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Antiretroviral Concentration in Hair as a Measure for Antiretroviral Medication Adherence: A Systematic Review of Global Literature

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Abstract

This review aims to validate hair antiretroviral concentration (HAC) as a measure for antiretroviral medication adherence. This review included 31 studies that analyzed a total of 11 ARV drugs in four different drug classes. The associations between HAC and non-pharmacokinetic measures were generally lower than the association between HAC and other pharmacokinetic measures: the correlation coefficients (r) ranged from − 0.20 to 0.38 for self-report or pill counts and 0.20 to 0.85 for electronic drug monitoring; HAC and other pharmacokinetic measures were positively correlated with the correlation coefficients (r) ranging from 0.20 to 0.72, 0.34 to 0.86, 0.50 to 0.85 for antiretroviral concentration in plasma, peripheral blood mononuclear cells, and dried blood spots, respectively. HAC was one of the strongest independent predictors of virologic responses. HAC of tenofovir was significantly associated with renal toxicity in large sample studies. This review suggests that HAC is a valid biomarker of antiretroviral medication adherence.

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References

  1. Hsieh AC, Mburu G, Garner AB, Teltschik A, Ram M, Mallouris C, et al. Community and service provider views to inform the 2013 WHO consolidated antiretroviral guidelines: key findings and lessons learnt. AIDS. 2014;28(2):205–16.

    Google Scholar 

  2. Palella FJ Jr, Baker RK, Moorman AC, Chmiel JS, Wood KC, Brooks JT, et al. Mortality in the highly active antiretroviral therapy era: changing causes of death and disease in the HIV outpatient study. J Acquir Immune Defic Syndr. 2006;43(1):27–34.

    PubMed  CAS  Google Scholar 

  3. Robbins RN, Spector AY, Mellins CA, Remien RH. Optimizing ART adherence: update for HIV treatment and prevention. Curr HIV/AIDS Rep. 2014;11(4):423–33.

    PubMed  PubMed Central  Google Scholar 

  4. Haberer JE. Current concepts for PrEP adherence in the PrEP revolution: from clinical trials to routine practice. Curr Opin HIV AIDS. 2016;11(1):10–7.

    PubMed  PubMed Central  Google Scholar 

  5. ter Heine R, Beijnen JH, Huitema AD. Bioanalytical issues in patient-friendly sampling methods for therapeutic drug monitoring: focus on antiretroviral drugs. Bioanalysis. 2009;1(7):1329–38.

    PubMed  Google Scholar 

  6. Berg KM, Arnsten JH. Practical and conceptual challenges in measuring antiretroviral adherence. J Acquir Immune Defic Syndr. 2006;43(1):79–87.

    Google Scholar 

  7. Turner BJ. Adherence to antiretroviral therapy by human immunodeficiency virus-infected patients. J Infect Dis. 2002;185(2):143–51.

    Google Scholar 

  8. Castillo-Mancilla JR, Haberer JE. Adherence Measurements in HIV: New Advancements in Pharmacologic Methods and Real-Time Monitoring. Curr HIV/AIDS Rep. 2018;15(1):49–59.

    PubMed  PubMed Central  Google Scholar 

  9. Yamada E, Takagi R, Sudo K, Kato S. Determination of abacavir, tenofovir, darunavir, and raltegravir in human plasma and saliva using liquid chromatography coupled with tandem mass spectrometry. J Pharm Biomed Anal. 2015;114:390–7.

    PubMed  CAS  Google Scholar 

  10. Derissen EJ, Hillebrand MJ, Rosing H, Otten HM, Laille E, Schellens JH, et al. Quantitative determination of azacitidine triphosphate in peripheral blood mononuclear cells using liquid chromatography coupled with high-resolution mass spectrometry. J Pharm Biomed Anal. 2014;90:7–14.

    PubMed  CAS  Google Scholar 

  11. Koal T, Burhenne H, Romling R, Svoboda M, Resch K, Kaever V. Quantification of antiretroviral drugs in dried blood spot samples by means of liquid chromatography/tandem mass spectrometry. Rapid Commun Mass Spectrom. 2005;19(21):2995–3001.

    PubMed  CAS  Google Scholar 

  12. Wu Y, Yang J, Duan C, Chu L, Chen S, Qiao S, et al. Simultaneous determination of antiretroviral drugs in human hair with liquid chromatography-electrospray ionization-tandem mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci. 2018;1083:209–21.

