Search

Objectives To identify if HIV-infected individuals attending genitourinary clinics in the UK are not disclosing their HIV status, and to examine the potential utility of drug detection as a method to indicate nondisclosure. Methods HIV-positive samples from the unlinked anonymous seroprevalence survey from one London centre in 2009 had viral load (VL) assays performed to identify samples with VL below the level of detection (50 copies/ml, VLBLD) or <1000 copies/ml. After data matching, known HIV positives were excluded and the remaining samples analysed for the presence of a panel of antiretroviral drugs. Results Of 130 HIV-positive samples with sufficient clinical information and not undergoing an HIV test, 18 were classified as remaining undiagnosed after the clinic visit. Thirteen (72%, 95% CI: 47% to 90%) had a VLBLD (n = 11) or VL <1000 copies/ml (n = 2). Eight had sufficient volume to undergo ARV testing, and all were positive for the presence of drug; all with therapeutic levels of clinically appropriate combinations. Conclusions Non-disclosure of HIV status occurs among individuals attending sexual health services in the UK. This study demonstrates the feasibility and utility of using both VL and ARV assays in serum samples. Furthermore, the close correlation of detection of ARV with VLBLD suggests drug detection would be a useful tool to monitor non-disclosure prospectively, thus enabling the use of stored serum samples in future studies. The extent to which these findings can be extrapolated to other settings, and the potential impact of non-disclosure on undiagnosed estimates warrants urgent prospective study. [ABSTRACT FROM AUTHOR]

Comments on the celebration of the silver anniversary of the foundation of the 'British Journal on Clinical Pharmacology' (BJCP). Link between the origins of the journal to the creation of the clinical pharmacology research; Influence of the journal in promoting the development of clinical pharmacology and therapeutics; Officers of BJCP.

Background: The protease inhibitors lopinavir and atazanavir are both recommended for treatment of HIV-infected patients. Considerable inter-individual variability in plasma concentration has been observed for both drugs. The aim of this study was to evaluate which demographic factors and concomitant drugs are associated with lopinavir and atazanavir plasma concentration., Methods: Data from the Liverpool TDM (therapeutic drug monitoring) Registry were linked with the UK Collaborative HIV Cohort (CHIC) study. For each patient, the first measurement of lopinavir (twice daily) or atazanavir [once daily, ritonavir boosted (/r) or unboosted] plasma concentration was included. Linear regression was used to evaluate the association of dose, gender, age, weight, ethnicity and concomitant antiretroviral drugs or rifabutin with log-transformed drug concentration, adjusted for time since last intake., Results: Data from 439 patients on lopinavir (69% 400 mg/r, 31% 533 mg/r; 3% concomitant rifabutin) and 313 on atazanavir (60% 300 mg/r, 32% 400 mg/r, 8% 400 mg) were included. Multivariable models revealed the following predictors for lopinavir concentration: weight (11% decrease per additional 10 kg; P = 0.001); dose (25% increase for 533 mg/r; P = 0.024); and rifabutin (116% increase; P < 0.001). For atazanavir the predictors were dose (compared with 300 mg/r: 40% increase for 400 mg/r, 67% decrease for 400 mg; overall P < 0.001) and efavirenz (32% decrease; P = 0.016) but not tenofovir (P = 0.54)., Conclusions: This analysis confirms that efavirenz decreases atazanavir concentrations, and there was a negative association of weight and lopinavir concentrations. The strong impact of rifabutin on lopinavir concentration should be studied further.

Objectives: The aim of this study was to develop and validate a population pharmacokinetic model in order to describe ritonavir-boosted saquinavir concentrations dosed twice and once daily in human immunodeficiency virus (HIV)-infected patients from the UK, Uganda and Thailand and to identify factors that may influence saquinavir pharmacokinetics., Methods: Pharmacokinetic data from 10 clinical studies were combined. Non-linear mixed effects modelling (NONMEM version V) was applied to determine the saquinavir pharmacokinetic parameters, interindividual/interoccasion variability (IIV/IOV) and residual error. Various covariates potentially related to saquinavir pharmacokinetics were explored, and the final model was validated by means of 95% prediction interval and testing the predictive performance of the model with data not included in the model-building process., Results: Ninety-seven patients were included from the UK (n = 52), Uganda (n = 18) and Thailand (n = 27), contributing 347 saquinavir profiles (1-14 profiles per patient). A one-compartment model with zero-order absorption and lag-time best described the data with IIV/IOV on apparent oral clearance (CL/F) and volume of distribution (V/F) and with IIV on duration and absorption lag-time. The ritonavir area under the curve over the dosing interval was significantly associated with saquinavir CL/F and V/F. A typical patient from the UK had approximately 1.5- and 3-fold higher saquinavir CL/F compared with patients from Uganda (89.0 versus 49.8 L/h) and Thailand (89.0 versus 26.7 L/h), respectively., Conclusions: A model to characterize ritonavir-boosted saquinavir pharmacokinetics in HIV-infected adults has been developed and validated. The model could be used for dosage adaptation following therapeutic drug monitoring and to assess patients' suitability for once-daily boosted saquinavir therapy.