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A major emphasis in precision medicine is to optimally treat subgroups of patients who may benefit from certain therapeutic agents. And as such, enormous resources and innovative clinical trials designs in oncology are devoted to identifying predictive biomarkers. Predictive biomarkers are ones that will identify patients that are more likely to respond to specific therapies and they are usually discovered through retrospective analysis from large randomized phase II or phase III trials. One important design to consider is the stratified biomarker design, where patients will have their specimens obtained at baseline and the biomarker status will be assessed prior to random assignment. Regardless of their biomarker status, patients will be randomized to either an experimental arm or the standard of care arm. The stratified biomarker design can be used to test for a treatment-biomarker interaction in predicting a time-to event outcome. Many biomarkers, however, are derived from tissues from patients, and their levels may be heterogeneous. As a result, biomarker levels may be measured with error and this would have an adverse impact on the power of a stratified biomarker clinical trial. We present a trial design and an analysis framework for the stratified biomarker design. We show that the naïve test is biased and provide bias-corrected estimators for computing the sample size and the 95% confidence interval when testing for a treatment-biomarker interaction in predicting a time to event outcome. We propose a sample size formula that adjusts for misclassification and apply it in the design of a phase III clinical trial in renal cancer. [ABSTRACT FROM AUTHOR]

Regulatory agencies typically evaluate the efficacy and safety of new interventions and grant commercial approval based on randomized controlled trials (RCTs). Other major healthcare stakeholders, such as insurance companies and health technology assessment agencies, while basing initial access and reimbursement decisions on RCT results, are also keenly interested in whether results observed in idealized trial settings will translate into comparable outcomes in real world settings—that is, into so‐called "real world" effectiveness. Unfortunately, evidence of real world effectiveness for new interventions is not available at the time of initial approval. To bridge this gap, statistical methods are available to extend the estimated treatment effect observed in a RCT to a target population. The generalization is done by weighting the subjects who participated in a RCT so that the weighted trial population resembles a target population. We evaluate a variety of alternative estimation and weight construction procedures using both simulations and a real world data example using two clinical trials of an investigational intervention for Alzheimer's disease. Our results suggest an optimal approach to estimation depends on the characteristics of source and target populations, including degree of selection bias and treatment effect heterogeneity. [ABSTRACT FROM AUTHOR]

Confocal endoscopy has been widely used to obtain fine optically sectioned images. However, confocal endomicroscopic images are formed by point‐by‐point scanning in both lateral and axial directions, which results in long image acquisition time. Here, an endomicroscope with telecentric configuration is presented to achieve nonmechanical and rapid axial scanning for volumetric fluorescence imaging. In our system, optical sectioning in wide‐field fashion is obtained through HiLo imaging with a digital micromirror device. Axial scanning, without mechanical moving parts, is conducted by digital focus adjustment using an electrically tunable lens, offering constant magnification and contrast. We demonstrate imaging performance of our system with optically sectioned images using fluorescently labeled beads, as well as ex vivo mice cardiac tissue samples. Our system provides multiple advantages, in terms of improved scanning range, and reduced image acquisition time, which shows great potentials for three‐dimensional biopsies of volumetric biological samples. [ABSTRACT FROM AUTHOR]

Prognosis plays a pivotal role in patient management and trial design. A useful prognostic model should correctly identify important risk factors and estimate their effects. In this article, we discuss several challenges in selecting prognostic factors and estimating their effects using the Cox proportional hazards model. Although a flexible semiparametric form, the Cox's model is not entirely exempt from model misspecification. To minimize possible misspecification, instead of imposing traditional linear assumption, flexible modeling techniques have been proposed to accommodate the nonlinear effect. We first review several existing nonparametric estimation and selection procedures and then present a numerical study to compare the performance between parametric and nonparametric procedures. We demonstrate the impact of model misspecification on variable selection and model prediction using a simulation study and an example from a phase III trial in prostate cancer. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

ABSTRACT This study provides an appropriate analytical approach using stated preference analysis and the contingent valuation method to investigate consumers' willingness to pay a premium for genetically modified ( GM) foods together with their prior purchase intentions. Although most analyses treat consumers' attitudes and willingness to pay as separate issues, we introduce the idea of prior purchase intention to analyze these two issues as a whole. To achieve this purpose, a modeling technique invoking the multinomial logistic model and the accelerated failure time model is presented. Based on the data collected from an essential double-bounded design, our empirical results suggest that Taiwanese consumers are willing to pay a premium of about 11 NT dollars (7% of the given average market price of 150 NT dollars for the non- GM salmon) to avoid GM-soybean-fed salmon. In addition, the results of this study provide evidence that our stated-preference double-bounded design has a better-off statistical efficiency than the single-bounded one. [ABSTRACT FROM AUTHOR]

Optical sectioning endoscopy such as confocal endoscopy offers capabilities to obtain three‐dimensional (3D) information from various biological samples by discriminating between the desired in‐focus signals and out‐of‐focus background. However, in general confocal images are formed through point‐by‐point scanning and the scanning time is proportional to the 3D space‐bandwidth product. Recently, structured illumination endoscopy has been utilized for optically sectioned wide‐field imaging, but it still needs axial scanning to acquire images from different depths of focal plane. Here, we report wide‐field, multiplane, optical sectioning endoscopic imaging, incorporating 3D active speckle‐based illumination and multiplexed volume holographic gratings, to simultaneously obtain images of fluorescently labeled tissue structures from different depths, without the need of scanning. We present the design, and implementation, as well as experimental data, demonstrating this endoscopic system's ability to obtain optically sectioned multiplane fluorescent images of tissue samples, with cellular level resolution in wide‐field fashion, and no need for mechanical or optical axial scanning.(A) Schematic drawing of the SIHN endoscopy to simultaneously acquire multiplane images from different depths. (B) Uniform, and (C) SIHN illuminated images of standard fluorescence beads (25 μm in diameter) for the two axial planes. (D) Intensity profile on fluorescently labeled signal (ie, in‐focus) and background (ie, out‐of‐focus) of microspheres. To obtain wide field, multiplane, optical sectioning endoscopic imaging, we proposed speckle holographic illumination non‐scanning endoscopy by utilizing speckle‐based structured illumination and multiplexed volume holographic gratings into endoscopic system. Compared to confocal endoscopy, our system obtains three‐dimensional images from different depths simultaneously, and only needs two shots for each optical sectioning imaging without point‐by‐point scanning and mechanical moving part. [ABSTRACT FROM AUTHOR]