Microcirculatory changes in the liver of patients with refractory ascites and their relationship with diabetes and alcohol.

OBJECTIVES: The determinants of refractory ascites have not been fully characterized. The aims of this study were to assess liver histopathological alterations associated with refractory ascites and their relationship with comorbidities. METHODS: Consecutive patients with cirrhosis who underwent liver transplantation were retrospectively included. Patients' characteristics at the time of listing were analysed. The native livers were reviewed and lesions associated with refractory ascites were examined. RESULTS: Out of the 89 patients included, 30 had refractory ascites and 59 did not (including 35 without ascites and 24 with diuretic-sensitive ascites). Patients with and without refractory ascites had a similar amount of fibrous tissue and features of fatty liver disease. By contrast, microvascular changes, namely sinusoidal dilatation (P < 0.001), diffuse perisinusoidal fibrosis (P = 0.001), hepatic venous thromboses (P = 0.004) and vascular proliferation (P = 0.01) were more frequently observed in the livers of patients with refractory ascites. Diabetes (57% vs. 31%, P = 0.02) and alcohol as a causal factor for cirrhosis (80% vs. 42%, P = 0.001) were more frequent in patients with refractory ascites than in those without. By multivariate analysis, refractory ascites was independently associated with diabetes mellitus [odds ratio (OR) (95% confidence interval, CI) 6.15 (1.47-25.71); P = 0.01], alcohol as a causal factor for cirrhosis [OR (95% CI) 4.63 (1.07-20.02); P = 0.04], higher Model For End Stage Liver Diseases [OR (95% CI) 1.21 (1.05-1.38); P = 0.008] and lower serum sodium [OR (95% CI) 0.87 (0.78-0.98); P = 0.03]. CONCLUSION: Liver microcirculatory changes are associated with refractory ascites. Diabetes and alcohol may explain refractory ascites by causing microangiopathy.

Candida vertebral osteomyelitis (CVO) 28 cases from a 10-year retrospective study in France.

Although increasingly frequent, little is known about the clinical presentation, radiological signs, and outcome of Candida vertebral osteomyelitis (CVO).We performed a nationwide retrospective study of laboratory-confirmed cases of CVO over a 10 year-period in France with a prolonged follow-up. We describe demographic, clinical, biological, and radiological characteristics of patients with CVO, patients' management, and long-term outcome and determine factors associated with a poor outcome.In total, 28 patients with laboratory-confirmed CVO were included. A prior systemic Candida infection was evidenced in 13/28 (46%), occurring a median of 6 weeks before CVO was diagnosed. Twenty-six of 28 (93%) had at least 1 underlying condition at risk of invasive fungal disease, and in 19/28 (68%) CVO was health-care related. C albicans was most frequently identified (21/28; 75%) Lumbo-sacral involvement was the most prevalent (20/28-71%). Nearly half patients had no fever at presentation, but all had pain. Initial antifungal therapy consisted in fluconazole in 15/28 (53%); surgery was needed in 5 (18%) cases.One-year mortality was 21% (6/28), directly related to fungal infection in 2 patients. Risk-factors associated with 1-year mortality were age (P=.02), a high Charlson comorbidity index (P = .001), and a shorter treatment duration (median, 3 months vs 6 months; P = .02). Among 22 patients who survived, the median follow up duration was 15.5 months (8-93.5); 10 had sequelae, consisting in pain in all and neurological deficit in one. A longer treatment duration was significantly associated with healing without sequelae (P = .04).CVO concerns patients with serious underlying conditions and risk-factors for invasive candidiasis. Prolonged antifungal treatment appears to improve survival without sequelae.

Adherence profiles and therapeutic responses of treatment-naive HIV-infected patients starting boosted atazanavir-based therapy in the ANRS 134-COPHAR 3 trial.

