Adaptive multi-interventional trial platform to improve patient care for fibrotic interstitial lung diseases.

BACKGROUND: Fibrotic interstitial lung diseases (fILDs) are a heterogeneous group of lung diseases associated with significant morbidity and mortality. Despite a large increase in the number of clinical trials in the last 10 years, current regulatory-approved management approaches are limited to two therapies that prevent the progression of fibrosis. The drug development pipeline is long and there is an urgent need to accelerate this process. This manuscript introduces the concept and design of an innovative research approach to drug development in fILD: a global Randomised Embedded Multifactorial Adaptive Platform in fILD (REMAP-ILD). METHODS: Description of the REMAP-ILD concept and design: the specific terminology, design characteristics (multifactorial, adaptive features, statistical approach), target population, interventions, outcomes, mission and values, and organisational structure. RESULTS: The target population will be adult patients with fILD, and the primary outcome will be a disease progression model incorporating forced vital capacity and mortality over 12 months. Responsive adaptive randomisation, prespecified thresholds for success and futility will be used to assess the effectiveness and safety of interventions. REMAP-ILD embraces the core values of diversity, equity, and inclusion for patients and researchers, and prioritises an open-science approach to data sharing and dissemination of results. CONCLUSION: By using an innovative and efficient adaptive multi-interventional trial platform design, we aim to accelerate and improve care for patients with fILD. Through worldwide collaboration, novel analytical methodology and pragmatic trial delivery, REMAP-ILD aims to overcome major limitations associated with conventional randomised controlled trial approaches to rapidly improve the care of people living with fILD.

Design and Statistical Innovations in a Platform Trial for Amyotrophic Lateral Sclerosis.

Platform trials allow efficient evaluation of multiple interventions for a specific disease. The HEALEY ALS Platform Trial is testing multiple investigational products in parallel and sequentially in persons with amyotrophic lateral sclerosis (ALS) with the goal of rapidly identifying novel treatments to slow disease progression. Platform trials have considerable operational and statistical efficiencies compared with typical randomized controlled trials due to their use of shared infrastructure and shared control data. We describe the statistical approaches required to achieve the objectives of a platform trial in the context of ALS. This includes following regulatory guidance for the disease area of interest and accounting for potential differences in outcomes of participants within the shared control (potentially due to differences in time of randomization, mode of administration, and eligibility criteria). Within the HEALEY ALS Platform Trial, the complex statistical objectives are met using a Bayesian shared parameter analysis of function and survival. This analysis serves to provide a common integrated estimate of treatment benefit, overall slowing in disease progression, as measured by function and survival while accounting for potential differences in the shared control group using Bayesian hierarchical modeling. Clinical trial simulation is used to provide a better understanding of this novel analysis method and complex design. ANN NEUROL 2023;94:547-560.

Adaptive Platform Trials to Transform Amyotrophic Lateral Sclerosis Therapy Development.

Current therapeutic development in amyotrophic lateral sclerosis (ALS) relies on individual randomized clinical trials to test a specific investigational product in a single patient population. This approach has intrinsic limitations, including cost, time, and lack of flexibility. Adaptive platform trials represent a novel approach to investigate several interventions for a single disease in a continuous manner. Already in use in oncology, this approach is now being employed more often in neurology. Here, we describe a newly launched platform trial for ALS. The Healey ALS Platform Trial is testing multiple investigational products concurrently in people with ALS, with the goal of rapidly identifying novel treatments, biomarkers, and trial endpoints. ANN NEUROL 2022;91:165-175.

Safety and efficacy of N-acetylmannosamine (ManNAc) in patients with GNE myopathy: an open-label phase 2 study.

