Gel Stent Versus Trabeculectomy: The Randomized, Multicenter, Gold-Standard Pathway Study (GPS) of Effectiveness and Safety at 12 Months.

Purpose: To compare effectiveness and safety of the gel stent to trabeculectomy in open-angle glaucoma (OAG).

Design: Prospective, randomized, multicenter, noninferiority study.

Methods: Patients with OAG and intraocular pressure (IOP) 15 to 44 mm Hg on topical IOP-lowering medication were randomized 2:1 to gel stent implantation or trabeculectomy.

A novel prognostic biomarker CD3G that correlates with the tumor microenvironment in cervical cancer.

Cervical cancer (CESC) is the fourth most common and death-causing gynecological cancer, mostly induced by infection of human papillomavirus (HPV). Multiple components of the tumor microenvironment (TME), such as tumor infiltrating immune cells, could be targets of immunotherapy for HPV-related CESC. However, little is known about the TME of CESC until now.

Engineering of Neutrophil Membrane Camouflaging Nanoparticles Realizes Targeted Drug Delivery for Amplified Antitumor Therapy.

Purpose: Although the neutrophil membrane (NM)-based nanoparticulate delivery system has exhibited rapid advances in tumor targeting stemmed from the inherited instinct, the antitumor effect requires further improvement due to inefficient cellular internalization in the absence of specific interactions between NM-coated nanoparticles and tumor cells.

Methods: Herein, we fabricated drug-paclitaxel loaded NM camouflaging nanoparticles (TNM-PN) modified with tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), favorable for the cellular internalization.

Results: The results showed that TNM-PN exerted a significant cytotoxicity to tumor cells by TRAIL-mediated endocytosis and strong adhesion to inflamed endothelial cells in vitro.

Bayesian Two-stage Biomarker-based Adaptive Design for Targeted Therapy Development.

We propose a Bayesian two-stage biomarker-based adaptive randomization (AR) design for the development of targeted agents. The design has three main goals: (1) to test the treatment efficacy, (2) to identify prognostic and predictive markers for the targeted agents, and (3) to provide better treatment for patients enrolled in the trial. To treat patients better, both stages are guided by the Bayesian AR based on the individual patient's biomarker profiles.

Bayesian two-step Lasso strategy for biomarker selection in personalized medicine development for time-to-event endpoints.

Clinical trial designs for targeted therapy development are progressing toward the goal of personalized medicine. Motivated by the need of ongoing efforts to develop targeted agents for lung cancer patients, we propose a Bayesian two-step Lasso procedure for biomarker selection under the proportional hazards model. We seek to identify the key markers that are either prognostic or predictive with respect to treatment from a large number of biomarkers.

A five-gene and corresponding protein signature for stage-I lung adenocarcinoma prognosis.

Purpose: Identification of effective markers for outcome is expected to improve the clinical management of non-small cell lung cancer (NSCLC). Here, we assessed in NSCLC the prognostic efficacy of genes, which we had previously found to be differentially expressed in an in vitro model of human lung carcinogenesis.

Experimental Design: Prediction algorithms and risk-score models were applied to the expression of the genes in publicly available NSCLC expression data sets.

Reconstructive strategies for partial sacrectomy defects based on surgical outcomes.

Background: Partial sacrectomy creates heterogeneous defects amenable to a wide variety of reconstructive techniques. Important factors to guide the choice of reconstruction technique have not been elucidated. The purpose of this study was to determine what factors best guide selection of reconstructive techniques following partial sacrectomy to optimize outcomes.

Bayesian adaptive randomization designs for targeted agent development.

Background: With better understanding of the disease's etiology and mechanism, many targeted agents are being developed to tackle the root cause of problems, hoping to offer more effective and less toxic therapies. Targeted agents, however, do not work for everyone. Hence, the development of target agents requires the evaluation of prognostic and predictive markers.

A simulation study for comparing testing statistics in response-adaptive randomization.

Background: Response-adaptive randomizations are able to assign more patients in a comparative clinical trial to the tentatively better treatment. However, due to the adaptation in patient allocation, the samples to be compared are no longer independent. At large sample sizes, many asymptotic properties of test statistics derived for independent sample comparison are still applicable in adaptive randomization provided that the patient allocation ratio converges to an appropriate target asymptotically.

Identification of gene signatures and molecular markers for human lung cancer prognosis using an in vitro lung carcinogenesis system.

Lung cancer continues to be a major deadly malignancy. The mortality of this disease could be reduced by improving the ability to predict cancer patients' survival. We hypothesized that genes differentially expressed among cells constituting an in vitro human lung carcinogenesis model consisting of normal, immortalized, transformed, and tumorigenic bronchial epithelial cells are relevant to the clinical outcome of non-small cell lung cancer (NSCLC).