Transmitted drug resistance (TDR) can lead to treatment failure, and screening for HIV drug resistance (HIVDR) before antiretroviral therapy (ART) initiation is recommended in high-income countries.1 However, such screening is not routinely done in developing countries due to infrastructure and cost constraints. Most available data on the association of TDR with treatment failure are from developed countries where HIV-1 subtype B predominates1,2 and similar data from settings with non-B subtypes are limited.3,4
Several threshold surveillance studies in 2005–2006 revealed low prevalence of TDR (<5%) in Asia and sub-Saharan Africa5–9 as compared to 8%–19% prevalence in developed countries, where ART has been used longer.10–14 More recent TDR surveillance in Thailand showed increasing TDR trends in both heterosexual (4.9%)15 and male homosexual populations (6.8%).16 Long-term TDR data and their impact on ART outcome from low- and middle-income Asian countries are still limited especially in South-East Asia, where circulating recombinant form (CRF)01_AE predominates.17
TREAT Asia Studies to Evaluate Resistance-Monitoring (TASER-M) is an observational cohort study designed to monitor HIVDR in Asian patients starting combination antiretroviral therapy (cART) or switching to second-line ART upon treatment failure. In a preliminary report, Sungkanuparph et al18 found that 13.8% of 682 patients had ≥1 primary HIVDR mutation. In this study, we examined the effects of TDR on longitudinal treatment outcomes, such as virological failure (VF) and mortality in TASER-M patients initiating cART.
TASER-M patients were recruited from 12 sites in Thailand (5 sites), Malaysia (3), Hong Kong (2), the Philippines and Indonesia (1 site each). Informed consent was obtained before enrollment, and the study protocol was approved by the institutional review boards of the participating sites and coordinating centers.
Genotypic HIVDR Testing and Analysis
Commercial (TrueGene and ViroSeq) and in-house genotypic HIVDR assays5 were used by clinical sites depending on local availability. All laboratories participated in the TREAT Asia Quality Assessment Scheme external quality assurance program.19 Resistance mutations and drug susceptibility predictions were obtained from the Stanford HIV Database algorithm (version 6.1.1).20 HIV-1 subtypes were predicted by the REGA Subtyping Tool.21 TDR was defined as ≥1 amino acid mutation according to the World Health Organization (WHO) 2009 surveillance HIVDR mutation list.22
Patients were classified into 3 groups: (1) “no TDR,” (2) “TDR with susceptible ART”: TDR and full predicted susceptibility to the initial ART regimen (susceptible and potential low-level resistance by the Stanford algorithm), and (3) “TDR with suboptimal ART”: TDR and at least 1 initial drug with predicted reduced susceptibility (low-level, intermediate, and high-level resistance by the Stanford algorithm).
For survival analysis, the endpoint was defined as all-cause mortality. Factors associated with survival were analyzed using the Cox regression model, stratified by site.
VF was defined as viral load (VL) ≥400 copies per milliliter after at least 6 months on cART. To account for VF occurring at the same time point among different patients due to VL assessments being scheduled annually as per protocol, regression models were analyzed using discrete time conditional logistic models, conditioned on site and time interval. Analysis time was divided into 6-monthly intervals to account for patients with VL testing outside of their scheduled annual monitoring. As such, there were 7 intervals for the regression models: (1) 6 months to 1 year, (2) 1–1.5 years, (3) 1.5–2 years, (4) 2–2.5 years, (5) 2.5–3 years, (6) 3–3.5 years, and (7) 3.5–4 years.
Other covariates included age at start of cART, sex, HIV exposure mode, pretreatment VL and CD4, initial ART, hepatitis B/C co-infection, prior AIDS diagnosis, subtype, and ART adherence, obtained from the 30-day Adherence Visual Analogue Scale at each clinical visit. Factors significant in the multivariate model at the 5% level were adjusted for in the final model. Descriptive statistics were analyzed using χ2 test/Fisher exact test for categorical data and Kruskal–Wallis test for continuous data.
Analyses were performed using SAS version 9.2 (SAS Institute, Inc., Cary, NC) and STATA version 12.0 (STATA Corp., College Station, TX).
Of a total of 1471 patients included, 1411 (95.9%) were in the “no TDR” group, 26 (1.8%) in the “TDR with susceptible ART” group, and 34 (2.3%) in the “TDR with suboptimal ART” group (Table 1). Most patients (90.7%) received WHO-recommended first-line ART, that is, nucleoside reverse transcriptase inhibitor (NRTI) + nonnucleoside reverse transcriptase inhibitor (NNRTI). There was no significant difference in the proportions of those who received NRTI + NNRTI vs NRTI + protease inhibitor (PI) vs NRTI only for all TDR groups (P = 0.065). There was also no significant difference in the proportions of TDR for AE, B, and other non-B subtypes (P = 0.312).
