Performance evaluation in Bayesian adaptive randomization

Bayesian adaptive randomization (BAR) is an attractive approach to allocate more patients to the putatively superior arm based on the interim data while maintains good statistical properties attributed to randomization. Under this approach, patients are adaptively assigned to a treatment group based on the probability that the treatment is better. The basic randomization scheme can be modified by introducing a tuning parameter, replacing the posterior estimated response probability, setting a boundary to randomization probabilities. Under randomization settings comprised of the above modifications, operating characteristics, including type I error, power, sample size, imbalance of sample size, interim success rate, and overall success rate, were evaluated through simulation. All randomization settings have low and comparable type I errors. Increasing tuning parameter decreases power, but increases imbalance of sample size and interim success rate. Compared with settings using the posterior probability, settings using the estimated response rates have higher power and overall success rate, but less imbalance of sample size and lower interim success rate. Bounded settings have higher power but less imbalance of sample size than unbounded settings. All settings have better performance in the Bayesian design than in the frequentist design. This simulation study provided practical guidance on the choice of how to implement the adaptive design. ^

Apply response adaptive randomization to group sequential with early stopping

Group sequential methods and response adaptive randomization (RAR) procedures have been applied in clinical trials due to economical and ethical considerations. Group sequential methods are able to reduce the average sample size by inducing early stopping, but patients are equally allocated with half of chance to inferior arm. RAR procedures incline to allocate more patients to better arm; however it requires more sample size to obtain a certain power. This study intended to combine these two procedures. We applied the Bayesian decision theory approach to define our group sequential stopping rules and evaluated the operating characteristics under RAR setting. The results showed that Bayesian decision theory method was able to preserve the type I error rate as well as achieve a favorable power; further by comparing with the error spending function method, we concluded that Bayesian decision theory approach was more effective on reducing average sample size.^

Functional data analysis approaches for genotype-phenotype association studies from next-generation sequencing

Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

A hybrid method in combining treatment effects from matched and unmatched studies

In the biomedical studies, the general data structures have been the matched (paired) and unmatched designs. Recently, many researchers are interested in Meta-Analysis to obtain a better understanding from several clinical data of a medical treatment. The hybrid design, which is combined two data structures, may create the fundamental question for statistical methods and the challenges for statistical inferences. The applied methods are depending on the underlying distribution. If the outcomes are normally distributed, we would use the classic paired and two independent sample T-tests on the matched and unmatched cases. If not, we can apply Wilcoxon signed rank and rank sum test on each case. ^ To assess an overall treatment effect on a hybrid design, we can apply the inverse variance weight method used in Meta-Analysis. On the nonparametric case, we can use a test statistic which is combined on two Wilcoxon test statistics. However, these two test statistics are not in same scale. We propose the Hybrid Test Statistic based on the Hodges-Lehmann estimates of the treatment effects, which are medians in the same scale.^ To compare the proposed method, we use the classic meta-analysis T-test statistic on the combined the estimates of the treatment effects from two T-test statistics. Theoretically, the efficiency of two unbiased estimators of a parameter is the ratio of their variances. With the concept of Asymptotic Relative Efficiency (ARE) developed by Pitman, we show ARE of the hybrid test statistic relative to classic meta-analysis T-test statistic using the Hodges-Lemann estimators associated with two test statistics.^ From several simulation studies, we calculate the empirical type I error rate and power of the test statistics. The proposed statistic would provide effective tool to evaluate and understand the treatment effect in various public health studies as well as clinical trials.^

Bayesian estimation of multilevel item response model with missing data

This study proposed a novel statistical method that modeled the multiple outcomes and missing data process jointly using item response theory. This method follows the "intent-to-treat" principle in clinical trials and accounts for the correlation between outcomes and missing data process. This method may provide a good solution to chronic mental disorder study. ^ The simulation study demonstrated that if the true model is the proposed model with moderate or strong correlation, ignoring the within correlation may lead to overestimate of the treatment effect and result in more type I error than specified level. Even if the within correlation is small, the performance of proposed model is as good as naïve response model. Thus, the proposed model is robust for different correlation settings if the data is generated by the proposed model.^

