Impact of covariate model building methods on their clinical relevance evaluation in population pharmacokinetic analyses: comparison of the full model, stepwise covariate model (SCM) and SCM+ approaches.

Covariate analysis in population pharmacokinetics is key for adjusting doses for patients. The main objective of this work was to compare the adequacy of various modeling approaches on covariate clinical relevance decision-making. The full model, stepwise covariate model (SCM) and SCM+ PsN algorithms were compared in a clinical trial simulation of a 383-patient population pharmacokinetic study mixing rich and sparse designs. A one-compartment model with first-order absorption was used. A base model including a body weight effect on CL/F and V/F and a covariate model including 4 additional covariates-parameters relationships were simulated. As for forest plots, ratios between covariates at a specific value and that of a typical individual were calculated with their 90% confidence interval (CI90) using standard errors. Covariates on CL, V and KA were considered relevant if their CI90 fell completely outside the reference area [0.8-1.2]. All approaches provided unbiased covariate ratio estimates. For covariates with a simulated effect, the 3 approaches correctly identify their clinical relevance. However, significant covariates were missed in up to 15% of cases with SCM/SCM+. For covariate with no simulated effects, the full model mainly identified them as non-relevant or with insufficient information while SCM/SCM+ mainly did not select them. SCM/SCM+ assume that non-selected covariates are non-relevant when it could be due to insufficient information, whereas the full model does not make this assumption and is faster. This study must be extended to other methods and completed by a more complex high-dimensional simulation framework.

cLRT-Mod: An efficient methodology for pharmacometric model-based analysis of longitudinal phase II dose finding studies under model uncertainty.

Within the challenging context of phase II dose-finding trials, longitudinal analyses may increase drug effect detection power compared to an end-of-treatment analysis. This work proposes cLRT-Mod, a pharmacometric adaptation of the MCP-Mod methodology, which allows the use of nonlinear mixed effect models to first detect a dose-response signal and then identify the doses for the confirmatory phase while accounting for model structure uncertainty. The method was evaluated through extensive clinical trial simulations of a hypothetical phase II dose-finding trial using different scenarios and comparing different methods such as MCP-Mod. The results show an increase in power using cLRT with longitudinal data compared to an EOT multiple contrast tests for scenarios with small sample size and weak drug effect while maintaining pre-specifiability of the models prior to data analysis and the nominal type I error. This work shows how model averaging provides better coverage probability of the drug effect in the prediction step, and avoids under-estimation of the size of the confidence interval. Finally, for illustration purpose cLRT-Mod was applied to the analysis of a real phase II dose-finding trial.

Population Pharmacokinetics and Exposure-Response Relationships of Baloxavir Marboxil in Influenza Patients at High Risk of Complications.

Baloxavir marboxil, a prodrug of cap-dependent endonuclease inhibitor baloxavir acid, reduces the time to improvement of influenza symptoms in patients infected with type A or B influenza virus. To characterize its pharmacokinetics, a population pharmacokinetic model for baloxavir acid was developed using 11,846 plasma concentration data items from 1,827 subjects, including 2,341 plasma concentration data items from 664 patients at high risk of influenza complications. A three-compartment model with first-order elimination and first-order absorption with lag time well described the plasma concentration data. Body weight and race were found to be the most important factors influencing clearance and volume of distribution. The exposures in high-risk patients were similar to those in otherwise healthy patients, and no pharmacokinetic difference was identified regarding any risk factors for influenza complications. Exposure-response analyses were performed regarding the time to improvement of symptoms and the reduction in the influenza virus titer in high-risk patients. The analyses suggested that body weight-based dosage, 40 mg for patients weighing <80 kg and 80 mg for patients weighing ≥80 kg, can shorten the time to improvement of influenza symptoms and reduce virus titer for both type A and B influenza virus regardless of the exposure levels of the high-risk patients as well as for the otherwise healthy influenza patients. The results of our population pharmacokinetic and exposure-response analyses in patients with risk factors of influenza complications should provide useful information on the pharmacokinetic and pharmacodynamic characteristics of baloxavir marboxil and also for the optimization of dose regimens.

