Objective: Antiretroviral (ARV) therapies fail when behavioral or biologic factors lead to inadequate medication exposure. The currently available methods to assess ARV exposure are limited. Levels of ARVs in hair reflect plasma concentrations over weeks to months, and may provide a novel method for predicting therapeutic responses.
Design/methods: The Women's Interagency HIV Study, a prospective cohort of HIV-infected women, provided the basis for developing and assessing methods to measure commonly prescribed protease inhibitors (lopinavir/ritonavir and atazanavir) in small hair samples. We examined the association between hair protease inhibitor levels and initial virologic responses to therapy in multivariate logistic regression models.
Results: ARV concentrations in hair were strongly and independently associated with treatment response for 224 women starting a new protease inhibitor-based regimen. For participants initiating lopinavir/ritonavir, the odds ratio (OR) for virologic suppression was 39.8 [95% confidence interval (CI) = 2.8–564] for those with lopinavir hair levels in the top tertile (>1.9 ng/mg) compared to the bottom (≤0.41 ng/mg) when controlling for self-reported adherence, age, race, starting viral load and CD4 cell count, and prior experience with protease inhibitors. For women starting atazanavir, the adjusted OR for virologic success was 7.7 (95% CI = 2.0–29.7) for those with hair concentrations in the top tertile (>3.4 ng/mg) compared to the lowest (≤1.2 ng/mg).
Conclusion: Protease inhibitor levels in small hair samples were the strongest independent predictor of virologic success in a diverse group of HIV-infected adults. This non-invasive method for determining ARV exposure may have particular relevance for the epidemic in resource-poor settings due to the ease of collecting and storing hair.
aDepartment of Medicine, USA
bDepartment of Clinical Pharmacy, USA
cDepartment of Epidemiology/Biostatistics, University of California, San Francisco, San Francisco, California, USA
dBloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA
eDepartment of Medicine, Albert Einstein College of Medicine, Bronx, New York, USA
fDepartment of Medicine, University of Southern California, USA
gCity of Hope National Medical Center, Los Angeles, California, USA
hDepartment of Medicine, SUNY Downstate Medical Center, Brooklyn, New York, USA
iCook County Bureau of Health Services, Chicago, Illinois, USA
jDepartment of Medicine, Georgetown University Medical Center, Washington DC, USA.
Received 21 October, 2008
Revised 24 November, 2008
Accepted 5 December, 2008
Correspondence to Monica Gandhi, MD, MPH, Assistant Professor of Medicine, Division of HIV/AIDS and Division of Infectious Diseases, University of California, San Francisco, 405 Irving Street, 2nd Floor, San Francisco, CA 94122, USA. Tel: +1 415 502 6285; fax: +1 415 476 8528; e-mail: email@example.com
Highly-active antiretroviral therapy (HAART) continues to markedly reduce the morbidity and mortality of HIV infection in treated populations . Treatment outcomes on an individual basis, however, vary widely. The response to treatment is influenced by interindividual differences in drug exposure, but an optimal method to determine antiretroviral (ARV) exposure has not been elucidated.
Although commonly used as surrogates for ARV exposure, adherence measures are imperfect indicators of the amount of drug that eventually reaches the site of viral activity. Not only are methods of evaluating adherence limited by patient recollection and accuracy , but also adherence measurements do not account for interindividual biologic variability in the amount of drug that is absorbed, metabolized and eliminated [3–5]. Measurement of plasma drug levels as a method of therapeutic drug monitoring (TDM) has had inconsistent success in predicting treatment outcomes [6–9], probably because single plasma levels only represent a small window of exposure. Other limitations of blood levels for TDM include significant intraindividual variation in plasma ARV levels , ‘white-coat’ effects , in which adherence just prior to medical appointments improves above average, and imprecision in reporting the timing of recent doses.