Optimal, minimax, and Bayesian two-stage designs in two-dose phase II clinical trials

Background: For most cytotoxic and biologic anti-cancer agents, the response rate of the drug is commonly assumed to be non-decreasing with an increasing dose. However, an increasing dose does not always result in an appreciable increase in the response rate. This may especially be true at high doses for a biologic agent. Therefore, in a phase II trial the investigators may be interested in testing the anti-tumor activity of a drug at more than one (often two) doses, instead of only at the maximum tolerated dose (MTD). This way, when the lower dose appears equally effective, this dose can be recommended for further confirmatory testing in a phase III trial under potential long-term toxicity and cost considerations. A common approach to designing such a phase II trial has been to use an independent (e.g., Simon's two-stage) design at each dose ignoring the prior knowledge about the ordering of the response probabilities at the different doses. However, failure to account for this ordering constraint in estimating the response probabilities may result in an inefficient design. In this dissertation, we developed extensions of Simon's optimal and minimax two-stage designs, including both frequentist and Bayesian methods, for two doses that assume ordered response rates between doses. ^ Methods: Optimal and minimax two-stage designs are proposed for phase II clinical trials in settings where the true response rates at two dose levels are ordered. We borrow strength between doses using isotonic regression and control the joint and/or marginal error probabilities. Bayesian two-stage designs are also proposed under a stochastic ordering constraint. ^ Results: Compared to Simon's designs, when controlling the power and type I error at the same levels, the proposed frequentist and Bayesian designs reduce the maximum and expected sample sizes. Most of the proposed designs also increase the probability of early termination when the true response rates are poor. ^ Conclusion: Proposed frequentist and Bayesian designs are superior to Simon's designs in terms of operating characteristics (expected sample size and probability of early termination, when the response rates are poor) Thus, the proposed designs lead to more cost-efficient and ethical trials, and may consequently improve and expedite the drug discovery process. The proposed designs may be extended to designs of multiple group trials and drug combination trials.^

A simulation study of the effects of small center enrollment in multi -center clinical trials

Multi-center clinical trials are very common in the development of new drugs and devices. One concern in such trials, is the effect of individual investigational sites enrolling small numbers of patients on the overall result. Can the presence of small centers cause an ineffective treatment to appear effective when treatment-by-center interaction is not statistically significant?^ In this research, simulations are used to study the effect that centers enrolling few patients may have on the analysis of clinical trial data. A multi-center clinical trial with 20 sites is simulated to investigate the effect of a new treatment in comparison to a placebo treatment. Twelve of these 20 investigational sites are considered small, each enrolling less than four patients per treatment group. Three clinical trials are simulated with sample sizes of 100, 170 and 300. The simulated data is generated with various characteristics, one in which treatment should be considered effective and another where treatment is not effective. Qualitative interactions are also produced within the small sites to further investigate the effect of small centers under various conditions.^ Standard analysis of variance methods and the "sometimes-pool" testing procedure are applied to the simulated data. One model investigates treatment and center effect and treatment-by-center interaction. Another model investigates treatment effect alone. These analyses are used to determine the power to detect treatment-by-center interactions, and the probability of type I error.^ We find it is difficult to detect treatment-by-center interactions when only a few investigational sites enrolling a limited number of patients participate in the interaction. However, we find no increased risk of type I error in these situations. In a pooled analysis, when the treatment is not effective, the probability of finding a significant treatment effect in the absence of significant treatment-by-center interaction is well within standard limits of type I error. ^

Transplantation of human embryonic stem cell-derived alveolar epithelial type II cells abrogates acute lung injury in mice.

Respiratory diseases are a major cause of mortality and morbidity worldwide. Current treatments offer no prospect of cure or disease reversal. Transplantation of pulmonary progenitor cells derived from human embryonic stem cells (hESCs) may provide a novel approach to regenerate endogenous lung cells destroyed by injury and disease. Here, we examine the therapeutic potential of alveolar type II epithelial cells derived from hESCs (hES-ATIICs) in a mouse model of acute lung injury. When transplanted into lungs of mice subjected to bleomycin (BLM)-induced acute lung injury, hES-ATIICs behaved as normal primary ATIICs, differentiating into cells expressing phenotypic markers of alveolar type I epithelial cells. Without experiencing tumorigenic side effects, lung injury was abrogated in mice transplanted with hES-ATIICs, demonstrated by recovery of body weight and arterial blood oxygen saturation, decreased collagen deposition, and increased survival. Therefore, transplantation of hES-ATIICs shows promise as an effective therapeutic to treat acute lung injury.

