Bayesian Adaptive Designs for Early Phase Clinical Trials

My dissertation focuses mainly on Bayesian adaptive designs for phase I and phase II clinical trials. It includes three specific topics: (1) proposing a novel two-dimensional dose-finding algorithm for biological agents, (2) developing Bayesian adaptive screening designs to provide more efficient and ethical clinical trials, and (3) incorporating missing late-onset responses to make an early stopping decision. Treating patients with novel biological agents is becoming a leading trend in oncology. Unlike cytotoxic agents, for which toxicity and efficacy monotonically increase with dose, biological agents may exhibit non-monotonic patterns in their dose-response relationships. Using a trial with two biological agents as an example, we propose a phase I/II trial design to identify the biologically optimal dose combination (BODC), which is defined as the dose combination of the two agents with the highest efficacy and tolerable toxicity. A change-point model is used to reflect the fact that the dose-toxicity surface of the combinational agents may plateau at higher dose levels, and a flexible logistic model is proposed to accommodate the possible non-monotonic pattern for the dose-efficacy relationship. During the trial, we continuously update the posterior estimates of toxicity and efficacy and assign patients to the most appropriate dose combination. We propose a novel dose-finding algorithm to encourage sufficient exploration of untried dose combinations in the two-dimensional space. Extensive simulation studies show that the proposed design has desirable operating characteristics in identifying the BODC under various patterns of dose-toxicity and dose-efficacy relationships. Trials of combination therapies for the treatment of cancer are playing an increasingly important role in the battle against this disease. To more efficiently handle the large number of combination therapies that must be tested, we propose a novel Bayesian phase II adaptive screening design to simultaneously select among possible treatment combinations involving multiple agents. Our design is based on formulating the selection procedure as a Bayesian hypothesis testing problem in which the superiority of each treatment combination is equated to a single hypothesis. During the trial conduct, we use the current values of the posterior probabilities of all hypotheses to adaptively allocate patients to treatment combinations. Simulation studies show that the proposed design substantially outperforms the conventional multi-arm balanced factorial trial design. The proposed design yields a significantly higher probability for selecting the best treatment while at the same time allocating substantially more patients to efficacious treatments. The proposed design is most appropriate for the trials combining multiple agents and screening out the efficacious combination to be further investigated. The proposed Bayesian adaptive phase II screening design substantially outperformed the conventional complete factorial design. Our design allocates more patients to better treatments while at the same time providing higher power to identify the best treatment at the end of the trial. Phase II trial studies usually are single-arm trials which are conducted to test the efficacy of experimental agents and decide whether agents are promising to be sent to phase III trials. Interim monitoring is employed to stop the trial early for futility to avoid assigning unacceptable number of patients to inferior treatments. We propose a Bayesian single-arm phase II design with continuous monitoring for estimating the response rate of the experimental drug. To address the issue of late-onset responses, we use a piece-wise exponential model to estimate the hazard function of time to response data and handle the missing responses using the multiple imputation approach. We evaluate the operating characteristics of the proposed method through extensive simulation studies. We show that the proposed method reduces the total length of the trial duration and yields desirable operating characteristics for different physician-specified lower bounds of response rate with different true response rates

Concordane of OSTA and lumbar spine BMD by DXA in identifying risk of osteoporosis

OBJECTIVE: To investigate the accuracy of Osteoporosis Self-assessment Tool for Asians (OSTA) in identifying the risk of osteoporosis in postmenopausal women. To validate use of OSTA risk index by comparing it with the bone mineral density (BMD) of lumbar spine measured by dual energy X-ray absorptiometry (DXA). METHODS: The data of lumbar spine BMD (LS BMD) measurements by DXA of 218 postmenopausal women of Han nationality in Sichuan province were compared with OSTA risk index. The concordance of OSTA and LS BMD were calculated and analyzed by fourfold table and receiver operating characteristic (ROC) curve. RESULTS: The prevalence of osteoporosis in these women was 40.4% and 61.5%, with the LS BMD T score cutoffs -2.5 and -2.0, respectively. The sensitivity, specificity, and accuracy of OSTA risk index compared with T score cutoff -2.5 of LS BMD were 59.1%, 56.9% and 57.8%, respectively, while they were 57.5%, 63.1%, 59.6% by T score cutoff -2.0. CONCLUSION: For identifying risk of osteoporosis, the concurrence was lower than those reported studies when comparing LS BMD measurements to OSTA risk index in Chinese Han nationality postmenopausal women of Sichuan province. Physicians should identify women who need BMD measurement according to more factors rather than age and body weight