TDR was found in 60 patients (4.1%); 60% of which had NRTI-associated mutations, 43% NNRTI-associated mutations, and 18% PI-associated mutations. The most common NRTI-associated mutation was M184V, whereas the most common NNRTI- and PI-associated mutations were K103N and M46L, respectively. Two or more thymidine analogue mutations were found in 4 patients.
TDR and Mortality
Of the 1471 treatment-naive patients, there were 60 deaths. The median follow-up time was 1.8 years (interquartile range, 0.9–2.4) with a mortality rate of 2.4 per 100 patient-years. Factors associated with mortality in the final multivariate model were age (P < 0.001), sex (P = 0.011), and prior AIDS diagnosis (P = 0.004). Patients older than 51 years when starting cART had more than 4 times the hazard of dying compared to those who were 30 years or younger [hazard ratio (HR) = 4.53, 95% confidence interval (CI): 1.90 to 10.79; P = 0.001]. Being female provided a 62% hazard reduction compared to males (HR = 0.38, 95% CI: 0.18 to 0.80; P = 0.011), and having prior AIDS diagnosis before initiating cART more than doubled the hazard of mortality (HR = 2.3, 95% CI: 1.30 to 4.06; P = 0.004). TDR was not a significant factor in determining mortality in the univariate analysis.
TDR and VF
There were 1173 patients who had at least 1 VL measurement after 6 months from start of cART. The median frequency of VL testing was twice per patient per year (interquartile range, 1–3). There was no significant difference in median VL frequency across the TDR groups (P = 0.343). Of these 1173 patients, 120 (10%) experienced VF: 112 (10%) of the 1122 patients in the “no TDR” group; 1 (4.8%) of the 21 patients in the “TDR with susceptible ART” group; and 7 (23.3%) of the 30 patients in the “TDR with suboptimal ART” group. The “TDR with suboptimal ART” group had most failures, with all occurring in the first year of cART.
Factors associated with VF in the adjusted model were TDR (P = 0.033), CD4 count (P = 0.012), and adherence (P < 0.001) (Table 2). Patients from the “TDR with suboptimal ART” group were more than 3 times as likely to fail compared to the “no TDR” group [odds ratio (OR) = 3.12, 95% CI: 1.31 to 7.43; P = 0.010]. However, there was no significant difference in the odds of failure for those from the “TDR with susceptible ART” group compared to the “no TDR” group (OR = 0.62, 95% CI: 0.08 to 4.68; P = 0.647). Patients who initiated cART at CD4 count of >200 cells per microliter had a 59% reduction in the odds of failure compared to the group with CD4 count ≤50 cells per microliter (OR = 0.41, 95% CI: 0.22 to 0.74; P = 0.003). Having suboptimal adherence (<95%) was associated with higher odds of failure (OR = 9.37, 95% CI: 5.00 to 17.56; P < 0.001).
In this Asian cohort of 1471 ART-naive HIV-infected patients, infected mostly with HIV-1 CRF01_AE, HIVDR mutations were found in 4.1% before ART initiation. Factors associated with mortality included older age, male sex, and prior AIDS diagnosis but not TDR. In 1173 patients with available VL at follow-up, 10% experienced VF. In addition to CD4 count and adherence that were significant predictors of VF, patients with TDR and taking suboptimal ART were more than 3 times as likely to fail cART than patients with no TDR.
The level of TDR in this study (4.1%) is slightly lower than a parallel study in sub-Saharan Africa that showed a prevalence of 5.6% TDR among a population of 2436 patients.23 In an earlier report, Sungkanuparph et al18 reported a 13.8% prevalence of primary HIVDR mutations in 682 patients of the TASER-M cohort. The much higher prevalence of primary HIVDR mutations in that report may be due to the use of the IAS-USA mutation list instead of the WHO mutation list as in the current study. Using the WHO mutation list for TDR, a recent survey in 466 patients from a university hospital in Bangkok found a prevalence of 4.9%15 TDR, which is similar to findings in our cross-Asian cohort.
