Protocol for the Prone and Oscillation Pediatric Clinical Trial (PROSpect).

OBJECTIVES: Respiratory management for pediatric acute respiratory distress syndrome (PARDS) remains largely supportive without data to support one approach over another, including supine versus prone positioning (PP) and conventional mechanical ventilation (CMV) versus high-frequency oscillatory ventilation (HFOV). DESIGN: We present the research methodology of a global, multicenter, two-by-two factorial, response-adaptive, randomized controlled trial of supine versus PP and CMV versus HFOV in high moderate-severe PARDS, the Prone and Oscillation Pediatric Clinical Trial (PROSpect, www.ClinicalTrials.gov, NCT03896763). SETTING: Approximately 60 PICUs with on-site extracorporeal membrane oxygenation support in North and South America, Europe, Asia, and Oceania with experience using PP and HFOV in the care of patients with PARDS. PATIENTS: Eligible pediatric patients (2 wk old or older and younger than 21 yr) are randomized within 48 h of meeting eligibility criteria occurring within 96 h of endotracheal intubation. INTERVENTIONS: One of four arms, including supine/CMV, prone/CMV, supine/HFOV, or prone/HFOV. We hypothesize that children with high moderate-severe PARDS treated with PP or HFOV will demonstrate greater than or equal to 2 additional ventilator-free days (VFD). MEASUREMENTS AND MAIN RESULTS: The primary outcome is VFD through day 28; nonsurvivors receive zero VFD. Secondary and exploratory outcomes include nonpulmonary organ failure-free days, interaction effects of PP with HFOV on VFD, 90-day in-hospital mortality, and among survivors, duration of mechanical ventilation, PICU and hospital length of stay, and post-PICU functional status and health-related quality of life. Up to 600 patients will be randomized, stratified by age group and direct/indirect lung injury. Adaptive randomization will first occur 28 days after 300 patients are randomized and every 100 patients thereafter. At these randomization updates, new allocation probabilities will be computed based on intention-to-treat trial results, increasing allocation to well-performing arms and decreasing allocation to poorly performing arms. Data will be analyzed per intention-to-treat for the primary analyses and per-protocol for primary, secondary, and exploratory analyses. CONCLUSIONS: PROSpect will provide clinicians with data to inform the practice of PP and HFOV in PARDS.

Optimal sample size division in two-stage seamless designs.

Inferentially seamless 2/3 designs are increasingly popular in clinical trials. It is important to understand their relative advantages compared with separate phase 2 and phase 3 trials, and to understand the consequences of design choices such as the proportion of patients included in the phase 2 portion of the design. Extending previous work in this area, we perform a simulation study across multiple numbers of arms and efficacy response curves. We consider a design space crossing the choice of a separate versus seamless design with the choice of allocating 0%-100% of available patients in phase 2, with the remainder in phase 3. The seamless designs achieve greater power than their separate trial counterparts. Importantly, the optimal seamless design is more robust than the optimal separate program, meaning that one range of values for the proportion of patients used in phase 2 (30%-50% of the total phase 2/3 sample size) is nearly optimal for a wide range of response scenarios. In contrast, a percentage of patients used in phase 2 for separate trials may be optimal for some alternative scenarios but decidedly inferior for other alternative scenarios. When operationally and scientifically viable, seamless trials provide superior performance compared with separate phase 2 and phase 3 trials. The results also provide guidance for the implementation of these trials in practice.

Allocation in platform trials to maintain comparability across time and eligibility.

Platform trials, with arms entering and leaving the trial over time, are complex. In addition to trial changes over time, certain arms in a platform may come with patient restrictions. Both of these issues (time and eligibility) can create biases in comparing active arms to control. The largest of these biases, using non-concurrent controls or including control patients that were ineligible for an active arm, have been extensively discussed in the literature. Here we show that even restricting to concurrent, eligible controls can induce biases if proper allocation ratios are not maintained throughout the platform. We also build on results in Ventz et al. Biostat., 19:199-215, 2018 to describe an algorithm that guarantees comparability between active and control groups in arm analyses in both time and eligibility, and allows for both re-randomization of patients and two-stage randomization procedures. The resulting method is both flexible and easily implemented, allowing robust comparisons when assumptions that underlie alternative randomization methods are in doubt.

