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Inventi Impact: Preventive & Social Medicines

Articles

  • Inventi:hpsm/24022/17
    Factors Associated with Pre-Treatment HIV RNA: Application for the Use of Abacavir and Rilpivirine\nas the First-Line Regimen for HIV-Infected Patients in Resource-Limited Settings
    01-Jan-1970 Research 2017 : October - December
    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

    Background: Abacavir and rilpivirine are alternative antiretroviral drugs for treatment-naÃ?¯ve HIV-infected patients.\nHowever, both drugs are only recommended for the patients who have pre-treatment HIV RNA <100,000 copies/mL.\nIn resource-limited settings, pre-treatment HIV RNA is not routinely performed and not widely available. The aims of\nthis study are to determine factors associated with pre-treatment HIV RNA <100,000 copies/mL and to construct a\nmodel to predict this outcome.\nMethods: HIV-infected adults enrolled in the TREAT Asia HIV Observational Database were eligible if they had an HIV\nRNA measurement documented at the time of ART initiation. The dataset was randomly split into a derivation data set\n(75% of patients) and a validation data set (25%). Factors associated with pre-treatment HIV RNA <100,000 copies/mL\nwere evaluated by logistic regression adjusted for study site. A prediction model and prediction scores were created.\nResults: A total of 2592 patients were enrolled for the analysis. Median [interquartile range (IQR)] age was 35.8 (29.9ââ?¬â??\n42.5) years; CD4 count was 147 (50ââ?¬â??248) cells/mm3; and pre-treatment HIV RNA was 100,000 (34,045ââ?¬â??301,075) copies/\nmL. Factors associated with pre-treatment HIV RNA <100,000 copies/mL were age <30 years [OR 1.40 vs. 41ââ?¬â??50 years;\n95% confidence interval (CI) 1.10ââ?¬â??1.80, p = 0.01], body mass index >30 kg/m2 (OR 2.4 vs. <18.5 kg/m2; 95% CI 1.1ââ?¬â??5.1,\np = 0.02), anemia (OR 1.70; 95% CI 1.40ââ?¬â??2.10, p < 0.01), CD4 count >350 cells/mm3 (OR 3.9 vs. <100 cells/mm3; 95%\nCI 2.0ââ?¬â??4.1, p < 0.01), total lymphocyte count >2000 cells/mm3 (OR 1.7 vs. <1000 cells/mm3; 95% CI 1.3ââ?¬â??2.3, p < 0.01),\nand no prior AIDS-defining illness (OR 1.8; 95% CI 1.5ââ?¬â??2.3, p < 0.01). Receiver-operator characteristic (ROC) analysis\nyielded area under the curve of 0.70 (95% CI 0.67ââ?¬â??0.72) among derivation patients and 0.69 (95% CI 0.65ââ?¬â??0.74) among\nvalidation 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\nderivation patients.\nConclusion: A model prediction for pre-treatment HIV RNA <100,000 copies/mL produced an area under the ROC\ncurve of 0.70. A larger sample size for prediction model development as well as for model validation is warranted.

    How to Cite this Article
    CC Compliant Citation: Kiertiburanakul, Sasisopin, et al. \"Factors associated with pre-treatment HIV RNA: application for the use\nof abacavir and rilpivirine as the first-line regimen for HIV-infected patients in resource-limited settings.\" AIDS research and\ntherapy 14.1 (2017): 27, DOI 10.1186/s12981-017-0151-1, http://creativecommons.org/licenses/by/4.0/.
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