PURPOSE: To evaluate the safety and efficacy of N-acetylmannosamine (ManNAc) in GNE myopathy, a genetic muscle disease caused by deficiency of the rate-limiting enzyme in N-acetylneuraminic acid (Neu5Ac) biosynthesis. METHODS: We conducted an open-label, phase 2, single-center (NIH, USA) study to evaluate oral ManNAc in 12 patients with GNE myopathy (ClinicalTrials.gov NCT02346461). Primary endpoints were safety and biochemical efficacy as determined by change in plasma Neu5Ac and sarcolemmal sialylation. Clinical efficacy was evaluated using secondary outcome measures as part of study extensions, and a disease progression model (GNE-DPM) was tested as an efficacy analysis method. RESULTS: Most drug-related adverse events were gastrointestinal, and there were no serious adverse events. Increased plasma Neu5Ac (+2,159 nmol/L, p < 0.0001) and sarcolemmal sialylation (p = 0.0090) were observed at day 90 compared to baseline. A slower rate of decline was observed for upper extremity strength (p = 0.0139), lower extremity strength (p = 0.0006), and the Adult Myopathy Assessment Tool (p = 0.0453), compared to natural history. Decreased disease progression was estimated at 12 (γ = 0.61 [95% CI: 0.09, 1.27]) and 18 months (γ = 0.55 [95% CI: 0.12, 1.02]) using the GNE-DPM. CONCLUSION: ManNAc showed long-term safety, biochemical efficacy consistent with the intended mechanism of action, and preliminary evidence clinical efficacy in patients with GNE myopathy.

Bayesian adaptive design for clinical trials in Duchenne muscular dystrophy.

A Bayesian adaptive design is proposed for a clinical trial in Duchenne muscular dystrophy. The trial was designed to demonstrate treatment efficacy on an ambulatory-based clinical endpoint and to identify early success on a biomarker (dystrophin protein levels) that can serve as a basis for accelerated approval in the United States. The trial incorporates placebo augmentation using placebo data from past clinical trials. A thorough simulation study was conducted to understand the operating characteristics of the trial. This trial design was selected for the US FDA Complex Innovative Trial Design Pilot Meeting Program and the experience in that program is summarized.

A novel cognitive disease progression model for clinical trials in autosomal-dominant Alzheimer's disease.

Clinical trial outcomes for Alzheimer's disease are typically analyzed by using the mixed model for repeated measures (MMRM) or similar models that compare an efficacy scale change from baseline between treatment arms with or without participants' disease stage as a covariate. The MMRM focuses on a single-point fixed follow-up duration regardless of the exposure for each participant. In contrast to these typical models, we have developed a novel semiparametric cognitive disease progression model (DPM) for autosomal dominant Alzheimer's disease based on the Dominantly Inherited Alzheimer Network (DIAN) observational study. This model includes 3 novel features, in which the DPM (1) aligns and compares participants by disease stage, (2) uses a proportional treatment effect similar to the concept of the Cox proportional hazard ratio, and (3) incorporates extended follow-up data from participants with different follow-up durations using all data until last participant visit. We present the DPM model developed by using the DIAN observational study data and demonstrate through simulation that the cognitive DPM used in hypothetical intervention clinical trials produces substantial gains in power compared with the MMRM.

The DIAN-TU Next Generation Alzheimer's prevention trial: Adaptive design and disease progression model.

INTRODUCTION: The Dominantly Inherited Alzheimer Network Trials Unit (DIAN-TU) trial is an adaptive platform trial testing multiple drugs to slow or prevent the progression of Alzheimer's disease in autosomal dominant Alzheimer's disease (ADAD) families. With completion of enrollment of the first two drug arms, the DIAN-TU now plans to add new drugs to the platform, designated as the Next Generation (NexGen) prevention trial. METHODS: In collaboration with ADAD families, philanthropic organizations, academic leaders, the DIAN-TU Pharma Consortium, the National Institutes of Health, and regulatory colleagues, the DIAN-TU developed innovative clinical study designs for the DIAN-TU NexGen prevention trial. RESULTS: Our expanded trial toolbox consists of a disease progression model for ADAD, primary end point DIAN-TU cognitive performance composite, biomarker development, self-administered cognitive assessments, adaptive dose adjustments, and blinded data collection through the last participant completion. CONCLUSION: These steps represent elements to improve efficacy of the adaptive platform trial and a continued effort to optimize prevention and treatment trials in ADAD.

Building efficient comparative effectiveness trials through adaptive designs, utility functions, and accrual rate optimization: finding the sweet spot.