A pure population of lung alveolar epithelial type II cells derived from human embryonic stem cells.

Alveolar epithelial type II (ATII) cells are small, cuboidal cells that constitute approximately 60% of the pulmonary alveolar epithelium. These cells are crucial for repair of the injured alveolus by differentiating into alveolar epithelial type I cells. ATII cells derived from human ES (hES) cells are a promising source of cells that could be used therapeutically to treat distal lung diseases. We have developed a reliable transfection and culture procedure, which facilitates, via genetic selection, the differentiation of hES cells into an essentially pure (>99%) population of ATII cells (hES-ATII). Purity, as well as biological features and morphological characteristics of normal ATII cells, was demonstrated for the hES-ATII cells, including lamellar body formation, expression of surfactant proteins A, B, and C, alpha-1-antitrypsin, and the cystic fibrosis transmembrane conductance receptor, as well as the synthesis and secretion of complement proteins C3 and C5. Collectively, these data document the successful generation of a pure population of ATII cells derived from hES cells, providing a practical source of ATII cells to explore in disease models their potential in the regeneration and repair of the injured alveolus and in the therapeutic treatment of genetic diseases affecting the lung.

Exploring the role of viral infection in type 2 diabetes

Viral infection is known to play a role in type I diabetes, but there is a paucity of information on the role of viruses in type 2 diabetes. This research examined the seroprevalence of selected viruses in a group of predominantly Mexican-American patients with End Stage Renal Disease (ESRD). Using a case control design, patients with type 2 diabetes were compared with a group of non-diabetic controls. ^ One hundred and thirteen patients, 83 with type 2 diabetes and 30 controls without diabetes, underwent hemodialysis at the same chronic dialysis facility in San Antonio, Texas. AD subjects were tested for IgG, IgM, and neutralizing antibodies against Coxsackie B viruses (CBV), and IgG and IgM antibodies against cytomegalovirus (CMV) and parvovirus B19 (PVB19). Hepatitis B virus antigen (HBVAg), Hepatitis B virus antibody (HBVAb), Hepatitis C virus antibody (HCVAb), and Rubella (IgG) were also measured. A subset of 91 patients, 66 with diabetes and 25 controls, were tested bimonthly for six months. There was a significant difference (P = 0.04) in the seroprevalence of IgG antibodies to CMV between patients with type 2 diabetes (98%) and non-diabetic controls (87%) in the initial sample (OR = 6.2, 95% CI:1.1–36.0). A greater seroprevalence of CMV IgG antibodies was observed over the six month period among patients with type 2 diabetes (M) compared to controls (84%). This difference was also statistically (P < 0.03), with a greater odds ratio (OR = 12.4, 95% CI: 1.3–116.9), but with larger confidence interval related to the small number of subjects. However, when adjusted for age by logistic regression analysis there was no difference between the groups (OR = 1). ^ After one sample, there was a greater seroprevalence of HCVAb in the group without diabetes (28%), compared to those with type 2 diabetes (10%) (P = 0.04). This difference was no longer significant when adjusted for patient age. The prevalence of antibodies to PVB19, HBSAg, HBV, and Rubella was not significantly different in patients with type 2 diabetes and controls. There were significantly more vascular complications (P < 0.02) among patients with diabetes. ^ These results indicate that the significant associations observed in this population between viral infection with CMV, HCV, and type 2 diabetes are confounded by age. Accelerated atherosclerosis has been associated with age, diabetes, as well as CMV. Latent infection may be a factor that links these processes. ^

