Cohort Profile: A European Multidisciplinary Network for the Fight against HIV Drug Resistance (EuResist Network)

: The EuResist cohort was established in 2006 with the purpose of developing a clinical decision-support tool predicting the most effective antiretroviral therapy (ART) for persons living with HIV (PLWH), based on their clinical and virological data. Further to continuous extensive data collection from several European countries, the EuResist cohort later widened its activity to the more general area of antiretroviral treatment resistance with a focus on virus evolution. The EuResist cohort has retrospectively enrolled PLWH, both treatment-naïve and treatment-experienced, under clinical follow-up from 1998, in nine national cohorts across Europe and beyond, and this article is an overview of its achievement. A clinically oriented treatment-response prediction system was released and made available online in 2008. Clinical and virological data have been collected from more than one hundred thousand PLWH, allowing for a number of studies on the response to treatment, selection and spread of resistance-associated mutations and the circulation of viral subtypes. Drawing from its interdisciplinary vocation, EuResist will continue to investigate clinical response to antiretroviral treatment against HIV and monitor the development and circulation of HIV drug resistance in clinical settings, along with the development of novel drugs and the introduction of new treatment strategies. The support of artificial intelligence in these activities is essential

Only Slight Impact of Predicted Replicative Capacity for Therapy Response Prediction

BACKGROUND: Replication capacity (RC) of specific HIV isolates is occasionally blamed for unexpected treatment responses. However, the role of viral RC in response to antiretroviral therapy is not yet fully understood. MATERIALS AND METHODS: We developed a method for predicting RC from genotype using support vector machines (SVMs) trained on about 300 genotype-RC pairs. Next, we studied the impact of predicted viral RC (pRC) on the change of viral load (VL) and CD4(+) T-cell count (CD4) during the course of therapy on about 3,000 treatment change episodes (TCEs) extracted from the EuResist integrated database. Specifically, linear regression models using either treatment activity scores (TAS), the drug combination, or pRC or any combination of these covariates were trained to predict change in VL and CD4, respectively. RESULTS: The SVM models achieved a Spearman correlation (rho) of 0.54 between measured RC and pRC. The prediction of change in VL (CD4) was best at 180 (360) days, reaching a correlation of rho = 0.45 (rho = 0.27). In general, pRC was inversely correlated to drug resistance at treatment start (on average rho = -0.38). Inclusion of pRC in the linear regression models significantly improved prediction of virological response to treatment based either on the drug combination or on the TAS (t-test; p-values range from 0.0247 to 4 10(-6)) but not for the model using both TAS and drug combination. For predicting the change in CD4 the improvement derived from inclusion of pRC was not significant. CONCLUSION: Viral RC could be predicted from genotype with moderate accuracy and could slightly improve prediction of virological treatment response. However, the observed improvement could simply be a consequence of the significant correlation between pRC and drug resistance

A Comparison Between the Populations of Late Presenters and Non-late Presenters

Funding Information: We want to thank Frank Tang, Bin Lin, Mike Cohen and the rest of the Google speech team for their insightful discussions and inputs. Publisher Copyright: Copyright © 2022 Miranda, Pingarilho, Pimentel, Martins, Kaiser, Seguin-Devaux, Paredes, Zazzi, Incardona and Abecasis.Background: The increased use of antiretroviral therapy (ART) has decreased mortality and morbidity of HIV-1 infected people but increasing levels of HIV drug resistance threatens the success of ART regimens. Conversely, late presentation can impact treatment outcomes, health costs, and potential transmission of HIV. Objective: To describe the patterns of transmitted drug resistance (TDR) and acquired drug resistance (ADR) in HIV-1 infected patients followed in Europe, to compare its patterns in late presenters (LP) vs non-late presenters (NLP), and to analyze the most prevalent drug resistance mutations among HIV-1 subtypes. Methods: Our study included clinical, socio-demographic, and genotypic information from 26,973 HIV-1 infected patients from the EuResist Integrated Database (EIDB) between 1981 and 2019. Results: Among the 26,973 HIV-1 infected patients in the analysis, 11,581 (42.9%) were ART-naïve patients and 15,392 (57.1%) were ART-experienced. The median age was 37 (IQR: 27.0–45.0) years old and 72.6% were males. The main transmission route was through heterosexual contact (34.9%) and 81.7% of patients originated from Western Europe. 71.9% of patients were infected by subtype B and 54.8% of patients were classified as LP. The overall prevalence of TDR was 12.8% and presented an overall decreasing trend (p for trend < 0.001), the ADR prevalence was 68.5% also with a decreasing trend (p for trend < 0.001). For LP and NLP, the TDR prevalence was 12.3 and 12.6%, respectively, while for ADR, 69.9 and 68.2%, respectively. The most prevalent TDR drug resistance mutations, in both LP and NLP, were K103N/S, T215rev, T215FY, M184I/V, M41I/L, M46I/L, and L90M. Conclusion: Our study showed that the overall TDR (12.8%) and ADR (68.5%) presented decreasing trends during the study time period. For LP, the overall TDR was slightly lower than for NLP (12.3 vs 12.6%, respectively); while this pattern was opposite for ADR (LP slightly higher than NLP). We suggest that these differences, in the case of TDR, can be related to the dynamics of fixation of drug resistance mutations; and in the case of ADR with the more frequent therapeutic failure in LPs.publishersversionpublishe