    PubMed  PubMed Central  CAS  Google Scholar 

  13. Chu L, Wu Y, Duan C, Yang J, Yang H, Xie Y, et al. Simultaneous quantitation of zidovudine, efavirenz, lopinavir and ritonavir in human hair by liquid chromatography-atmospheric pressure chemical ionization-tandem mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci. 2018;1097–1098:54–63.

    PubMed  Google Scholar 

  14. Stalter RM, Moench TR, MacQueen KM, Tolley EE, Owen DH, Consortium for Ring A. Biomarkers and biometric measures of adherence to use of ARV-based vaginal rings. J Int AIDS Soc 2016; 19(1):20746.

    PubMed  PubMed Central  Google Scholar 

  15. Podsadecki TJ, Vrijens BC, Tousset EP, Rode RA, Hanna GJ. “White coat compliance” limits the reliability of therapeutic drug monitoring in HIV-1-infected patients. HIV Clin Trials. 2008;9(4):238–46.

    PubMed  Google Scholar 

  16. Castillo-Mancilla JR, Zheng JH, Rower JE, Meditz A, Gardner EM, Predhomme J, et al. Tenofovir, emtricitabine, and tenofovir diphosphate in dried blood spots for determining recent and cumulative drug exposure. AIDS Res Hum Retroviruses. 2013;29(2):384–90.

    PubMed  PubMed Central  CAS  Google Scholar 

  17. Castillo-Mancilla J, Seifert S, Campbell K, Coleman S, McAllister K, Zheng JH, et al. Emtricitabine-Triphosphate in Dried Blood Spots as a Marker of Recent Dosing. Antimicrob Agents Ch. 2016;60(11):6692–7.

    CAS  Google Scholar 

  18. Gandhi M, Greenblatt RM. Hair it is: The long and short of monitoring antiretroviral treatment. Ann Intern Med. 2002;137(8):696–7.

    PubMed  Google Scholar 

  19. Huang Y, Gandhi M, Greenblatt RM, Gee W, Lin ET, Messenkoff N. Sensitive analysis of anti-HIV drugs, efavirenz, lopinavir and ritonavir, in human hair by liquid chromatography coupled with tandem mass spectrometry. Rapid Commun Mass Spectrom. 2008;22(21):3401–9.

    PubMed  PubMed Central  CAS  Google Scholar 

  20. Shah SA, Mullin R, Jones G, Shah I, Barker J, Petroczi A, et al. Simultaneous analysis of antiretroviral drugs abacavir and tenofovir in human hair by liquid chromatography-tandem mass spectrometry. J Pharm Biomed Anal. 2013;74:308–13.

    PubMed  CAS  Google Scholar 

  21. Saberi P, Neilands TB, Ming K, Johnson MO, Kuncze K, Koss CA, et al. Strong Correlation Between Concentrations of Antiretrovirals in Home-Collected and Study-Collected Hair Samples: Implications for Adherence Monitoring. J Acquir Immune Defic Syndr. 2017;76(4):101–3.

    Google Scholar 

  22. Garrison LE, Haberer JE. Technological methods to measure adherence to antiretroviral therapy and preexposure prophylaxis. Curr Opin HIV AIDS. 2017;12(5):467–74.

    PubMed  Google Scholar 

  23. Moher D, Liberati A, Tetzlaff J, Altman DG, Group P. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097.

    Google Scholar 

  24. Yan J, Liu J, Su B, Pan X, Wang Z, Wu J, et al. Lamivudine Concentration in Hair and Prediction of Virologic Failure and Drug Resistance among HIV Patients Receiving Free ART in China. PLoS ONE. 2016;11(4):e0154421.

    PubMed  PubMed Central  Google Scholar 

  25. Abaasa A, Hendrix C, Gandhi M, Anderson P, Kamali A, Kibengo F, et al. Utility of Different Adherence Measures for PrEP: Patterns and Incremental Value. AIDS Behav. 2018;22(4):1165–73.

    PubMed  Google Scholar 

  26. Baxi SM, Liu A, Bacchetti P, Mutua G, Sanders EJ, Kibengo FM, et al. Comparing the Novel Method of Assessing PrEP Adherence/Exposure Using Hair Samples to Other Pharmacologic and Traditional Measures. J Acquir Immune Defic Syndr. 2015;68(1):13–20.

    PubMed  CAS  Google Scholar 

  27. Baxi SM, Vittinghoff E, Bacchetti P, Huang Y, Chillag K, Wiegand R, et al. Comparing pharmacologic measures of tenofovir exposure in a U.S. pre-exposure prophylaxis randomized trial. PLoS One 2018; 13(1):e0190118.

