Berry Consultants LLC

Austin, TX, United States

Berry Consultants LLC

Austin, TX, United States
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Broglio K.R.,Berry Consultants LLC | Sandalic L.,Seattle Genetics | Albertson T.,Seattle Genetics | Berry S.M.,Berry Consultants LLC
Contemporary Clinical Trials | Year: 2015

We present a Phase I dose escalation trial design based on a modified continual reassessment method that allows for sharing of information between populations. We describe our approach in the context of a trial for patients with acute lymphoblastic leukemia (ALL) that is currently being conducted. The ALL trial enrolls both adult and pediatric patient populations. Dose escalation and the determination of the maximum tolerated dose (MTD) are performed separately for each population, but to increase efficiency, information about the dose-toxicity curve is shared. Dose escalation rules allow pediatric patients to skip dose levels provided safety has been shown in adults and the dose level is estimated to be safe for pediatric patients. Trial objectives are to efficiently determine the MTD for each population and to minimize the number of pediatric patients required for dose escalation. © 2015 Elsevier Inc.

PubMed | University of Southern California, Medical University of South Carolina, University of Lorraine, Ohio State University and 2 more.
Type: Review | Journal: Journal of the American College of Cardiology | Year: 2016

The Expedited Access for Premarket Approval and De Novo Medical Devices Intended for Unmet Medical Need for Life Threatening or Irreversibly Debilitating Diseases or Conditions document was issued as a guidance for industry and for the Food and Drug Administration. The Expedited Access Pathway was designed as a new program for medical devices thatdemonstrated the potential to address unmet medical needs for life threatening or irreversibly debilitating conditions. The Food and Drug Administration would consider assessments of a devices effect on intermediate endpoints that, when improving in a congruent fashion, are reasonably likely to predict clinical benefit. The purpose of this review is toprovide evidence to support the use of 3 such intermediate endpoints: natriuretic peptides, such as N-terminal pro-B-type natriuretic peptide/B-type natriuretic peptide, the 6-min walk test distance, and health-related quality of life in heart failure.

Lewis R.J.,University of California at Los Angeles | Lewis R.J.,Los Angeles Biomedical Research Institute | Lewis R.J.,Berry Consultants LLC | Viele K.,Berry Consultants LLC | And 4 more authors.
Critical Care Medicine | Year: 2013

OBJECTIVES:: Sepsis is the tenth leading cause of death in the United States. Despite extensive research, mortality rates for sepsis have not substantially improved in the last several decades. We describe an innovative phase II clinical trial design for evaluating the addition of L-carnitine to the treatment of vasopressor-dependent septic shock. DESIGN:: The design incorporates a variety of features to increase efficiency, including a normal dynamic linear dose-response model, adaptive randomization, and early stopping for futility or success based on the probability that a future phase III trial using a 28-day mortality outcome would be successful. SETTING:: Trial design and computer simulation of a trial to be conducted in the emergency department and ICU. INTERVENTIONS:: Proposed to study intravenous L-carnitine. MEASUREMENTS:: The proposed trial uses an early endpoint, the 48-hour change in Sequential Organ Failure Assessment score, to drive adaptive randomization and dose selection. MAIN RESULTS:: We use existing data to model the expected relationship between the Sequential Organ Failure Assessment change and the 28-day mortality to determine the trial's operating characteristics using Monte Carlo simulation. CONCLUSIONS:: The resulting trial efficiently identifies the best dose of L-carnitine and provides clear guidance regarding whether to continue development into phase III. Copyright © 2013 by the Society of Critical Care Medicine and Lippincott.

Lewis R.J.,University of California at Los Angeles | Lewis R.J.,Los Angeles Biomedical Research Institute | Lewis R.J.,Berry Consultants LLC
Clinical Trials | Year: 2016

Background/aims A learning health care system ideally incorporates the ability to adapt to the pace of change, the incorporation of new clinical research paradigms, and leverages electronic health record systems and clinical decision support systems to narrow the divide between research and clinical practice. Methods An adaptive clinical trial can be embedded into the sites and practice of clinical care in a highly pragmatic way to simultaneously generate high-quality data on treatment efficacy and improve the care of patients. This approach can be expanded into a pragmatic platform trial, meaning a trial that is intended to evaluate multiple treatments for a disease or diseases, possibly in combination, and with the available treatments potentially changing over time. This strategy is illustrated using a trial currently being implemented in Europe and funded by the European Union, evaluating three different "domains" of treatments for patients with severe community-acquired pneumonia requiring intensive care. Results Simulation studies demonstrate that this approach has the potential to save lives while identifying the best treatment strategies for this critically ill population. Conclusion Patients are likely to benefit if we can merge clinical trials and decision support into a single continuous learning process. © The Society for Clinical Trials.