Design and logistical considerations for the randomized adaptive non-inferiority storage-duration-ranging CHIlled Platelet Study.

BACKGROUND: Platelet transfusion is a potentially life-saving therapy for actively bleeding patients, ranging from those undergoing planned surgical procedures to those suffering unexpected traumatic injuries. Platelets are currently stored at room temperature (20°C-24°C) with a maximum storage duration of 7 days after donation. The CHIlled Platelet Study trial will compare the efficacy and safety of standard room temperature-stored platelets with platelets that are cold-stored (1°C-6°C), that is, chilled, with a maximum of storage up to 21 days in adult and pediatric patients undergoing complex cardiac surgical procedures. METHODS/RESULTS: CHIlled Platelet Study will use a Bayesian adaptive design to identify the range of cold storage durations for platelets that are non-inferior to standard room temperature-stored platelets. If cold-stored platelets are non-inferior at durations greater than 7 days, a gated superiority analysis will identify durations for which cold-stored platelets may be superior to standard platelets. We present example simulations of the CHIlled Platelet Study design and discuss unique challenges in trial implementation. The CHIlled Platelet Study trial has been funded and will be implemented in approximately 20 clinical centers. Early randomization to enable procurement of cold-stored platelets with different storage durations will be required, as well as a platelet tracking system to eliminate platelet wastage and maximize trial efficiency and economy. DISCUSSION: The CHIlled Platelet Study trial will determine whether cold-stored platelets are non-inferior to platelets stored at room temperature, and if so, will determine the maximum duration (up to 21 days) of storage that maintains non-inferiority. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04834414.

National Institutes of Health Stroke Scale as an Outcome in Stroke Research: Value of ANCOVA Over Analyzing Change From Baseline.

National Institutes of Health Stroke Scale (NIHSS), measured a few hours to days after stroke onset, is an attractive outcome measure for stroke research. NIHSS at the time of presentation (baseline NIHSS) strongly predicts the follow-up NIHSS. Because of the need to account for the baseline NIHSS in the analysis of follow-up NIHSS as an outcome measure, a common and intuitive approach is to define study outcome as the change in NIHSS from baseline to follow-up (ΔNIHSS). However, this approach has important limitations. Analyzing ΔNIHSS implies a very strong assumption about the relationship between baseline and follow-up NIHSS that is unlikely to be satisfied, drawing into question the validity of the resulting statistical analysis. This reduces the precision of the estimates of treatment effects and the power of clinical trials that use this approach to analysis. ANCOVA allows for the analysis of follow-up NIHSS as the dependent variable while adjusting for baseline NIHSS as a covariate in the model and addresses several challenges of using ΔNIHSS outcome using simple bivariate comparisons (eg, a t test, Wilcoxon rank-sum, linear regression without adjustment for baseline) for stroke research. In this article, we use clinical trial simulations to illustrate that variability in NIHSS outcome is less when follow-up NIHSS is adjusted for baseline compared to ΔNIHSS and how a reduction in this variability improves the power. We outline additional, important clinical and statistical arguments to support the superiority of ANCOVA using the final measurement of the NIHSS adjusted for baseline over, and caution against using, the simple bivariate comparison of absolute NIHSS change (ie, delta).

On model-based time trend adjustments in platform trials with non-concurrent controls.

BACKGROUND: Platform trials can evaluate the efficacy of several experimental treatments compared to a control. The number of experimental treatments is not fixed, as arms may be added or removed as the trial progresses. Platform trials are more efficient than independent parallel group trials because of using shared control groups. However, for a treatment entering the trial at a later time point, the control group is divided into concurrent controls, consisting of patients randomised to control when that treatment arm is in the platform, and non-concurrent controls, patients randomised before. Using non-concurrent controls in addition to concurrent controls can improve the trial's efficiency by increasing power and reducing the required sample size, but can introduce bias due to time trends. METHODS: We focus on a platform trial with two treatment arms and a common control arm. Assuming that the second treatment arm is added at a later time, we assess the robustness of recently proposed model-based approaches to adjust for time trends when utilizing non-concurrent controls. In particular, we consider approaches where time trends are modeled either as linear in time or as a step function, with steps at time points where treatments enter or leave the platform trial. For trials with continuous or binary outcomes, we investigate the type 1 error rate and power of testing the efficacy of the newly added arm, as well as the bias and root mean squared error of treatment effect estimates under a range of scenarios. In addition to scenarios where time trends are equal across arms, we investigate settings with different time trends or time trends that are not additive in the scale of the model. RESULTS: A step function model, fitted on data from all treatment arms, gives increased power while controlling the type 1 error, as long as the time trends are equal for the different arms and additive on the model scale. This holds even if the shape of the time trend deviates from a step function when patients are allocated to arms by block randomisation. However, if time trends differ between arms or are not additive to treatment effects in the scale of the model, the type 1 error rate may be inflated. CONCLUSIONS: The efficiency gained by using step function models to incorporate non-concurrent controls can outweigh potential risks of biases, especially in settings with small sample sizes. Such biases may arise if the model assumptions of equality and additivity of time trends are not satisfied. However, the specifics of the trial, scientific plausibility of different time trends, and robustness of results should be carefully considered.

