Determinants of HIV-1 Late Presentation in Patients Followed in Europe

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Abstract

To control the Human Immunodeficiency Virus (HIV) pandemic, the World Health Organization (WHO) set the 90-90-90 target to be reached by 2020. One major threat to those goals is late presentation, which is defined as an individual presenting a TCD4+ count lower than 350 cells/mm ³ or an AIDS-defining event. The present study aims to identify determinants of late presentation in Europe based on the EuResist database with HIV-1 infected patients followed-up between 1981 and 2019. Our study includes clinical and socio-demographic information from 89851 HIV-1 infected patients. Statistical analysis was performed using RStudio and SPSS and a Bayesian network was constructed with the WEKA software to analyze the association between all variables. Among 89,851 HIV-1 infected patients included in the analysis, the median age was 33 (IQR: 27.0–41.0) years and 74.4% were males. Of those, 28,889 patients (50.4%) were late presenters. Older patients (>56), heterosexuals, patients originated from Africa and patients presenting with log VL >4.1 had a higher probability of being late presenters ( p < 0.001). Bayesian networks indicated VL, mode of transmission, age and recentness of infection as variables that were directly associated with LP. This study highlights the major determinants associated with late presentation in Europe. This study helps to direct prevention measures for this population.

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Global prevalence of injecting drug use and sociodemographic characteristics and prevalence of HIV, HBV, and HCV in people who inject drugs: a multistage systematic review

Louisa Degenhardt, Amy Peacock, Samantha Colledge … (2017)

Summary Background Sharing of equipment used for injecting drug use (IDU) is a substantial cause of disease burden and a contributor to blood-borne virus transmission. We did a global multistage systematic review to identify the prevalence of IDU among people aged 15–64 years; sociodemographic characteristics of and risk factors for people who inject drugs (PWID); and the prevalence of HIV, hepatitis C virus (HCV), and hepatitis B virus (HBV) among PWID. Methods Consistent with the GATHER and PRISMA guidelines and without language restrictions, we systematically searched peer-reviewed databases (MEDLINE, Embase, and PsycINFO; articles published since 2008, latest searches in June, 2017), searched the grey literature (websites and databases, searches between April and August, 2016), and disseminated data requests to international experts and agencies (requests sent in October, 2016). We searched for data on IDU prevalence, characteristics of PWID, including gender, age, and sociodemographic and risk characteristics, and the prevalence of HIV, HCV, and HBV among PWID. Eligible data on prevalence of IDU, HIV antibody, HBsAg, and HCV antibody among PWID were selected and, where multiple estimates were available, pooled for each country via random effects meta-analysis. So too were eligible data on percentage of PWID who were female; younger than 25 years; recently homeless; ever arrested; ever incarcerated; who had recently engaged in sex work, sexual risk, or injecting risk; and whose main drugs injected were opioids or stimulants. We generated regional and global estimates in line with previous global reviews. Findings We reviewed 55 671 papers and reports, and extracted data from 1147 eligible records. Evidence of IDU was recorded in 179 of 206 countries or territories, which cover 99% of the population aged 15–64 years, an increase of 31 countries (mostly in sub-Saharan Africa and the Pacific Islands) since a review in 2008. IDU prevalence estimates were identified in 83 countries. We estimate that there are 15·6 million (95% uncertainty interval [UI] 10·2–23·7 million) PWID aged 15–64 years globally, with 3·2 million (1·6–5·1 million) women and 12·5 million (7·5–18·4 million) men. Gender composition varied by location: women were estimated to comprise 30·0% (95% UI 28·5–31·5) of PWID in North America and 33·4% (31·0–35·6) in Australasia, compared with 3·1% (2·1–4·1) in south Asia. Globally, we estimate that 17·8% (10·8–24·8) of PWID are living with HIV, 52·3% (42·4–62·1) are HCV-antibody positive, and 9·0% (5·1–13·2) are HBV surface antigen positive; there is substantial geographic variation in these levels. Globally, we estimate 82·9% (76·6–88·9) of PWID mainly inject opioids and 33·0% (24·3–42·0) mainly inject stimulants. We estimate that 27·9% (20·9–36·8) of PWID globally are younger than 25 years, 21·7% (15·8–27·9) had recently (within the past year) experienced homelessness or unstable housing, and 57·9% (50·5–65·2) had a history of incarceration. Interpretation We identified evidence of IDU in more countries than in 2008, with the new countries largely consisting of low-income and middle-income countries in Africa. Across all countries, a substantial number of PWID are living with HIV and HCV and are exposed to multiple adverse risk environments that increase health harms. Funding Australian National Drug and Alcohol Research Centre, Australian National Health and Medical Research Council, Open Society Foundation, World Health Organization, the Global Fund, and UNAIDS.

