Hybrid Controlled Clinical Trials Using Concurrent Registries in Amyotrophic Lateral Sclerosis: A Feasibility Study.

Hybrid designs with both randomized arms and an external control cohort preserve key features of randomization and utilize external information to augment clinical trials. In this study, we propose to leverage high-quality, patient-level concurrent registries to enhance clinical trials and illustrate the impact on trial design for amyotrophic lateral sclerosis. The proposed methodology was evaluated in a randomized, placebo-controlled clinical trial. We used patient-level information from a well-defined, population-based registry, that was running parallel to the randomized clinical trial, to identify concurrently nonparticipating, eligible patients who could be matched with trial participants, and integrate them into the statistical analysis. We assessed the impact of the addition of the external controls on the treatment effect estimate, precision, and time to reach a conclusion. During the runtime of the trial, a total of 1,141 registry patients were alive; 473 (41.5%) of them fulfilled the eligibility criteria and 133 (11.7%) were enrolled in the study. A matched control population could be identified among the nonparticipating patients. Augmenting the randomized controls with matched external controls could have avoided unnecessary randomization of 17 patients (-12.8%) as well as reducing the study duration from 30.1 months to 22.6 months (-25.0%). Matching eligible external controls from a different calendar period led to bias in the treatment effect estimate. Hybrid trial designs utilizing a concurrent registry with rigorous matching can minimize bias due to a mismatch in calendar time and differences in standard of care, and may accelerate the development of new treatments.

Properties of Macroalgae Biopolymer Films Reinforcement with Polysaccharide Microfibre.

Developing robust and biodegradable biopolymer films based on macroalgae is a challenging task because of its inadequate mechanical strength and poor moisture barrier attribute to its hydrophilic nature. A promising and sustainable approach to overcome this challenge is to reinforce the biopolymer film with polysaccharide microfibre (microcrystalline cellulose) derived from Gigantochloa levis bamboo (GL-MCC). Eucheuma cottonii macroalgae were used for the development of biopolymer films without further extraction and purification, which was considered economical and easy. The mechanical, water contact angle (WCA), water absorption capacity (WSC), and thermal behaviour of macroalgae-based biopolymer films revealed that the inclusions of GL-MCC significantly enhanced the durability, moisture barrier, and thermal stability of the biopolymer films. The enhancement is ascribed to the interaction between macroalgae and GL-MCC due to high compatibility. Moreover, the incorporation of GL-MCC successfully increased the rigidity of the macroalgae-based biopolymer films against microorganism and moisture attack, but remain biodegradable and environmental-friendly. The developed biodegradable macroalgae/GL-MCC biopolymer films can potentially be used as packaging materials.

Postoperative adjunctive bevacizumab versus placebo in primary trabeculectomy surgery for glaucoma.

AIM: To compare the effectiveness of postoperative adjunctive use of subconjunctival bevacizumab in altering the outcome of primary trabeculectomy in terms of sustained lowering of intraocular pressure (IOP) and reduction of postoperative bleb vascularization and fibrosis. METHODS: A prospective, one center, randomized, placebo-control study. Fifty-nine patients (59 eyes) with uncontrolled IOP under maximal tolerated medical treatment (MTMT) were recruited. A primary trabeculectomy with mitomycin C (MMC) was done and the patients were randomized to either postoperative subconjunctival injection of bevacizumab (1.25 mg/0.05 mL) or balanced salt solution (BSS). Forty-seven patients (47 eyes) completed at least one year of follow up and were included in the study. The main outcome measure was the IOP, and secondary outcome measures include bleb morphology, vascularization, and fibrosis, as well as the need for glaucoma medications and 5-fluorouracil (5-FU) needling. RESULTS: At 1-year follow up, there was no significant difference between groups for IOP (P=0.65), bleb morphology (P=0.65), and the need for glaucoma medications (P=0.65) or 5-FU needling requirements (P=0.11). However, the bevacizumab group had a higher rate of success results, lower use of glaucoma medications after surgery, and optimal bleb aspect in more patients, but more 5-FU needling procedures required. CONCLUSION: A bigger sample size is needed in order to determine whether the differences found in the bevacizumab group are statistically significant.