The time is right for the use of Bayesian Adaptive Designs (BAD) in comparative effectiveness trials. For example, Patient Centered Outcomes Research Institute has joined the Food and Drug Administration and National Intitutes of Health in adopting policies/guidelines encouraging their use. There are multiple aspects to BAD that need to be considered when designing a comparative effectiveness design. First, the adaptation rules can determine the expected size of the trial. Second, a utility function can be used to combine extremely important co-endpoints (e.g., efficacy and tolerability) and is a valuable tool for incorporating clinical expertise and potentially patient preference. Third, accrual rate is also very, very important. Specifically, there is a juxtaposition related to accrual and BAD. If accrual rate is too fast we never gain efficient information for adapting. If accrual rate is too slow we never finish the clinical trial. We propose methodology for finding the 'sweet spot' for BAD that addresses these as design parameters. We demonstrate the methodology on a comparative effectiveness BAD of pharmaceutical agents in cryptogenic sensory polyneuropathy. The study has five arms with two endpoints that are combined with a utility function. The accrual rate is assumed to stem from multiple sites. We perform simulations from which the composite accrual rates across sites result in various piecewise Poisson distributions as parameter inputs. We balance both average number of patients needed and average length of time to finish the study.

Pathological response in resectable non-small cell lung cancer: a systematic literature review and meta-analysis.

BACKGROUND: Surrogate endpoints for overall survival in patients with resectable non-small cell lung cancer receiving neoadjuvant therapy are needed to provide earlier treatment outcome indicators and accelerate drug approval. This study's main objectives were to investigate the association among pathological complete response, major pathological response, event-free survival and overall survival and to determine whether treatment effects on pathological complete response and event-free survival correlate with treatment effects on overall survival. METHODS: A comprehensive systematic literature review was conducted to identify neoadjuvant studies in resectable non-small cell lung cancer. Analysis at the patient level using frequentist and Bayesian random effects (hazard ratio [HR] for overall survival or event-free survival by pathological complete response or major pathological response status, yes vs no) and at the trial level using weighted least squares regressions (hazard ratio for overall survival or event-free survival vs pathological complete response, by treatment arm) were performed. RESULTS: In both meta-analyses, pathological complete response yielded favorable overall survival compared with no pathological complete response (frequentist, 20 studies and 6530 patients: HR = 0.49, 95% confidence interval = 0.42 to 0.57; Bayesian, 19 studies and 5988 patients: HR = 0.48, 95% probability interval = 0.43 to 0.55) and similarly for major pathological response (frequentist, 12 studies and 1193 patients: HR = 0.36, 95% confidence interval = 0.29 to 0.44; Bayesian, 11 studies and 1018 patients: HR = 0.33, 95% probability interval = 0.26 to 0.42). Across subgroups, estimates consistently showed better overall survival or event-free survival in pathological complete response or major pathological response compared with no pathological complete response or no major pathological response. Trial-level analyses showed a moderate to strong correlation between event-free survival and overall survival hazard ratios (R2 = 0.7159) but did not show a correlation between treatment effects on pathological complete response and overall survival or event-free survival. CONCLUSION: There was a strong and consistent association between pathological response and survival and a moderate to strong correlation between event-free survival and overall survival following neoadjuvant therapy for patients with resectable non-small cell lung cancer.

Incorporating prior biologic information for high-dimensional rare variant association studies.

BACKGROUND: Given the increasing scale of rare variant association studies, we introduce a method for high-dimensional studies that integrates multiple sources of data as well as allows for multiple region-specific risk indices. METHODS: Our method builds upon the previous Bayesian risk index by integrating external biological variant-specific covariates to help guide the selection of associated variants and regions. Our extension also incorporates a second level of uncertainty as to which regions are associated with the outcome of interest. RESULTS: Using a set of study-based simulations, we show that our approach leads to an increase in power to detect true associations in comparison to several commonly used alternatives. Additionally, the method provides multi-level inference at the pathway, region and variant levels. CONCLUSION: To demonstrate the flexibility of the method to incorporate various types of information and the applicability to high-dimensional data, we apply our method to a single region within a candidate gene study of second primary breast cancer and to multiple regions within a candidate pathway study of colon cancer.

Analysis of sodium phenylbutyrate and taurursodiol survival effect in ALS using external controls.