Item Response Theory as an Efficient Tool to Describe a Heterogeneous Clinical Rating Scale in De Novo Idiopathic Parkinson's Disease Patients.

PURPOSE: This manuscript aims to precisely describe the natural disease progression of Parkinson's disease (PD) patients and evaluate approaches to increase the drug effect detection power. METHODS: An item response theory (IRT) longitudinal model was built to describe the natural disease progression of 423 de novo PD patients followed during 48 months while taking into account the heterogeneous nature of the MDS-UPDRS. Clinical trial simulations were then used to compare drug effect detection power from IRT and sum of item scores based analysis under different analysis endpoints and drug effects. RESULTS: The IRT longitudinal model accurately describes the evolution of patients with and without PD medications while estimating different progression rates for the subscales. When comparing analysis methods, the IRT-based one consistently provided the highest power. CONCLUSION: IRT is a powerful tool which enables to capture the heterogeneous nature of the MDS-UPDRS.

Prediction of shrinkage of individual parameters using the bayesian information matrix in non-linear mixed effect models with evaluation in pharmacokinetics.

PURPOSE: When information is sparse, individual parameters derived from a non-linear mixed effects model analysis can shrink to the mean. The objective of this work was to predict individual parameter shrinkage from the Bayesian information matrix (M BF ). We 1) Propose and evaluate an approximation of M BF by First-Order linearization (FO), 2) Explore by simulations the relationship between shrinkage and precision of estimates and 3) Evaluate prediction of shrinkage and individual parameter precision. METHODS: We approximated M BF using FO. From the shrinkage formula in linear mixed effects models, we derived the predicted shrinkage from M BF . Shrinkage values were generated for parameters of two pharmacokinetic models by varying the structure and the magnitude of the random effect and residual error models as well as the design. We then evaluated the approximation of M BF FO and compared it to Monte-Carlo (MC) simulations. We finally compared expected and observed shrinkage as well as the predicted and estimated Standard Errors (SE) of individual parameters. RESULTS: M BF FO was similar to M BF MC. Predicted and observed shrinkages were close . Predicted and estimated SE were similar. CONCLUSIONS: M BF FO enables prediction of shrinkage and SE of individual parameters. It can be used for design optimization.

Clinical pharmacology of emicizumab for the treatment of hemophilia A.

INTRODUCTION: Emicizumab is a humanized bispecific antibody approved for the routine prophylaxis of bleeding episodes in patients with hemophilia A (PwHA) regardless of the presence of factor VIII (FVIII) inhibitors. It mimics the cofactor function of missing activated FVIII by bridging activated factor IX and factor X, thereby restoring hemostasis. AREAS COVERED: This review covers the clinical pharmacology of emicizumab and the translation of its pharmacokinetics (PK) and pharmacodynamics (PD) to clinical efficacy and safety. The PK of emicizumab is linear, with an approximately 1-month half-life. Once-weekly to every-4-week subcutaneous (SC) administrations maintain effective trough concentrations throughout the dosing intervals, associated with a coagulation potential analogous to that in patients with mild hemophilia A. In combination with activated prothrombin complex concentrate, and to a lesser extent with recombinant activated factor VII, emicizumab exerts a synergistic effect, whereas combination with FVIII may result in a non-additive coagulation potential at normal FVIII activity. EXPERT OPINION: The translation of emicizumab PK/PD into clinical effects was demonstrated in several phase III studies, which showed remarkable bleed control and a favorable safety profile in PwHA. These emicizumab attributes, together with the convenience of use (infrequent SC injections), offer a novel paradigm for the management of PwHA.

A Pharmacokinetics-Time to Alleviation of Symptoms Model to Support Extrapolation of Baloxavir Marboxil Clinical Efficacy in Different Ethnic Groups with Influenza A or B.