Adaptive enrichment designs for confirmatory trials.

After an overview of the Food and Drugs Administration's 2012 draft guidance on enrichment strategies for clinical trials to support drug/biologic approval, we describe subsequent advances in adaptive enrichment designs in this direction. We also provide a concrete application in the enrichment design of the Diffusion and Perfusion Imaging Evaluation for Understanding Stroke Evolution 3 trial comparing a new endovascular treatment with standard of care for ischemic stroke patients.

Inactivation of ferric uptake regulator (Fur) attenuates Helicobacter pylori J99 motility by disturbing the flagellar motor switch and autoinducer-2 production.

BACKGROUND: Flagellar motility of Helicobacter pylori has been shown to be important for the bacteria to establish initial colonization. The ferric uptake regulator (Fur) is a global regulator that has been identified in H. pylori which is involved in the processes of iron uptake and establishing colonization. However, the role of Fur in H. pylori motility is still unclear. MATERIALS AND METHODS: Motility of the wild-type, fur mutant, and fur revertant J99 were determined by a soft-agar motility assay and direct video observation. The bacterial shape and flagellar structure were evaluated by transmission electron microscopy. Single bacterial motility and flagellar switching were observed by phase-contrast microscopy. Autoinducer-2 (AI-2) production in bacterial culture supernatant was analyzed by a bioluminescence assay. RESULTS: The fur mutant showed impaired motility in the soft-agar assay compared with the wild-type J99 and fur revertant. The numbers and lengths of flagellar filaments on the fur mutant cells were similar to those of the wild-type and revertant cells. Phenotypic characterization showed similar swimming speed but reduction in switching rate in the fur mutant. The AI-2 production of the fur mutant was dramatically reduced compared with wild-type J99 in log-phase culture medium. CONCLUSIONS: These results indicate that Fur positively modulates H. pylori J99 motility through interfering with bacterial flagellar switching.

A new approach to regression analysis of censored competing-risks data.

An approximate likelihood approach is developed for regression analysis of censored competing-risks data. This approach models directly the cumulative incidence function, instead of the cause-specific hazard function, in terms of explanatory covariates under a proportional subdistribution hazards assumption. It uses a self-consistent iterative procedure to maximize an approximate semiparametric likelihood function, leading to an asymptotically normal and efficient estimator of the vector of regression parameters. Simulation studies demonstrate its advantages over previous methods.

Power of an Adaptive Trial Design for Endovascular Stroke Studies: Simulations Using IMS (Interventional Management of Stroke) III Data.

BACKGROUND AND PURPOSE: Adaptive trial designs that allow enrichment of the study population through subgroup selection can increase the chance of a positive trial when there is a differential treatment effect among patient subgroups. The goal of this study is to illustrate the potential benefit of adaptive subgroup selection in endovascular stroke studies. METHODS: We simulated the performance of a trial design with adaptive subgroup selection and compared it with that of a traditional design. Outcome data were based on 90-day modified Rankin Scale scores, observed in IMS III (Interventional Management of Stroke III), among patients with a vessel occlusion on baseline computed tomographic angiography (n=382). Patients were categorized based on 2 methods: (1) according to location of the arterial occlusive lesion and onset-to-randomization time and (2) according to onset-to-randomization time alone. The power to demonstrate a treatment benefit was based on 10 000 trial simulations for each design. RESULTS: The treatment effect was relatively homogeneous across categories when patients were categorized based on arterial occlusive lesion and time. Consequently, the adaptive design had similar power (47%) compared with the fixed trial design (45%). There was a differential treatment effect when patients were categorized based on time alone, resulting in greater power with the adaptive design (82%) than with the fixed design (57%). CONCLUSIONS: These simulations, based on real-world patient data, indicate that adaptive subgroup selection has merit in endovascular stroke trials as it substantially increases power when the treatment effect differs among subgroups in a predicted pattern.

Design of clinical trials with failure-time endpoints and interim analyses: An update after fifteen years.

