BACKGROUND: Antiretroviral compounds have been predominantly studied in human immunodeficiency virus type 1 (HIV-1) subtype B, but only ~10% of infections worldwide are caused by this subtype. The analysis of the impact of different HIV subtypes on treatment outcome is important. METHODS: The effect of HIV-1 subtype B and non-B on the time to virological failure while taking combination antiretroviral therapy (cART) was analyzed. Other studies that have addressed this question were limited by the strong correlation between subtype and ethnicity. Our analysis was restricted to white patients from the Swiss HIV Cohort Study who started cART between 1996 and 2009. Cox regression models were performed; adjusted for age, sex, transmission category, first cART, baseline CD4 cell counts, and HIV RNA levels; and stratified for previous mono/dual nucleoside reverse-transcriptase inhibitor treatment. RESULTS: Included in our study were 4729 patients infected with subtype B and 539 with non-B subtypes. The most prevalent non-B subtypes were CRF02_AG (23.8%), A (23.4%), C (12.8%), and CRF01_AE (12.6%). The incidence of virological failure was higher in patients with subtype B (4.3 failures/100 person-years; 95% confidence interval [CI], 4.0-4.5]) compared with non-B (1.8 failures/100 person-years; 95% CI, 1.4-2.4). Cox regression models confirmed that patients infected with non-B subtypes had a lower risk of virological failure than those infected with subtype B (univariable hazard ratio [HR], 0.39 [95% CI, .30-.52; P < .001]; multivariable HR, 0.68 [95% CI, .51-.91; P = .009]). In particular, subtypes A and CRF02_AG revealed improved outcomes (multivariable HR, 0.54 [95% CI, .29-.98] and 0.39 [95% CI, .19-.79], respectively). CONCLUSIONS: Improved virological outcomes among patients infected with non-B subtypes invalidate concerns that these individuals are at a disadvantage because drugs have been designed primarily for subtype B infections.
BACKGROUND: Antiretroviral compounds have been predominantly studied in human immunodeficiency virus type 1 (HIV-1) subtype B, but only ~10% of infections worldwide are caused by this subtype. The analysis of the impact of different HIV subtypes on treatment outcome is important. METHODS: The effect of HIV-1 subtype B and non-B on the time to virological failure while taking combination antiretroviral therapy (cART) was analyzed. Other studies that have addressed this question were limited by the strong correlation between subtype and ethnicity. Our analysis was restricted to whitepatients from the Swiss HIV Cohort Study who started cART between 1996 and 2009. Cox regression models were performed; adjusted for age, sex, transmission category, first cART, baseline CD4 cell counts, and HIV RNA levels; and stratified for previous mono/dual nucleoside reverse-transcriptase inhibitor treatment. RESULTS: Included in our study were 4729 patients infected with subtype B and 539 with non-B subtypes. The most prevalent non-B subtypes were CRF02_AG (23.8%), A (23.4%), C (12.8%), and CRF01_AE (12.6%). The incidence of virological failure was higher in patients with subtype B (4.3 failures/100 person-years; 95% confidence interval [CI], 4.0-4.5]) compared with non-B (1.8 failures/100 person-years; 95% CI, 1.4-2.4). Cox regression models confirmed that patients infected with non-B subtypes had a lower risk of virological failure than those infected with subtype B (univariable hazard ratio [HR], 0.39 [95% CI, .30-.52; P < .001]; multivariable HR, 0.68 [95% CI, .51-.91; P = .009]). In particular, subtypes A and CRF02_AG revealed improved outcomes (multivariable HR, 0.54 [95% CI, .29-.98] and 0.39 [95% CI, .19-.79], respectively). CONCLUSIONS: Improved virological outcomes among patients infected with non-B subtypes invalidate concerns that these individuals are at a disadvantage because drugs have been designed primarily for subtype B infections.
Authors: Rami Kantor; Laura Smeaton; Saran Vardhanabhuti; Sarah E Hudelson; Carol L Wallis; Srikanth Tripathy; Mariza G Morgado; Shanmugham Saravanan; Pachamuthu Balakrishnan; Marissa Reitsma; Stephen Hart; John W Mellors; Elias Halvas; Beatriz Grinsztejn; Mina C Hosseinipour; Johnstone Kumwenda; Alberto La Rosa; Umesh G Lalloo; Javier R Lama; Mohammed Rassool; Breno R Santos; Khuanchai Supparatpinyo; James Hakim; Timothy Flanigan; Nagalingeswaran Kumarasamy; Thomas B Campbell; Susan H Eshleman Journal: Clin Infect Dis Date: 2015-02-13 Impact factor: 9.079
Authors: Trevor A Crowell; Donn J Colby; Suteeraporn Pinyakorn; James L K Fletcher; Eugène Kroon; Alexandra Schuetz; Shelly J Krebs; Bonnie M Slike; Louise Leyre; Nicolas Chomont; Linda L Jagodzinski; Irini Sereti; Netanya S Utay; Robin Dewar; Rungsun Rerknimitr; Nitiya Chomchey; Rapee Trichavaroj; Victor G Valcour; Serena Spudich; Nelson L Michael; Merlin L Robb; Nittaya Phanuphak; Jintanat Ananworanich Journal: Clin Infect Dis Date: 2018-05-02 Impact factor: 9.079