The adherence profile of HIV-infected patients predicts the therapeutic outcome, in particular during the early phase of antiretroviral therapy (ART). We conducted a prospective observational multicenter trial monitoring adherence and virological and immunological parameters over the initial 6 months of treatment. Thirty-five subjects were starting a treatment regimen including atazanavir, ritonavir, and emtricitabine-tenofovir. Adherence was assessed using self-completed questionnaires, announced pill counts, and the medication event monitoring system (MEMS) for each drug. Three MEMS measures were defined: the percentages of doses taken, days with the correct dosing, and doses taken on time (± 3 h). Dynamic virological suppression (DVS) was defined as a reduction in the plasma HIV-RNA level of >1 log10 per month or <40 copies/ml. The cumulative treatment time was 5,526 days. A high level of adherence was observed. The MEMS-defined adherence for correct dosing (-0.68% per 4-week period, P < 0.03) and timing compliance (-1.60% per 4-week period, P < 0.003) decreased significantly over time. The MEMS-defined adherence data were concordant with the pill counts during the trial but not with the data from the questionnaires. The median [range] percentages of doses taken (100% [50 to 102]), days with the correct dosing (95% [41 to 100]), and doses taken on time (86% [32 to 100]) were significantly associated with DVS in separate models. Among these three measures, the percentage of doses taken on time had the greatest ability to predict DVS. Timing compliance should be supported to optimize DVS during the early phase of treatment by once-daily boosted protease inhibitor-based ART. (This study has been registered at ClinicalTrials.gov under registration no. NCT00528060.).

Role of hepatic HCV-RNA level on the severity of chronic hepatitis C and response to antiviral therapy.

BACKGROUND: Correlation between hepatic HCV-RNA and serum HCV-RNA, severity of liver disease and response to therapy is poorly known. OBJECTIVES: To assess the influence of hepatic HCV-RNA level on severity of liver disease and response to therapy in a large cohort of chronic hepatitis C (CHC) patients. STUDY DESIGN: HCV-RNA was measured in frozen liver biopsies and serum samples from 130 CHC patients the day of liver biopsy prior to treatment. Liver fibrosis was assessed by Ishaq scoring. A Sustained Virological Response (SVR) was observed in 52% of the patients, non-response (NR) in 34%. RESULTS: Mean±standard deviation hepatic HCV-RNA level was 7.69±0.67 log(10) copies/mg of liver. Mean serum HCV-RNA level was 6.21±0.72 log(10) copies/ml. There was a correlation between hepatic and serum HCV-RNA in genotype 1 and 4 (p=0.008 and p=0.03) and age (p=0.006). Mean hepatic HCV-RNA was 7.70±0.69 vs 7.67±0.68 log(10) copies/mg of liver, in patients with significant fibrosis vs those with mild fibrosis, respectively (p=0.7); 8.04±0.68; 7.44±0.47; 7.43±0.49 and 7.44±0.71 log(10) copies/mg of liver in genotypes 1, 2, 3 and 4, respectively (p=0.0001); higher in women than in men (p=0.04); 7.60±0.63, 7.71±0.54 and 7.96±0.73 log(10) copies/mg in SVR, relapsers and NR, respectively (p=0.1). Multivariate analysis showed that high hepatic HCV-RNA level was independently associated with genotype and response to therapy was associated with genotype independently from hepatic HCV-RNA level. CONCLUSIONS: Hepatic HCV-RNA level was not associated with severity of liver disease. High level was strongly associated with HCV genotype independently from response to therapy.

Host factors and portal of entry outweigh bacterial determinants to predict the severity of Escherichia coli bacteremia.

Escherichia coli ranks among the organisms most frequently isolated from cases of bacteremia. The relative contribution of the host and bacteria to E. coli bacteremia severity remains unknown. We conducted a prospective multicenter cohort study to identify host and bacterial factors associated with E. coli bacteremia severity. The primary endpoint was in-hospital death, up to 28 days after the first positive blood culture. Among 1,051 patients included, 136 (12.9%) died. Overall, 604 (57.5%) patients were female. The median age was 70 years, and 202 (19.2%) episodes were nosocomial. The most frequent comorbidities were immunocompromised status (37.9%), tobacco addiction (21.5%), and diabetes mellitus (20.1%). The most common portal of entry was the urinary tract (56.9%). Most E. coli isolates belonged to phylogenetic group B2 (52.0%). The multivariate analysis retained the following factors as predictive of death: older age (odds ratio [OR] = 1.25 [95% confidence interval {CI}, 1.09 to 1.43] for each 10-year increment), cirrhosis (OR = 4.85 [95% CI, 2.49 to 9.45]), hospitalization before bacteremia (OR = 4.13 [95% CI, 2.49 to 6.82]), being an immunocompromised patient not hospitalized before bacteremia (OR = 3.73 [95% CI, 2.25 to 6.18]), and a cutaneous portal of entry (OR = 6.45 [95% CI, 1.68 to 24.79]); a urinary tract portal of entry and the presence of the ireA virulence gene were negatively correlated with death (OR = 0.46 [95% CI, 0.30 to 0.70] and OR = 0.53 [95% CI, 0.30 to 0.91], respectively). In summary, host factors and the portal of entry outweigh bacterial determinants for predicting E. coli bacteremia severity.

