AMG 145, a monoclonal antibody against PCSK9, facilitates achievement of national cholesterol education program-adult treatment panel III low-density lipoprotein cholesterol goals among high-risk patients: an analysis from the LAPLACE-TIMI 57 trial (LDL-C assessment with PCSK9 monoclonal antibody inhibition combined with statin thErapy-thrombolysis in myocardial infarction 57).

OBJECTIVES: This study sought to define the ability of AMG 145, a monoclonal antibody directed against proprotein convertase subtilisin kexin type 9 (PCSK9), to enable subjects at high risk for major adverse cardiovascular events to achieve National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATP III) parameters for low-density lipoprotein cholesterol (LDL-C) and other lipid goals. BACKGROUND: Many patients at high risk for adverse cardiovascular events are unable to achieve the NCEP-ATP III LDL-C goal of <70 mg/dl, even with high-potency statin therapy. METHODS: In 282 subjects from the LAPLACE-TIMI 57 (LDL-C Assessment with PCSK9 monoclonaL Antibody Inhibition Combined With Statin thErapy-Thrombolysis In Myocardial Infarction 57) trial at high risk according to NCEP-ATP III criteria, we compared the proportion of subjects achieving the NCEP-ATP III recommended LDL-C goal of <70 mg/dl across treatment arms. Other outcomes included the triple goals of LDL-C <70 mg/dl, non-high-density lipoprotein cholesterol (HDL-C) <100 mg/dl, and apolipoprotein B (ApoB) <80 mg/dl. RESULTS: During the dosing interval, more than 90% of subjects in both of the top dose groups every 2 weeks and every 4 weeks attained this lipid target over the dosing interval, with similar success rates for the triple lipid goal. CONCLUSIONS: PCSK9 inhibition with AMG 145 enables high-risk patients to achieve established lipid goals. If this therapy demonstrates efficacy for reducing cardiovascular events with a favorable safety profile in ongoing phase 3 trials, we believe it will have major public health implications.

Assessment of Alzheimer's disease risk with functional magnetic resonance imaging: an arterial spin labeling study.

Functional magnetic resonance imaging (fMRI) of older adults at risk for Alzheimer's disease (AD) by virtue of their cognitive (i.e., mild cognitive impairment [MCI]) and/or genetic (i.e., apolipoprotein E [APOE] ε4 allele) status demonstrate divergent brain response patterns during memory encoding across studies. Using arterial spin labeling MRI, we examined the influence of AD risk on resting cerebral blood flow (CBF) as well as the CBF and blood oxygenation level dependent (BOLD) signal response to memory encoding in the medial temporal lobes (MTL) in 45 older adults (29 cognitively normal [14 APOE ε4 carriers and 15 noncarriers]; 16 MCI [8 APOE ε4 carriers, 8 noncarriers]). Risk groups were comparable in terms of mean age, years of education, gender distribution, and vascular risk burden. Individuals at genetic risk for AD by virtue of the APOE ε4 allele demonstrated increased MTL resting state CBF relative to ε4 noncarriers, whereas individuals characterized as MCI showed decreased MTL resting state CBF relative to their cognitively normal peers. For percent change CBF, there was a trend toward a cognitive status by genotype interaction. In the cognitively normal group, there was no difference in percent change CBF based on APOE genotype. In contrast, in the MCI group, APOE ε4 carriers demonstrated significantly greater percent change in CBF relative to ε4 noncarriers. No group differences were found for BOLD response. Findings suggest that abnormal resting state CBF and CBF response to memory encoding may be early indicators of brain dysfunction in individuals at risk for developing AD.

Bayesian meta-experimental design: evaluating cardiovascular risk in new antidiabetic therapies to treat type 2 diabetes.

Recent guidance from the Food and Drug Administration for the evaluation of new therapies in the treatment of type 2 diabetes (T2DM) calls for a program-wide meta-analysis of cardiovascular (CV) outcomes. In this context, we develop a new Bayesian meta-analysis approach using survival regression models to assess whether the size of a clinical development program is adequate to evaluate a particular safety endpoint. We propose a Bayesian sample size determination methodology for meta-analysis clinical trial design with a focus on controlling the type I error and power. We also propose the partial borrowing power prior to incorporate the historical survival meta data into the statistical design. Various properties of the proposed methodology are examined and an efficient Markov chain Monte Carlo sampling algorithm is developed to sample from the posterior distributions. In addition, we develop a simulation-based algorithm for computing various quantities, such as the power and the type I error in the Bayesian meta-analysis trial design. The proposed methodology is applied to the design of a phase 2/3 development program including a noninferiority clinical trial for CV risk assessment in T2DM studies.