Many drugs are incorporated into hair as it grows, but use of hair specimen testing has largely been limited to forensic applications . Recently, the potential utility of hair specimen assays in the assessment of exposure to chronically administered medications has been reported [13–15], including testing for indinavir (IDV) [16–19], an HIV protease inhibitor. In a manner analogous to glycosylated hemoglobin A1C (HbA1C) providing information on average glucose levels over prolonged periods of time , the concentration of medications in hair reflects drug uptake from the systemic circulation over weeks to months. Therefore, drug levels in hair provide an advantage over single plasma drug concentrations in estimating an average level of medication exposure .
The use of hair specimens for TDM could have broad applicability because hair collection and storage is simple and non-invasive, and hair levels can provide information about cumulative exposure to chronically administered medications in a single assay. Although this method would have clear utility for HIV treatment monitoring in developed counties, it also may also provide a unique approach for monitoring treatment outcomes in resource poor settings, in which virologic monitoring can be prohibitively expensive.
We developed new laboratory techniques for measuring the most commonly used protease inhibitors in HIV treatment using very small amounts of hair and simple methods of sample preparation. We then examined the relationship between concentrations of these protease inhibitors [lopinavir (LPV)/ritonavir (RTV) and atazanavir (ATV)] in hair and virologic outcomes in a cohort of treatment-experienced HIV-infected women.
For the purposes of assay development, we collected full sets of scalp hair from 10 HIV-positive volunteers on HAART who exhibited optimal virologic responses to therapy and consented to have their heads shaved . Most of these participants were recruited by providers at the San Francisco Veteran's Administration Hospital as approved by both the University of California, San Francisco and Veteran's Administration Medical Center review boards. Testing of the relationship between ARV levels measured in hair and viral load outcomes utilized specimens collected longitudinally from participants in the Women's Interagency HIV study (WIHS), an ongoing multicenter, prospective cohort of HIV-infected (and at-risk uninfected) women established in 1994 [22,23]. Every 6 months, WIHS participants are seen for a study visit comprised of an extensive interviewer-administered questionnaire, physical examination, and specimen collection.
Between October 2003 and October 2005, 70 women in WIHS initiated a LPV/RTV-based regimen for the first time. Between October 2004 and October 2006, 154 women in WIHS initiated an ATV-based regimen. Of the 154 women on ATV, 129 were concomitantly taking RTV. We analyzed hair levels of LPV, RTV, and ATV in these women at the semiannual WIHS visit following the initiation of the target protease inhibitor and examined the relationship between these ARV levels in hair and virologic success. WIHS study protocols and consent materials were reviewed and approved by institutional review boards at all of the participating institutions.
Women's Interagency HIV Study hair specimen collection and processing
Hair samples were collected in the following manner: 10–20 strands of hair (approximately 1–3 mg) are cut from underneath the top layer of hair (to eliminate environmental effects ) and from the occiput, an area with less variability in hair growth rates than other regions [25,26]. The small thatch of hair is cut with clean scissors as close to the scalp as possible. The distal portion is labeled with marked tape as drug concentrations may be highest in proximal specimens, depending on the date medications were started. The hair sample is then wrapped in aluminum foil to avoid excessive light exposure and stored at room temperature in a plastic bag with a desiccant until analysis.
The development of methods for measuring ARVs in small samples of hair is summarized in a separate laboratory methods paper  and includes assessment of the most efficient means of hair extraction and analysis, as well as details on calibration standards and quality assurance controls. Briefly, the methods established for LPV, RTV, and ATV extraction and analysis are as follows: 2 mg of cut hair (∼5–10 strands) are placed into a test tube and 1 ml of methanol (MeOH) is added as the organic solvent for LPV and RTV. For the maximally efficient extraction of ATV, a more acidified organic solvent, specifically MeOH/trifluoroacetic acid in the ratio of 9: 1 was used. After the initial extraction with organic solvent at 37°C overnight (∼14 h), the samples are then extracted under weak alkaline conditions using methyl tertiary-butyl ether/ethyl acetate (1/1).
