Evidence map›Paper›PMID 27291892›Full record

ArticleThe Brazilian journal of infectious diseases : an official publication of the Brazilian Society of Infectious Diseases

Extensive variation in drug-resistance mutational profile of Brazilian patients failing antiretroviral therapy in five large Brazilian cities.

Carlos Brites, Lauro Pinto-Neto, Melissa Medeiros, Estevão Nunes, Eduardo Sprinz, Mariana Carvalho

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Article in The Brazilian journal of infectious diseases : an official publication of the Brazilian Society of Infectious Diseases. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Carlos BritesFundação Bahiana de Infectologia (FBaI), Salvador, BA, Brazil; Universidade Federal da Bahia (UFBA), Laboratório de Pesquisa em Infectologia (LAPI), Salvador, BA, Brazil. Electronic address: crbrites@gmail.com.
Lauro Pinto-NetoEscola de Ciências da Saúde da Santa Casa de Vitoria, Vitória, ES, Brazil.
Melissa MedeirosUnichristus, Fortaleza, CE, Brazil.
Estevão NunesFundação Oswaldo Cruz (FIOCRUZ), Instituto de Infectologia Evandro Chagas, Rio de Janeiro, RJ, Brazil.
Eduardo SprinzHospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil.
Mariana CarvalhoUniversidade de Campinas (UNICAMP), Campinas, SP, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDevelopment of drug-resistance mutations is the main cause of failure in antiretroviral therapy. In Brazil, there is scarce information on resistance pattern for patients failing antiretroviral therapy.

objectivesTo define the HIV mutational profile associated with drug resistance in Brazilian patients from 5 large cities, after first, second or further failures to antiretroviral therapy.

methodsWe reviewed genotyping results of 1520 patients failing therapy in five Brazilian cities. Frequency of mutations, mean number of active drugs, viral susceptibility to each antiretrovirals drug, and regional differences were assessed.

resultsMean time of antiretrovirals use was 22.7±41.1 months. Mean pre-genotyping viral load was 4.2±0.8log (2.1±2.0 after switching antiretrovirals). Mean number of remaining active drugs was 9.4, 9.0, and 7.9 after 1st, 2nd, and 3rd failure, respectively. We detected regional variations in drug susceptibility: while BA and RS showed the highest (∼40%) resistance level to ATV/r, FPV/r and LPV/r, in the remaining cities it was around half of this rate. We detected 90% efavirenz/nevirapine resistance in SP, only 45% in RS, and levels between 25% and 30% in the other cities. Regarding NRTI, we found a similar pattern, with RJ presenting the highest, and CE the lowest susceptibility rates for all NRTI. Zidovudine resistance was detected in only 3% of patients in RJ, against 45-65% in the other cities. RJ and RS showed 3% resistance to tenofovir, while in CE it reached 55%. DRV/r (89-97%) and etravirine (61-85%) were the most active drugs, but again, with a wide variation across cities.

conclusionsThe resistance mutational profile of Brazilian patients failing antiretroviral therapy is quite variable, depending on the city where patients were tested. This variation likely reflects distinctive choice of antiretrovirals drugs to initiate therapy, adherence to specific drugs, or circulating HIV-1 strains. Overall, etravirine and DRV/r remain as the most active drugs.

Indexed as

AdultAnti-HIV AgentsAntiretroviral Therapy, Highly ActiveDrug Resistance, ViralGenotypeHIV-1HIV InfectionsHumansMutationReverse Transcriptase InhibitorsViral LoadAnti-HIV AgentsReverse Transcriptase InhibitorsBrazilHIVMutationsResistance

Identifiers

PMID27291892
PMCPMC9427579

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.