Benefit of therapeutic drug monitoring of protease inhibitors in HIV-infected patients depends on PI used in HAART regimen--ANRS 111 trial.

As a result of high inter-patient variability, and efficacy-concentration and toxicity-concentration relationships, optimization of HIV-protease inhibitor (PI) doses based on plasma concentrations could be beneficial. During a 48-week open prospective non-randomized interventional study of 115 protease inhibitor-naïve patients initiating an indinavir/ritonavir- or lopinavir/ritonavir-, or nelfinavir-containing therapy, protease inhibitor dose was modified when plasma trough concentrations (C(trough)) at weeks 2, 8, 16 and 24 were outside predefined optimal concentration ranges. Failure of the strategy was defined as the proportions of patients with HIV-RNA above 200 copies/mL from weeks 24 to 48 and/or experiencing grades 2, 3 or 4 PI-related adverse events during the study; proportion of patients with last C(trough) measurement outside the concentration range was determined at each visit. Virological failure and/or occurrence of adverse event were observed in 37/94 assessable patients (39%; 95% CI: 29.4-50.0). In the on-treatment analysis, failure of the strategy was noted in 16% of indinavir/r- or lopinavir/r-treated patients (8/51; 95% CI: 7.0-28.6; virological failure: 2; adverse event: 6) but in 44% of nelfinavir-treated patients (11/25; 95% CI: 24.4-65.1; virological failure: 10; adverse event: 1); C(trough) concentrations outside the range were less frequent at the last measurement than at W2 (41% vs. 66%; P < 0.05), with proportions of 35% for indinavir/r- or lopinavir/r-treated patients, but 57% for nelfinavir-treated patients. The proposed strategy of therapeutic drug monitoring may be beneficial to indinavir/r- and lopinavir/r-treated patients, but failed to move concentrations into the predefined range and to produce the expected virological success for nelfinavir-treated patients.

Influence of pharmacogenetics on indinavir disposition and short-term response in HIV patients initiating HAART.

AIMS: To assess the relationship between genetic polymorphisms and indinavir pharmacokinetic variability and to study the link between concentrations and short-term response or metabolic safety. METHODS: Forty protease inhibitor-naive patients initiating highly active antiretroviral therapy (HAART) including indinavir/ritonavir and enrolled in the COPHAR 2-ANRS 111 trial were studied. At week 2, four blood samples were taken before and up to 6 h following drug intake. A population pharmacokinetic analysis was performed using the stochastic approximation expectation maximization (SAEM) algorithm implemented in MONOLIX software. The area under the concentration-time curve (AUC) and maximum (C(max)) and trough concentrations (C(trough)) of indinavir were derived from the population model and tested for their correlation with short-term viral response and safety measurements, while for ritonavir, these same three parameters were tested for their correlation with short-term biochemical safety RESULTS: A one-compartment model with first-order absorption and elimination best described both indinavir and ritonavir concentrations. For indinavir, the estimated clearance and volume of distribution were 22.2 L/h and 97.3 L, respectively. The eight patients with the *1B/*1B genotype for the CYP3A4 gene showed a 70% decrease in absorption compared to those with the *1A/*1B or *1A/*1A genotypes (0.5 vs. 2.1, P = 0.04, likelihood ratio test by permutation). The indinavir AUC and C(trough) were positively correlated with the decrease in human immunodeficiency virus RNA between week 0 and week 2 (r = 0.4, P = 0.03 and r = -0.4, P = 0.03, respectively). Patients with the *1B/*1B genotype also had a significantly lower indinavir C(max) (median 3.6, range 2.1-5.2 ng/mL) than those with the *1A/*1B or *1A/*1A genotypes (median 4.4, range 2.2-8.3 ng/mL) (P = 0.04) and a lower increase in triglycerides during the first 4 weeks of treatment (median 0.1, range -0.7 to 1.4 vs. median 0.6, range -0.5 to 1.7 mmol/L, respectively; P = 0.02). For ritonavir, the estimated clearance and volume of distribution were 8.3 L/h and 60.7 L, respectively, and concentrations were not found to be correlated to biochemical safety. Indinavir and ritonavir absorption rate constants were found to be correlated, as well as their apparent volumes of distribution and clearances, indicating correlated bioavailability of the two drugs. CONCLUSION: The CYP3A4*1B polymorphism was found to influence the pharmacokinetics of indinavir and, to some extent, the biochemical safety of indinavir.