Drug resistance testing through remote genotyping and predicted treatment options in human immunodeficiency virus type 1 infected Tanzanian subjects failing first or second line antiretroviral therapy

Antiretroviral therapy (ART) has been successfully introduced in low-middle income countries. However an increasing rate of ART failure with resistant virus is reported. We therefore described the pattern of drug resistance mutations at antiretroviral treatment (ART) failure in a real-life Tanzanian setting using the remote genotyping procedure and thereafter predicted future treatment options using rule-based algorithm and the EuResist bioinformatics predictive engine. According to national guidelines, the default first-line regimen is tenofovir + lamivudine + efavirenz, but variations including nevirapine, stavudine or emtricitabine can be considered. If failure on first-line ART occurs, a combination of two nucleoside reverse transcriptase inhibitors (NRTIs) and boosted lopinavir or atazanavir is recommended

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

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/mm3 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 89,851 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 89851 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

Early versus delayed antiretroviral therapy based on genotypic resistance test: Results from a large retrospective cohort study

Rapid start of antiretroviral therapy (ART) pending genotypic resistance test&nbsp;(GRT) has been recently proposed, but the effectiveness of this strategy is still debated.&nbsp;The rate of virological success (VS), defined as HIV-RNA\u2009&lt;\u200950 copies/ml, with and without GRT was compared in drug-na\uefve individuals enrolled in the Italian ARCA cohort who started ART between 2015 and 2018.&nbsp;521 individuals started ART: 397 without GRT (pre-GRT group) and 124 following GRT (post-GRT group). Overall, 398 (76%) were males and 30 (6%) were diagnosed with AIDS. In the pre-GRT group, baseline CD4+\u2009cell counts were lower (p\u2009&lt;\u20090.001), and viral load was higher (p\u2009&lt;\u20090.001) than in the post-GRT group. The estimated probability of VS in pre-GRT versus post-GRT group was 72.54% (CI95 : 67.78-76.60) versus 66.94% (CI95 : 57.53-74.26) at Week 24&nbsp;and 92.40% (CI95 : 89.26-94.62) versus 92.92% (CI95 : 86.35-96.33) at Week 48, respectively (p\u2009=\u20090.434). At Week 48, VS was less frequent among individuals with baseline CD4+\u2009cell counts &lt;200 versus &gt;500 (90.33% vs. 97.33%), log viral load &lt;5.00&nbsp;versus &gt;5.70 log10 cps/ml (97.17% vs 78.16%;&nbsp;p\u2009&lt;\u20090.001), and those treated with protease inhibitors or non-nucleoside reverse transcriptase inhibitors versus those treated with integrase strand transfer inhibitors (p\u2009&lt;\u20090.001).&nbsp;The rate of VS does not seem to be affected by an early ART initiation pending GRT results, but it could be influenced by the composition of the ART regimen, as well as immuno-virological parameters

Earlier initiation of antiretroviral treatment coincides with an initial control of the HIV-1 sub-subtype F1 outbreak among men-having-sex-with-men in Flanders, Belgium

Human immunodeficiency virus type 1 (HIV-1) non-B subtype infections occurred in Belgium since the 1980s, mainly amongst migrants and heterosexuals, whereas subtype B predominated in men-having-sex-with-men (MSM). In the last decade, the diagnosis of F1 sub-subtype in particular has increased substantially, which prompted us to perform a detailed reconstruction of its epidemiological history. To this purpose, the Belgian AIDS Reference Laboratories collected HIV-1 pol sequences from all sub-subtype F1-infected patients for whom genotypic drug resistance testing was requested as part of routine clinical follow-up. This data was complemented with HIV-1 pol sequences from countries with a high burden of F1 infections or a potential role in the global origin of sub-subtype F1. The molecular epidemiology of the Belgian subtype F1 epidemic was investigated using Bayesian phylogenetic inference and transmission dynamics were characterized based on birth-death models. F1 sequences were retained from 297 patients diagnosed and linked to care in Belgium between 1988 and 2015. Phylogenetic inference indicated that among the 297 Belgian F1 sequences, 191 belonged to a monophyletic group that mainly contained sequences from people likely infected in Belgium (OR 26.67, 95% CI 9.59-74.15), diagnosed in Flanders (OR 7.28, 95% CI 4.23-12.53), diagnosed at a recent stage of infection (OR 7.19, 95% CI 2.88-17.95) or declared to be MSM (OR 34.8, 95% CI 16.0-75.6). Together with a Spanish clade, this Belgian clade was embedded in the genetic diversity of Brazilian subtype F1 strains and most probably emerged after one or only a few migration events from Brazil to the European continent before 2002. The origin of the Belgian outbreak was dated back to 2002 (95% higher posterior density 2000-2004) and birth-death models suggested that its extensive growth had been controlled (Re < 1) by 2012, coinciding with a time period where delay in antiretroviral treatment initiation substantially declined. In conclusion, phylogenetic reconstruction of the Belgian HIV-1 sub-subtype F1 epidemic illustrates the introduction and substantial dissemination of viral strains in a geographically restricted risk group that was most likely controlled by effective treatment as prevention.publishersversionpublishe