    PubMed  PubMed Central  Google Scholar 

  28. Gandhi M, Glidden DV, Liu A, Anderson PL, Horng H, Defechereux P, et al. Strong Correlation Between Concentrations of Tenofovir (TFV) Emtricitabine (FTC) in Hair and TFV Diphosphate and FTC Triphosphate in Dried Blood Spots in the iPrEx Open Label Extension: Implications for Pre-exposure Prophylaxis Adherence Monitoring. J Infect Dis. 2015;212(9):1402–6.

    PubMed  PubMed Central  CAS  Google Scholar 

  29. Gandhi M, Glidden DV, Mayer K, Schechter M, Buchbinder S, Grinsztejn B, et al. Association of age, baseline kidney function, and medication exposure with declines in creatinine clearance on pre-exposure prophylaxis: an observational cohort study. The Lancet HIV. 2016;3(11):521–8.

    Google Scholar 

  30. Gandhi M, Murnane PM, Bacchetti P, Elion R, Kolber MA, Cohen SE, et al. Hair levels of preexposure prophylaxis drugs measure adherence and are associated with renal decline among men/transwomen. AIDS. 2017;31(16):2245–51.

    PubMed  CAS  Google Scholar 

  31. Koss CA, Bacchetti P, Hillier SL, Livant E, Horng H, Mgodi N, et al. Differences in Cumulative Exposure and Adherence to Tenofovir in the VOICE, iPrEx OLE, and PrEP Demo Studies as Determined via Hair Concentrations. AIDS Res Hum Retroviruses. 2017;33(8):778–83.

    PubMed  PubMed Central  CAS  Google Scholar 

  32. Koss CA, Hosek SG, Bacchetti P, Anderson PL, Liu AY, Horng H, et al. Comparison of Measures of Adherence to Human Immunodeficiency Virus Preexposure Prophylaxis Among Adolescent and Young Men Who Have Sex With Men in the United States. Clin Infect Dis. 2018;66(2):213–9.

    PubMed  CAS  Google Scholar 

  33. Liu AY, Yang Q, Huang Y, Bacchetti P, Anderson PL, Jin C, et al. Strong relationship between oral dose and tenofovir hair levels in a randomized trial: hair as a potential adherence measure for pre-exposure prophylaxis (PrEP). PLoS ONE. 2014;9(1):e83736.

    PubMed  PubMed Central  Google Scholar 

  34. Seifert SM, Castillo-Mancilla JR, Erlandson K, Morrow M, Gandhi M, Kuncze K, et al. Brief Report: Adherence Biomarker Measurements in Older and Younger HIV-Infected Adults Receiving Tenofovir-Based Therapy. J Acquir Immune Defic Syndr. 2018;77(3):295–8.

    PubMed  PubMed Central  Google Scholar 

  35. Tabb ZJ, Mmbaga BT, Gandhi M, Louie A, Kuncze K, Okochi H, et al. Antiretroviral drug concentrations in hair are associated with virologic outcomes among young people living with HIV in Tanzania. AIDS. 2018;32(9):1115–23.

    PubMed  CAS  Google Scholar 

  36. Baxi SM, Greenblatt RM, Bacchetti P, Jin C, French AL, Keller MJ, et al. Nevirapine Concentration in Hair Samples Is a Strong Predictor of Virologic Suppression in a Prospective Cohort of HIV-Infected Patients. PLoS ONE. 2015;10(6):e0129100.

    PubMed  PubMed Central  Google Scholar 

  37. Rohrich CR, Drogemoller BI, Ikediobi O, van der Merwe L, Grobbelaar N, Wright GE, et al. CYP2B6*6 and CYP2B6*18 Predict Long-Term Efavirenz Exposure Measured in Hair Samples in HIV-Positive South African Women. AIDS Res Hum Retroviruses. 2016;32(6):529–38.

    PubMed  PubMed Central  Google Scholar 

  38. Cohan D, Natureeba P, Koss CA, Plenty A, Luwedde F, Mwesigwa J, et al. Efficacy and safety of lopinavir/ritonavir versus efavirenz-based antiretroviral therapy in HIV-infected pregnant Ugandan women. AIDS. 2015;29(2):183–91.

    PubMed  CAS  Google Scholar 

  39. Koss CA, Natureeba P, Mwesigwa J, Cohan D, Nzarubara B, Bacchetti P, et al. Hair concentrations of antiretrovirals predict viral suppression in HIV-infected pregnant and breastfeeding Ugandan women. AIDS. 2015;29(7):825–30.

    PubMed  CAS  Google Scholar 

  40. Bernard L, Peytavin G, Vuagnat A, de Truchis P, Perronne C. Indinavir concentrations in hair from patients receiving highly active antiretroviral therapy. The Lancet. 1998;352(9142):1757–8.