Extension of the SAEM algorithm for nonlinear mixed models with 2 levels of random effects.

This article focuses on parameter estimation of multilevel nonlinear mixed-effects models (MNLMEMs). These models are used to analyze data presenting multiple hierarchical levels of grouping (cluster data, clinical trials with several observation periods, ...). The variability of the individual parameters of the regression function is thus decomposed as a between-subject variability and higher levels of variability (e.g. within-subject variability). We propose maximum likelihood estimates of parameters of those MNLMEMs with 2 levels of random effects, using an extension of the stochastic approximation version of expectation-maximization (SAEM)-Monte Carlo Markov chain algorithm. The extended SAEM algorithm is split into an explicit direct expectation-maximization (EM) algorithm and a stochastic EM part. Compared to the original algorithm, additional sufficient statistics have to be approximated by relying on the conditional distribution of the second level of random effects. This estimation method is evaluated on pharmacokinetic crossover simulated trials, mimicking theophylline concentration data. Results obtained on those data sets with either the SAEM algorithm or the first-order conditional estimates (FOCE) algorithm (implemented in the nlme function of R software) are compared: biases and root mean square errors of almost all the SAEM estimates are smaller than the FOCE ones. Finally, we apply the extended SAEM algorithm to analyze the pharmacokinetic interaction of tenofovir on atazanavir, a novel protease inhibitor, from the Agence Nationale de Recherche sur le Sida 107-Puzzle 2 study. A significant decrease of the area under the curve of atazanavir is found in patients receiving both treatments.

The 20-core prostate biopsy protocol--a new gold standard?

PURPOSE: We investigated the ability of a 20-core prostate biopsy protocol to enhance the prostate cancer diagnosis rate. MATERIALS AND METHODS: We compared the diagnosis rate of prostate biopsies in 2 groups of consecutive patients, including group 1-10 cores and group 2-20 cores. The prostate specific antigen range in the 2 groups was 3 to 30 ng/ml and biopsies were performed because of increased prostate specific antigen (more than 3 ng/ml) and/or abnormal digital rectal examination. To analyze the results we divided each group into 3 subgroups according to prostate specific antigen, including group 1-3 to less than 6 ng/ml, group 2-6 or greater to less than 10 ng/ml and group 3-10 or greater to up to 30 ng/ml. Multivariate analysis was performed to assess the difference in the diagnosis rate among the subgroups according to the number of cores taken. RESULTS: The percent of positive biopsies was 39.7% in group 1 and 51.7% in group 2. Multivariate analysis confirmed that the number of biopsies taken was a factor that independently and significantly correlated with the prostate cancer diagnosis. The 20-core biopsy protocol was more efficient than the 10-core protocol in the 3 subgroups with 47.2% vs 28.1% of patients diagnosed in group 1 (OR 3.26, p = 0.001), 40.5% vs 36.1% in group 2 (OR 2.37, p = 0.009) and 69.8% vs 39.7% in group 3 (OR 2.01, p = 0.015). CONCLUSIONS: The 20-core biopsy protocol was more efficient than the 10-core biopsy protocol, especially in patients with prostate specific antigen between 3 and 6 ng/ml. Nevertheless, it is mandatory to confirm whether detected tumors are clinically significant on pathological examination of the radical prostatectomy specimens.

Population pharmacokinetic analysis of lamivudine, stavudine and zidovudine in controlled HIV-infected patients on HAART.

