A cross-sectional study of hepatitis C among people living with HIV in Cambodia: Prevalence, risk factors, and potential for targeted screening

Weggheleire, Anja De; An, Shengli; Baetselier, Irith De; Soeung, Pisith; Keath, Huy; So, Veasna; Ros, Sreyphors; Teav, Syna; Smekens, Bart; Buyze, Jozefien; Florence, Éric; Griensven, Johan van; Thai, Sopheak; Francque, Sven; Lynen, Lutgarde

doi:10.1371/journal.pone.0183530

Cited by 26 publications

(37 citation statements)

References 33 publications

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“…In contrast, HCV emerged earlier than HIV from at least three HCV-independent introductions. However, those infections were unknown given the lack of routine diagnosis and no apparent HCV symptoms [30, 31]. Another possibility to explain this temporal difference may be related to a reduced transmissibility of HIV, with a lower ex vivo viability in needles/syringes (few hours for HIV versus at least 7 days for HCV), as documented by some researchers [32].…”

Section: Discussionmentioning

confidence: 99%

Massive Iatrogenic Outbreak of Human Immunodeficiency Virus Type 1 in Rural Cambodia, 2014–2015

Raffi

Nouhin

Zheng

et al. 2017

Clinical Infectious Diseases

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Background In 2014–2015, 242 individuals aged 2–89 were newly HIV-1 diagnosed in Roka, a rural commune in Cambodia. A case-control study attributed the outbreak to unsafe injections. We aimed to reconstruct the likely transmission history of the outbreak. Methods We assessed in 209 (86.4%) HIV-infected cases the presence of hepatitis C and B viruses (HCV, HBV). We identified recent infections using antibody (Ab) avidity testing for HIV and HCV, and HBcIgM Ab for HBV. We performed evolutionary phylogenetic analyses of viral strains. Geographical coordinates and parenteral exposure through medical services provided by an unlicensed health care practitioner were obtained from 193 cases and 1499 controls during interviews. Results Cases were co-infected with HCV (78.5%) and HBV (12.9%). We identified 79 (37.8%) recent (<130 days) HIV infections. Phylogeny of 202 HIV env C2V3 sequences showed a 198-sample CRF01_AE strains cluster, with time to most recent common ancestor (tMRCA) in September 2013 (95% highest posterior density, August 2012–July 2014), and a peak of 15 infections/day in September 2014. Three geospatial HIV hotspots were discernible in Roka and correlated with high exposure to the practitioner (P=0.04). Fifty-nine (38.6%) of 153 tested cases showed recent (<180 days) HCV infections. Ninety HCV NS5B sequences formed three main clades, one containing 34 subtypes 1b with tMRCA in 2012, and two with 51 subtypes 6e and tMRCAs in 2002–2003. Conclusions Unsafe injections in Cambodia most likely led to an explosive iatrogenic spreading of HIV, associated with a long-standing and more genetically-diverse HCV propagation.

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Section: Discussionmentioning

confidence: 99%

Massive Iatrogenic Outbreak of Human Immunodeficiency Virus Type 1 in Rural Cambodia, 2014–2015

Raffi

Nouhin

Zheng

et al. 2017

Clinical Infectious Diseases

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“…Isso ocorre porque ambas as doenças apresentam vias de transmissão semelhantes. Em pacientes coinfectados, a agressividade e a progressão da infecção por HCV é maior em decorrência da alta replicação viral, e, como consequência, ocorre o maior risco para o desenvolvimento de cirrose hepática e carcinoma hepatocelular (24)(25)(26) .…”