After the second extraction, the samples are reconstituted with 0.2 ml of 50% MeOH, and 10 μl are injected into a liquid chromatography/tandem mass spectrometer (LC/MS/MS) system for analyzing drug concentrations in the same manner as in plasma [27–31]. The extracted RTV, ATV, and LPV from hair are separated by reversed phase chromatography and detected by tandem mass spectrometry in electrospray positive ionization with multiple reaction monitoring mode. Using 2 mg of human hair, RTV is detected in concentrations as low as 0.01 ng/mg hair, whereas LPV and ATV are detected in concentrations as low as 0.05 ng/mg hair. This method has been validated from 0.01 to 4.0 ng/mg hair for RTV and from 0.05–20 ng/mg hair for LPV and ATV with good linearity (r2 > 0.99) and reproducibility (coefficient of variation <17% for LPV; coefficient of variation <14% for ATV and RTV). No significant matrix ionization suppression was observed.
The aim of our study was to evaluate the association between ARV levels in hair and initial virologic outcome in WIHS participants starting a new LPV or ATV-based regimen. Virologic success was defined as achieving a viral load of less than 80 copies/ml or more than a 2 log10 (100-fold) drop in viral load from the time of regimen initiation to when the drug was measured in hair at the subsequent WIHS visit (∼6 months) .
The Wilcoxon rank-sum test was used to assess whether the distribution of hair levels in those who achieved virologic success differed from that in the failures. Multivariate logistic regression models were used to estimate the association of hair drug levels with the dichotomous outcome of virologic response. Included in these models were variables that could impact virologic response, including age, race, viral load at the time of regimen initiation (continuous or dichotomized), prior ARV experience (dichotomized as yes/no) and degree of experience with protease inhibitors (categorized into naïve to protease inhibitors, experience with one protease inhibitor, or experience with two or more protease inhibitors in the past), nadir and pretreatment CD4 cell counts, and self-reported adherence. Core WIHS visits are approximately 6 months apart, but the time between visits varied by participant, so the total time on drug was calculated and also assessed as a covariate. Adherence to the target protease inhibitor was reported by the participant as the percentage of prescribed doses consumed over 6 months, 30 days, or 3 days; visual analog scales were used to aid women in estimating percentages . The level of adherence was either analyzed as a continuous measure or dichotomized into greater than or equal to 95% or less than 95% over the time interval assessed.
Because LPV/RTV is a combination tablet, hair levels of each of these agents are substantially collinear, so separate models were run with LPV and RTV. Separate models were also run for the 129 women taking RTV in the group on ATV-based HAART.
Collection of hair specimens in WIHS for participants on treatment was implemented in April 2003 and is ongoing. Of note, 87% of women consent to sampling of these small amounts (10–20 strands) of hair at each visit, indicating a high degree of acceptance for this noninvasive specimen collection. Providing information that the scalp normally loses approximately 100 hair strands per day  has aided in the acceptability of collection.
Table 1 summarizes the demographic and covariate data for the 224 participants (70 women initiating LPV/RTV and 154 women initiating ATV-based regimens), including the distribution in tertiles of protease inhibitor concentrations in hair at the subsequent WIHS visit. The racial/ethnic distribution of the combined study sample mirrors the demographics of HIV among US women , with approximately 60% African–Americans, 23% Hispanics, and 17% whites. Approximately 95% of the combined cohort had experience with one or more ARVs in the past, and less than one-third of participants were naïve to protease inhibitors. The median time on the new HAART regimen prior to the measurement of hair concentrations collectively was 4.5 (range 2.0–11.3) months.
Distribution of protease inhibitor hair concentrations by virologic outcome
Patients were classified as virologic successes or failures based on their viral load response at the visit following initiation of the new protease inhibitor-based regimen. On the basis of this definition, 52 women (74%) on LPV/RTV and 122 women (79%) on ATV had a successful virologic response. Figure 1a,b shows the distribution of LPV and ATV hair concentrations, respectively, with respect to the virologic successes versus the failures. LPV concentrations in hair were significantly higher in virologic successes versus failures (median 1.58 versus 0.290 ng/mg, Wilcoxon rank-sum test P = 0.0008). The distribution of ATV concentrations was also significantly higher in virologic successes versus failures (median 2.60 versus 0.669 ng/mg, Wilcoxon rank-sum test P < 0.0001). Hair concentrations of RTV in the 70 patients on LPV/RTV and the 129 participants on ATV who were also on RTV were also significantly higher in the virologic successes versus the failures (Wilcoxon rank-sum test P = 0.005 for LPV/RTV; P = 0.0017 for ATV/RTV).