OBJECTIVE: Sodium phenylbutyrate and taurursodiol (PB and TURSO) was evaluated in amyotrophic lateral sclerosis (ALS) in the CENTAUR trial encompassing randomized placebo-controlled and open-label extension phases. On intent-to-treat (ITT) survival analysis, median overall survival (OS) was 4.8 months longer and risk of death 36% lower in those originally randomized to an initial 6-month double-blind period of PB and TURSO versus placebo. To estimate PB and TURSO treatment effect without placebo-to-active crossover, we performed a post hoc survival analysis comparing PB and TURSO-randomized participants from CENTAUR and a propensity score-matched, PB and TURSO-naïve external control cohort from the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database. METHODS: Clinical trial control participants from the PRO-ACT database who met prespecified eligibility criteria were propensity score matched 1:1 with PB and TURSO-randomized CENTAUR participants using prognostically significant covariates in ALS. RESULTS: Baseline characteristics including propensity score-matched covariates were generally well balanced between CENTAUR PB and TURSO (n = 89) and PRO-ACT external control (n = 85) groups. Estimated median (IQR) OS was 23.54 (14.56-39.32) months in the CENTAUR PB and TURSO group and 13.15 (9.83-19.20) months in the PRO-ACT external control group; hazard of death was 52% lower in the former group (hazard ratio, 0.48; 95% CI, 0.31-0.72; p = 0.00048). INTERPRETATION: This analysis suggests potentially greater survival benefit with PB and TURSO in ALS without placebo-to-active crossover than seen on ITT analysis in CENTAUR. Analyses using well-matched external controls may provide additional context for evaluating survival effects in future ALS trials.

Incorporating model uncertainty in detecting rare variants: the Bayesian risk index.

We are interested in investigating the involvement of multiple rare variants within a given region by conducting analyses of individual regions with two goals: (1) to determine if regional rare variation in aggregate is associated with risk; and (2) conditional upon the region being associated, to identify specific genetic variants within the region that are driving the association. In particular, we seek a formal integrated analysis that achieves both of our goals. For rare variants with low minor allele frequencies, there is very little power to statistically test the null hypothesis of equal allele or genotype counts for each variant. Thus, genetic association studies are often limited to detecting association within a subset of the common genetic markers. However, it is very likely that associations exist for the rare variants that may not be captured by the set of common markers. Our framework aims at constructing a risk index based on multiple rare variants within a region. Our analytical strategy is novel in that we use a Bayesian approach to incorporate model uncertainty in the selection of variants to include in the index as well as the direction of the associated effects. Additionally, the approach allows for inference at both the group and variant-specific levels. Using a set of simulations, we show that our methodology has added power over other popular rare variant methods to detect global associations. In addition, we apply the approach to sequence data from the WECARE Study of second primary breast cancers.

Temporal order of clinical and biomarker changes in familial frontotemporal dementia.

Unlike familial Alzheimer's disease, we have been unable to accurately predict symptom onset in presymptomatic familial frontotemporal dementia (f-FTD) mutation carriers, which is a major hurdle to designing disease prevention trials. We developed multimodal models for f-FTD disease progression and estimated clinical trial sample sizes in C9orf72, GRN and MAPT mutation carriers. Models included longitudinal clinical and neuropsychological scores, regional brain volumes and plasma neurofilament light chain (NfL) in 796 carriers and 412 noncarrier controls. We found that the temporal ordering of clinical and biomarker progression differed by genotype. In prevention-trial simulations using model-based patient selection, atrophy and NfL were the best endpoints, whereas clinical measures were potential endpoints in early symptomatic trials. f-FTD prevention trials are feasible but will likely require global recruitment efforts. These disease progression models will facilitate the planning of f-FTD clinical trials, including the selection of optimal endpoints and enrollment criteria to maximize power to detect treatment effects.

Rare Variants in the DNA Repair Pathway and the Risk of Colorectal Cancer.

BACKGROUND: Inherited susceptibility is an important contributor to colorectal cancer risk, and rare variants in key genes or pathways could account in part for the missing proportion of colorectal cancer heritability. METHODS: We conducted an exome-wide association study including 2,327 cases and 2,966 controls of European ancestry from three large epidemiologic studies. Single variant associations were tested using logistic regression models, adjusting for appropriate study-specific covariates. In addition, we examined the aggregate effects of rare coding variation at the gene and pathway levels using Bayesian model uncertainty techniques. RESULTS: In an exome-wide gene-level analysis, we identified ST6GALNAC2 as the top associated gene based on the Bayesian risk index (BRI) method [summary Bayes factor (BF)BRI = 2604.23]. A rare coding variant in this gene, rs139401613, was the top associated variant (P = 1.01 × 10-6) in an exome-wide single variant analysis. Pathway-level association analyses based on the integrative BRI (iBRI) method found extreme evidence of association with the DNA repair pathway (BFiBRI = 17852.4), specifically with the nonhomologous end joining (BFiBRI = 437.95) and nucleotide excision repair (BFiBRI = 36.96) subpathways. The iBRI method also identified RPA2, PRKDC, ERCC5, and ERCC8 as the top associated DNA repair genes (summary BFiBRI ≥ 10), with rs28988897, rs8178232, rs141369732, and rs201642761 being the most likely associated variants in these genes, respectively. CONCLUSIONS: We identified novel variants and genes associated with colorectal cancer risk and provided additional evidence for a role of DNA repair in colorectal cancer tumorigenesis. IMPACT: This study provides new insights into the genetic predisposition to colorectal cancer, which has potential for translation into improved risk prediction.