Baloxavir marboxil, the prodrug of baloxavir acid, is an anti-influenza antiviral. Here, a pharmacokinetics-time to alleviation of symptoms (PK-TTAS) model was developed and used to (I) characterize the PK-TTAS relationship, (II) quantify the impact of covariates, and (III) predict TTAS in different ethnic groups. Data from 1781 otherwise-healthy (OwH) or high-risk (HR) patients included in phase II (JapicCTI-153090) and III studies (NCT02954354 and NCT02949011) were used; patients received either placebo or oral baloxavir marboxil. The natural distribution of TTAS in placebo-treated patients was modeled, then TTAS data from the baloxavir marboxil arms were added to model the impact of baloxavir acid concentration on TTAS. PK parameters estimated by a population PK model and informed by phase I data (NCT03959332 and KCT0003535) were included to simulate TTAS in Chinese and South Korean patients. Composite symptom score at baseline (TSS0), ethnicity, sex, and patient type (OwH or HR) significantly impacted the natural TTAS distribution. TTAS reduced with increasing baloxavir acid concentrations. Compared with placebo, high and low baloxavir acid exposures (AUC0-inf 5.13-16.65 and 0.72-5.13 µg.hr/mL, respectively) significantly reduced TTAS; no covariates affected the drug effect on TTAS. Simulated TTAS was similar between OwH or HR Chinese, South Korean, and other Asian patients, with median reductions from placebo between 18.3-18.8 hours and 21.2-22.0 hours in OwH and HR patients, respectively, assuming TSS0 > 10. Ethnicity (Asian vs. non-Asian) did not significantly impact the drug effect on TTAS; predicted TTAS was similar across different Asian populations. This suggests Chinese and South Korean patients may benefit from similar efficacy as other Asian patients.

Disease Modeling and Model-Based Meta-Analyses to Define a New Direction for a Phase III Program of Gantenerumab in Alzheimer's Disease.

Selecting the right dose is a significant challenge in designing clinical development programs, especially for slowly progressing diseases lacking predictive biomarkers of efficacy that may require long-term treatment to assess clinical benefit. Gantenerumab, a fully human monoclonal antibody (mAb) that binds to aggregated amyloid-beta, was tested in two 24-month phase III studies (NCT01224106, NCT02051608) in participants with prodromal and mild Alzheimer's disease (AD), respectively. Dosing in the first phase III study was suspended after a preplanned interim futility analysis in 2014. Subsequently, a dose-response relationship was observed in a subgroup of fast AD progressors that, together with contemporary aducanumab (another anti-amyloid-beta mAb) data, indicated higher doses may be needed for clinical efficacy. The gantenerumab phase III studies were therefore transformed into dose-finding, open-label extension (OLE) trials. Two exposure-response models were developed to support dose selection via simulations for the OLEs: a pharmacokinetics (PK)/PET (positron emission tomography) model describing amyloid removal using PET data from low-dose gantenerumab and high-dose aducanumab, and a PK/ARIA-E (amyloid-related imaging abnormalities-edema) model describing the occurrence of ARIA-E events leveraging an existing bapineuzumab model. Multiple regimens were designed to gradually up-titrate participants to the target dose of 1,200 mg gantenerumab every 4 weeks to mitigate the increased risk of ARIA-E events that may be associated with higher doses of anti-amyloid-beta antibodies. Favorable OLE data that matched well with model predictions supported the decision to continue the gantenerumab clinical development program and further apply model-based analytical techniques to optimize the design of new phase III studies.

Pharmacokinetics, safety, and simulated efficacy of an influenza treatment, baloxavir marboxil, in Chinese individuals.