Tolerance of allografts across MHC barriers by allochimeric class I MHC proteins

Class I MHC proteins have been shown to induce accelerated rejection or prolong survival of allografts in various experimental models. These immunological effects have been attributed to the highly polymorphic alpha helical regions of the extracellular portions of the class I MHC molecule. The present experiments were designed to elucidate the immunomodulatory effects of these polymorphic regions and delineate the mechanisms involved. Soluble allochimeric class I MHC proteins were produced by substituting the PVG class I MHC RT1.Ac amino acid residues within the a 1 helical region with those of the donor BN ( a 1hn-RT1.Ac), the a 2 helical region of BN ( a 2hn-RT1.Ac), and both the a 1 and a 2 helical regions (RT1.An). The class I MHC proteins were produced in an E. coli protein expression system. The a 2hn-RT1.Ac and RT1.An proteins, when administered subcutaneously into PVG hosts 7 days prior to transplantation, resulted in accelerated rejection of BN cardiac allografts. The a 1hn-RT1.Ac construct did not demonstrate such immunogenic effects. Intra-portal administration of a 1hn-RT1.Ac or RT1.An, in combination with perioperative CsA, induced tolerance to BN cardiac allografts. The a 1hn-RT1.Ac protein was able to induce tolerance in a larger majority of the PVG recipients and at a lower dose of protein when compared to the RT1.An protein. RT1.An administered orally to PVG recipients also induced long term survival of cardiac allografts. In vitro analysis revealed that lymphocytes from tolerant hosts were hyporesponsive to donor splenocytes, but responsive to 3rd party splenocytes. Evaluation of T cell cytokine expression patterns revealed that rejector PVG hosts displayed a Type I T-cell response when re-challenged with donor splenocytes, in contrast to tolerant animals that displayed a Type II T-cell response. FACS analysis of the T cells revealed that the ratio of CD4 to CD8 cells was 3:1 and was consistent in the groups tested suggesting a complex interaction between the subsets of T cells, yielding the observed results. Histologic analysis of the cardiac allografts revealed that tolerant PVG hosts maintained BN cardiac allografts without any evidence of acute or chronic rejection after 300 days post transplant. This body of work has demonstrated that the use of soluble donor/recipient allochimeric class I MHC proteins with a short peri-operative course of CsA resulted in transplant tolerance. This treatment regimen proffers a clinically relevant approach to the induction of tolerance across MHC barriers. ^

Collagen I modulates growth and gene expression in prostate cancer cells

Prostate cancer is the second leading cause of male cancer-related deaths in the United States. Interestingly, prostate cancer preferentially metastasizes to skeletal tissue. Once in the bone microenvironment, advanced prostate cancer becomes highly resistant to therapeutic modalities. Several factors, such as extracellular matrix (ECM) components, have been implicated in the spread and propagation of prostatic carcinoma. In these studies, we have utilized the PC3 cell line, derived from a human bone metastasis, to investigate the influence of the predominant bone ECM protein, type I collagen, on prostate cancer cell proliferation and gene expression. We have also initiated the design and production of ribozymes to specific gene targets that may influence prostate cancer bone metastasis. ^ Our results demonstrate that PC3 cells rapidly adhere and spread on collagen I to a greater degree than on fibronectin (FN) or poly-L-lysine (PLL). Flow cytometry analysis reveals the presence of the α1, α2 and α3 collagen binding integrin subunits. The use of antibody function blocking studies reveals that PC3 cells can utilize α2β 1 and α3β1 integrins to adhere to collagen I. Once plated on collagen I, the cells exhibit increased rates of proliferation compared with cells plated on FN or tissue culture plastic. Additionally, cells plated on collagen I show increased expression of proteins associated with progression through G1 phase of the cell cycle. Inhibitor studies point to a role for phosphatidylinositol 3-kinase (PI3K), MAP kinase (MAPK), and p70 S6 kinase in collagen I-mediated PC3 cell proliferation and cyclin D1 expression. To further characterize the effect of type I collagen on prostate cancer bone metastasis, we utilized a cDNA microarray strategy to monitor type I collagen-mediated changes in gene expression. Results of this analysis revealed a gene expression profile reflecting the increased proliferation occurring on type I collagen. Microarray analysis also revealed differences in the expression of specific gene targets that may impact on prostate cancer metastasis to bone. ^ As a result of our studies on the interaction of prostate cancer cells and the skeletal ECM, we sought to develop novel molecular tools for future gene therapy of functional knockdown experiments. To this end, we developed a series of ribozymes directed against the α2 integrin and at osteopontin, a protein implicated in the metastasis of various cancers, including prostate. These ribozymes should facilitate the future study of the mechanism of prostate cancer cell proliferation, and disease progression occurring at sites of skeletal metastasis where a type I collagen-based environment predominates. ^ Together these studies demonstrate the involvement of bone ECM proteins on prostate cancer cell proliferation and suggest that they may play a significant role on the growth of prostate metastases once in the bone microenvironment. ^

