A phase 2 multiple ascending dose trial of bapineuzumab in mild to moderate Alzheimer disease.

BACKGROUND: Bapineuzumab, a humanized anti-amyloid-beta (Abeta) monoclonal antibody for the potential treatment of Alzheimer disease (AD), was evaluated in a multiple ascending dose, safety, and efficacy study in mild to moderate AD. METHODS: The study enrolled 234 patients, randomly assigned to IV bapineuzumab or placebo in 4 dose cohorts (0.15, 0.5, 1.0, or 2.0 mg/kg). Patients received 6 infusions, 13 weeks apart, with final assessments at week 78. The prespecified primary efficacy analysis in the modified intent-to-treat population assumed linear decline and compared treatment differences within dose cohorts on the Alzheimer's Disease Assessment Scale-Cognitive and Disability Assessment for Dementia. Exploratory analyses combined dose cohorts and did not assume a specific pattern of decline. RESULTS: No significant differences were found in the primary efficacy analysis. Exploratory analyses showed potential treatment differences (p < 0.05, unadjusted for multiple comparisons) on cognitive and functional endpoints in study "completers" and APOE epsilon4 noncarriers. Reversible vasogenic edema, detected on brain MRI in 12/124 (9.7%) bapineuzumab-treated patients, was more frequent in higher dose groups and APOE epsilon4 carriers. Six vasogenic edema patients were asymptomatic; 6 experienced transient symptoms. CONCLUSIONS: Primary efficacy outcomes in this phase 2 trial were not significant. Potential treatment differences in the exploratory analyses support further investigation of bapineuzumab in phase 3 with special attention to APOE epsilon4 carrier status. CLASSIFICATION OF EVIDENCE: Due to varying doses and a lack of statistical precision, this Class II ascending dose trial provides insufficient evidence to support or refute a benefit of bapineuzumab.

Clinical trials in Alzheimer's disease. Calculating Alzheimer's Disease Assessment Scale-cognitive subsection with the data from the consortium to establish a registry for Alzheimer's disease.

The database of the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) is a seminal work in the field of cognitive dysfunction and Alzheimer's disease. This 24-center study of 1,094 patients with Alzheimer's disease who received no treatment for their cognitive dysfunction and 463 normal control subjects is rich in neurobehavioral data and contains extensive imaging and neuropathologic findings. However, the Alzheimer's Disease Assessment Scale (ADAS) was not administered as part of the CERAD study, which limits the study's applicability to modern drug trials, in which the ADAS-cognitive subsection (ADAS-cog) is a popular end point. The purpose of this investigation was to develop a derived ADAS-cog score from the neurobehavioral data obtained from subjects during their evaluation in the CERAD study. Two calculated ADAS-cog scores were developed. The first was based on clinically mapping the items on the ADAS-cog to assessments that were performed in the CERAD study. The second was based on rescaling the Mini-Mental Status Exam (MMSE), using published results correlating the ADAS-cog to the MMSE. Standard characteristics of both calculated ADAS-cog scores were calculated and compared with each other and with the literature. Both calculated ADAS-cog scores performed comparably to published characteristics of the ADAS-cog. The clinically based calculated ADAS-cog outperformed the rescaled MMSE. Using the CERAD database, it is now possible to model the progression of an untreated (placebo) population of patients with Alzheimer's disease and correlate it to a study using ADAS-cog.

Response surface model for anesthetic drug interactions.