OBJECTIVE: This work aimed at building a population pharmacokinetic (PK) model for lamivudine (LMV), stavudine (STV) and zidovudine (ZDV), estimating their inter and intraindividual PK variability and investigating the influence of different covariates. METHODS: Population PK of LMV, STV and ZDV was separately evaluated from plasma concentrations obtained in 54, 39 and 27 HIV1-infected patients, respectively, enrolled in the COPHAR1-ANRS102 trial. The primary objective of this trial was to study the pharmacokinetics of indinavir (IDV) and nelfinavir (NFV) in treated patients with a sustained virological response. Concentrations of nucleoside analogs (NA) were measured in plasma as a secondary objective. A one-compartment model with first-order elimination was used, with zero-order absorption for LMV and first-order absorption for STV and ZDV. RESULTS: Mean parameters [interpatient variability in coefficient of variation (CV%)] of LMV, STV and ZDV were: oral volume of distribution (V/F) 145 l (52%), 24 l (81%) and 248 l (80%), oral clearance (Cl/F) 32 l/h, 16 l/h (74%) and 124 l/h (51%), respectively. For LMV, absorption duration (Ta) was 1.46 h (64%). For STV and ZDV, ka was 0.46 h(-1) and 2.9 h(-1), respectively. We found a systematic effect of combination with NFV vs. IDV. We found that intrapatient variability was greater than interpatient variability (except for STV) and greater than 55% for the three drugs. CONCLUSION: This trial enabled the estimation of the population PK parameters of three NA in patients with a sustained virological response, and the median curves could be used as references for concentration-controlled strategies. We observed, as for the protease inhibitors, a great variability of PK parameters.

Impact of modelling intra-subject variability on tests based on non-linear mixed-effects models in cross-over pharmacokinetic trials with application to the interaction of tenofovir on atazanavir in HIV patients.

We evaluated the impact of modelling intra-subject variability on the likelihood ratio test (LRT) and the Wald test based on non-linear mixed effects models in pharmacokinetic interaction and bioequivalence cross-over trials. These tests were previously found to achieve a good power but an inflated type I error when intra-subject variability was not taken into account. Trials were simulated under H0 and several H1 and analysed with the NLME function. Different configurations of the number of subjects n and of the number of samples per subject J were evaluated for pharmacokinetic interaction and bioequivalence trials. Assuming intra-subject variability in the model dramatically improved the type I error of both interaction tests. For the Wald test, the type I error decreased from 22, 14 and 7.7 per cent for the original (n = 12, J = 10), intermediate (n = 24, J = 5) and sparse (n = 40, J = 3) designs, respectively, down to 7.5, 6.4 and 3.5 per cent when intra-subject variability was modelled. The LRT achieved very similar results. This improvement seemed mostly due to a better estimation of the standard error of the treatment effect. For J = 10, the type I error was found to be closer to 5 per cent when n increased when modelling intra-subject variability. Power was satisfactory for both tests. For bioequivalence trials, the type I error of the Wald test was 6.4, 5.7 and 4.2 per cent for the original, intermediate and sparse designs, respectively, when modelling intra-subject variability. We applied the Wald test to the pharmacokinetic interaction of tenofovir on atazanavir, a novel protease inhibitor. A significant decrease of the area under the curve of atazanavir was found when patients received tenofovir.

High variability of indinavir and nelfinavir pharmacokinetics in HIV-infected patients with a sustained virological response on highly active antiretroviral therapy.