Lipsky A.M.,University of California at Los Angeles | Lipsky A.M.,Gertner Institute for Epidemiology and Health Policy Research | Lewis R.J.,University of California at Los Angeles | Lewis R.J.,Berry Consultants LLC.
Statistics in Medicine | Year: 2013

Adaptive randomization is used in clinical trials to increase statistical efficiency. In addition, some clinicians and researchers believe that using adaptive randomization leads necessarily to more ethical treatment of subjects in a trial. We develop Bayesian, decision-theoretic, clinical trial designs with response-adaptive randomization and a primary goal of estimating treatment effect and then contrast these designs with designs that also include in their loss function a cost for poor subject outcome. When the loss function did not incorporate a cost for poor subject outcome, the gains in efficiency from response-adaptive randomization were accompanied by ethically concerning subject allocations. Conversely, including a cost for poor subject outcome demonstrated a more acceptable balance between the competing needs in the trial. A subsequent, parallel set of trials designed to control explicitly types I and II error rates showed that much of the improvement achieved through modification of the loss function was essentially negated. Therefore, gains in efficiency from the use of a decision-theoretic, response-adaptive design using adaptive randomization may only be assumed to apply to those goals that are explicitly included in the loss function. Trial goals, including ethical ones, which do not appear in the loss function, are ignored and may even be compromised; it is thus inappropriate to assume that all adaptive trials are necessarily more ethical. Controlling types I and II error rates largely negates the benefit of including competing needs in favor of the goal of parameter estimation. © 2013 John Wiley & Sons, Ltd.

Broglio K.R.,Berry Consultants LLC | Connor J.T.,Berry Consultants LLC | Connor J.T.,University of Central Florida | Berry S.M.,Berry Consultants LLC
Journal of Biopharmaceutical Statistics | Year: 2014

We present a Bayesian adaptive design for a confirmatory trial to select a trials sample size based on accumulating data. During accrual, frequent sample size selection analyses are made and predictive probabilities are used to determine whether the current sample size is sufficient or whether continuing accrual would be futile. The algorithm explicitly accounts for complete follow-up of all patients before the primary analysis is conducted. We refer to this as a Goldilocks trial design, as it is constantly asking the question, "Is the sample size too big, too small, or just right?" We describe the adaptive sample size algorithm, describe how the design parameters should be chosen, and show examples for dichotomous and time-to-event endpoints. © 2014 Taylor and Francis Group, LLC.

PubMed | Juno Therapeutics, Berry Consultants LLC and University of Central Florida
Type: | Journal: Contemporary clinical trials | Year: 2016

We present a novel Bayesian adaptive phase 1 design to determine the optimal dosing regimen for an adoptive T-cell therapy in a mixed patient population. Our design is motivated by a B-cell Non-Hodgkin Lymphoma trial evaluating multiple dosing regimens within multiple disease subtypes. A utility score is calculated from both safety and efficacy utility functions and used to guide dose-escalation decisions. We pool safety data across disease subtypes and use a single dose-toxicity model while sharing efficacy information between disease subtypes using a hierarchical dose-response model. In addition, an adaptive randomization approach is applied to dynamically assign patients to a regimen when more than one regimen is open for enrollment. We illustrate this study design through a simulated trial example, and we investigate the operating characteristics using simulation studies.