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Automated subtyping of HIV-1 genetic sequences for clinical and surveillance purposes: performance evaluation of the new REGA version 3 and seven other tools.

Stijn Imbrechts, Arley Gómez-López, Carlos Camacho … (2013)

To investigate differences in pathogenesis, diagnosis and resistance pathways between HIV-1 subtypes, an accurate subtyping tool for large datasets is needed. We aimed to evaluate the performance of automated subtyping tools to classify the different subtypes and circulating recombinant forms using pol, the most sequenced region in clinical practice. We also present the upgraded version 3 of the Rega HIV subtyping tool (REGAv3). HIV-1 pol sequences (PR+RT) for 4674 patients retrieved from the Portuguese HIV Drug Resistance Database, and 1872 pol sequences trimmed from full-length genomes retrieved from the Los Alamos database were classified with statistical-based tools such as COMET, jpHMM and STAR; similarity-based tools such as NCBI and Stanford; and phylogenetic-based tools such as REGA version 2 (REGAv2), REGAv3, and SCUEAL. The performance of these tools, for pol, and for PR and RT separately, was compared in terms of reproducibility, sensitivity and specificity with respect to the gold standard which was manual phylogenetic analysis of the pol region. The sensitivity and specificity for subtypes B and C was more than 96% for seven tools, but was variable for other subtypes such as A, D, F and G. With regard to the most common circulating recombinant forms (CRFs), the sensitivity and specificity for CRF01_AE was ~99% with statistical-based tools, with phylogenetic-based tools and with Stanford, one of the similarity based tools. CRF02_AG was correctly identified for more than 96% by COMET, REGAv3, Stanford and STAR. All the tools reached a specificity of more than 97% for most of the subtypes and the two main CRFs (CRF01_AE and CRF02_AG). Other CRFs were identified only by COMET, REGAv2, REGAv3, and SCUEAL and with variable sensitivity. When analyzing sequences for PR and RT separately, the performance for PR was generally lower and variable between the tools. Similarity and statistical-based tools were 100% reproducible, but this was lower for phylogenetic-based tools such as REGA (~99%) and SCUEAL (~96%). REGAv3 had an improved performance for subtype B and CRF02_AG compared to REGAv2 and is now able to also identify all epidemiologically relevant CRFs. In general the best performing tools, in alphabetical order, were COMET, jpHMM, REGAv3, and SCUEAL when analyzing pure subtypes in the pol region, and COMET and REGAv3 when analyzing most of the CRFs. Based on this study, we recommend to confirm subtyping with 2 well performing tools, and be cautious with the interpretation of short sequences. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

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COMET: adaptive context-based modeling for ultrafast HIV-1 subtype identification

Daniel Struck, Glenn Lawyer, Anne-Marie Ternes … (2014)

Viral sequence classification has wide applications in clinical, epidemiological, structural and functional categorization studies. Most existing approaches rely on an initial alignment step followed by classification based on phylogenetic or statistical algorithms. Here we present an ultrafast alignment-free subtyping tool for human immunodeficiency virus type one (HIV-1) adapted from Prediction by Partial Matching compression. This tool, named COMET, was compared to the widely used phylogeny-based REGA and SCUEAL tools using synthetic and clinical HIV data sets (1 090 698 and 10 625 sequences, respectively). COMET's sensitivity and specificity were comparable to or higher than the two other subtyping tools on both data sets for known subtypes. COMET also excelled in detecting and identifying new recombinant forms, a frequent feature of the HIV epidemic. Runtime comparisons showed that COMET was almost as fast as USEARCH. This study demonstrates the advantages of alignment-free classification of viral sequences, which feature high rates of variation, recombination and insertions/deletions. COMET is free to use via an online interface.