OBJECTIVES: To describe plasma concentrations of indinavir alone or combined with ritonavir, and of nelfinavir and its active metabolite M8, and to measure their variabilities in HIV-infected patients treated with a stable antiretroviral regimen and experiencing a sustained virological response for at least 12 months. PATIENTS AND METHODS: In this prospective trial, blood samples were drawn during a 6-hour time interval between two doses at enrolment to assess protease inhibitor (PI) pharmacokinetic parameters, and 4 months later to assess plasma trough and peak concentrations. Safety and adherence assessments and laboratory data were collected during an 8-month period. PI pharmacokinetic characteristics were analysed using a non-compartmental approach. Inter- and intrapatient variabilities were estimated using a linear mixed-effect model. The impact of different covariates on plasma trough concentrations was investigated. Eighty-eight patients were analysed: 42 treated with indinavir and 46 with nelfinavir. RESULTS: The interquartile range (IQR) of the plasma trough concentration corrected for the sampling time (Ccalc) was 116-374 microg/L for indinavir alone and 163-508 microg/L for indinavir/ritonavir. Ritonavir significantly increased indinavir elimination half-life and plasma exposure. For nelfinavir, the IQR of Ccalc was 896-2059 microg/L for three-times-daily administration and 998-2124 microg/L for twice-daily administration. Variabilities were high for both PIs. Intrapatient variability for indinavir alone (and indinavir + ritonavir) was 76% (107%) and interpatient variability was 58% (10%) in adherent patients. Intrapatient variability for nelfinavir three times daily (and twice daily) was 41% (74%) and interpatient variability was 62% (50%). Intrapatient variability was lowered in patients with a high adherence level. CONCLUSION: Although performed in a homogeneous population, this study documented a high interpatient but also intrapatient variability of indinavir and nelfinavir pharmacokinetics, which should be taken into account when interpreting therapeutic drug monitoring. Once patients have reached a sustained virological response, plasma PI monitoring may have a limited impact.

Evaluation by simulation of tests based on non-linear mixed-effects models in pharmacokinetic interaction and bioequivalence cross-over trials.

We propose tests based on non-linear mixed effects models (NLMEM) in pharmacokinetic interaction and bioequivalence cross-over trials comparing two treatments or two formulations. To compare the logarithm of the area under the curve (AUC) using these models, two approaches are studied: in the first one, concentration data are analysed globally, with and without the estimation of a treatment effect; and in the second one, they are analysed separately in each treatment group with the estimation of the individual parameters. Four tests for comparison of the logarithm AUC between two treatment arms are studied: a likelihood-ratio test (LRT), a Wald test and two tests, parametric and non-parametric, comparing the individual Empirical Bayes (EB) estimates. These tests are adapted to the case of equivalence, except the LRT which does not have any simple extension. We evaluate by simulation of the type I error and the power for both comparison and equivalence tests. They are compared to the standard tests recommended by the FDA and the EMEA, based on non-compartmental (NC) AUC. Trials for a usual PK model are simulated under H(0) and several H(1) using S-plus software and analysed with the nlme function. Different configurations of the number of subjects (n=12, 24 and 40) and of the number of samples per subject (J=10, 5 and 3) are studied. The type I error alpha of LRT and Wald comparison test in the 5000 replications of interaction cross-over trials is found to be 20.9 per cent and 21.7 per cent, respectively, in the original design (n=12, J=10), which is far superior to 5 per cent, and decreases when n increases. When n is fixed, alpha is found to increase with J. Power is satisfactory for both tests, after correction of the significance threshold. Results of EB and NC tests are similar with satisfactory powers and a type I error close to 5 per cent, except when J=3 for EB tests. Similar results are obtained for equivalence tests, except for EB and NC Student tests, which are not of a great interest. NC tests keep their place when the number of samples per subject J is large, but NLMEM seem useful for cross-over studies performed in special populations where J limited; the evaluation by Monte-Carlo simulations of empirical threshold seems however necessary because of the inflation of the type I error.

Indinavir plasma concentration and adherence score are codeterminant of early virologic response in HIV-infected patients of the APROCO cohort.

To study the respective roles of indinavir concentrations and treatment adherence as predictors of early virologic response, we analyzed the patients of the APROCO cohort treated by indinavir 800 mg TID during the first 4 months. Minimum (Cmin), maximum (Cmax), and the ratio of the measured to expected concentrations (CR) were estimated for each patient at M4, from a population pharmacokinetic analysis of all data. The relationship among virologic success at M4 [plasma HIV RNA (VL) <500 copies/mL], baseline characteristics, estimated indinavir concentrations, and adherence score measured by a self-administered questionnaire, was analyzed by multivariate logistic regression. In the 216 studied patients, baseline median HIV RNA was 4.4 log10 copies/mL, and CD4 cell count was 309/mm. Virologic success was achieved in 195 (90%) patients; it was independently related to baseline viral load (OR = 0.524, CI 0.29-0.93; P = 0.03), antiretroviral treatment naive status (OR = 3.89, CI 1.29-11.76; P = 0.01), and indinavir Cmin (OR = 1.06, CI 1.02-1.10; P = 0.004) when adherence score was not included in the model, whereas full adherence was the only independent related factor when included in the model (OR = 8.8, 95% CI 2.85-27.3; P < 10). In the 168 fully adherent patients, virologic success was more frequent in patients with shorter duration of antiretrovirals at baseline (P = 0.03), lower baseline HIV RNA (P = 0.03), and higher indinavir CR (P < 10); the most discriminating Cmin cut-off was 194 ng/mL. Data on the relationship between indinavir plasma concentration and virologic success are therefore misleading without a concomitant assessment of adherence. These data suggest that any strategy of therapeutic drug monitoring must imply first a combined evaluation of plasma concentrations and adherence level and second an intervention target based on the results of both assessments.

