Generalized Likelihood Ratios for Designing Dose Optimization Studies of Targeted Therapies

Dose optimization studies of new therapeutic agents aim to identify one or more promising doses for further evaluation in subsequent studies. Traditionally, dose optimization has focused on finding the maximum tolerated dose (MTD), assuming that drug activity and efficacy generally increase with increasing dose. For modern targeted agents, the dose-activity relationship is often non-monotone and such that activity starts to plateau or even decline before reaching the MTD. Finding the optimal biological dose (OBD) for a targeted agent requires considering both toxicity and activity in dose optimization. This article proposes a new design for finding the OBD that utilizes generalized likelihood ratios (GLRs) to measure statistical evidence regarding key scientific questions on toxicity and activity. This GLR-based design requires no parametric modeling assumptions and only assumes that the dose-toxicity relationship is monotone and that the dose-activity relationship follows a two-sided isotonic regression model. Compared with existing designs that operate under similar assumptions, the GLR-based design is more general and more flexible, and performs competitively in simulation experiments where drug activity starts to plateau or decline before reaching the MTD.</p

DataSheet_1_Role of ocean circulation and settling of particulate organic matter in the decoupling between the oxygen minimum zone and the phytoplankton productive zone in the Arabian Sea: A modeling study.docx

The oxygen minimum zone has a significant effect on primary production, marine biodiversity, food web structure, and marine biogeochemical cycle. The Arabian Sea oxygen minimum zone (ASOMZ) is one of the largest and most extreme oxygen minimum zones in the world, with a positional decoupling from the region of phytoplankton blooms. The core of the ASOMZ is located to the east of the high primary production region in the western Arabian Sea. In this study, a coupled physical–biogeochemical numerical model was used to quantify the impact of ocean circulation and settling of particulate organic matters (POMs) on the decoupling of the ASOMZ. Model results demonstrate that the increased (decreased) dissolved oxygen replenishment in the western (central) Arabian Sea is responsible for decoupling. The oxygen-rich intermediate water (200–1,000 m) from the southern Arabian Sea enters the Arabian Sea along the west coast and hardly reaches the central Arabian Sea, resulting in a significant oxygen replenishment in the western Arabian Sea high-productivity region (Gulf of Aden) but only a minor contribution in the central Arabian Sea. Besides that, the POMs that are remineralized to consume central Arabian Sea dissolved oxygen comprises not only local productivity in winter bloom but also the transport from the western Arabian Sea high-productivity region (Oman coast) in summer bloom. More dissolved oxygen replenishment in the western Arabian Sea, and higher dissolved oxygen consumption and fewer dissolved oxygen replenishment in the central Arabian Sea could contribute to the decoupling of the ASOMZ and phytoplankton productive zone.</p

An Instrumental Variable Approach to Learning the Causal Exposure–Response Relationship in a Randomized Dose Comparison Trial

We consider the problem of estimating the causal effect of drug exposure on clinical response in a randomized dose comparison trial where each group receives a different dose. Because exposure is not randomized, the exposure–response relationship is subject to confounding in this setting. Conventional statistical methods for confounding adjustment with a continuous exposure typically assume that there are no unmeasured confounders. This article provides an instrumental variable approach that does not require the assumption of no unmeasured confounders. Specifically, we use randomized dose assignment as an instrumental variable and characterize the causal exposure–response relationship using a control variable under a mild monotonicity assumption on individual dose–exposure profiles. Based on this characterization, we derive partial identification bounds for the causal exposure–response relationship, which are model-free but may be too wide to be useful in practice. For practicality, we further develop a simple estimation method based on a regression model for the mean response conditional on exposure and the control variable. Simulation results show that, in the presence of unmeasured confounding, the model-based estimation method reduces estimation bias effectively at the expense of increased variability, as compared to existing methods. The method is illustrated with real data from a study of chimeric antigen receptor T cell therapy for treating chronic lymphocytic leukemia.</p

Co₃O₄/Carbon Aerogel Hybrids as Anode Materials for Lithium-Ion Batteries with Enhanced Electrochemical Properties