Broglio K.R.,Berry Consultants LLC | Stivers D.N.,Alere Inc | Berry D.A.,Berry Consultants LLC | Berry D.A.,University of Texas M. D. Anderson Cancer Center
Trials | Year: 2014

Background: Announcements of interim analyses of a clinical trial convey information about the results beyond the trial's Data Safety Monitoring Board (DSMB). The amount of information conveyed may be minimal, but the fact that none of the trial's stopping boundaries has been crossed implies that the experimental therapy is neither extremely effective nor hopeless. Predicting success of the ongoing trial is of interest to the trial's sponsor, the medical community, pharmaceutical companies, and investors. We determine the probability of trial success by quantifying only the publicly available information from interim analyses of an ongoing trial. We illustrate our method in the context of the National Surgical Adjuvant Breast and Bowel (NSABP) trial, C-08.Methods: We simulated trials based on the specifics of the NSABP C-08 protocol that were publicly available. We quantified the uncertainty around the treatment effect using prior weights for the various possibilities in light of other colon cancer studies and other studies of the investigational agent, bevacizumab. We considered alternative prior distributions.Results: Subsequent to the trial's third interim analysis, our predictive probabilities were: that the trial would eventually be successful, 48.0%; would stop for futility, 7.4%; and would continue to completion without statistical significance, 44.5%. The actual trial continued to completion without statistical significance.Conclusions: Announcements of interim analyses provide information outside the DSMB's sphere of confidentiality. This information is potentially helpful to clinical trial prognosticators. 'Information leakage' from standard interim analyses such as in NSABP C-08 is conventionally viewed as acceptable even though it may be quite revealing. Whether leakage from more aggressive types of adaptations is acceptable should be assessed at the design stage. © 2014 Broglio et al.; licensee BioMed Central Ltd.

Broglio K.R.,Berry Consultants LLC | Connor J.T.,Berry Consultants LLC | Berry S.M.,Berry Consultants LLC
Journal of Biopharmaceutical Statistics | Year: 2013

Prior to marketing, the long-term safety profile of a new therapy is often uncertain. One recommendation for premarket safety studies is to compare the new therapy to an appropriate control to determine whether the 95% confidence interval of the risk ratio is entirely less than a prespecified threshold (e.g., 1.8). The restriction to the risk ratio, however, has consequences that may not be intended. Risk difference may be a more appropriate measure of risk in this setting when event rates are very low. We propose using a suitable combination of risk ratio and risk difference in demonstrating noninferiority. © 2013 Copyright Taylor and Francis Group, LLC.

Hochberg M.C.,University of Maryland Baltimore County | Berry S.,Berry Consultants LLC | Broglio K.,Berry Consultants LLC | Rosenblatt L.,Bristol Myers Squibb | And 3 more authors.
Current Medical Research and Opinion | Year: 2013

Objective: To determine the comparative efficacy and tolerability of abatacept and tumor necrosis factor inhibitors (TNFi) in patients with rheumatoid arthritis (RA) and inadequate response to conventional disease modifying anti-rheumatic drugs (DMARDs). Research design and methods: A systematic review identified RCTs in RA patients who responded inadequately to conventional DMARDs and were treated with one of the following biologic agents: abatacept, adalimumab, etanercept, infliximab, certolizumab pegol, or golimumab. Bayesian hierarchical models were used to compare efficacy and tolerability outcomes of abatacept and combined TNFi at 6 months and 1 year. Results: In this mixed treatment comparison (MTC), the likelihood of achieving ACR response was comparable between abatacept and combined TNFi at 6 months for ACR20, 50, and 70: (odds ratio [OR] = 0.98 [95% confidence interval (CI): 0.73, 1.27], 0.99 [0.73, 1.31], and 0.91 [0.62, 1.27], respectively); and at 12 months for ACR20 (OR = 1.27 [0.92, 1.71]) and ACR50 (1.21 [0.82, 1.68]), with a higher likelihood of achieving an ACR70 response at 12 months (1.41 [1.02, 1.82]). Odds of DAS28 remission at 12 months was greater for abatacept than the combined TNFi (OR = 2.03 [1.04, 3.58]). Abatacept had better tolerability, defined as a lower likelihood of withdrawal due to adverse events, at both 6 and 12 months (OR = 0.38 [0.10, 0.88] and 0.51 [0.27, 0.86], respectively). These analyses include indirect comparisons across clinical trials and are not a replacement for head-to-head data. While all TNFi have been grouped into one class, there may be some differences between the individual TNFi that are not captured in our study. Conclusions: In this MTC, abatacept demonstrated similar efficacy at 6 months, a higher likelihood of achieving ACR70 response and DAS28 remission at 12 months and better tolerability relative to the combined TNFi in patients with RA who had an inadequate response to conventional DMARDs. © 2013 All rights reserved.

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