Enhanced saquinavir exposure in human immunodeficiency virus type 1-infected patients with diarrhea and/or wasting syndrome.

The protease inhibitor saquinavir was administered to 100 human immunodeficiency virus type 1 (HIV-1)-infected patients as a single 600-mg oral dose (hard gelatin capsules) with a standard breakfast, including 200 ml of grapefruit juice, during an open-label trial to assess whether diarrhea and/or wasting syndrome has consequences on its pharmacokinetics. Three groups of patients were enrolled: group 1, asymptomatic patients (n = 30); group 2, AIDS symptomatic patients without body weight loss or diarrhea (n = 37); and group 3, AIDS symptomatic patients with severe body weight loss and/or diarrhea (n = 33). Clinical and biological data (covariates) were collected. A population approach was performed with three blood samples per patient to estimate the mean population pharmacokinetic parameters (clearance [CL]/oral bioavailability [F], V/F, k(a), and lag time) and the derived ones (k(el), C(max), T(max), and area under the curve [AUC]). The relationships between groups, exposure (i.e., estimated individual post hoc AUCs), and covariates were explored by using multiple linear regressions. A significant increase in median AUCs (165, 349, and 705 ng. h. ml(-1) for groups 1, 2, and 3, respectively [P < 0.0001]) was observed. The enhancement in saquinavir exposure could be due to the destruction of the transporters in enterocytes and/or to the enlargement of their tight junctions, allowing a paracellular crossing of saquinavir as the illness spreads. Because of grapefruit juice intake by every patient, no implication of CYP3A4 could be assessed. These results strongly suggest that, despite its low intrinsic oral bioavailability, saquinavir can be considered as a relevant treatment for HIV-1-infected patients with diarrhea and/or wasting syndrome. This must be evaluated in a long-term period.

Construction of a global score quantifying allelic imbalance among biallelic SIDP markers in bladder cancer.

The purpose of this paper is the construction of an adapted statistical test for urinary detection of bladder cancer based on the assessment of allelic imbalance using biallelic Short Insertion/Deletion Polymorphism DNA markers. This test is based on the comparison of several of these markers, analysed from urinary DNA, to the distribution of their analogues in blood, which is taken as reference. A reproductibility study is first performed in blood in order to make a selection among the 23 available markers and 18 are retained. A global score based on the chi2 distribution is then built to test for allelic imbalance among all informative markers for each patient. It avoids the count of DNA abnormalities marker by marker and allows to take into account the degree of abnormality of each marker. That method is preliminarily evaluated on a sample of 53 patients and 27 controls. The estimated specificity (96.3%) on that reduced sample is satisfactory, whereas sensitivity (60.4%) could be improved by an augmentation of the number of tested markers. Several issues regarding the validity of the method are discussed.

Emergence of resistance in normal human aerobic commensal flora during telithromycin and amoxicillin-clavulanic acid treatments.

Mean fecal global yeast counts increased similarly during 7 days of treatment with telithromycin (800 mg once daily) or amoxicillin-clavulanic acid (amoxiclav) (1 g of amoxicillin and 125 mg of clavulanic acid 3 times daily) in human volunteers and decreased slowly thereafter. On skin, coagulase-negative staphylococci of decreased susceptibility (DS) to telithromycin increased in the telithromycin group, whereas those with DS to methicillin increased in the amoxiclav group. A similar antibiotic-related shift towards homologous DS was observed for oral nongroupable streptococci (NGS), but in addition, the prevalence of NGS resistant to both classes of antibiotics was significantly greater in the amoxiclav group at days 8 (P < 0.01) and 45 (P < 0.015).