Baloxavir marboxil is an endonuclease inhibitor indicated for the treatment of influenza in patients ≥12 years. No data exist for Chinese patients in global studies. This randomized, open-label, phase I study evaluated the pharmacokinetics (PK) and safety of baloxavir marboxil in healthy Chinese volunteers and was used to anticipate efficacy in Chinese patients. Patients received a single oral dose of baloxavir marboxil (40 or 80 mg [1:1]). Serial blood samples were collected predose and at various timepoints up to 14 days postdose. Baloxavir marboxil and acid plasma concentrations were determined by liquid chromatography tandem mass spectrometry. PK parameters of baloxavir acid were estimated by noncompartmental analysis. Adverse events (AEs) were recorded. Time to alleviation of symptoms (TTAS) was simulated for otherwise healthy (OwH) and high-risk (HR) Chinese and Asian patients. Thirty-two male patients received baloxavir marboxil. Baloxavir acid plasma concentration peaked 4 h postdose. Mean maximum concentration (Cmax ) was 107.6 and 206.9 ng/ml, and mean area under the plasma concentration-time curve from zero to infinity (AUC0-inf ) was 6955 and 9643 ng·h/ml in the 40 and 80 mg cohorts, respectively. AEs were mild and transient; no new safety signals were identified. Simulated median TTAS for OwH and HR Chinese patients agreed with simulated values in Asian patients. PK parameters were similar to Asian populations in other studies. The globally adopted baloxavir marboxil dosing strategy was consistent with the established safety profile of baloxavir marboxil in this population. Simulated efficacy indicated Chinese patients could benefit from similar efficacy to Asian patients.

Exposure-Bleeding Count Modeling of Emicizumab for the Prophylaxis of Bleeding in Persons with Hemophilia A with/Without Inhibitors Against Factor VIII.

BACKGROUND AND OBJECTIVE: Emicizumab is a monoclonal antibody that bridges activated coagulation factor IX and factor X to restore effective hemostasis in persons with hemophilia A. It is indicated for routine prophylaxis of bleeding episodes in persons with hemophilia A. The aim of the present study is to describe the exposure-response relationship between emicizumab concentrations and bleeding frequency, and to confirm adequate bleeding control of the investigated dosing regimens 1.5 mg/kg once weekly, 3 mg/kg every 2 weeks, and 6 mg/kg every 4 weeks. METHODS: Treated bleeding events were pooled from 445 persons with hemophilia A with and without inhibitors against factor VIII, participating in six clinical studies. Emicizumab concentrations were predicted using a previously developed population pharmacokinetic model. A count model was used to quantify the exposure-response relationship. These models were used to illustrate the relationship between emicizumab concentrations and cumulative count of bleeding over 1 year (annualized bleeding rate). RESULTS: The final exposure-response model, based on a generalized Poisson distribution and an inhibitory Emax relationship, adequately describes the relationship between daily emicizumab concentrations and daily bleed frequency. A significant effect of factor VIII prophylaxis among persons with hemophilia A without inhibitors was found. Annualized bleeding rate simulations show that the three emicizumab dosing regimens maintain the concentrations close to the plateau of the effect. At the average steady-state concentration across all regimens (53.5 µg/mL), the predicted mean annualized bleeding rate is 1.28, corresponding to a 94.0% reduction from baseline. CONCLUSIONS: These results confirm that average emicizumab concentrations achieved with all three emicizumab dosing regimens provide adequate bleeding control.

Population Pharmacokinetic Analysis and Exploratory Exposure-Bleeding Rate Relationship of Emicizumab in Adult and Pediatric Persons with Hemophilia A.

BACKGROUND: Emicizumab is a bispecific monoclonal antibody developed for routine prophylaxis of bleeding in people with hemophilia A (PwHA). This work characterizes the pharmacokinetics of emicizumab in adult and pediatric PwHA, identifies factors contributing to its between-person variabilities, compares the pharmacokinetics following different dosing regimens, and makes a descriptive assessment of the exposure-bleeding events relationship. METHODS: A population pharmacokinetic model was developed, using a database of 389 PwHA from five clinical studies. Potential baseline covariate effects were assessed, including body size, age, race, presence of factor VIII inhibitors, and albumin levels. Using the population pharmacokinetic model, the estimated individual average exposures over the administration period were compared across categories of annualized bleeding rate. RESULTS: A linear one-compartment model with first-order absorption and elimination processes and no lag time best described the emicizumab pharmacokinetics. Body weight, albumin levels, age, and black race were statistically correlated with primary pharmacokinetic parameters, but only body weight had an important influence on exposure. Dosing regimens of 1.5 mg/kg weekly, 3 mg/kg every 2 weeks, or 6 mg/kg every 4 weeks provided similar average concentrations at steady state. A trend for lower exposure was observed in the small proportion of PwHA having an annualized bleeding rate > 4 (11.9%), suggesting that reducing exposure to lower levels may potentially increase the bleeding risk. CONCLUSIONS: Emicizumab pharmacokinetics in PwHA was described with dose-independent parameters. Body weight was an important predictor of emicizumab pharmacokinetics. All three dosing regimens are predicted to achieve similar exposure associated with clinically meaningful prevention of bleeding.