    CAS  Google Scholar 

  41. Bernard L, Vuagnat A, Peytavin G, Hallouin MC, Bouhour D, Nguyen TH, et al. Relationship between levels of indinavir in hair and virologic response to highly active antiretroviral therapy. Ann Intern Med. 2002;137(8):656–9.

    PubMed  CAS  Google Scholar 

  42. Duval X, Peytavin G, Breton G, Ecobichon JL, Descamps D, Thabut G, et al. Hair versus plasma concentrations as indicator of indinavir exposure in HIV-1-infected patients treated with indinavir/ritonavir combination. AIDS. 2007;21(1):106–8.

    PubMed  CAS  Google Scholar 

  43. Servais J, Peytavin G, Arendt V, Staub T, Schneider F, Hemmer R, et al. Indinavir hair concentration in highly active antiretroviral therapy-treated patients: association with viral load and drug resistance. AIDS. 2001;15(7):941–3.

    PubMed  CAS  Google Scholar 

  44. Chawana TD, Gandhi M, Nathoo K, Ngara B, Louie A, Horng H, et al. Defining a Cutoff for Atazanavir in Hair Samples Associated With Virological Failure Among Adolescents Failing Second-Line Antiretroviral Treatment. J Acquir Immune Defic Syndr. 2017;76(1):55–9.

    PubMed  PubMed Central  CAS  Google Scholar 

  45. Gandhi M, Ameli N, Bacchetti P, Anastos K, Gange SJ, Minkoff H, et al. Atazanavir concentration in hair is the strongest predictor of outcomes on antiretroviral therapy. Clin Infect Dis. 2011;52(10):1267–75.

    PubMed  PubMed Central  CAS  Google Scholar 

  46. Gandhi M, Ameli N, Bacchetti P, Gange SJ, Anastos K, Levine A, et al. Protease inhibitor levels in hair strongly predict virologic response to treatment. AIDS. 2009;23(4):471–8.

    PubMed  CAS  Google Scholar 

  47. Gandhi M, Bacchetti P, Ofokotun I, Jin C, Ribaudo HJ, Haas DW, et al. Antiretroviral Concentrations in Hair Strongly Predict Virologic Response in a Large Human Immunodeficiency Virus Treatment-naive Clinical Trial. Clin Infect Dis. 2019;68(6):1044–7.

    PubMed  Google Scholar 

  48. Pintye J, Bacchetti P, Teeraananchai S, Kerr S, Prasitsuebsai W, Singtoroj T, et al. Brief Report: Lopinavir Hair Concentrations Are the Strongest Predictor of Viremia in HIV-Infected Asian Children and Adolescents on Second-Line Antiretroviral Therapy. J Acquir Immune Defic Syndr. 2017;76(4):367–71.

    PubMed  PubMed Central  CAS  Google Scholar 

  49. Prasitsuebsai W, Kerr SJ, Truong KH, Ananworanich J, Do VC, Nguyen LV, et al. Using Lopinavir Concentrations in Hair Samples to Assess Treatment Outcomes on Second-Line Regimens Among Asian Children. AIDS Res Hum Retroviruses. 2015;31(10):1009–14.

    PubMed  PubMed Central  CAS  Google Scholar 

  50. van Zyl GU, van Mens TE, McIlleron H, Zeier M, Nachega JB, Decloedt E, et al. Low lopinavir plasma or hair concentrations explain second-line protease inhibitor failures in a resource-limited setting. J Acquir Immune Defic Syndr. 2011;56(4):333–9.

    PubMed  PubMed Central  Google Scholar 

  51. Olds PK, Kiwanuka JP, Nansera D, Huang Y, Bacchetti P, Jin C, et al. Assessment of HIV antiretroviral therapy adherence by measuring drug concentrations in hair among children in rural Uganda. AIDS Care. 2015;27(3):327–32.

    PubMed  Google Scholar 

  52. Hickey MD, Salmen CR, Tessler RA, Omollo D, Bacchetti P, Magerenge R, et al. Antiretroviral concentrations in small hair samples as a feasible marker of adherence in rural Kenya. J Acquir Immune Defic Syndr. 2014;66(3):311–5.

    PubMed  PubMed Central  CAS  Google Scholar 

  53. Gandhi M, Greenblatt RM, Bacchetti P, Jin C, Huang Y, Anastos K, et al. A single-nucleotide polymorphism in CYP2B6 leads to > 3-fold increases in efavirenz concentrations in plasma and hair among HIV-infected women. J Infect Dis. 2012;206(9):1453–61.