Value-Generating Exploratory Trials in Neurodegenerative Dementias.

Drug development for Alzheimer disease and other neurodegenerative dementias, including frontotemporal dementia, has experienced a long history of phase 2 and phase 3 clinical trials that failed to show efficacy of investigational drugs. Despite differences in clinical and behavioral characteristics, these disorders have shared pathologies and face common challenges in designing early-phase trials that are predictive of late-stage success. Here, we discuss exploratory clinical trials in neurodegenerative dementias. These are generally phase 1b or phase 2a trials that are designed to assess pharmacologic effects and rely on biomarker outcomes, with shorter treatment durations and fewer patients than traditional phase 2 studies. Exploratory trials can establish go/no-go decision points, support proof of concept and dose selection, and terminate drugs that fail to show target engagement with suitable exposure and acceptable safety profiles. Early failure saves valuable resources including opportunity costs. This is especially important for programs in academia and small biotechnology companies but may be applied to high-risk projects in large pharmaceutical companies to achieve proof of concept more rapidly at lower costs than traditional approaches. Exploratory studies in a staged clinical development program may provide promising data to warrant the substantial resources needed to advance compounds through late-stage development. To optimize the design and application of exploratory trials, the Alzheimer's Drug Discovery Foundation and the Association for Frontotemporal Degeneration convened an advisory panel to provide recommendations on outcome measures and statistical considerations for these types of studies and study designs that can improve efficiency in clinical development.

Strategies to Promote ResiliencY (SPRY): a randomised embedded multifactorial adaptative platform (REMAP) clinical trial protocol to study interventions to improve recovery after surgery in high-risk patients.

INTRODUCTION: As the population ages, there is interest in strategies to promote resiliency, especially for frail patients at risk of its complications. The physiological stress of surgery in high-risk individuals has been proposed both as an important cause of accelerated age-related decline in health and as a model testing the effectiveness of strategies to improve resiliency to age-related health decline. We describe a randomised, embedded, multifactorial, adaptative platform (REMAP) trial to investigate multiple perioperative interventions, the first of which is metformin and selected for its anti-inflammatory and anti-ageing properties beyond its traditional blood glucose control features. METHODS AND ANALYSIS: Within a multihospital, single healthcare system, the Core Protocol for Strategies to Promote ResiliencY (SPRY) will be embedded within both the electronic health record (EHR) and the healthcare culture generating a continuously self-learning healthcare system. Embedding reduces the administrative burden of a traditional trial while accessing and rapidly analysing routine patient care EHR data. SPRY-Metformin is a placebo-controlled trial and is the first SPRY domain evaluating the effectiveness of three metformin dosages across three preoperative durations within a heterogeneous set of major surgical procedures. The primary outcome is 90-day hospital-free days. Bayesian posterior probabilities guide interim decision-making with predefined rules to determine stopping for futility or superior dosing selection. Using response adaptative randomisation, a maximum of 2500 patients allows 77%-92% power, detecting >15% primary outcome improvement. Secondary outcomes include mortality, readmission and postoperative complications. A subset of patients will be selected for substudies evaluating the microbiome, cognition, postoperative delirium and strength. ETHICS AND DISSEMINATION: The Core Protocol of SPRY REMAP and associated SPRY-Metformin Domain-Specific Appendix have been ethically approved by the Institutional Review Board and are publicly registered. Results will be publicly available to healthcare providers, patients and trial participants following achieving predetermined platform conclusions. TRIAL REGISTRATION NUMBER: NCT03861767.

A Bayesian adaptive phase 1 design to determine the optimal dose and schedule of an adoptive T-cell therapy in a mixed patient population.