Multivariate logistic regression models of virologic response
Participants on lopinavir/ritonavir
Table 2 shows the estimated associations of various covariates, including LPV or ATV levels in hair, with the outcome of virologic response early during therapy. Hair levels of the protease inhibitor showed the strongest association with virologic response in each multivariate model. For each doubling of LPV level, the odds ratio (OR) for virologic response was 2.1 [95% confidence interval (CI) = 1.32–3.5, P = 0.002]. The linearity assumption for logarithmically transformed hair levels was assessed by addition of a quadratic term, which did not show strong evidence for nonlinearity (P = 0.99). Therefore, we examined the association between category of hair level, as assessed in tertiles, and virologic response. The adjusted ORs for virologic success increased by tertile of hair concentration: the OR for virologic success was 39.8 (95% CI = 2.8–564, P = 0.006) for those with LPV hair levels in the top tertile for the group (>1.86 ng/mg) compared with the bottom tertile (≤0.41 ng/mg) when controlling for self-reported adherence, age, race, starting viral load and CD4 cell count, total time on drug, and prior ARV experience.
Self-reported adherence was moderately associated with treatment outcome. The odds of achieving virologic success were 2.89 (95% CI = 0.74–11.3, P = 0.13) times greater in women with self-reported adherence of at least 95% than in women with adherence levels less than 95%. Models with measures of adherence presented continuously or assessed over shorter time intervals produced similar results. An HIV RNA level above 100 000 copies/ml and a CD4 cell count less than 200 cells/μl upon treatment initiation were each associated with a lower odds of virologic success. Age, race, and past experience with protease inhibitors did not reach statistical significance in terms of association with response. Similar results were seen for the RTV hair levels in patients treated with LPV/RTV, in which adherence measurements, pretreatment HIV viral loads and CD4 cell counts, and hair concentrations of RTV were independently associated with virologic response.
Because there were only 18 virologic nonresponders among the women who reported taking LPV/RTV, we also fitted more parsimonious models with both medications by dropping the variables with the largest P-values, one by one, until only adherence and LPV (or RTV) level remained. In each of the resulting models, results were similar.
Participants on atazanavir-based regimens
In multivariate logistic regression models, the odds of achieving virologic success increased by a factor of 1.61 (95% CI = 1.28–2.03, P < 0.0001) for each doubling of ATV level in hair. As the linearity assumption for logarithmically transformed hair levels was verified (P = 0.84 for nonlinearity), we then looked at the association of category of hair level with response. The adjusted ORs for virologic success increased by tertile of hair concentrations: for women starting ATV, the OR for virologic success was 7.74 (95% CI = 2.01–29.7, P = 0.003) for those in the third tertile (>3.43 ng/mg) compared to the lowest (≤1.19 ng/mg). Self-reported adherence and pretreatment CD4 cell counts were also significantly associated with treatment outcome. Age, race, pretreatment HIV RNA level, and degree of experience with protease inhibitors appeared to have little association with the outcome of virologic success. Similar results were seen for the 129 patients in the ATV-treated group who were concomitantly on RTV and, again, more parsimonious models with fewer covariates yielded similar results.
In a cohort of HIV-infected women initiating new protease inhibitor-based combination regimens, the strongest independent predictor for virologic response in adjusted analyses was hair concentration of the anchor drug. Monitoring drug exposure may be important for chronically administered medications when drug exposure is variable and the consequences of treatment failure are high. Interest in TDM using hair levels has recently extended to anticonvulsant [15,36,37] and psychotropic [38–41] medications. Similar to ARVs, the therapeutic index of these medications is narrow, intraindividual variation in drug levels is significant [10,42], patient adherence greatly influences efficacy, drug–drug interactions alter pharmacokinetics , and administration of these medications is often lifelong, making dose optimization important.