Section: Discussionunclassified

Dinâmica Espacial E Temporal Da Infecção Pelo Vírus Da Hepatite C

Santos

Araújo

Menezes

et al. 2017

ACS

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Introdução: O Vírus da Hepatite C (HCV) é uma das principais causas de doença hepática crônica em todo o mundo. O Brasil é um país com uma prevalência intermediária de 1% a 2% e com características epidemiológicas distintas conforme região geográfica estudada. Objetivo: Analisar a dinâmica espacial e a tendência temporal da infecção pelo vírus da hepatite C no estado de Sergipe, durante o período de 2007 a 2015. Material e métodos: Estudo ecológico e descritivo, através do uso de dados secundários dos casos de HCV notificados no Sistema de Informação de Agravos de Notificação (SINAN), de 2007 a 2015. Analisaram-se as tendências temporais por sexo e faixa etária através de regressão linear, considerando-se p<0,05 e obtendo-se a variação percentual anual (APC). Para a análise espacial foi adotado o estimador de densidade Kernel, sendo as análises realizadas no software TerraView 4.2.2. Resultados: Foram notificados 567 casos de hepatite C no estado de Sergipe. Predominou o sexo masculino (62,08%); pardo (66,13%); faixa etária de 50 a 59 anos (31,74%). A coinfecção HIV/HCV ocorreu em 5,64% (n=32). A prevalência variou de 2,51 (2007) para 3,34 (2015) casos por 100 mil habitantes, aumento de 33,06%. Observaram-se tendências decrescentes para crianças e adultos de 20 a 39 anos, e crescentes, para adolescentes, adultos de 40 a 59 anos e idosos. A análise espacial permitiu a construção de mapas apontando a existência de clusters (“hot spots”), no entanto não foi verificada presença de autocorrelação espacial, apresentando uma distribuição espacial heterogênea da infecção pelo HCV. Conclusão: Apesar das flutuações nas taxas, no geral ocorreu uma tendência crescente da ocorrência de casos de hepatite C no estado de Sergipe.

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“…We compared the performance of the predictive models on a dataset of a cross-sectional HCV diagnostic study conducted in the HIV cohort of Sihanouk Hospital Center of Hope (SHCH) in Phnom Penh, Cambodia (clinicaltrials.gov NCT02361541) [5]. The information on potential predictors (by history-taking, physical examination and laboratory testing) was collected prospectively following a pre-specified study protocol, and whilst results of HCV diagnostic testing were yet unknown.…”

Section: Data Sourcementioning

confidence: 99%

“…Until recently, treating HCV was complex, not affordable, poorly successful and not considered for programming in low and middle income countries (LMIC). Recently, with the advent of affordable generic HCV Direct Acting Antivirals this low-to-intermediate HCV/HIV co-infection rates among HIV populations without specific risk profile [5,6], targeted HCV screening is potentially a more feasible and cost-effective screening strategy for many HIV cohorts in LMIC (except for HIV populations with higher risk profile, as men having sex with men, and people who use drugs), especially in this initial phase of HCV care scaleup. Simple tools or scores to guide targeted screening, other than birth-cohort screening, do not exist.…”

Section: Introductionmentioning

confidence: 99%

Comparison of predictive models for hepatitis C co-infection among HIV patients in Cambodia

et al. 2020

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Background: Hepatitis C virus (HCV) infection is a major global health problem. WHO guidelines recommend screening all people living with HIV for hepatitis C. Considering the limited resources for health in low and middle income countries, targeted HCV screening is potentially a more feasible screening strategy for many HIV cohorts. Hence there is an interest in developing clinician-friendly tools for selecting subgroups of HIV patients for whom HCV testing should be prioritized. Several statistical methods have been developed to predict a binary outcome. Multiple studies have compared the performance of different predictive models, but results were inconsistent. Methods: A cross-sectional HCV diagnostic study was conducted in the HIV cohort of Sihanouk Hospital Center of Hope in Phnom Penh, Cambodia. We compared the performance of logistic regression, Spiegelhalter-Knill-Jones and CART to predict Hepatitis C co-infection in this cohort. We estimated the number of HCV co-infections that would be missed. To correct for over-optimism, the leave-one-out bootstrap estimator was used for estimating this quantity. Results: Logistic regression misses the fewest HCV co-infections (8%), but would still refer 98% of HIV patients for HCV testing. Spiegelhalter-Knill-Jones (SKJ) and CART respectively miss 12% and 29% of HCV co-infections but would only refer about 30% for HCV testing. Conclusions: In our dataset, logistic regression has the highest log-likelihood and smallest proportions of HCV co-infections missed but Spiegelhalter-Knill-Jones has the highest area under the ROC curve. The likelihood ratios estimated by Spiegelhalter-Knill-Jones might be easier to interpret for clinicians than odds ratios estimated by logistic regression or the decision tree from CART. CART is the most flexible method, and no model has to be specified regarding presence of interactions and form of the relationship between outcome and predictor variables.

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A cross-sectional study of hepatitis C among people living with HIV in Cambodia: Prevalence, risk factors, and potential for targeted screening

Cited by 26 publications

References 33 publications

Massive Iatrogenic Outbreak of Human Immunodeficiency Virus Type 1 in Rural Cambodia, 2014–2015

Massive Iatrogenic Outbreak of Human Immunodeficiency Virus Type 1 in Rural Cambodia, 2014–2015

Dinâmica Espacial E Temporal Da Infecção Pelo Vírus Da Hepatite C

Comparison of predictive models for hepatitis C co-infection among HIV patients in Cambodia

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