BACKGROUND: Anesthetic drug interactions traditionally have been characterized using isobolographic analysis or multiple logistic regression. Both approaches have significant limitations. The authors propose a model based on response-surface methodology. This model can characterize the entire dose-response relation between combinations of anesthetic drugs and is mathematically consistent with models of the concentration-response relation of single drugs. METHODS: The authors defined a parameter, theta, that describes the concentration ratio of two potentially interacting drugs. The classic sigmoid Emax model was extended by making the model parameters dependent on theta. A computer program was used to estimate response surfaces for the hypnotic interaction between midazolam, propofol, and alfentanil, based on previously published data. The predicted time course of effect was simulated after maximally synergistic bolus dose combinations. RESULTS: The parameters of the response surface were identifiable. With the test data, each of the paired combinations showed significant synergy. Computer simulations based on interactions at the effect site predicted that the maximally synergistic three-drug combination tripled the duration of effect compared with propofol alone. CONCLUSIONS: Response surfaces can describe anesthetic interactions, even those between agonists, partial agonists, competitive antagonists, and inverse agonists. Application of response-surface methodology permits characterization of the full concentration-response relation and therefore can be used to develop practical guidelines for optimal drug dosing.

A technique for population pharmacodynamic analysis of concentration-binary response data.

BACKGROUND: Pharmacodynamic data frequently consist of the binary assessment (a "yes" or "no" answer) of the response to a defined stimulus (verbal stimulus, intubation, skin incision, and so on) for multiple patients. The concentration-effect relation is usually reported in terms of C50, the drug concentration associated with a 50% probability of drug effect, and a parameter the authors denote gamma, which determines the shape of the concentration-probability of effect curve. Accurate estimation of gamma, a parameter describing the entire curve, is as important as the estimation of C50, a single point on this curve. Pharmacodynamic data usually are analyzed without accounting for interpatient variability. The authors postulated that accounting for interpatient variability would improve the accuracy of estimation of gamma and allow the estimation of C50 variability. METHODS: A probit-based model for the individual concentration-response relation was assumed, characterized by two parameters, C50 and gamma. This assumption was validated by comparing probit regression with the more commonly used logistic regression of data from individual patients found in the anesthesiology literature. The model was then extended to analysis of population data by assuming that C50 has a log-normal distribution. Population data were analyzed in terms of three parameters, (C50), the mean value of C50 in the population; omega, the standard deviation of the distribution of the logarithm of C50; and gamma. The statistical characteristics of the technique were assessed using simulated data. The data were generated for a range of gamma and omega values, assuming that C50 and gamma had a log-normal distribution. RESULTS: The probit-based model describes data from individual patients and logistic regression does. Population analysis using the extended probit model accurately estimated (C50), gamma, and omega for a range of values, despite the fact that the technique accounts for C50 variability but not gamma variability. CONCLUSIONS: A probit-based method of pharmacodynamic analysis of pooled population data facilitates accurate estimation of the concentration-response curve.

Preoperative anxiety and fear: a comparison of assessments by patients and anesthesia and surgery residents.

We sought to compare self-assessment of preoperative anxiety levels and selection of worst fears by surgical patients with the assessments made by the anesthesia and surgery residents providing intraoperative care for those patients. One hundred inpatients at a Veterans Affairs hospital (Group 1) and 45 patients at a University hospital (Group 2) were asked to complete a brief questionnaire; the residents were asked to complete the same questionnaire. Group 1 results showed that median patient visual analog scale (VAS) scores were lower for anxiety about anesthesia compared to surgery (16 vs 22, P < or = 0.05). Anesthesia resident VAS scores were higher than patient or surgery resident scores. Neither type of resident was able to predict their individual patient's VAS score (Kendall's tau). The fear chosen with the greatest incidence by Group 1 patients and residents was "whether surgery would work". A significant number of residents (34%, anesthesia or surgery, P < or = 0.05) matched their patient's fear choice. Residents commonly chose fears related to their specialty (e.g., anesthesia residents chose anesthesia-related fears more often than surgery residents, 50% vs 28%, P < or = 0.001). In Group 2, residents demonstrated an improved ability to predict patient scores. For instance, both surgery and anesthesia residents were able to predict individual University patient VAS scores (P < or = 0.01). The fear chosen with the greatest frequency by Group 2 patients was "pain after the operation". Sixty percent of anesthesia residents matched their patients' fear choice (P < or = 0.001). This study indicates a variable ability of anesthesia and surgery residents to predict patient anxiety and fear which may be due, in part, to difficulty in understanding a Veterans Affairs hospital patient population.