Despite its potential importance, there is no gold standard or even optimal method for the assessment of drug exposure in the field of HIV therapeutics. Self-reported adherence can be a poor surrogate for assessing ARV exposure in situations in which inaccuracy of reporting is likely, drug formulations are unpredictable, and parameters of bioavailability or clearance vary. Single or infrequent plasma levels of ARVs represent only a brief snapshot of drug exposure and have not consistently contributed to improving HIV treatment outcomes. Hair levels of drug may be superior to plasma measurements in providing a prolonged assessment of drug exposure, analogous to the advantage of HbA1C monitoring over single glucose levels in predicting long-term outcomes of diabetes mellitus .
Another research group has examined levels of IDV in hair samples and correlated these levels with virologic responses [16–19]; concentrations of IDV in hair showed a stronger correlation with virologic suppression than plasma IDV levels in 43 HIV-infected patients . This study had several limitations: relatively large thatches of hair were required to measure IDV concentrations, which may limit the acceptability of repeated collection; lengthy sample preparation procedures were required prior to hair analysis; the relative value of hair concentrations versus self-reported adherence to HAART was not assessed; and protease inhibitors in more prevalent use in the current treatment era were not studied.
Our study is the first to demonstrate quantification of the most commonly prescribed protease inhibitors in small hair samples (approximately 1–5 mg or between 10–20 strands) using laboratory methods similar to measuring plasma levels. LC-tandem MS is a well described method for drug level determination , available in commercial laboratories, and can be performed in laboratories distant from sites of hair collection. The collection of small amounts of hair may be more acceptable to patients, and our sample preparation and analysis methods are simple and inexpensive.
Unlike phlebotomy, hair collection is non-invasive and does not require specific skills, sterile or designated equipment, or storage materials. The collection of hair samples for analysis of ARV levels merely requires a pair of scissors and aluminium foil for storage. The drug–protein complex in hair is highly stable, so that hair does not require immediate processing after collection. Hair can be stored for indefinite periods of time at room temperature and shipped without precautions for biohazardous materials, offering additional feasibility advantages over blood levels for TDM. These features of this monitoring tool may make hair measurement of ARVs a useful method for assessing exposure in the developing world, in which hair levels can be collected on-site and sent to outside laboratories for analysis. This approach may also be helpful when specimen collection is difficult such as in pediatrics or when drug exposure is unpredictable such as during pregnancy  or with multiple drug–drug interactions.
Assessing hair exposure of ARVs in resource-constrained settings may be cost-effective when HIV RNA quantification is too expensive for routine monitoring. In these settings, treatment failure may be detected late, after the accumulation of multiple viral resistance mutations . The cost of hair collection is nominal, nonbiohazardous shipping costs are inexpensive, and a high throughput hair analysis laboratory can perform the test economically. One possible algorithm for testing would involve measuring hair ARV levels a few months after starting a new ARV regimen, and only performing HIV viral load testing if the hair levels fall below the range observed to predict virologic success in treated populations. After a patient is on stable HIV therapy, hair ARV measurements need not be performed routinely, but only when clinical disease progression is observed or when an alteration in drug exposure is predicted, such as a new drug–drug interaction, pregnancy, change in dietary patterns, or a change in hepatic or renal function.
The association of both adherence and hair levels of protease inhibitors with virologic control in our models indicates that exposure is a function of both behavioral and biologic factors. Drug levels measured in hair therefore add unique information that cannot be provided by measures of adherence. If hair drug levels are low, careful assessment of adherence is indicated, and consideration of biologic factors that impede bioavailability or increase clearance should be considered, such as concomitant use of an interacting drug. Low levels of drug in hair in patients who profess optimal adherence may also prompt more comprehensive pharmacokinetic evaluation.