TDR is expected to increase with time after large-scale ART rollout. This is particularly true for resource-limited settings where VL and resistance monitoring are limited. In the developed world, data show a mixed picture of increased, stable, and decreased TDR trends.24–26 Timing of TDR determination is also important, with chronic infections having less TDR compared to acute infections27,28 due to resistance mutations reverting to wild type or becoming minor variants. In reviewing published reports of TDR from across the world during the periods before 2001, 2001–2003, and 2003–2009, Frentz et al29 found that although NRTI resistance declined over time in resource-rich settings, it increased in Asia and Africa, and NNRTI resistance increased in all regions. This was supported by a separate meta-regression analysis, which showed that TDR, especially NNRTI resistance, increased significantly over time since ART rollout (2001–2011) in several regions of sub-Saharan Africa to as high as 7.4% (4.3%–12.7%), although the change in TDR over time was unclear in Asia.14
The significance of drug-specific or drug class–specific TDR to treatment outcome is not fully understood, especially when 1 or more drugs or drug classes in the regimen are still effective. Our findings indicate that after adjusting for confounders, patients taking cART with at least 1 “suboptimal” drug will have a 3.12-fold higher chance of VF compared to those without resistance. Low baseline CD4 cell count (CD4 ≤ 50 cells/μL) and suboptimal adherence (adherence < 95%) were also significantly associated with VF. Our findings confirm a report from Africa in different HIV-1 subtypes,3 where taking ART with at least 1 “suboptimal” drug had an OR of 2.13 (95% CI: 1.44 to 3.14; P < 0.0001) in developing VF after a mean follow-up of 12 months, and a European multicohort analysis, which found that patients who had TDR to at least 1 prescribed drug in the first-line regimen had a HR of 3.13 (95% CI: 2.33 to 4.20) in developing VF after 12 months.30
One of the main arguments in using HIVDR testing before ART initiation is cost-effectiveness. The higher the prevalence of TDR, the more cost-effective the resistance testing is. Although the use of HIVDR testing after initial treatment failure was found to be cost-effective,31–33 the cost-effectiveness of resistance testing before initiation of ART remains controversial, particularly when TDR prevalence is <5%.34,35 In a cost-effectiveness study in the United States where TDR was set at 8.3%, HIVDR testing before starting cART was as cost-effective as other HIV care interventions.35 The cost-effectiveness is lost if prevalence of TDR is equal to or below 1%.
There are certain limitations in this study. First, only 5 countries were involved, thus results cannot be generalized to all of Asia. Second, TDR may be overestimated because 62% of patients were from Thailand where ART was in use longer than other countries except Hong Kong. Third, self-reporting of ART-naive status may not be completely reliable. Fourth, our study may be underpowered due to the small number of patients with resistance mutations and the small number of endpoints. Finally, our analyses did not examine changes to ART susceptibility over time due to a limited number of follow-up genotypic sequences available.
In summary, our results show that without HIVDR testing before starting ART, at least 2.3% of the patients could be put on regimens with at least 1 drug to which the virus is resistant, especially the commonly used NNRTIs, with their low genetic barrier to resistance. This treatment resistance discordance resulted in significantly higher VF rates, particularly in patients with low CD4 counts and suboptimal ART adherence. Although the cost of HIVDR testing is high, the cost of second-line ART in developing countries is 4–5 times higher than first-line ART and therapy is lifelong. Therefore, it is important to investigate what level of TDR will make routine HIVDR testing before starting ART cost-effective.
MEMBERS OF THE TASER STUDY
P.C.K. Li*¶ and M.P. Lee, Queen Elizabeth Hospital and KH Wong, Integrated Treatment Centre, Hong Kong, China; N. Kumarasamy*§ and S. Saghayam, YRGCARE Medical Centre, Chennai, India; S. Pujari* and K. Joshi, Institute of Infectious Diseases, Pune, India; T.P. Merati*† and F. Yuliana, Faculty of Medicine, Udayana University & Sanglah Hospital, Bali, Indonesia; C.K.C. Lee* and B. Heng, Hospital Sungai Buloh, Kuala Lumpur, Malaysia; A. Kamarulzaman*¶ and L.Y. Ong, University of Malaya, Kuala Lumpur, Malaysia; M. Mustafa* and N. Nordin, Hospital Raja Perempuan Zainab II, Kota Bharu, Malaysia; R. Ditangco*‡ and R.O. Bantique, Research Institute for Tropical Medicine, Manila, Philippines; Y.M.A. Chen*§ and Y.T. Lin, Kaohsiung Medical University, Kaohsiung City, Taiwan; P. Phanuphak* and S. Sirivichayakul, HIV-NAT/Thai Red Cross AIDS Research Centre, Bangkok, Thailand; S. Sungkanuparph*, S. Kiertiburanakul, and L. Chumla, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand; T. Sirisanthana* and J. Praparattanapan, Research Institute for Health Sciences, Chiang Mai University, Chiang Mai, Thailand; P. Kantipong* and P. Kambua, Chiangrai Prachanukroh Hospital, Chiang Rai, Thailand; W. Ratanasuwan* and R. Sriondee, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand; R. Kantor*, Brown University, Providence, RI; A.H. Sohn, N. Durier,* and T. Singtoroj, TREAT Asia, amfAR—The Foundation for AIDS Research, Bangkok, Thailand; D.A. Cooper, M.G. Law*, A Jiamsakul, and D.C. Boettiger, The Kirby Institute, University of New South Wales, Sydney, Australia.
*TASER Steering Committee member, †Steering Committee Chair, ‡Co-Chair, §Protocol Chair, and ¶Protocol Co-Chair.
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