Delayed Thrombus Resolution and Fibroproliferative Vascular Wound Healing From Deficiency of Type III Collagen: a Paradoxical Mechanism for Tissue Fragility

Vascular Ehlers-Danlos syndrome is a heritable disease of connective tissue caused by mutations in COL3A1, conferring a tissue deficiency of type III collagen. Cutaneous wounds heal poorly in these patients, and they are susceptible to spontaneous and catastrophic rupture of expansible hollow organs like the gut, uterus, and medium-sized to large arteries, which leads to premature death. Although the predisposition for organ rupture is often attributed to inherent tissue fragility, investigation of arteries from a haploinsufficient Col3a1 mouse model (Col3a1+/-) demonstrates that mutant arteries withstand even supraphysiologic pressures comparably to wild-type vessels. We hypothesize that injury that elicits occlusive thrombi instead unmasks defective thrombus resolution resulting from impaired production of type III collagen, which causes deranged remodeling of matrix, persistent inflammation, and dysregulated behavior by resident myofibroblasts, culminating in the development of penetrating neovascular channels that disrupt the mechanical integrity of the arterial wall. Vascular injury and thrombus formation following ligation of the carotid artery reveals an abnormal persistence and elevated burden of occlusive thrombi at 21 post-operative days in vessels from Col3a1+/- mice, as opposed to near complete resolution and formation of a patent and mature neointima in wild-type mice. At only 14 days, both groups harbor comparable burdens of resolving thrombi, but wild-type mice increase production of type III collagen in actively resolving tissues, while mutant mice do not. Rather, thrombi in mutant mice contain higher burdens of macrophages and proliferative myofibroblasts, which persist through 21 days while wild-type thrombi, inflammatory cells, and proliferation all regress. At the same time that increased macrophage burdens were observed at 14 and 21 days post ligation, the medial layer of mutant arterial walls concurrently harbored a significantly higher incidence of penetrating neovessels compared with those in wild-type mice. To assess whether limited type III collagen production alters myofibroblast behavior, fibroblasts from vEDS patients with COL3A1 missense mutations were seeded into three-dimensional fibrin gel constructs and stimulated with transforming growth factor-β1 to initiate myofibroblast differentiation. Although early signaling events occur similarly in all cell lines, late extracellular matrix- and mechanically-regulated events like transcriptional upregulation of type I and type III collagen secretion are delayed in mutant cultures, while transcription of genes encoding intracellular contractile machinery is increased. Sophisticated imaging of collagen synthesized de novo by resident myofibroblasts visualizes complex matrix reorganization by control cells but only meager remodeling by COL3A1 mutant cells, concordant with their compensatory contraction to maintain tension in the matrix. Finally, administration of immunosuppressive rapamycin to mice following carotid ligation sufficiently halts the initial inflammatory phase of thrombus resolution and fully prevents both myofibroblast migration into the thrombus and the differential development of neovessels between mutant and wild-type mice, suggesting that pathological defects in mutant arteries develop secondarily to myofibroblast dysfunction and chronic inflammatory stimulation, rather than as a manifestation of tissue fragility. Together these data establish evidence that pathological defects in the vessel wall architecture develop in mutant arteries as sequelae to abnormal healing and remodeling responses activated by arterial injury. Thus, these data support the hypothesis that events threatening the integrity of type III collagen-deficient vessels develop not as a result of inherent tissue weakness and fragility at baseline but instead as an episodic byproduct of abnormally persistent granulation tissue and fibroproliferative intravascular remodeling.