Prolonging the success of current and novel HIV medications is important in terms of treating the burgeoning HIV epidemic worldwide. We have developed methods to monitor HIV drug exposure in hair and shown these levels to be the strongest predictor of treatment response in multivariate modeling. The field of HIV diagnostics lacks an optimal method for assessing exposure to medications, and hair levels have the potential of addressing that gap. Further study of this tool for TDM is indicated to demonstrate its utility in enhancing treatment responses in the global HIV setting.
Monica Gandhi developed the study protocol, provided study oversight, designed the analysis plan, interpreted the data, and wrote the paper. Monica Gandhi and Ruth M. Greenblatt contributed to the study concept. Niloufar Ameli and Peter Bacchetti provided data management, performed most of the statistical analyses, and edited the draft. Ruth M. Greenblatt, Stephen J. Gange, Kathryn Anastos, Alexandra Levine, Charles L. Hyman, Mardge Cohen, and Mary Young contributed to the data interpretation and critically revised the manuscript. Yong Huang developed the laboratory methods for analysis of ARV levels in hair.
Data in this manuscript were collected by the WIHS Collaborative Study Group. The WIHS is funded by the National Institute of Allergy and Infectious Diseases (NAIAD), with supplemental funding from the National Cancer Institute and the National Institute on Drug Abuse (UO1-AI-35004, UO1-AI-31834, UO1-AI-34994, UO1-AI-34989, UO1-AI-34993, and UO1-AI-42590). Funding is also provided by the National Institute of Child Health and Human Development (UO1-CH-32632) and the National Center for Research Resources (MO1-RR-00071, MO1-RR-00079, and MO1-RR-00083). Dr Gandhi was supported by a Mentored Patient-Oriented Research Career Development Award (K23 A1067065) from NIAID. A research grant from Bristol Meyers Squibb partially funded the development of hair methods for ATV.
All authors declare that they have no conflict of interests. Data were previously presented as an oral abstract at the 14th Conference on Retroviruses and Opportunistic Infections, 25–28 February 2007, Los Angeles, California .
1. Lima VD, Hogg RS, Harrigan PR, Moore D, Yip B, Wood E, Montaner JS. Continued improvement in survival among HIV-infected individuals with newer forms of highly active antiretroviral therapy. AIDS 2007; 21:685–692.
2. Berg KM, Arnsten JH. Practical and conceptual challenges in measuring antiretroviral adherence. J Acquir Immune Defic Syndr 2006; 43(Suppl 1):S79–S87.
3. Back D, Khoo S, Gibbons S, Merry C. The role of therapeutic drug monitoring in treatment of HIV infection. Br J Clin Pharmacol 2001; 52:89S–96S.
4. Marzolini C, Buclin T, Decosterd L, Biollaz J, Telenti A. Nelfinavir plasma levels under twice-daily and three-times-daily regimens: high interpatient and low intrapatient variability. Ther Drug Monit 2001; 23:394–398.
5. Stahle L, Moberg L, Svensson J-O, Sonnerborg A. Efavirenz plasma concentrations in HIV-infected patients: inter- and intraindividual variability and clinical effects. Ther Drug Monit 2004; 26:267–270.
6. Clevenbergh P, Boulme R, Kirstetter M, Dellamonica P. Efficacy, safety and predictive factors of virological success of a boosted amprenavir-based salvage regimen in heavily antiretroviral-experienced HIV-1-infected patients. HIV Med 2004; 5:284–288.
7. Clevenbergh P, Garaffo R, Durant J, Dellamonica P. PharmAdapt: a randomized prospective study to evaluate the benefit of therapeutic monitoring of protease inhibitors: 12 week results. AIDS 2002; 16:2311–2315.
8. Wertheimer BZ, Freedberg KA, Walensky RP, Yazdanapah Y, Losina E. Therapeutic drug monitoring in HIV treatment: a literature review. HIV Clin Trials 2006; 7:59–69.
9. Demeter L, Jiang H, Mukherjee L, Morse G, DiFrancesco R, Klingman K, et al. A prospective, randomized, controlled, open-label trial evaluating the effect of therapeutic drug monitoring and protease inhibitor dose escalation on viral load responses in antiretroviral-experienced, HIV-infected patients with a normalized inhibitory quotient.