Oscillatory electrostatic potential on graphene induced by group IV element decoration

The structures and electronic properties of partial C, Si and Ge decorated graphene were investigated by first-principles calculations. The calculations show that the interaction between graphene and the decoration patches is weak and the semiconductor patches act as agents for weak electron doping without much disturbing graphene electronic π-bands. Redistribution of electrons due to the partial decoration causes the electrostatic potential lower in the decorated graphene areas, thus induced an electric field across the boundary between the decorated and non-decorated domains. Such an alternating electric field can change normal stochastic adatom diffusion to biased diffusion, leading to selective mass transport

World-Wide Efficacy of Bone Marrow Derived Mesenchymal Stromal Cells in Preclinical Ischemic Stroke Models: Systematic Review and Meta-Analysis

Background: Following extensive, positive results in pre-clinical experiments, Bone Marrow Derived-Mesenchymal Stromal Cells (BM-MSCs) are now being tested as a novel therapy for ischemic stroke in ongoing clinical trials. However, multiple critical questions relating to their translational application remain to be clarified. We performed a comprehensive, systematic review and meta-analysis of pre-clinical studies to evaluate the efficacy of BM-MSCs on functional outcomes after ischemic stroke, as well as the independent role of translational factors on their effect size.Methods: We systematically reviewed the literature and identified articles using BM-MSCs in animal models of focal ischemic stroke. After abstraction of all relevant data, we performed a meta-analysis to estimate the combined effect size of behavioral endpoints after BM-MSC administration. To describe the effect size across many behavioral outcomes, we divided these outcomes into four categories: (1) Composite scores, (2) Motor Tests, (3) Sensorimotor Tests, and (4) Cognitive Tests. We also performed a meta-regression analysis for measuring the effect of individual characteristics of BM-MSC administration on the effect size.Results: Our results from 141 articles indicate a significant beneficial effect on composite, motor, and sensorimotor outcomes after treatment with BM-MSCs compared to control groups. We found no major differences in treatment effect based on delivery route, dose, fresh vs. frozen preparation, or passage number. There were no consistent findings supporting a difference in treatment effect based on time windows from acute periods (0–6 h) vs. later windows (2–7 days). Furthermore, these positive treatment effects on functional outcome were consistent across different labs in different parts of the world as well as over the last 18 years. There was a negative correlation between publication year and impact factor.Conclusions: Our results show worldwide efficacy of BM-MSCs in improving functional outcomes in pre-clinical animal models of stroke and support testing these cells in clinical trials in various ranges of time windows using different delivery routes. The continued growing number of publications showing functional benefit of BM-MSCs are now adding limited value to an oversaturated literature spanning 18 years. Researchers should focus on identifying definitive mechanisms on how BM-MSCs lead to benefit in stroke models

Long intergenic non-coding RNA expression signature in human breast cancer

Breast cancer is a complex disease, characterized by gene deregulation. There is less systematic investigation of the capacity of long intergenic non-coding RNAs (lincRNAs) as biomarkers associated with breast cancer pathogenesis or several clinicopathological variables including receptor status and patient survival. We designed a two-stage study, including 1,000 breast tumor RNA-seq data from The Cancer Genome Atlas (TCGA) as the discovery stage, and RNA-seq data of matched tumor and adjacent normal tissue from 50 breast cancer patients as well as 23 normal breast tissue from healthy women as the replication stage. We identified 83 lincRNAs showing the significant expression changes in breast tumors with a false discovery rate (FDR) < 1% in the discovery dataset. Thirty-seven out of the 83 were validated in the replication dataset. Integrative genomic analyses suggested that the aberrant expression of these 37 lincRNAs was probably related with the expression alteration of several transcription factors (TFs). We observed a differential co-expression pattern between lincRNAs and their neighboring genes. We found that the expression levels of one lincRNA (RP5-1198O20 with Ensembl ID ENSG00000230615) were associated with breast cancer survival with P < 0.05. Our study identifies a set of aberrantly expressed lincRNAs in breast cancer