Derivation and cross-validation of pharmacokinetic parameters for computer-controlled infusion of lidocaine in pain therapy.

BACKGROUND: Lidocaine administered intravenously is efficacious in treating neuropathic pain at doses that do not cause sedation or other side effects. Using a computer-controlled infusion pump (CCIP), it is possible to maintain the plasma lidocaine concentration to allow drug equilibration between the plasma and the site of the drug effect. Pharmacokinetic parameters were derived for CCIP administration of lidocaine in patients with chronic pain. METHODS: Thirteen patients (mean age 45 yr, mean weight 66 kg) were studied. Eight subjects received a computer-controlled infusion, targeting four increasing lidocaine concentrations (1-7 micrograms.ml-1) for 30 min each, based on published kinetic parameters in which venous samples were obtained infrequently after bolus administration. From the observations in these eight patients, new lidocaine pharmacokinetic parameters were estimated. These were prospectively tested in five additional patients. From the complete data set (13 patients), final structural parameters were estimated using a pooled analysis approach. The interindividual variability was determined with a mixed-effects model, with the structural model parameters fixed at the values obtained from the pooled analysis. Internal cross-validation was used to estimate the residual error in the final pharmacokinetic model. RESULTS: The lidocaine administration based on the published parameters consistently produced higher concentrations than desired, resulting in acute lidocaine toxicity in most of the first eight patients. The highest measured plasma concentration was 15.3 micrograms.ml-1. The pharmacokinetic parameters estimated from these eight patients differed from the initial estimates and included a central volume one-sixth of the initial estimate. In the subsequent prospective test in five subjects, the new parameters resulted in concentrations evenly distributed around the target concentration. None of the second group of subjects had evidence of acute lidocaine toxicity. The final parameters ( +/- population variability expressed as %CV) were estimated as follows: V1 0.101 +/- 53% 1.kg-1, V2 0.452 +/- 33% 1.kg-1, Cl1 0.0215 +/- 25% 1.kg-1.min-1, and Cl2 0.0589 +/- 35% 1.kg-1.min-1. The median error measured by internal cross-validation was +1.9%, and the median absolute error was 14%. CONCLUSIONS: Pharmacokinetic parameters for lidocaine were derived and administration was prospectively tested via computer-controlled infusion pumps for patients with chronic neuropathic pain. The estimated parameters performed well when tested prospectively. A second estimation step further refined the parameters and improved performance, as measured using internal cross-validation.

Semilinear canonical correlation applied to the measurement of the electroencephalographic effects of midazolam and flumazenil reversal.

BACKGROUND: The electroencephalographic (EEG) effect of benzodiazepines, and midazolam in particular, has been described using simple measures such as total power in the beta band, waves.s(-1) in the beta band and total power from aperiodic analysis. All these parameters failed to consistently describe the EEG effect of midazolam in a study in which large doses of midazolam were infused, and the effect subsequently reversed with flumazenil. Using a technique called semilinear correlation it is possible to extract a parameter from the EEG that is statistically optimally correlated with the apparent concentration of the benzodiazepine in the effect site. This method has been used to develop new univariate measures of the effects of opioids on the EEG but has not previously been applied to the EEG effects of benzodiazepines. METHODS: Data from ten subjects who received an infusion of midazolam were analyzed. The data were divided into "learning" and "test" sets. The learning set consisted of ten studies in which the volunteers received an infusion of 2.5 mg.min(-1) midazolam. Semilinear canonical correlation was used to extract an univariate descriptor of the EEG effect by weighting the different frequency bands of the EEG power spectrum. The test set comprised the same subjects on subsequent visits, in which the subjects received a continuous infusion of midazolam to maintain 20% or 80% of the peak drug effect for 3h. Twenty minutes after start of the midazolam infusion, the patient received an infusion of flumazenil to acutely reverse the benzodiazepine drug effect. The weights obtained from the learning set were tested prospectively in the test set, based on the coefficient of multiple determination, R(2), obtained by fitting the EEG effect to a sigmoid Emax model. RESULTS: The canonical univariate parameter of benzodiazepine drug effect on the EEG, when applied to the test set receiving the midazolam infusion with flumazenil reversal, yielded a median R(2) of 0.78. The median R(2) of six commonly used empirical EEG measures of drug effect ranged from 0.18 to 0.55. CONCLUSIONS: The canonical univariate parameter for benzodiazepine drug effect on the EEG correlates more accurately and consistently with the predicted EEG effects of midazolam and its reversal than previously reported EEG measures of benzodiazepine effect.