In: 15th Conference on Retroviruses and Opportunistic Infections
; 3–6 February 2008. Boston, MA.
10. Nettles RE, Kieffer TL, Parsons T, Johnson J, Cofrancesco J Jr, Gallant JE, et al
. Marked intraindividual variability in antiretroviral concentrations may limit the utility of therapeutic drug monitoring. Clin Infect Dis 2006; 42:1189–1196.
11. Podsadecki T, Vrijens B, Touseet E, Rode R, Hanna G. White coat compliance patterns make therapeutic drug monitoring (TDM) a potentially unreliable tool for assessing long-term drug exposure.
In: 13th Conference on Retroviruses and Opportunistic Infections
; 5–8 February 2006. Denver, Colorado.
12. Pepin G, Gaillard Y. Concordance between self-reported drug use and findings in hair about cocaine and heroin. Forensic Sci Int 1997; 84:37–41.
13. Beumer JH, Bosman IJ, Maes RA. Hair as a biological specimen for therapeutic drug monitoring. Int J Clin Pract 2001; 55:353–357.
14. Nakahara Y. Hair analysis for abused and therapeutic drugs. J Chromatogr B Biomed Sci Appl 1999; 733:161–180.
15. Tsatsakis AM, Psillakis T, Paritsis N. Phenytoin concentration in head hair sections: a method to evaluate the history of drug use. J Clin Psychopharmacol 2000; 20:560–573.
16. 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; 137:656–659.
17. Bernard L, Peytavin G, Vuagnat A, de Truchis P, Perronne C. Indinavir concentrations in hair from patients receiving highly active antiretroviral therapy. Lancet 1998; 352:1757–1758.
18. 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; 15:941–943.
19. Duval X, Peytavin G, Breton G, Ecobichon JL, Descamps D, Thabut G, Leport C. Hair versus plasma concentrations as indicator of indinavir exposure in HIV-1-infected patients treated with indinavir/ritonavir combination. AIDS 2007; 21:106–108.
20. Koenig RJ, Peterson CM, Jones RL, Saudek C, Lehrman M, Cerami A. Correlation of glucose regulation and hemoglobin AIc in diabetes mellitus. N Engl J Med 1976; 295:417–420.
21. Huang Y, Gandhi M, Greenblatt RM, Gee W, Lin E, Messenkoff N. Sensitive analysis of anti-HIV drugs, efavirenz, lopinavir and ritonavir, in human hair samples by liquid chromatography coupled with tandem mass spectrometry. Rapid Commun Mass Spectrom 2008; 22:3401–3409.
22. Barkan SE, Melnick SL, Preston-Martin S, Weber K, Kalish LA, Miotti P, et al
. The women's interagency HIV study. Epidemiology 1998; 9:117–125.
23. Bacon MC, von Wyl V, Alden C, Sharp G, Robison E, Hessol N, et al
. The women's interagency HIV study: an observational cohort brings clinical sciences to the bench. Clin Diagn Lab Immunol 2005; 12:1013–1019.
24. Skopp G, Pötsch L, Mauden M. Stability of cannabinoids in hair samples exposed to sunlight. Clin Chem 2000; 46:1846–1848.
25. Cassani M, Da Re N, Giuliani L, Sesana F. Experience with hair testing in the clinical biochemistry laboratory of Ca' Granda Niguarda Hospital, Milan, Italy. Forensic Sci Int 1997; 84:17–24.
26. Kosuge K, Uematsu T, Araki SI, Matsuno H, Ohashi K, Nakashima M. Comparative dispositions of ofloxacin in human head, axillary, and pubic hairs. Antimicrob Agents Chemother 1998; 42:1298–1302.
27. Egge-Jacobsen W, Unger M, Niemann CU, Baluom M, Hirai S, Benet LZ, Christians U. Automated, fast, and sensitive quantification of drugs in human plasma by LC/LC-MS: quantification of 6 protease inhibitors and 3 nonnucleoside transcriptase inhibitors. Ther Drug Monit 2004; 26:546–562.
