Longitudinal trends of HIV drug resistance in a large Canadian cohort, 1996–2016

Rocheleau, Genevieve; Brumme, Chanson J.; Shoveller, Jeannie; Lima, Viviane D.; Harrigan, P. Richard

doi:10.1016/j.cmi.2017.06.014

Cited by 38 publications

(50 citation statements)

References 27 publications

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“…Azidothymidine (AZT), lamivudine (3TC), and tenofovir (TDF), as rst-line NRTI drugs in China, have meager rates of transmission resistance (0.3%, 0.15%, and 0%, respectively). However, unlike the ndings reported in other studies, [4,5,[36][37][38][39][40] NRTI resistance showed the most signi cant increase (from 0% to 5.17%) from 2009 to 2017 in this study. Although the prevalence of TDR to PIs (0.44%) was signi cantly lower than the prevalence of TDR to NNRTIs/NRTIs, the I54M mutation caused universal resistance to PI drugs.…”

Section: Discussioncontrasting

confidence: 99%

Increase in HIV-1 transmitted drug resistance among untreated 16~25-y-old youths in the China-Myanmar border areas during 2009~2017

Ding¹,

Chen²,

Wang³

et al. 2020

Preprint

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Background Transmitted drug resistance (TDR) can affect antiretroviral therapy (ART) efficacy. Surveillance drug resistance mutations in untreated youths newly reported with HIV-1 are highly representative of local TDR. We investigated HIV-1 TDR, TDR transmission based on molecular networks, and the effect of TDR mutations (TDRMs) on the CD4 count among youths in the China-Myanmar border area near the "Golden Triangle" to better understand TDR and guide ART.Methods From 2009 to 2017, 573 ART-naïve youths (16~25 y) newly reported with HIV-1 were enrolled. CD4 counts were obtained from whole blood. HIV pol gene sequences were amplified from RNA extracted from plasma. The Stanford REGA program and phylogenetic trees were used to determine genotypes. TDRMs were analyzed using the Stanford Calibrated Population Resistance tool. TDR transmission was evaluated from molecular networks of HIV-1 pol genes.Results The average prevalence of TDR was 6.3%, and the resistance to NNRTIs, NRTIs, and PIs was 3.49%, 2.62%, and 0.52%, respectively. TDR prevalence increased significantly during the period 2009~2017 (3.92%~9.48%, p<0.05). The mean CD4 count was significantly lower among individuals with TDRMs (373/mm3 vs. 496/mm3, p=0.013). The rate of network entry of youths harboring TDRMs (63.89%) was significantly higher than that of youths without TDRMs (44.9%).Conclusions The HIV-1 TDR increase and low CD4 count of patients with TDRMs in Dehong at the China-Myanmar border suggest the need for early ART and completion of resistance testing before initiating ART in HIV hotspots. Youths with TDRMs are likely to have links to others, necessitating intervention in onward transmission.

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Section: Discussioncontrasting

confidence: 99%

Increase in HIV-1 transmitted drug resistance among untreated 16~25-y-old youths in the China-Myanmar border areas during 2009~2017

Ding¹,

Chen²,

Wang³

et al. 2020

Preprint

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“…This is likely due to multiple factors, potentially including patient management, cohort-wide adherence, and improvements in regimens resulting in greater genetic barriers to resistance. Research expanding upon this finding has recently been published, but more work is required to determine causation [ 33 ].…”

Section: Discussionmentioning

confidence: 99%

Sociodemographic correlates of HIV drug resistance and access to drug resistance testing in British Columbia, Canada