Time to event is the clinically definitive endpoint in Phase III trials of new treatments of cancer, cardiovascular and many other diseases. Because these trials involve relatively long follow-up, their protocols usually incorporate periodic interim analyses of the data by a Data and Safety Monitoring Board/Committee. This paper gives a review of the major developments in the design of these trials in the 21st century, spurred by the need for better clinical trial designs to cope with the remarkable advances in cancer biology, genomics and imaging that can help predict patients' sensitivity or resistance to certain treatments. In addition to this overview and discussion of related issues and challenges, we also introduce a new approach to address some of these issues.

Adaptive design of confirmatory trials: Advances and challenges.

The past decade witnessed major developments in innovative designs of confirmatory clinical trials, and adaptive designs represent the most active area of these developments. We give an overview of the developments and associated statistical methods in several classes of adaptive designs of confirmatory trials. We also discuss their statistical difficulties and implementation challenges, and show how these problems are connected to other branches of mainstream Statistics, which we then apply to resolve the difficulties and bypass the bottlenecks in the development of adaptive designs for the next decade.

Innovative designs of point-of-care comparative effectiveness trials.

One of the provisions of the health care reform legislation in 2010 was for funding pragmatic clinical trials or large observational studies for comparing the effectiveness of different approved medical treatments, involving broadly representative patient populations. After reviewing pragmatic clinical trials and the issues and challenges that have made them just a small fraction of comparative effectiveness research (CER), we focus on a recent development that uses point-of-care (POC) clinical trials to address the issue of "knowledge-action gap" in pragmatic CER trials. We give illustrative examples of POC-CER trials and describe a trial that we are currently planning to compare the effectiveness of newly approved oral anticoagulants. We also develop novel stage-wise designs of information-rich POC-CER trials under competitive budget constraints, by using recent advances in adaptive designs and other statistical methodologies.

Prostaglandin agonist effect on matrix metalloproteinase aqueous levels in glaucoma patients.

OBJECTIVE: To determine whether the aqueous levels of matrix metalloproteinases (MMPs) differ between patients with glaucoma treated with topical prostaglandin analogues and normal, nonglaucomatous control patients. Also, to note any difference in MMP levels between latanoprost, travoprost, and bimatoprost that might suggest a difference in efficacy or mechanism of action between these drugs. DESIGN: Prospective, observational study. PARTICIPANTS: Patients who were scheduled to undergo routine intraocular surgery (phacoemulsification or combined phacotrabeculectomy) as part of their standard clinical care were included. Eighteen eyes of 18 patients with glaucoma using any 1 prostaglandin analogue (latanoprost, travoprost, or bimatoprost) were compared with 8 normal control patients. METHODS: This was a multicentre study. Aqueous humour (0.2 mL) was aspirated at the beginning of the intraocular surgery through a clear corneal paracentesis. MMP-2 and -9 were quantified in the aqueous of all participants using enzyme-linked immunosorbent assay. RESULTS: There was no significant difference in the levels of either MMP-2 (p = 0.216) or MMP-9 (p = 0.552) between the control patients and the patients with glaucoma on prostaglandins. There was no difference in the levels of MMP-2 or -9 between the latanoprost, travoprost, or bimatoprost groups. CONCLUSIONS: The levels of MMP-2 and -9 in aqueous of glaucomatous eyes on topical prostaglandin analogues were the same as those of normal age-matched control patients. This could reflect either a return to normal levels with efficacious treatment or a lack of difference between disease and nondisease states.

ABO mismatch is associated with increased nonrelapse mortality after allogeneic hematopoietic cell transplantation.