Endovascular Thrombectomy for Mild Strokes: How Low Should We Go? A Multicenter Cohort Study

Background and Purpose:Endovascular thrombectomy (EVT) is effective for acute ischemic stroke with large vessel occlusion (LVO) and NIHSS ≥6. However, EVT benefit for mild deficits LVOs (NIHSS Methods: A retrospective cohort of patients with anterior circulation LVO and NIHSSoutcome; mRS=0–2 was the secondary. Symptomatic intracerebral hemorrhage (sICH) was the safety outcome. Clinical outcomes were compared through a multivariable logistic regression after adjusting for age, presentation NIHSS, time-last-seen-normal-to-presentation, center, IV-alteplase, ASPECTS, and thrombus location. We then performed propensity score matching as a sensitivity analysis. Results were also stratified by thrombus location. Results: 214 patients (EVT-124, medical management-90) were included from 8 US and Spain centers between January/2012 and March/2017. The groups were similar in age, ASPECTS, IValteplase rate and time-last-seen-normal-to-presentation. There was no difference in mRS=0–1 between EVT and medical management (55.7% versus 54.4%, respectively, aOR=1.3, 95%CI=0.64–2.64, p=0.47). Similar results were seen for mRS=0–2 (63.3% EVT versus 67.8% medical management, aOR=0.9, 95%CI=0.43–1.88, p=0.77). In a propensity matching analysis, there was no treatment effect in 62 matched pairs (53.5%EVT, 48.4% medical management; OR=1.17, 95%CI=0.54–2.52, p=0.69). There was no statistically significant difference when stratified by any thrombus location; M1 approached significance (p=0.07). sICH rates were higher with thrombectomy (5.8% EVT versus 0% medical management, p=0.02). Conclusions: Our retrospective multicenter cohort study showed no improvement in excellent and independent functional outcomes in mild strokes (NIHS

Biodiversity Soup II: A bulk-sample metabarcoding pipeline emphasizing error reduction

Despite widespread recognition of its great promise to aid decision-making in environmental management, the applied use of metabarcoding requires improvements to reduce the multiple errors that arise during PCR amplification, sequencing and library generation. We present a co-designed wet-lab and bioinformatic workflow for metabarcoding bulk samples that removes both false-positive (tag jumps, chimeras, erroneous sequences) and false-negative ('dropout') errors. However, we find that it is not possible to recover relative-abundance information from amplicon data, due to persistent species-specific biases. To present and validate our workflow, we created eight mock arthropod soups, all containing the same 248 arthropod morphospecies but differing in absolute and relative DNA concentrations, and we ran them under five different PCR conditions. Our pipeline includes qPCR-optimized PCR annealing temperature and cycle number, twin-tagging, multiple independent PCR replicates per sample, and negative and positive controls. In the bioinformatic portion, we introduce Begum, which is a new version of DAMe (Zepeda-Mendoza et al., 2016. BMC Res. Notes 9:255) that ignores heterogeneity spacers, allows primer mismatches when demultiplexing samples and is more efficient. Like DAMe, Begum removes tag-jumped reads and removes sequence errors by keeping only sequences that appear in more than one PCR above a minimum copy number per PCR. The filtering thresholds are user-configurable. We report that OTU dropout frequency and taxonomic amplification bias are both reduced by using a PCR annealing temperature and cycle number on the low ends of the ranges currently used for the Leray-FolDegenRev primers. We also report that tag jumps and erroneous sequences can be nearly eliminated with Begum filtering, at the cost of only a small rise in dropouts. We replicate published findings that uneven size distribution of input biomasses leads to greater dropout frequency and that OTU size is a poor predictor of species input biomass. Finally, we find no evidence for 'tag-biased' PCR amplification. To aid learning, reproducibility, and the design and testing of alternative metabarcoding pipelines, we provide our Illumina and input-species sequence datasets, scripts, a spreadsheet for designing primer tags and a tutorial