28. Villani P, Feroggio M, Gianelli L, Bartoli A, Montagna M, Maserati R, Regazzi MB. Antiretrovirals: simultaneous determination of five protease inhibitors and three nonnucleoside transcriptase inhibitors in human plasma by a rapid high-performance liquid chromatography: mass spectrometry assay. Ther Drug Monit 2001; 23:380–388.
29. Chi J, Jayewardene AL, Stone JA, Motoya T, Aweeka FT. Simultaneous determination of five HIV protease inhibitors nelfinavir, indinavir, ritonavir, saquinavir and amprenavir in human plasma by LC/MS/MS. J Pharm Biomed Anal 2002; 30:675–684.
30. Chi J, Jayewardene AL, Stone JA, Aweeka FT. An LC-MS-MS method for the determination of nevirapine, a nonnucleoside reverse transcriptase inhibitor, in human plasma. J Pharm Biomed Anal 2003; 31:953–959.
31. Frerichs VA, DiFrancesco R, Morse GD. Determination of protease inhibitors using liquid chromatography-tandem mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci 2003; 787:393–403.
32. Department of Health and Human Services and Henry J. Kaiser Family Foundation living document. Guidelines for the use of antiretroviral agents in HIV-infected adolescents and adults
33. Giordano TP, Guzman D, Clark R, Charlebois ED, Bangsberg DR. Measuring adherence to antiretroviral therapy in a diverse population using a visual analogue scale. HIV Clin Trials 2004; 5:74–79.
34. Shapiro J. Clinical practice. Hair loss in women. N Engl J Med 2007; 357:1620–1630.
36. Williams J, Patsalos PN, Mei Z, Schapel G, Wilson JF, Richens A. Relation between dosage of carbamazepine and concentration in hair and plasma samples from a compliant inpatient epileptic population. Ther Drug Monit 2001; 23:15–20.
37. Williams J, Patsalos P, Wilson J. Hair analysis as a potential index of therapeutic compliance in the treatment of epilepsy. Forensic Sci Int 1997; 84:113–122.
38. Shen M, Xiang P, Wu H, Shen B, Huang Z. Detection of antidepressant and antipsychotic drugs in human hair. Forensic Sci Int 2002; 126:153–161.
39. Thieme D, Sachs H. Examination of a long-term clozapine administration by high resolution segmental hair analysis. Forensic Sci Int 2007; 166:110–114.
40. Kronstrand R, Nystrom I, Josefsson M, Hodgins S. Segmental ion spray LC-MS-MS analysis of benzodiazepines in hair of psychiatric patients. J Anal Toxicol 2002; 26:479–484.
41. Cirimele V, Kintz P, Gosselin O, Ludes B. Clozapine dose-concentration relationships in plasma, hair and sweat specimens of schizophrenic patients. Forensic Sci Int 2000; 107:289–300.
42. Banh HL, Burton ME, Sperling MR. Interpatient and intrapatient variability in phenytoin protein binding. Ther Drug Monit 2002; 24:379–385.
43. Spina E, Perucca E. Clinical significance of pharmacokinetic interactions between antiepileptic and psychotropic drugs. Epilepsia 2002; 43(Suppl 2):37–44.
44. Roustit M, Jlaiel M, Leclercq P, Stanke-Labesque F. Pharmacokinetics and therapeutic drug monitoring of antiretrovirals in pregnant women. Br J Clin Pharmacol 2008; 66:179–195.
45. Marcelin AG, Jarrousse B, Derache A, Ba M, Dakouo ML, Doumbia A, et al
. HIV drug resistance after the use of generic fixed-dose combination stavudine/lamivudine/nevirapine as standard first-line regimen. AIDS 2007; 21:2341–2343.
46. Gandhi M, Bacchetti P, Ameli N, Huang Y, Greenblatt RM. Concentrations of lopinavir and ritonavir in hair are strongly correlated with virologic success
[paper #51]. In: 14th Conference of Retroviruses and Opportunistic Infections
; 25–28 February 2007; Los Angeles, CA.