et al. 2017

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Sociodemographic correlates of engagement in human immunodeficiency virus (HIV) care are well studied, however the association with accessing drug resistance testing (DRT) and the development of drug resistance have not been characterized. Between 1996–2014, 11 801 HIV patients accessing therapy in British Columbia were observed longitudinally. A subset of 9456 patients had testable viral load; of these 8398 were linked to census data. Sociodemographic (census tract-level) and clinical (individual-level) correlates of DRT were assessed using multivariable General Estimating Equation logistic regression adjusted odds ratios (aOR). The mean number of tests per patient was 2.1 (Q1-Q3; 0–3). Separately, any drug resistance was determined using IAS-USA (2013) list for 5703 initially treatment naïve patients without baseline resistance; 5175 were census-linked (mean of 1.5 protease-reverse transcriptase sequences/patient, Q1-Q3; 0–2). Correlates of detecting drug resistance in this subset were analyzed using Cox PH regression adjusted hazard ratios (aHR). Our results indicate baseline CD4 <200 cells/μL (aOR: 1.5, 1.3–1.6), nRTI-only baseline regimens (aOR: 1.4, 1.3–1.6), and unknown (therapy initiation before routine pVL in BC) baseline pVL (aOR: 1.8, 1.5–2.1) were among individual-level clinical covariates strongly associated with having accessed DRT; while imperfect adherence (aHR: 2.2, 1.9–2.5), low baseline CD4 count (aHR: 1.9, 1.6–2.3), and high baseline pVL (aHR: 2.0, 1.6–2.6) were associated with a higher likelihood of developing drug resistance. A higher median income (aOR: 0.83, 0.77–0.89) and higher percentage of those with aboriginal ancestry (aOR: 0.85, 0.76–0.95) were census tract-level sociodemographic covariates associated with decreased access to DRT. Similarly, aboriginal ancestry (aHR: 1.2, 1.1–1.5) was associated with development of drug resistance. In conclusion, clinical covariates continue to be the strongest correlates of development of drug resistance and access to DRT for individuals. Regions of high median income and high aboriginal ancestry were weak census-level sociodemographic indicators of reduced DRT uptake, however high aboriginal ancestry was the only sociodemographic indicator for development of drug resistance.

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“…NNRTIs, or "non-nukes," had a different mode of action than other reverse transcriptase inhibitors then available, and triple reverse transcriptase-inhibitor therapy became an alternative to the existing PIbased treatments. In the 2000s and 2010s, NNRTIbased therapy became a very common HIV treatment (Rocheleau et al, 2018), but like all previous treatments, the NNRTI-based treatments were not evolution-proof. In a study published in 2009 (Hoffmann et al, 2009), Hoffman and colleagues followed South African patients treated with one of two common NNRTI-based regimens: zidovudine (AZT)+ 3TC + efavirenz (EFV) (95% of patients) or AZT + 3TC + nevirapine (NVP) (5% of patients).…”

Section: Order Of Resistance Mutations On Protease Inhibitor-based Trmentioning

confidence: 99%

“…Indeed, we argue that what actually happened in the years following the introduction of triple-drug cocktails represents an enduring mystery, one that has been in plain sight this whole time. Resistance rates did fall, but each year, a substantial number of patients on triple-drug therapy continued to develop drug resistance (Lee et al, 2014;Rocheleau et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Understanding patterns of HIV multi-drug resistance through models of temporal and spatial drug heterogeneity

Feder

Harper

Brumme

et al. 2019

Preprint

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Under the current standard of care, individuals with HIV take three antiretroviral drugs simultaneously. Triple-drug combination therapies limit HIV drug resistance evolution, because viruses resistant to a subset of the cocktail are suppressed by the remainder of the drugs and should not complete replication and spread. Despite this, reanalysis of HIV genetic data shortly after triple drug therapies became available (1990s and 2000s) reveals ongoing drug resistance in patients on three-drug therapies. In disagreement with expected patterns of evolution in three-drug therapy-treated HIV populations, resistance usually evolves one mutation at a time in a semi-predictable order. We argue here that these surprising observations can be explained using a model that divides the human body into compartments (for example, the gut, lymph nodes and brain). If one drug reaches a compartment that the other two drugs cannot, this creates a single-drug compartment that can select for single-drug resistant viruses. Such viruses can potentially become resistant to additional drugs, if they migrate to another compartment where a second drug is present, and so on. In addition to a compartment model, for some drug combinations, an alternative model of time-heterogeneity due to short half-lives combined with sub-optimal adherence could also explain the observations. We discuss how these lessons from HIV drug resistance evolution may be useful for other systems.

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Longitudinal trends of HIV drug resistance in a large Canadian cohort, 1996–2016

Abstract: HIV drug resistance transitioned from being primarily selected de-novo to being driven by TDR. Among those who started treatment in the past 5 years, ADR is rare and observed mostly in the lowest adherence strata.

Cited by 38 publications

References 27 publications

Increase in HIV-1 transmitted drug resistance among untreated 16~25-y-old youths in the China-Myanmar border areas during 2009~2017

Increase in HIV-1 transmitted drug resistance among untreated 16~25-y-old youths in the China-Myanmar border areas during 2009~2017

Sociodemographic correlates of HIV drug resistance and access to drug resistance testing in British Columbia, Canada

Understanding patterns of HIV multi-drug resistance through models of temporal and spatial drug heterogeneity

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