We evaluated ABO associated outcomes in 1737 patients who underwent allogeneic hematopoietic cell transplantation (allo-HCT) at Stanford University between January 1986 and July 2011. Grafts were 61% ABO matched, 18% major mismatched (MM), 17% minor MM, and 4% bidirectional MM. Median follow-up was 6 years. In multivariate analysis, overall survival (OS) was inferior in minor MM hematopoietic cell transplantations (median 2.1 versus 6.3 years; hazard ratio [HR], 1.56; 95% confidence interval [CI], 1.19 to 2.05; P = .001) in comparison with ABO-matched grafts. ABO minor MM was associated with an increase in early nonrelapse mortality (NRM) (18% versus 13%; HR, 1.48; 95% CI, 1.06 to 2.06; P = .02). In an independent Center for International Blood and Marrow Transplant Research (CIBMTR) analysis of 435 lymphoma patients receiving mobilized peripheral blood grafts, impairment of OS (HR, 1.55; 95% CI, 1.07 to 2.25; P = .021) and increased NRM (HR, 1.72; 95% CI, 1.11 to 2.68; P = .03) were observed in recipients of ABO minor-MM grafts. A second independent analysis of a CIBMTR data set including 5179 patients with acute myeloid leukemia and myelodysplastic syndrome identified a nonsignificant trend toward decreased OS in recipients of ABO minor-MM grafts and also found ABO major MM to be significantly associated with decreased OS (HR, 1.19; 95% CI, 1.08 to 1.31; P < .001) and increased NRM (HR, 1.23; 95% CI, 1.08 to 1.4; P = .002). ABO minor and major MM are risk factors for worse transplantation outcomes, although the associated hazards may not be uniform across different transplantation populations. Further study is warranted to determine which patient populations are at greatest risk, and whether this risk can be modified by anti-B cell therapy or other peri-transplantation treatments.

Adaptive choice of patient subgroup for comparing two treatments.

This paper is motivated by a randomized controlled trial to compare an endovascular procedure with conventional medical treatment for stroke patients, in which the endovascular procedure may be effective only in a subgroup of patients. Since the subgroup is not known at the design stage but can be learned statistically from the data collected during the course of the trial, we develop a novel group sequential design that incorporates adaptive choice of the patient subgroup among several possibilities which include the entire patient population as a choice. We define the type I and type II errors of a test in this design and show how a prescribed type I error can be maintained by using the closed testing principle in multiple testing. We also show how asymptotically optimal tests can be constructed by using generalized likelihood ratio statistics for parametric problems and analogous standardized or Studentized statistics for nonparametric tests such as Wilcoxon's rank sum test commonly used for treatment comparison in stroke patients.

A new approach to designing phase I-II cancer trials for cytotoxic chemotherapies.

Recently, there has been much work on early phase cancer designs that incorporate both toxicity and efficacy data, called phase I-II designs because they combine elements of both phases. However, they do not explicitly address the phase II hypothesis test of H0 : p ≤ p0 , where p is the probability of efficacy at the estimated maximum tolerated dose η from phase I and p0 is the baseline efficacy rate. Standard practice for phase II remains to treat p as a fixed, unknown parameter and to use Simon's two-stage design with all patients dosed at η. We propose a phase I-II design that addresses the uncertainty in the estimate p=p(η) in H0 by using sequential generalized likelihood theory. Combining this with a phase I design that incorporates efficacy data, the phase I-II design provides a common framework that can be used all the way from the first dose of phase I through the final accept/reject decision about H0 at the end of phase II, utilizing both toxicity and efficacy data throughout. Efficient group sequential testing is used in phase II that allows for early stopping to show treatment effect or futility. The proposed phase I-II design thus removes the artificial barrier between phase I and phase II and fulfills the objectives of searching for the maximum tolerated dose and testing if the treatment has an acceptable response rate to enter into a phase III trial.

Group sequential designs for developing and testing biomarker-guided personalized therapies in comparative effectiveness research.

Biomarker-guided personalized therapies offer great promise to improve drug development and improve patient care, but also pose difficult challenges in designing clinical trials for the development and validation of these therapies. We first give a review of the existing approaches, briefly for clinical trials in new drug development and in more detail for comparative effectiveness trials involving approved treatments. We then introduce new group sequential designs to develop and test personalized treatment strategies involving approved treatments.

Clinical trial designs for testing biomarker-based personalized therapies.

