An information-theoretic approach for the assessment of a continuous outcome as a surrogate for a binary true endpoint based on causal inference: Application to vaccine evaluation.

Within the causal association paradigm, a method is proposed to assess the validity of a continuous outcome as a surrogate for a binary true endpoint. The methodology is based on a previously introduced information-theoretic definition of surrogacy and has two main steps. In the first step, a new model is proposed to describe the joint distribution of the potential outcomes associated with the putative surrogate and the true endpoint of interest. The identifiability issues inherent to this type of models are handled via sensitivity analysis. In the second step, a metric of surrogacy new to this setting, the so-called individual causal association is presented. The methodology is studied in detail using theoretical considerations, some simulations, and data from a randomized clinical trial evaluating an inactivated quadrivalent influenza vaccine. A user-friendly R package Surrogate is provided to carry out the evaluation exercise.

Assessing the Operational Characteristics of the Individual Causal Association as a Metric of Surrogacy in the Binary Continuous Setting.

In a causal inference framework, a new metric has been proposed to quantify surrogacy for a continuous putative surrogate and a binary true endpoint, based on information theory. The proposed metric, termed the individual causal association (ICA), was quantified using a joint causal inference model for the corresponding potential outcomes. Due to the non-identifiability inherent in this type of models, a sensitivity analysis was introduced to study the behavior of the ICA as a function of the non-identifiable parameters characterizing the aforementioned model. In this scenario, to reduce uncertainty, several plausible yet untestable assumptions like monotonicity, independence, conditional independence or homogeneous variance-covariance, are often incorporated into the analysis. We assess the robustness of the methodology regarding these simplifying assumptions via simulation. The practical implications of the findings are demonstrated in the analysis of a randomized clinical trial evaluating an inactivated quadrivalent influenza vaccine.

Implementing the meta-analytic approach for the evaluation of surrogate endpoints in SAS and R: a word of caution.

The meta-analytic approach has become the gold-standard methodology for the evaluation of surrogate endpoints and several implementations are currently available in SAS and R. The methodology is based on hierarchical models that are numerically demanding and, when the amount of data is limited, maximum likelihood algorithms may not converge or may converge to an ill-conditioned maximum such as a boundary solution. This may produce misleading conclusions and have negative implications for the evaluation of new drugs. In the present work, we explore the use of two distinct functions in R (lme and lmer) and the MIXED procedure in SAS to assess the validity of putative surrogate endpoints in the meta-analytic framework, via simulations and the analysis of a real case study. We describe some problems found with the lmer function in R that led to a poorer performance as compared with the lme function and MIXED procedure.

A Comparative Pharmacokinetics Study of the Anti-Parkinsonian Drug Pramipexole.

The present study aimed to compare pharmacokinetic parameters of two pramipexole 0.25 mg formulations in order to show bioequivalence. The study was conducted in a randomized, open-label, two-period, two-sequence, and crossover design, involving 23 healthy volunteers. One of the 0.25 mg formulations of pramipexole evaluated in the study was manufactured by PT Dexa Medica, Palembang, Indonesia, the other, used as the reference, by Boehringer Ingelheim Pharma GmbH & Co. KG, Ingelheim am Rhein, Germany. All eligible subjects were required to fast before each drug administration period, which was separated by a one-week washout period. Pramipexole concentrations in plasma were assayed using a validated ultra performance liquid chromatography with mass spectrometry (UPLC-MS/MS) detector. The evaluated pharmacokinetic parameters included the area under the plasma concentration curve from time zero to the last observed measurable concentration (AUC0-t), the area under the plasma concentration curve extrapolated to infinite time (AUC0-∞), the maximum plasma concentration (Cmax), the time to reach Cmax (tmax), and the plasma concentration half-life (t1/2). To evaluate the bioequivalence of those two pramipexole formulations, 90% confidence intervals (CIs) for geometric mean ratios of both formulations were calculated for AUC and Cmax parameters, while tmax and t1/2 differences were analyzed on the non-transformed data using Wilcoxon matched-pairs and a Student's paired t-test, respectively. The 90% CIs for the geometric mean ratios of the two pramipexole formulations were 95.89% (90.73%-101.34%), 95.53% (89.75%-101.68%), and 92.11% (84.35%-100.58%) for AUC0-t, AUC0-∞, and Cmax, respectively. There were no statistically significant differences for tmax and t1/2 between the two pramipexole formulations. It is concluded that two pramipexole formulations in this study were bioequivalent.

Pharmacokinetic equivalence study of two formulations of the anticonvulsant pregabalin.

PURPOSE: The present study was conducted to evaluate whether the bioavailability of pregabalin capsules 150 mg manufactured by PT Dexa Medica was equivalent to the reference formulation. METHODS: This was a randomized, open-label, two-period, two-sequence, and crossover study under fasting condition, with a 1-week washout period. Plasma concentrations of pregabalin from 20 subjects were determined by using a validated liquid chromatography with tandem mass spectrometry (LC-MS/MS) detection method. Pharmacokinetic parameters assessed in this study were: area under the plasma concentration-time curve from time zero to last observed quantifiable concentration (AUC0-t), area under the plasma concentration-time curve from time zero to infinity (AUC0-∞), maximum plasma concentration (Cmax), time to maximum plasma concentration (tmax), and terminal half-life (t1/2). The 90% confidence intervals (CIs) for the geometric mean ratios of test formulation/reference formulation were calculated for the AUC and Cmax parameters; while tmax difference was analyzed nonparametrically on the original data using the Wilcoxon matched-pairs test, and t1/2 difference was analyzed using Student's paired t-test. RESULTS: The mean (standard deviation [SD]) AUC0-t, AUC0-∞, Cmax, and t1/2 of pregabalin from the test formulation were 27,845.86 (4,508.27) ng · h/mL, 28,311.70 (4,790.55) ng · h/mL, 3,999.71 (801.52) ng/mL, and 5.66 (1.20) hours, respectively; while the mean (SD) AUC0-t, AUC0-∞,Cmax, and t1/2 of pregabalin from the reference formulation were 27,398.12 (4,266.28) ng · h/mL, 27,904.24 (4,507.31) ng · h/mL, 3,849.50 (814.50) ng/mL, and 5.87 (1.25) hours, respectively. The median (range) tmax of pregabalin from the test formulation and reference formulation was 1.00 (0.67-2.00) hours and 1.00 (0.67-3.00) hours, respectively. The 90% CIs for the geometric mean ratios of test formulation/reference formulation for pregabalin were 101.54% (98.75%-104.41%) for AUC0-t, 101.35% (98.66%-104.11%) for AUC0-∞, and 104.19% (98.75%-109.93%) for Cmax. CONCLUSION: The study concluded that the two formulations of pregabalin capsules studied were bioequivalent.