Fisher information matrix for nonlinear mixed effects multiple response models: evaluation of the appropriateness of the first order linearization using a pharmacokinetic/pharmacodynamic model.

We focus on the Fisher information matrix used for design evaluation and optimization in nonlinear mixed effects multiple response models. We evaluate the appropriateness of its expression computed by linearization as proposed for a single response model. Using a pharmacokinetic-pharmacodynamic (PKPD) example, we first compare the computation of the Fisher information matrix with approximation to one derived from the observed matrix on a large simulation using the stochastic approximation expectation-maximization algorithm (SAEM). The expression of the Fisher information matrix for multiple responses is also evaluated by comparison with the empirical information obtained through a replicated simulation study using the first-order linearization estimation methods implemented in the NONMEM software (first-order (FO), first-order conditional estimate (FOCE)) and the SAEM algorithm in the MONOLIX software. The predicted errors given by the approximated information matrix are close to those given by the information matrix obtained without linearization using SAEM and to the empirical ones obtained with FOCE and SAEM. The simulation study also illustrates the accuracy of both FOCE and SAEM estimation algorithms when jointly modelling multiple responses and the major limitations of the FO method. This study highlights the appropriateness of the approximated Fisher information matrix for multiple responses, which is implemented in PFIM 3.0, an extension of the R function PFIM dedicated to design evaluation and optimization. It also emphasizes the use of this computing tool for designing population multiple response studies, as for instance in PKPD studies or in PK studies including the modelling of the PK of a drug and its active metabolite.

Predicted propofol effect-site concentration for induction and emergence of anesthesia during early pregnancy.

BACKGROUND: Pregnancy is associated with decreased hypnotic requirement, allegedly related to progesterone. However, the effects of pregnancy and progesterone on propofol requirement have not been thoroughly investigated. We conducted this study to determine whether propofol dose and predicted effect-site concentration for loss of consciousness (LOC) during induction of anesthesia, and eye opening during emergence from anesthesia, are decreased during early pregnancy. We also investigated whether blood progesterone was correlated with propofol dose and effect-site concentration for LOC. METHODS: We studied 57 ASA I-II women patients undergoing elective termination of pregnancy and 55 control patients undergoing transvaginal oocyte puncture for in vitro fertilization. Anesthesia was induced by administration of a 1% propofol infusion at 200 mL/min. Propofol dose and calculated effect-site concentration (Schnider model) were recorded at the time of LOC during induction. We also calculated effect-site concentration at the time of eye opening upon emergence from anesthesia. Blood progesterone was measured after surgery. RESULTS: Mean (+/-1 SD) propofol dose at LOC was significantly reduced in the pregnant patients compared with the nonpregnant control patients (108.57 +/- 20.04 vs 117.59 +/- 17.98 mg, respectively; P = 0.014). Similarly, the calculated propofol effect-site concentration at LOC was significantly lower in the pregnant patients than the nonpregnant control patients (4.59 +/- 0.72 vs 5.01 +/- 0.64 microg/mL, respectively; P = 0.0014). There was no difference in the calculated effect-site concentration on eye opening upon emergence. No significant relationship was observed between blood progesterone and propofol dose or calculated propofol effect-site concentration at LOC. CONCLUSION: Propofol dose and predicted propofol effect-site concentration at LOC are decreased during early pregnancy. Progesterone does not explain this result.