BACKGROUND: Advances in molecular therapeutics in the past decade have opened up new possibilities for treating cancer patients with personalized therapies, using biomarkers to determine which treatments are most likely to benefit them, but there are difficulties and unresolved issues in the development and validation of biomarker-based personalized therapies. We develop a new clinical trial design to address some of these issues. The goal is to capture the strengths of the frequentist and Bayesian approaches to address this problem in the recent literature and to circumvent their limitations. METHODS: We use generalized likelihood ratio tests of the intersection null and enriched strategy null hypotheses to derive a novel clinical trial design for the problem of advancing promising biomarker-guided strategies toward eventual validation. We also investigate the usefulness of adaptive randomization (AR) and futility stopping proposed in the recent literature. RESULTS: Simulation studies demonstrate the advantages of testing both the narrowly focused enriched strategy null hypothesis related to validating a proposed strategy and the intersection null hypothesis that can accommodate to a potentially successful strategy. AR and early termination of ineffective treatments offer increased probability of receiving the preferred treatment and better response rates for patients in the trial, at the expense of more complicated inference under small-to-moderate total sample sizes and some reduction in power. LIMITATIONS: The binary response used in the development phase may not be a reliable indicator of treatment benefit on long-term clinical outcomes. In the proposed design, the biomarker-guided strategy (BGS) is not compared to 'standard of care', such as physician's choice that may be informed by patient characteristics. Therefore, a positive result does not imply superiority of the BGS to 'standard of care'. The proposed design and tests are valid asymptotically. Simulations are used to examine small-to-moderate sample properties. CONCLUSION: Innovative clinical trial designs are needed to address the difficulties and issues in the development and validation of biomarker-based personalized therapies. The article shows the advantages of using likelihood inference and interim analysis to meet the challenges in the sample size needed and in the constantly evolving biomarker landscape and genomic and proteomic technologies.

Sequential design of phase II-III cancer trials.

Although traditional phase II cancer trials are usually single arm, with tumor response as endpoint, and phase III trials are randomized and incorporate interim analyses with progression-free survival or other failure time as endpoint, this paper proposes a new approach that seamlessly expands a randomized phase II study of response rate into a randomized phase III study of time to failure. This approach is based on advances in group sequential designs and joint modeling of the response rate and time to event. The joint modeling is reflected in the primary and secondary objectives of the trial, and the sequential design allows the trial to adapt to increase in information on response and survival patterns during the course of the trial and to stop early either for conclusive evidence on efficacy of the experimental treatment or for the futility in continuing the trial to demonstrate it, on the basis of the data collected so far.

Adaptive trial designs.

We review adaptive designs for clinical trials, giving special attention to the control of the Type I error in late-phase confirmatory trials, when the trial planner wishes to adjust the final sample size of the study in response to an unblinded analysis of interim estimates of treatment effects. We point out that there is considerable inefficiency in using the adaptive designs that employ conditional power calculations to reestimate the sample size and that maintain the Type I error by using certain weighted test statistics. Although these adaptive designs have little advantage over familiar group-sequential designs, our review also describes recent developments in adaptive designs that are both flexible and efficient. We also discuss the use of Bayesian designs, when the context of use demands control over operating characteristics (Type I and II errors) and correction of the bias of estimated treatment effects.

Efficient Adaptive Randomization and Stopping Rules in Multi-arm Clinical Trials for Testing a New Treatment.

Motivated by applications to confirmatory clinical trials for testing a new treatment against a placebo or active control when the new treatment has k possible treatment strategies (arms)-for example, k possible doses for a new drug-we develop an asymptotic theory for efficient outcome-adaptive randomization schemes and optimal stopping rules. Our approach consists of developing asymptotic lower bounds for the expected sample sizes from the k treatment arms and the control arm and using generalized sequential likelihood ratio procedures to achieve these bounds. Implementation details of our design and analysis and comparative simulation studies are also provided.

Incorporating individual and collective ethics into phase I cancer trial designs.

A general framework is proposed for Bayesian model based designs of Phase I cancer trials, in which a general criterion for coherence (Cheung, 2005, Biometrika 92, 863-873) of a design is also developed. This framework can incorporate both "individual" and "collective" ethics into the design of the trial. We propose a new design that minimizes a risk function composed of two terms, with one representing the individual risk of the current dose and the other representing the collective risk. The performance of this design, which is measured in terms of the accuracy of the estimated target dose at the end of the trial, the toxicity and overdose rates, and certain loss functions reflecting the individual and collective ethics, is studied and compared with existing Bayesian model based designs and is shown to have better performance than existing designs.