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.

Association of Pathologic Complete Response to Neoadjuvant Therapy in HER2-Positive Breast Cancer With Long-Term Outcomes: A Meta-Analysis.

IMPORTANCE: The expense and lengthy follow-up periods for randomized clinical trials (RCTs) of adjuvant systemic therapy in breast cancer make them impractical and even impossible to conduct. Randomized clinical trials of neoadjuvant systemic therapy for breast cancer may help resolve this dilemma. OBJECTIVE: To assess the utility of pathologic complete response (pCR) for neoadjuvant drug development in human epidermal growth factor receptor 2 (HER2 [also referred to as ERBB2])-positive breast cancer. DATA SOURCES: We searched MEDLINE (Ovid), Embase (Ovid), CENTRAL (Wiley), and Northern Light Life Sciences Conference Abstracts (Ovid) in December 2014. Searches combined terms for "breast cancer" and "neoadjuvant therapy," with no limit on publication date. STUDY SELECTION: Cohort studies and RCTs were selected that met following criteria: stages I to III HER2-positive breast cancer, neoadjuvant therapy, and reports of both pCR and an event-free survival (EFS)-type outcome. The initial search identified 2614 publications, of which 38 studies met the selection criteria. DATA EXTRACTION AND SYNTHESIS: Two authors independently screened each study for inclusion and extracted the data. Data were analyzed using Bayesian hierarchical models. MAIN OUTCOMES AND MEASURES: Event-free survival and overall survival (OS) hazard ratios (HRs) for pCR vs non-pCR. For RCTs, main outcome measures were treatment benefits in pCR and the corresponding treatment HRs for EFS and OS. RESULTS: A total of 36 studies with EFS by pCR status representing 5768 patients with HER2-positive breast cancer were included in the patient-level analysis. Overall, the improvement in EFS for pCR vs non-pCR was substantial: HR, 0.37 (95% probability interval [PI], 0.32-0.43). This association was greater for patients with hormone receptor-negative disease (HR, 0.29 [95% PI, 0.24-0.36]) than hormone receptor-positive disease (HR, 0.52 [95% PI, 0.40-0.66]). In RCTs, the R2 correlations between odds ratios for pCR and HRs were 0.63 for EFS and 0.29 for OS. Based on absolute treatment improvements in pCR rate, predicted HRs for EFS for RCTs were concordant with observed HRs. CONCLUSIONS AND RELEVANCE: Pathologic complete response in HER2-positive breast cancer is associated with substantially longer times to recurrence and death. This relationship is maintained in RCTs. For any particular new therapy the relationship between pCR and survival may differ. Quantifying the importance of pCR is necessary for designing efficient clinical trials, which should adapt to the relationship between pCR and survival for the therapy under investigation.

A Bayesian comparative effectiveness trial in action: developing a platform for multisite study adaptive randomization.

BACKGROUND: In the last few decades, the number of trials using Bayesian methods has grown rapidly. Publications prior to 1990 included only three clinical trials that used Bayesian methods, but that number quickly jumped to 19 in the 1990s and to 99 from 2000 to 2012. While this literature provides many examples of Bayesian Adaptive Designs (BAD), none of the papers that are available walks the reader through the detailed process of conducting a BAD. This paper fills that gap by describing the BAD process used for one comparative effectiveness trial (Patient Assisted Intervention for Neuropathy: Comparison of Treatment in Real Life Situations) that can be generalized for use by others. A BAD was chosen with efficiency in mind. Response-adaptive randomization allows the potential for substantially smaller sample sizes, and can provide faster conclusions about which treatment or treatments are most effective. An Internet-based electronic data capture tool, which features a randomization module, facilitated data capture across study sites and an in-house computation software program was developed to implement the response-adaptive randomization. RESULTS: A process for adapting randomization with minimal interruption to study sites was developed. A new randomization table can be generated quickly and can be seamlessly integrated in the data capture tool with minimal interruption to study sites. CONCLUSION: This manuscript is the first to detail the technical process used to evaluate a multisite comparative effectiveness trial using adaptive randomization. An important opportunity for the application of Bayesian trials is in comparative effectiveness trials. The specific case study presented in this paper can be used as a model for conducting future clinical trials using a combination of statistical software and a web-based application. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02260388 , registered on 6 October 2014.