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Alessandra Borsetti: Role: Academic Editor

Journal

Journal ID (nlm-ta): Pathogens

Journal ID (iso-abbrev): Pathogens

Journal ID (publisher-id): pathogens

Title: Pathogens

Publisher: MDPI

ISSN (Electronic): 2076-0817

Publication date (Electronic): 02 July 2021

Publication date Collection: July 2021

Volume: 10

Issue: 7

Electronic Location Identifier: 835

Affiliations

[1 ]Global Health and Tropical Medicine (GHTM), Institute of Hygiene and Tropical Medicine, New University of Lisbon (IHMT/UNL), 1349-008 Lisbon, Portugal; martapingarilho@ 123456ihmt.unl.pt (M.P.); victor.pimentel@ 123456ihmt.unl.pt (V.P.); mrfom@ 123456ihmt.unl.pt (M.d.R.O.M.); annemie.vandamme@ 123456uzleuven.be (A.-M.V.); ana.abecasis@ 123456ihmt.unl.pt (A.A.)

[2 ]Laboratory Clinical and Epidemiological Virology, Department of Microbiology and Immunology, KU Leuven, Rega Institute for Medical Research, 3000 Leuven, Belgium

[3 ]Gamaleya Research Center of Epidemiology and Microbiology, Department of General Virology, Gamaleya Scientific Research Institute, 123098 Moscow, Russia; mrbobkova@ 123456mail.ru

[4 ]Department of Medicine, Saarland University Hospital, 66421 Homburg, Germany; michael.boehm@ 123456uk-koeln.de

[5 ]Laboratory of Retrovirology, Department of Infection and Immunity, Luxembourg Institute of Health, L-4354 Esch-sur-Alzette, Luxembourg; carole.devaux@ 123456lih.lu

[6 ]Infectious Diseases Department and IrsiCaixa AIDS Research Institute, Hospital Universitari Germans Trias i Pujol, 08916 Badalona, Spain; rparedes@ 123456irsicaixa.es

[7 ]Hospital Universitario 12 de Octubre, Universidad Complutense de Madrid, 28026 Madrid, Spain; rafaelrubiogarcia@ 123456ucm.es

[8 ]Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy; maurizio.zazzi@ 123456unisi.it

[9 ]IPRO—InformaPRO S.r.l., 98, 00152 Rome, Italy; f.incardona@ 123456informa.pro

[10 ]EuResist Network, 98/100, 00152 Rome, Italy

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[* ]Correspondence: a21000919@ 123456ihmt.unl.pt ; Tel.: +351-213-652-600

Author information

Marta Pingarilho https://orcid.org/0000-0002-7928-3087

Maria do Rosário O. Martins https://orcid.org/0000-0002-7941-0285

Marina Bobkova https://orcid.org/0000-0001-5481-8957

Michael Böhm https://orcid.org/0000-0003-1208-8647

Carole Seguin-Devaux https://orcid.org/0000-0003-0636-5222

Maurizio Zazzi https://orcid.org/0000-0002-0344-6281

Ana Abecasis https://orcid.org/0000-0002-3903-5265

Article

Publisher ID: pathogens-10-00835

DOI: 10.3390/pathogens10070835

PMC ID: 8308660

PubMed ID: 34357985

SO-VID: f7b05cd3-e560-472e-a7f0-d52683a18dbf

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Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

Determinants of HIV-1 Late Presentation in Patients Followed in Europe

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Special feature: Europe and Education

Most cited references 37

Global prevalence of injecting drug use and sociodemographic characteristics and prevalence of HIV, HBV, and HCV in people who inject drugs: a multistage systematic review

Automated subtyping of HIV-1 genetic sequences for clinical and surveillance purposes: performance evaluation of the new REGA version 3 and seven other tools.

COMET: adaptive context-based modeling for ultrafast HIV-1 subtype identification

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