Validation of the alfentanil canonical univariate parameter as a measure of opioid effect on the electroencephalogram.

BACKGROUND: Several parameters derived from the multivariate electroencephalographic (EEG) signal have been used to characterize the effects of opioids on the central nervous system. These parameters were formulated on an empirical basis. A new statistical method, semilinear canonical correlation, has been used to construct a new EEG parameter (a certain combination of the powers in the EEG power spectrum) that correlates maximally with the concentration of alfentanil at the effect site. To date, this new canonical univariate parameter (CUP) has been tested only in a small sample of subjects receiving alfentanil. METHODS: The CUP was tested on EEG data from prior studies of the effect of five opioids: alfentanil (n = 5), fentanyl (n = 15), sufentanil (n = 11), trefentanil (n = 5), and remifentanil (n = 8). We compared the CUP to the commonly used EEG parameter spectral edge, SE95%. The comparison was based on the signal to noise ratio, obtained by fitting a nonlinear pharmacodynamic model to both parameters. The pharmacodynamic parameter estimates obtained using both measurements were also compared. RESULTS: The values for signal-to-noise ratio were significantly greater for the CUP than for SE95% when considering all the opioids at once. The pharmacodynamic estimates were similar between the two EEG parameters and with previously published results. Semilinear canonical correlation coefficients estimated within each drug group showed patterns similar to each other and to the coefficients in the CUP, but different from coefficients for propofol and midazolam. CONCLUSIONS: Although the CUP was originally designed and tested using alfentanil, we have proven it to be a general measure of opioid effect on the EEG.

Application of semilinear canonical correlation to the measurement of opioid drug effect.

To examine the relationship between the electroencephalograph (EEG) and plasma opioid concentration, one would like to collapse the high-dimensional EEG signal into a univariate quantity. Such a simplification of the EEG is desirable because a univariate quantity can be modeled using standard nonlinear regression techniques, and because most of the information in the EEG is redundant or unrelated to drug concentration. In previous studies of the EEG response to opioids, the manner in which a univariate component was extracted from the EEG was ad hoc. In this paper, this extraction was performed optimally using a new statistical technique, semilinear canonical correlation. Data from 15 patients who received an intravenous infusion of the semisynthetic opioid alfentanil were analyzed. The components of the EEG that were nearly maximally correlated with plasma drug concentration were found, based on a standard pharmacokinetic-pharmacodynamic model. Two new EEG components were produced from the powers in the frequency spectrum of the EEG: a weighted sum of the logarithms of the powers, and a weighted sum of the powers expressed as percentages of the total power. These components both had a median R2 of 0.84, compared to median R2s ranging from 0.37 to 0.83 for five commonly used ad hoc EEG components. The new components also had less variability in R2 between subjects.

Algorithms to rapidly achieve and maintain stable drug concentrations at the site of drug effect with a computer-controlled infusion pump.

Computer-controlled infusion pumps incorporating an internal model of drug pharmacokinetics can rapidly achieve and maintain constant drug concentrations in the plasma. Although these pumps offer more accurate titration of intravenous drugs than is possible with simple boluses or constant rate infusions, the choice of the plasma as the target site is arbitrary. The plasma is not the site of drug effect for most drugs. This manuscript describes two algorithms for calculation of the infusion rates necessary for a computer-controlled infusion pump to rapidly achieve, and then maintain, the desired target concentration at the site of drug effect rather than in the plasma.