Fulltext

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

Kiertiburanakul S 1 , Boettiger D 2 , Ng OT 3 , Van Kinh N 4 , Merati TP 5 , Avihingsanon A 6 Show all authors , Wong WW 7 , Lee MP 8 , Chaiwarith R 9 , Kamarulzaman A 10 , Kantipong P 11 , Zhang F 12 , Choi JY 13 , Kumarasamy N 14 , Ditangco R 15 , Cuong DD 16 , Oka S 17 , Sim BLH 18 , Ratanasuwan W 19 , Ly PS 20 , Yunihastuti E 21 , Pujari S 22 , Ross JL 23 , Law M 2 , Sungkanuparph S 1 , TREAT Asia HIV Observational Databases (TAHOD)

Affiliations 

  • 1 Department of Medicine, Faculty of Medicine Ramathibodi Hospital, Mahidol University, 270 Rama VI Road, Bangkok, 10400 Thailand
  • 2 The Kirby Institute, University of New South Wales, Sydney, Australia
  • 3 Tan Tock Seng Hospital, Singapore, Singapore
  • 4 National Hospital of Tropical Diseases, Hanoi, Vietnam
  • 5 Department of Medicine, Faculty of Medicine, Udayana University & Sanglah Hospital, Bali, Indonesia
  • 6 HIV-NAT/Thai Red Cross AIDS Research Centre, Bangkok, Thailand
  • 7 Taipei Veterans General Hospital, Taipei, Taiwan
  • 8 Queen Elizabeth Hospital, Hong Kong, China
  • 9 Research Institute for Health Sciences, Chiang Mai, Thailand
  • 10 University Malaya Medical Centre, Kuala Lumpur, Malaysia
  • 11 Chiangrai Prachanukroh Hospital, Chiang Rai, Thailand
  • 12 Beijing Ditan Hospital, Capital Medical University, Beijing, China
  • 13 Division of Infectious Diseases, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea
  • 14 Chennai Antiviral Research and Treatment Clinical Research Site (CART CRS), YRGCARE Medical Centre, VHS, Chennai, India
  • 15 Research Institute for Tropical Medicine, Manila, Philippines
  • 16 Bach Mai Hospital, Hanoi, Vietnam
  • 17 National Center for Global Health and Medicine, Tokyo, Japan
  • 18 Hospital Sungai Buloh, Sungai Buloh, Malaysia
  • 19 Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand
  • 20 National Center for HIV/AIDS, Dermatology & STDs, University of Health Sciences, Phnom Penh, Cambodia
  • 21 Faculty of Medicine Universitas Indonesia, Dr. Cipto Mangunkusumo General Hospital, Jakarta, Indonesia
  • 22 Institute of Infectious Diseases, Pune, India
  • 23 TREAT Asia, amfAR, The Foundation for AIDS Research, Bangkok, Thailand
AIDS Res Ther, 2017;14:27.
PMID: 28484509 DOI: 10.1186/s12981-017-0151-1

Abstract

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 350 cells/mm3(OR 3.9 vs. <100 cells/mm3; 95% CI 2.0-4.1, p 2000 cells/mm3(OR 1.7 vs. <1000 cells/mm3; 95% CI 1.3-2.3, p 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.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

MeSH terms
Similar publications