Comparison of Model Averaging and Model Selection in Dose Finding Trials Analyzed by Nonlinear Mixed Effect Models.

In drug development, pharmacometric approaches consist in identifying via a model selection (MS) process the model structure that best describes the data. However, making predictions using a selected model ignores model structure uncertainty, which could impair predictive performance. To overcome this drawback, model averaging (MA) takes into account the uncertainty across a set of candidate models by weighting them as a function of an information criterion. Our primary objective was to use clinical trial simulations (CTSs) to compare model selection (MS) with model averaging (MA) in dose finding clinical trials, based on the AIC information criterion. A secondary aim of this analysis was to challenge the use of AIC by comparing MA and MS using five different information criteria. CTSs were based on a nonlinear mixed effect model characterizing the time course of visual acuity in wet age-related macular degeneration patients. Predictive performances of the modeling approaches were evaluated using three performance criteria focused on the main objectives of a phase II clinical trial. In this framework, MA adequately described the data and showed better predictive performance than MS, increasing the likelihood of accurately characterizing the dose-response relationship and defining the minimum effective dose. Moreover, regardless of the modeling approach, AIC was associated with the best predictive performances.

Correction to: A phase III randomized trial of gantenerumab in prodromal Alzheimer's disease.

Following publication of the original article [1], the author reported errors in the formatting of the table. The details of the errors are as follows.

A phase III randomized trial of gantenerumab in prodromal Alzheimer's disease.

BACKGROUND: Gantenerumab is a fully human monoclonal antibody that binds aggregated amyloid-ß (Aß) and removes Aß plaques by Fc receptor-mediated phagocytosis. In the SCarlet RoAD trial, we assessed the efficacy and safety of gantenerumab in prodromal Alzheimer's disease (AD). METHODS: In this randomized, double-blind, placebo-controlled phase III study, we investigated gantenerumab over 2 years. Patients were randomized to gantenerumab 105 mg or 225 mg or placebo every 4 weeks by subcutaneous injection. The primary endpoint was the change from baseline to week 104 in Clinical Dementia Rating Sum of Boxes (CDR-SB) score. We evaluated treatment effects on cerebrospinal fluid biomarkers (all patients) and amyloid positron emission tomography (substudy). A futility analysis was performed once 50% of patients completed 2 years of treatment. Safety was assessed in patients who received at least one dose. RESULTS: Of the 3089 patients screened, 797 were randomized. The study was halted early for futility; dosing was discontinued; and the study was unblinded. No differences between groups in the primary (least squares mean [95% CI] CDR-SB change from baseline 1.60 [1.28, 1.91], 1.69 [1.37, 2.01], and 1.73 [1.42, 2.04] for placebo, gantenerumab 105 mg, and gantenerumab 225 mg, respectively) or secondary clinical endpoints were observed. The incidence of generally asymptomatic amyloid-related imaging abnormalities increased in a dose- and APOE ε4 genotype-dependent manner. Exploratory analyses suggested a dose-dependent drug effect on clinical and biomarker endpoints. CONCLUSIONS: The study was stopped early for futility, but dose-dependent effects observed in exploratory analyses on select clinical and biomarker endpoints suggest that higher dosing with gantenerumab may be necessary to achieve clinical efficacy. TRIAL REGISTRATION: ClinicalTrials.gov, NCT01224106 . Registered on October 14, 2010.

The use of simulated annealing for finding optimal population designs.

The development of functions for MATLAB and S-PLUS that can be used for the evaluation of specific population pharmacokinetic designs has been described recently. These functions are based on the evaluation of an approximation of the population Fisher information matrix. Optimisation of the design of the population experiment can be made on the basis of D-optimal design techniques, where the determinant of the population Fisher information matrix is maximised. This maximisation is complex due to the convoluted nature of the surface of the determinant. Four optimisation algorithms (simplex, non-adaptive random search, non-adaptive random search followed by simplex and simulated annealing) are compared in their ability to optimise the sampling times for various design structures for three examples of population pharmacokinetic models. In all cases, despite more computing time, simulated annealing was superior to the other methods for finding optimal designs with greater benefits being seen over the other algorithms for the more complex designs.