    PubMed  PubMed Central  CAS  Google Scholar 

  54. Bartelink IH, Savic RM, Mwesigwa J, Achan J, Clark T, Plenty A, et al. Pharmacokinetics of lopinavir/ritonavir and efavirenz in food insecure HIV-infected pregnant and breastfeeding women in Tororo. Uganda. J Clin Pharmacol. 2014;54(2):121–32.

    PubMed  CAS  Google Scholar 

  55. Haberer JE, Kiwanuka J, Nansera D, Wilson IB, Bangsberg DR. Challenges in using mobile phones for collection of antiretroviral therapy adherence data in a resource-limited setting. AIDS Behav. 2010;14(6):1294–301.

    PubMed  PubMed Central  Google Scholar 

  56. Gras A, Schneider S, Karasi JC, Ternes AM, Sauvageot N, Karasi-Omes C, et al. Evaluation of saliva as an alternative matrix for monitoring plasma Zidovudine, Lamivudine and nevirapine concentrations in Rwanda. Curr HIV Res. 2011;9(4):223–8.

    PubMed  CAS  Google Scholar 

  57. Rakhmanina NY, Capparelli EV, van den Anker JN, Williams K, Sever JL, Spiegel HM, et al. Nevirapine concentration in nonstimulated saliva: an alternative to plasma sampling in children with human immunodeficiency virus infection. Ther Drug Monit. 2007;29(1):110–7.

    PubMed  CAS  Google Scholar 

  58. Oboho I, Abraham AG, Benning L, Anastos K, Sharma A, Young M, et al. Tenofovir Use and Urinary Biomarkers Among HIV-Infected Women in the Women’s Interagency HIV Study (WIHS). J Acquir Immune Defic Syndr. 2013;62(4):388–95.

    PubMed  PubMed Central  CAS  Google Scholar 

  59. Haaland RE, Martin A, Holder A, Fountain JJ, Hall L, Pescatore NA, et al. Urine tenofovir and emtricitabine concentrations provide biomarker for exposure to HIV preexposure prophylaxis. AIDS. 2017;31(11):1647–50.

    PubMed  CAS  Google Scholar 

  60. De Clercq E. Anti-HIV drugs: 25 compounds approved within 25 years after the discovery of HIV. Int J Antimicrob Agents. 2009;33(4):307–20.

    PubMed  Google Scholar 

  61. Novakova L, Pavlik J, Chrenkova L, Martinec O, Cerveny L. Current antiviral drugs and their analysis in biological materials-Part I: Antivirals against respiratory and herpes viruses. J Pharm Biomed Anal. 2018;147:400–16.

    PubMed  CAS  Google Scholar 

  62. Stohr W, Back D, Dunn D, Sabin C, Winston A, Gilson R, et al. Factors influencing efavirenz and nevirapine plasma concentration: effect of ethnicity, weight and co-medication. Antivir Ther. 2008;13(5):675–85.

    PubMed  CAS  Google Scholar 

  63. Swaminathan S, Ramachandran G, Agibothu Kupparam HK, Mahalingam V, Soundararajan L, Perumal Kannabiran B, et al. Factors influencing plasma nevirapine levels: a study in HIV-infected children on generic antiretroviral treatment in India. J Antimicrob Chemother. 2011;66(6):1354–9.

    PubMed  PubMed Central  CAS  Google Scholar 

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Acknowledgments

The authors wish to thank Joanne Zwemer for assistance in preparing this review.

Funding

This study was funded by the National Institutes of Health (NIH) Research Grant (Grant numbers R01HD074221, R21AI122919), the Fundamental Research Funds for the Central Universities (Grant number 2018B03614), the Humanities and Social Science Foundation of Ministry of Education (Grant number 18YJCZH243) and the Natural Science Foundation of Jiangsu Province (Grant number BK20180503).

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  1. South Carolina SmartState Center for Healthcare Quality (CHQ), University of South Carolina Arnold School of Public Health, Discovery I, 915 Greene Street, Columbia, SC, 29028, USA

    Quan Zhang, Shan Qiao, Xueying Yang & Xiaoming Li

  2. Institute of Pedagogy and Applied Psychology, School of Public Administration, Hohai University, Nanjing, China

    Quan Zhang

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  1. Quan Zhang
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Zhang, Q., Qiao, S., Yang, X. et al. Antiretroviral Concentration in Hair as a Measure for Antiretroviral Medication Adherence: A Systematic Review of Global Literature. AIDS Behav 24, 311–330 (2020). https://doi.org/10.1007/s10461-019-02460-5

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