher (36.21%) than in the general Pakistani population which is 6.2% [
45]. In Pakistan, many patients with
β-thalassemia have limited access to regular and safe blood transfusions. Possible reasons for this are the lack of altruistic voluntary blood donors and the inadequate testing of blood donations for HCV. Many blood transfusion centers and hospitals have inadequate resources and kits for screening blood donations [
5]. The root cause of the high prevalence is predominantly the lack of adequate regulation of blood banks and monitoring to assess compliance with transfusion safety standards. It is well recognized that, with proper regulation driven by policy makers, transfusion transmitted infections are markedly reduced [
5]. Pakistan is a low resource country: the pooled prevalence of HCV in
β-thalassemia patients in Pakistan is higher than that in Iran [
46] (19%) or Bangladesh [
47] (14.7%). The findings of this study should act as a major safety alert for decision and policy-makers in the Pakistani health sector.
Our data on HCV infection prevalence among the β-thalassemia patients covers all provinces of Pakistan except Baluchistan and Gilgit-Baltistan. Our results showed that the prevalence of HCV infection in β-thalassemia patients was higher in Punjab (45.98%) than in Sindh (31.81%) and Khyber Pakhtunkhwa (28.04%).
In this paper, we observed that the prevalence of HCV in β-thalassemia patients rises with age, increasing from 33.87% in the under 10 years age group to 51.51% in the 10 years or above age group. This effect was not statistically significant at conventional levels. We believe that age is acting as a proxy for other effects. Age is associated with cumulative exposure to blood transfusions over a life time and it is the number of blood transfusions which is associated with increased risk of HCV infection. Unfortunately, we do not have data on the number of blood transfusion patients had received. Conversely, one could look at this more positively and suggest that the frequency of testing for HCV positive blood donations has improved and hence younger patients have a lower infection rate than their older fellow patients did when they were the same age, due to safer blood donations.
Meta-regression analyses showed that there was no significant change in the prevalence of HCV in β-thalassemia patients over the past three decades (with both years of publication and year of study (data collection).
To our knowledge, this is the first systematic review and meta-analysis to compile current data on the prevalence of HCV infection among β-thalassemia patients in Pakistan. The main strengths of this study are the use of a comprehensive and a predefined literature search strategy, and the involvement of two independent reviewers in the whole review process and data extraction. No publication bias was found within our analyses which suggests that we are unlikely to have missed any potential studies that could change the results of this meta-analysis. Furthermore, the methodological quality of all included articles had a low risk of bias. As showed by meta-regression analysis, the methodological quality of the studies had no influence on pooled prevalence estimates. Three provinces of Pakistan were covered in the investigation of HCV infection prevalence in β-thalassemia patients. On the other hand, the findings of this study have some limitations. Firstly, the meta-regression analysis was only based on bivariate analysis. We planned to use a multivariate meta-regression model by considering all the factors simultaneously, however, it was not possible to use multivariate meta-regression analysis due to the small number of studies. A multivariate meta-regression analysis requires at least ten studies per factor to estimate the meta-regression coefficients efficiently. Second, and as is common in meta-analyses, the study estimates revealed substantial heterogeneity between the included studies, which may be due to the other sources of variation may have been missed in our analysis, such as the number of blood transfusions, some genetic factors, and type of β-thalassemia; but we were unable to investigate these factors due to lack of data.
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