A facile hydrothermal and sol–gel polymerization route was developed for large-scale fabrication of well-designed Co₃O₄ nanoparticles anchored carbon aerogel (CA) architecture hybrids as anode materials for lithium-ion batteries with improved electrochemical properties. The three-dimensional (3D) mesoporous Co₃O₄/CA hierarchical hybrids display an improved lithium storage performance and cycling stability, because of the intimate integration and strong synergistic effects between the Co₃O₄ nanoparticles and CA matrices. Such an interconnected Co₃O₄/CA hierarchical hybrid can effectively utilize the good conductivity, large surface area, 3D interconnected mesoporous structure, mechanical flexibility, chemical stability, and the short length of Li-ion transport of the CA matrix. The incorporation of Co₃O₄ nanoparticles into the interconnected CA matrix effectively reduces the number of active sites of Co₃O₄/CA hybrids, thus greatly increasing the reversible specific capacity and the initial Coulombic efficiency of the hybrids. The Co₃O₄/CA hybrid material displays the best lithium storage performance and good cycling stability as the Co₃O₄ loading content is up to 25 wt %, retains a Coulombic efficiency of 99.5% and a specific discharge capacity of 779 mAh g^–1 after 50 cycles, 10.1 and 1.6 times larger than the specific discharge capacity of 73 mAh g^–1 and 478 mAh g^–1 for Co₃O₄ and CA samples, respectively. The hierarchical hybrid nanostructures with enhanced electrochemical activities using a CA matrix framework can find potential applications in the related conversion reaction electrodes

Joint Modeling of Transitional Patterns of Alzheimer's Disease

<div><p>While the experimental Alzheimer's drugs recently developed by pharmaceutical companies failed to stop the progression of Alzheimer's disease, clinicians strive to seek clues on how the patients would be when they visit back next year, based upon the patients' current clinical and neuropathologic diagnosis results. This is related to how to precisely identify the transitional patterns of Alzheimer's disease. Due to the complexities of the diagnosis of Alzheimer's disease, the condition of the disease is usually characterized by multiple clinical and neuropathologic measurements, including Clinical Dementia Rating (CDRGLOB), Mini-Mental State Examination (MMSE), a score derived from the clinician judgement on neuropsychological tests (COGSTAT), and Functional Activities Questionnaire (FAQ). In this research article, we investigate a class of novel joint random-effects transition models that are used to simultaneously analyze the transitional patterns of multiple primary measurements of Alzheimer's disease and, at the same time, account for the association between the measurements. The proposed methodology can avoid the bias introduced by ignoring the correlation between primary measurements and can predict subject-specific transitional patterns.</p></div

The estimated transition probability matrix of binary cognitive status measured by MMSE in Alzheimer's disease patients at the age of 55 or 85 and carrying no, one, or two APOE- 4 alleles.

<p>The estimated transition probability matrix of binary cognitive status measured by MMSE in Alzheimer's disease patients at the age of 55 or 85 and carrying no, one, or two APOE- 4 alleles.</p

A Case Study in Personalized Medicine: Rilpivirine Versus Efavirenz for Treatment-Naive HIV Patients

<p>Rilpivirine and efavirenz are two major nonnucleoside reverse transcriptase inhibitors currently available in the U.S. for treatment-naive adult patients infected with human immunodeficiency virus (HIV). Two randomized clinical trials comparing the two drugs suggested that their relative efficacy may depend on baseline viral load and CD4 cell count. This article is concerned with the potential utilities of these biomarkers in developing individualized treatment regimes that attempt to maximize the virologic response rate or the median of a composite outcome that combines virologic response with change in CD4 cell count (dCD4). Working with the median composite outcome removes the need to assign numerical values to the composite outcome, as would be necessary if we were to maximize its mean, and reduces the influence of extreme dCD4 values. To estimate the target quantities for a given treatment regime, we use G-computation, inverse probability weighting (IPW), and augmented IPW methods to deal with censoring and missing data under a monotone coarsening framework. The resulting estimates form the basis for optimization in a class of candidate regimes indexed by a small number of parameters. A cross-validation procedure is used to remove the resubstitution bias in evaluating an optimized treatment regime. Application of these methods to the HIV trial data yields candidate regimes of different forms together with cross-validated performance measure estimates, which suggest that optimized treatment regimes may be able to improve virologic response (but not the composite outcome) over uniform regimes that prescribe one drug for all patients. Supplementary materials for this article are available online.</p

The Alzheimer's disease data: Sample means of four responses in each group presented by age, years of education and the number of copies APOE- 4.

<p>The Alzheimer's disease data: Sample means of four responses in each group presented by age, years of education and the number of copies APOE- 4.</p

Analysis results of the Uniform Data Set in the National Alzheimer's Coordinating Center (three measurements): parameter estimates, sandwich estimators of variance (standard deviations) and covariance, and the -values of Wald tests.

<p>(The increment parameters are defined as: , ; ; ; ).</p

Analysis results of the Uniform Data Set in the National Alzheimer's Coordinating Center (four measurements): parameter estimates, sandwich estimators of variance (standard deviations) and covariance, and the -values of Wald tests.

<p>(The increment parameters are defined as: , ; ; ; ).</p