The Bayesian Time Machine: Accounting for temporal drift in multi-arm platform trials.

BACKGROUND: Multi-arm platform trials investigate multiple agents simultaneously, typically with staggered entry and exit of experimental treatment arms versus a shared control arm. In such settings, there is considerable debate whether to limit analyses for a treatment arm to concurrent randomized control subjects or to allow comparisons to both concurrent and non-concurrent (pooled) control subjects. The potential bias from temporal drift over time is at the core of this debate. METHODS: We propose time-adjusted analyses, including a "Bayesian Time Machine," to model potential temporal drift in the entire study population, such that primary analyses can incorporate all randomized control subjects from the platform trial. We conduct a simulation study to assess performance relative to utilizing concurrent or pooled controls. RESULTS: In multi-arm platform trials with staggered entry, analyses adjusting for temporal drift (either Bayesian or frequentist) have superior estimation of treatment effects and favorable testing properties compared to analyses using either concurrent or pooled controls. The Bayesian Time Machine generally provides estimates with greater precision and smaller mean square error than alternative approaches, at the risk of small bias and small Type I error inflation. CONCLUSIONS: The Bayesian Time Machine provides a compromise between bias and precision by smoothing estimates across time and leveraging all available data for the estimation of treatment effects. Prior distributions controlling the behavior of dynamic smoothing across time must be pre-specified and carefully calibrated to the unique context of each trial, appropriately accounting for the population, disease, and endpoints.

Hypothermia for Patients Requiring Evacuation of Subdural Hematoma: A Multicenter Randomized Clinical Trial.

BACKGROUND: Hypothermia is neuroprotective in some ischemia-reperfusion injuries. Ischemia-reperfusion injury may occur with traumatic subdural hematoma (SDH). This study aimed to determine whether early induction and maintenance of hypothermia in patients with acute SDH would lead to decreased ischemia-reperfusion injury and improve global neurologic outcome. METHODS: This international, multicenter randomized controlled trial enrolled adult patients with SDH requiring evacuation of hematoma within 6 h of injury. The intervention was controlled temperature management of hypothermia to 35 °C prior to dura opening followed by 33 °C for 48 h compared with normothermia (37 °C). Investigators randomly assigned patients at a 1:1 ratio between hypothermia and normothermia. Blinded evaluators assessed outcome using a 6-month Glasgow Outcome Scale Extended score. Investigators measured circulating glial fibrillary acidic protein and ubiquitin C-terminal hydrolase L1 levels. RESULTS: Independent statisticians performed an interim analysis of 31 patients to assess the predictive probability of success and the Data and Safety Monitoring Board recommended the early termination of the study because of futility. Thirty-two patients, 16 per arm, were analyzed. Favorable 6-month Glasgow Outcome Scale Extended outcomes were not statistically significantly different between hypothermia vs. normothermia groups (6 of 16, 38% vs. 4 of 16, 25%; odds ratio 1.8 [95% confidence interval 0.39 to ∞], p = .35). Plasma levels of glial fibrillary acidic protein (p = .036), but not ubiquitin C-terminal hydrolase L1 (p = .26), were lower in the patients with favorable outcome compared with those with unfavorable outcome, but differences were not identified by temperature group. Adverse events were similar between groups. CONCLUSIONS: This trial of hypothermia after acute SDH evacuation was terminated because of a low predictive probability of meeting the study objectives. There was no statistically significant difference in functional outcome identified between temperature groups.