Comparison of Classifier Fusion Methods for Predicting Response to Anti HIV-1 Therapy

BACKGROUND: Analysis of the viral genome for drug resistance mutations is state-of-the-art for guiding treatment selection for human immunodeficiency virus type 1 (HIV-1)-infected patients. These mutations alter the structure of viral target proteins and reduce or in the worst case completely inhibit the effect of antiretroviral compounds while maintaining the ability for effective replication. Modern anti-HIV-1 regimens comprise multiple drugs in order to prevent or at least delay the development of resistance mutations. However, commonly used HIV-1 genotype interpretation systems provide only classifications for single drugs. The EuResist initiative has collected data from about 18,500 patients to train three classifiers for predicting response to combination antiretroviral therapy, given the viral genotype and further information. In this work we compare different classifier fusion methods for combining the individual classifiers. PRINCIPAL FINDINGS: The individual classifiers yielded similar performance, and all the combination approaches considered performed equally well. The gain in performance due to combining methods did not reach statistical significance compared to the single best individual classifier on the complete training set. However, on smaller training set sizes (200 to 1,600 instances compared to 2,700) the combination significantly outperformed the individual classifiers (p<0.01; paired one-sided Wilcoxon test). Together with a consistent reduction of the standard deviation compared to the individual prediction engines this shows a more robust behavior of the combined system. Moreover, using the combined system we were able to identify a class of therapy courses that led to a consistent underestimation (about 0.05 AUC) of the system performance. Discovery of these therapy courses is a further hint for the robustness of the combined system. CONCLUSION: The combined EuResist prediction engine is freely available at http://engine.euresist.org

Comparison of HIV-1 Genotypic Resistance Test Interpretation Systems in Predicting Virological Outcomes Over Time

Background: Several decision support systems have been developed to interpret HIV-1 drug resistance genotyping results. This study compares the ability of the most commonly used systems (ANRS, Rega, and Stanford's HIVdb) to predict virological outcome at 12, 24, and 48 weeks. Methodology/Principal Findings: Included were 3763 treatment-change episodes (TCEs) for which a HIV-1 genotype was available at the time of changing treatment with at least one follow-up viral load measurement. Genotypic susceptibility scores for the active regimens were calculated using scores defined by each interpretation system. Using logistic regression, we determined the association between the genotypic susceptibility score and proportion of TCEs having an undetectable viral load (<50 copies/ml) at 12 (8-16) weeks (2152 TCEs), 24 (16-32) weeks (2570 TCEs), and 48 (44-52) weeks (1083 TCEs). The Area under the ROC curve was calculated using a 10-fold cross-validation to compare the different interpretation systems regarding the sensitivity and specificity for predicting undetectable viral load. The mean genotypic susceptibility score of the systems was slightly smaller for HIVdb, with 1.92±1.17, compared to Rega and ANRS, with 2.22±1.09 and 2.23±1.05, respectively. However, similar odds ratio's were found for the association between each-unit increase in genotypic susceptibility score and undetectable viral load at week 12; 1.6 [95% confidence interval 1.5-1.7] for HIVdb, 1.7 [1.5-1.8] for ANRS, and 1.7 [1.9-1.6] for Rega. Odds ratio's increased over time, but remained comparable (odds ratio's ranging between 1.9-2.1 at 24 weeks and 1.9-2.

Panniculitis and vitiligo occurring during BRAF and MEK inhibitors combination in advanced melanoma patients: Potential predictive role of treatment efficacy

Panniculitis and vitiligo-like lesions have been recently identified as rare cutaneous side effects of the combination of BRAF and MEK inhibitors, a standard of care in metastatic and locally advanced BRAF V600 mutated melanoma. An immune-mediated mechanism has been advocated in the pathogenesis of these skin lesions. Herein we retrospectively reviewed our institutional experience with the aim to explore the association between the occurrence of panniculitis and vitiligo-like lesions during combination therapy with dabrafenib (D) and trametinib (T) and outcome of advanced melanoma patients. Among 52 consecutive BRAF V600 mutated melanoma patients submitted to DT in our center, 12 (23%) developed immune related skin lesions (IRSLs): 8 panniculitis and 4 vitiligo. Patients with IRSLs diagnosis obtained a better disease response (83% versus 25%) (p = 0.001) than their counterpart and had a longer progression free survival and overall survival. The association of IRSLs and lower risk of disease progression (HR 0.19; CI 95% 0.04-0.90; p = 0.043) was confirmed after adjusting for major prognostic factors in multivariate analysis. IRSLs might represent an easy predictive surrogate marker for treatment response and favourable outcome in melanoma patients submitted to DT combination therapy