Virological failure and HIV drug resistance among adults living with HIV on second‐line antiretroviral therapy in the Asia‐Pacific

Abstract

Objectives To assess second‐line antiretroviral therapy (ART) virological failure and HIV drug resistance‐associated mutations (RAMs), in support of third‐line regimen planning in Asia. Methods Adults > 18 years of age on second‐line ART for ≥ 6 months were eligible. Cross‐sectional data on HIV viral load (VL) and genotypic resistance testing were collected or testing was conducted between July 2015 and May 2017 at 12 Asia‐Pacific sites. Virological failure (VF) was defined as VL > 1000 copies/mL with a second VL > 1000 copies/mL within 3–6 months. FASTA files were submitted to Stanford University HIV Drug Resistance Database and RAMs were compared against the IAS‐USA 2019 mutations list. VF risk factors were analysed using logistic regression. Results Of 1378 patients, 74% were male and 70% acquired HIV through heterosexual exposure. At second‐line switch, median [interquartile range (IQR)] age was 37 (32–42) years and median (IQR) CD4 count was 103 (43.5–229.5) cells/µL; 93% received regimens with boosted protease inhibitors (PIs). Median duration on second line was 3 years. Among 101 patients (7%) with VF, CD4 count > 200 cells/µL at switch [odds ratio (OR) = 0.36, 95% confidence interval (CI): 0.17–0.77 vs. CD4 ≤ 50) and HIV exposure through male–male sex (OR = 0.32, 95% CI: 0.17–0.64 vs. heterosexual) or injecting drug use (OR = 0.24, 95% CI: 0.12–0.49) were associated with reduced VF. Of 41 (41%) patients with resistance data, 80% had at least one RAM to nonnucleoside reverse transcriptase inhibitors (NNRTIs), 63% to NRTIs, and 35% to PIs. Of those with PI RAMs, 71% had two or more. Conclusions There were low proportions with VF and significant RAMs in our cohort, reflecting the durability of current second‐line regimens.

Virological failure and its predictors among human immunodeficiency virus infected individuals on second line antiretroviral treatment in North‐East Ethiopia, 2021

“…According to this study, the rate of VF was 15.4%. This result was consistent with previous studies conducted in Asia and Sub‐Saharan Africa (16.4%), 34 Rwanda (17%) 35 and Gondar (14.7%) 20 but higher than studies conducted in Asia‐Pacific sites (7%), 36 Cambodian (7%), 37 Malawi (9.3%), 38 and in Ethiopia (13.6%) 14 and it was Lower than studies conducted in Thailand (49%), 39 Vietnam (22.8%), 10 Uganda (23%), 40 and Ethiopia (25.11%) 41 and (18.4%) 42 . The higher magnitude of VF in this study could be attributed to the difference in the studied populations which were the inclusion of individuals who were on PI‐based regimen only or studied children or adults above the age of 18 and the use of clinical and immunological criteria to define TF which are less specific and sensitive measures 14,36–38 .…”

Determinants of Survival Among HIV/AIDS Patients With The Second-Line Antiretroviral Therapy In Henan Province of China 

“…The HR of death among HIV/AIDS patients with CD4 cell count lower than 200 cells/μl was 2.97 times that of higher than 500 cells/μl. Patients with lower CD4 cell count were found to be signi cantly associated with second-line ART failure and have higher probability of developing different opportunistic infections [22], all those more were apt to cause death. Anemia has been documented as a risk factor for morbidity and mortality in these patients, even if the CD4 cell count and viral load are controlled [23][24][25].…”

Causes of HIV Treatment Interruption during the Last 20 Years: A Multi-Cohort Real-Life Study

“…If it is true that EACS 11.0 guidelines removed first-generation PIs from the recommended and alternative treatment, these drugs represent the preferred second-line choice in many countries. Ross et al conducted a multicenter cohort study between 2015 and 2017 in 12 Asia-Pacific sites about second-line treatment; among 1378 PWH, 93% of people received regimens with PIs (55% LPV, 39% ATV); of these patients, 7% interrupted the treatment due to virologic failure [ 40 ]. Onoya et al conducted in 2016 a retrospective study to analyze predictors of early drug substitutions and treatment interruptions in a multicenter South African cohort between 2004 and 2013.…”