Design evaluation and optimisation in multiple response nonlinear mixed effect models: PFIM 3.0.

Nonlinear mixed effect models (NLMEM) with multiple responses are increasingly used in pharmacometrics, one of the main examples being the joint analysis of the pharmacokinetics (PK) and pharmacodynamics (PD) of a drug. Efficient tools for design evaluation and optimisation in NLMEM are necessary. The R functions PFIM 1.2 and PFIMOPT 1.0 were proposed for these purposes, but accommodate only single response models. The methodology used is based on the Fisher information matrix, developed using a linearisation of the model. In this paper, we present an extended version, PFIM 3.0, dedicated to both design evaluation and optimisation for multiple response models, using a similar method as for single response models. In addition to handling multiple response models, several features have been integrated into PFIM 3.0 for model specification and optimisation. The extension includes a library of classical analytical pharmacokinetics models and allows the user to describe more complex models using differential equations. Regarding the optimisation algorithm, an alternative to the Simplex algorithm has been implemented, the Fedorov-Wynn algorithm to optimise more practical D-optimal design. Indeed, this algorithm optimises design among a set of sampling times specified by the user. This R function is freely available at http://www.pfim.biostat.fr. The efficiency of this approach and the simplicity of use of PFIM 3.0 are illustrated with a real example of the joint PKPD analysis of warfarin, an oral anticoagulant, with a model defined by ordinary differential equations.

Automated ankle-brachial pressure index measurement by clinical staff for peripheral arterial disease diagnosis in nondiabetic and diabetic patients.

OBJECTIVE: Peripheral arterial disease (PAD) is a prognostic marker in cardiovascular disease. The use of Doppler-measured ankle-brachial pressure index (Dop-ABI) for PAD diagnosis is limited because of time, required training, and costs. We assessed automated oscillometric measurement of the ankle-brachial pressure index (Osc-ABI) by nurses and clinical staff. RESEARCH DESIGN AND METHODS: Clinical staff obtained Osc-ABI with an automated oscillometric device in 146 patients (83 with diabetes) at the time of Dop-ABI measurement and ultrasound evaluation. RESULTS: Measurements were obtained in most legs (Dop-ABI 98%; Osc-ABI 95.5%). Dop- and Osc-ABI were significantly related in diabetic and nondiabetic patients with good agreement over a wide range of values. When Dop-ABI

Ciprofloxacin dosage and emergence of resistance in human commensal bacteria.

BACKGROUND: Although optimization of the fluoroquinolone dosage increases the efficacy of this class of drugs against bacterial infections, its impact on the emergence of resistance in commensal bacteria is unknown. METHODS: Six different 14-day dosages of oral ciprofloxacin were randomly assigned to 48 healthy volunteers. Individual pharmacokinetic and pharmacodynamic parameters combining antibiotic exposure in plasma, saliva, and stool specimens and ciprofloxacin minimum inhibitory concentrations (MICs) and mutant prevention concentrations against viridans group streptococci in the pharyngeal flora and Escherichia coli in the fecal flora were estimated. Their links with the emergence of resistance to nalidixic acid or ciprofloxacin in the fecal flora and to levofloxacin in the pharyngeal flora 7, 14, or 42 days after ciprofloxacin initiation were investigated. RESULTS: Resistance emerged in the fecal and pharyngeal flora of 25% and 33% of the subjects, respectively, mainly when local concentrations of ciprofloxacin were less than the MIC. No variable that integrated pharmacokinetic data and pharmacodynamic parameters was found to differ significantly between the subjects in whom resistance emerged and those in whom it did not. Probabilities of the emergence of resistance were not significantly different across the different antibiotic dosages. CONCLUSIONS: Selection of resistant commensals during ciprofloxacin therapy is a frequent ecological side effect that is not preventable by dosage optimization. Trial registration. Clinical Trials.gov identifier: NCT00190151.