Effect of Vitamin C, Thiamine, and Hydrocortisone on Ventilator- and Vasopressor-Free Days in Patients With Sepsis: The VICTAS Randomized Clinical Trial.

Importance: Sepsis is a common syndrome with substantial morbidity and mortality. A combination of vitamin C, thiamine, and corticosteroids has been proposed as a potential treatment for patients with sepsis. Objective: To determine whether a combination of vitamin C, thiamine, and hydrocortisone every 6 hours increases ventilator- and vasopressor-free days compared with placebo in patients with sepsis. Design, Setting, and Participants: Multicenter, randomized, double-blind, adaptive-sample-size, placebo-controlled trial conducted in adult patients with sepsis-induced respiratory and/or cardiovascular dysfunction. Participants were enrolled in the emergency departments or intensive care units at 43 hospitals in the United States between August 2018 and July 2019. After enrollment of 501 participants, funding was withheld, leading to an administrative termination of the trial. All study-related follow-up was completed by January 2020. Interventions: Participants were randomized to receive intravenous vitamin C (1.5 g), thiamine (100 mg), and hydrocortisone (50 mg) every 6 hours (n = 252) or matching placebo (n = 249) for 96 hours or until discharge from the intensive care unit or death. Participants could be treated with open-label corticosteroids by the clinical team, with study hydrocortisone or matching placebo withheld if the total daily dose was greater or equal to the equivalent of 200 mg of hydrocortisone. Main Outcomes and Measures: The primary outcome was the number of consecutive ventilator- and vasopressor-free days in the first 30 days following the day of randomization. The key secondary outcome was 30-day mortality. Results: Among 501 participants randomized (median age, 62 [interquartile range {IQR}, 50-70] years; 46% female; 30% Black; median Acute Physiology and Chronic Health Evaluation II score, 27 [IQR, 20.8-33.0]; median Sequential Organ Failure Assessment score, 9 [IQR, 7-12]), all completed the trial. Open-label corticosteroids were prescribed to 33% and 32% of the intervention and control groups, respectively. Ventilator- and vasopressor-free days were a median of 25 days (IQR, 0-29 days) in the intervention group and 26 days (IQR, 0-28 days) in the placebo group, with a median difference of -1 day (95% CI, -4 to 2 days; P = .85). Thirty-day mortality was 22% in the intervention group and 24% in the placebo group. Conclusions and Relevance: Among critically ill patients with sepsis, treatment with vitamin C, thiamine, and hydrocortisone, compared with placebo, did not significantly increase ventilator- and vasopressor-free days within 30 days. However, the trial was terminated early for administrative reasons and may have been underpowered to detect a clinically important difference. Trial Registration: ClinicalTrials.gov Identifier: NCT03509350.

Dabrafenib plus trametinib in patients with BRAFV600E-mutated biliary tract cancer (ROAR): a phase 2, open-label, single-arm, multicentre basket trial.

BACKGROUND: Effective treatments for patients with cholangiocarcinoma after progression on gemcitabine-based chemotherapy are urgently needed. Mutations in the BRAF gene have been found in 5% of biliary tract tumours. The combination of dabrafenib and trametinib has shown activity in several BRAFV600E-mutated cancers. We aimed to assess the activity and safety of dabrafenib and trametinib combination therapy in patients with BRAFV600E-mutated biliary tract cancer. METHODS: This study is part of an ongoing, phase 2, open-label, single-arm, multicentre, Rare Oncology Agnostic Research (ROAR) basket trial in patients with BRAFV600E-mutated rare cancers. Patients were eligible for the biliary tract cancer cohort if they were aged 18 years or older, had BRAFV600E-mutated, unresectable, metastatic, locally advanced, or recurrent biliary tract cancer, an Eastern Cooperative Oncology Group performance status of 0-2, and had received previous systemic treatment. All patients were treated with oral dabrafenib 150 mg twice daily and oral trametinib 2 mg once daily until disease progression or intolerance of treatment. The primary endpoint was the overall response rate, which was determined by Response Evaluation Criteria in Solid Tumors version 1.1 in the intention-to-treat evaluable population, which comprised all enrolled patients regardless of receiving treatment who were evaluable (ie, had progression, began a new anticancer treatment, withdrew consent, died, had stable disease for 6 weeks or longer, or had two or more post-baseline assessments). The ROAR trial is registered with ClinicalTrials.gov, NCT02034110. These results are based on an interim analysis; the study is active but not recruiting. FINDINGS: Between March 12, 2014, and July 18, 2018, 43 patients with BRAFV600E-mutated biliary tract cancer were enrolled to the study and were evaluable. Median follow-up was 10 months (IQR 6-15). An investigator-assessed overall response was achieved by 22 (51%, 95% CI 36-67) of 43 patients. An independent reviewer-assessed overall response was achieved by 20 (47%, 95% CI 31-62) of 43 patients. The most common grade 3 or worse adverse event was increased γ-glutamyltransferase in five (12%) patients. 17 (40%) patients had serious adverse events and nine (21%) had treatment-related serious adverse events, the most frequent of which was pyrexia (eight [19%]). No treatment-related deaths were reported. INTERPRETATION: Dabrafenib plus trametinib combination treatment showed promising activity in patients with BRAFV600E-mutated biliary tract cancer, with a manageable safety profile. Routine testing for BRAFV600E mutations should be considered in patients with biliary tract cancer. FUNDING: GlaxoSmithKline and Novartis.

