AIDS Research and Therapy (May 2017)

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

  • Sasisopin Kiertiburanakul,
  • David Boettiger,
  • Oon Tek Ng,
  • Nguyen Van 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,
  • on behalf of the TREAT Asia HIV Observational Databases (TAHOD)

DOI
https://doi.org/10.1186/s12981-017-0151-1
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 8

Abstract

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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 30 kg/m2 (OR 2.4 vs. 350 cells/mm3 (OR 3.9 vs. 2000 cells/mm3 (OR 1.7 vs. 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.

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