Simple jQuery Dropdowns
Please use this identifier to cite or link to this item:
Title: Factors associated with pre-treatment HIV RNA: Application for the use of abacavir and rilpivirine as the first-line regimen for HIV-infected patients in resource-limited settings
Authors: Sasisopin Kiertiburanakul
David Boettiger
Oon Tek Ng
Nguyen Kinh
Tuti Parwati Merati
Anchalee Avihingsanon
Wing Wai Wong
Man Po Lee
Romanee Chaiwarith
Adeeba Kamarulzaman
Pacharee Kantipong
Fujie Zhang
Jun Yong Choi
Nagalingeswaran Kumarasamy
Rossana Ditangco
Do Duy Cuong
Shinichi Oka
Benedict Lim Heng Sim
Winai Ratanasuwan
Penh Sun Ly
Evy Yunihastuti
Sanjay Pujari
Jeremy L. Ross
Matthew Law
Somnuek Sungkanuparph
V. Khol
F. J. Zhang
H. X. Zhao
N. Han
P. C.K. Li
W. Lam
Y. T. Chan
S. Saghayam
C. Ezhilarasi
K. Joshi
S. Gaikwad
A. Chitalikar
D. N. Wirawan
F. Yuliana
D. Imran
A. Widhani
J. Tanuma
T. Nishijima
S. Na
J. M. Kim
Y. M. Gani
R. David
S. F. Syed Omar
S. Ponnampalavanar
I. Azwa
E. Uy
R. Bantique
W. W. Ku
P. C. Wu
P. L. Lim
L. S. Lee
P. S. Ohnmar
S. Gatechompol
P. Phanuphak
C. Phadungphon
L. Chumla
N. Sanmeema
T. Sirisanthana
W. Kotarathititum
J. Praparattanapan
P. Kambua
R. Sriondee
K. V. Nguyen
H. V. Bui
D. T.H. Nguyen
D. T. Nguyen
N. V. An
N. T. Luan
A. H. Sohn
B. Petersen
D. A. Cooper
A. Jiamsakul
D. C. Boettiger
Mahidol University
University of New South Wales (UNSW) Australia
Tan Tock Seng Hospital
National Hospital of Tropical Diseases
Universitas Udayana
The HIV Netherlands Australia Thailand Research Collaboration
Veterans General Hospital-Taipei
Queen Elizabeth Hospital Hong Kong
Research Institute for Health Sciences
University of Malaya Medical Centre
Chiangrai Prachanukroh Hospital
Beijing Ditan Hospital
Yonsei University College of Medicine
VHS Medical Centre India
Bach Mai Hospital
National Center for Global Health and Medicine
Hospital Sungai Buloh
University of Health Sciences
University of Indonesia, RSUPN Dr. Cipto Mangunkusumo
Institute of Infectious Diseases
Foundation for AIDS Research
National Hospital for Tropical Diseases
Keywords: Biochemistry, Genetics and Molecular Biology;Immunology and Microbiology
Issue Date: 5-May-2017
Citation: AIDS Research and Therapy. Vol.14, No.1 (2017)
Abstract: © 2017 The Author(s). Background: Abacavir and rilpivirine are alternative antiretroviral drugs for treatment-naïve HIV-infected patients. However, both drugs are only recommended for the patients who have pre-treatment HIV RNA <100,000 copies/mL. In resource-limited settings, pre-treatment HIV RNA is not routinely performed and not widely available. The aims of this study are to determine factors associated with pre-treatment HIV RNA <100,000 copies/mL and to construct a model to predict this outcome. Methods: HIV-infected adults enrolled in the TREAT Asia HIV Observational Database were eligible if they had an HIV RNA measurement documented at the time of ART initiation. The dataset was randomly split into a derivation data set (75% of patients) and a validation data set (25%). Factors associated with pre-treatment HIV RNA <100,000 copies/mL were evaluated by logistic regression adjusted for study site. A prediction model and prediction scores were created. Results: A total of 2592 patients were enrolled for the analysis. Median [interquartile range (IQR)] age was 35.8 (29.9-42.5) years; CD4 count was 147 (50-248) cells/mm3; and pre-treatment HIV RNA was 100,000 (34,045-301,075) copies/mL. Factors associated with pre-treatment HIV RNA <100,000 copies/mL were age <30 years [OR 1.40 vs. 41-50 years; 95% confidence interval (CI) 1.10-1.80, p = 0.01], body mass index >30 kg/m2 (OR 2.4 vs. <18.5 kg/m2; 95% CI 1.1-5.1, p = 0.02), anemia (OR 1.70; 95% CI 1.40-2.10, p < 0.01), CD4 count >350 cells/mm3 (OR 3.9 vs. <100 cells/mm3; 95% CI 2.0-4.1, p < 0.01), total lymphocyte count >2000 cells/mm3 (OR 1.7 vs. <1000 cells/mm3; 95% CI 1.3-2.3, p < 0.01), and no prior AIDS-defining illness (OR 1.8; 95% CI 1.5-2.3, p < 0.01). Receiver-operator characteristic (ROC) analysis yielded area under the curve of 0.70 (95% CI 0.67-0.72) among derivation patients and 0.69 (95% CI 0.65-0.74) among validation patients. A cut off score >25 yielded the sensitivity of 46.7%, specificity of 79.1%, positive predictive value of 67.7%, and negative predictive value of 61.2% for prediction of pre-treatment HIV RNA <100,000 copies/mL among derivation patients. Conclusion: A model prediction for pre-treatment HIV RNA <100,000 copies/mL produced an area under the ROC curve of 0.70. A larger sample size for prediction model development as well as for model validation is warranted.
ISSN: 17426405
Appears in Collections:Scopus 2016-2017

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.