Comparison of methods for control allocation in multiple arm studies using response adaptive randomization.

BACKGROUND/AIMS: Response adaptive randomization has many polarizing properties in two-arm settings comparing control to a single treatment. The generalization of these features to the multiple arm setting has been less explored, and existing comparisons in the literature reach disparate conclusions. We investigate several generalizations of two-arm response adaptive randomization methods relating to control allocation in multiple arm trials, exploring how critiques of response adaptive randomization generalize to the multiple arm setting. METHODS: We perform a simulation study to investigate multiple control allocation schemes within response adaptive randomization, comparing the designs on metrics such as power, arm selection, mean square error, and the treatment of patients within the trial. RESULTS: The results indicate that the generalization of two-arm response adaptive randomization concerns is variable and depends on the form of control allocation employed. The concerns are amplified when control allocation may be reduced over the course of the trial but are mitigated in the methods considered when control allocation is maintained or increased during the trial. In our chosen example, we find minimal advantage to increasing, as opposed to maintaining, control allocation; however, this result reflects an extremely limited exploration of methods for increasing control allocation. CONCLUSION: Selection of control allocation in multiple arm response adaptive randomization has a large effect on the performance of the design. Some disparate comparisons of response adaptive randomization to alternative paradigms may be partially explained by these results. In future comparisons, control allocation for multiple arm response adaptive randomization should be chosen to keep in mind the appropriate match between control allocation in response adaptive randomization and the metric or metrics of interest.

Comparison of response adaptive randomization features in multiarm clinical trials with control.

We investigate multiple features of response adaptive randomization (RAR) in the context of a multiple arm randomized trial with control, where the primary goal is the identification of the best arm for use in a broader patient population. We maintain constant control allocation and vary the length of time until RAR is started, interim frequency, the underlying quantity used to calculate the randomization probabilities, and a threshold resulting in temporary arm dropping. We evaluate the designs on five metrics measuring benefit to the internal trial population, the future external population, and statistical estimation. Our results indicate these features have minimal interaction within the space explored, with preference for earlier activation of RAR, more frequent interim analyses, randomizing in proportion to the probability each arm is the best, and aggressive thresholding for temporarily dropping arms. The results illustrate useful principles for maximizing the benefit of RAR in practice.

A phase 1 and randomized controlled phase 2 trial of the safety and efficacy of the combination of gemcitabine and docetaxel with ontuxizumab (MORAb-004) in metastatic soft-tissue sarcomas.

BACKGROUND: Ontuxizumab, a humanized monoclonal antibody, targets endosialin (tumor endothelial marker 1 [TEM-1] or CD248), which is expressed on sarcoma cells and is believed to be involved in tumor angiogenesis. This is the first trial to evaluate ontuxizumab in patients with sarcoma. METHODS: Part 1 was an open-label, dose-finding, safety lead-in: 4, 6, or 8 mg/kg with gemcitabine and docetaxel (G/D; 900 mg/m2 gemcitabine on days 1 and 8 and 75 mg/m2 docetaxel on day 8). In part 2, patients were randomized in a double-blind fashion in 2:1 ratio to ontuxizumab (8 mg/kg) or a placebo with G/D. Randomization was stratified by 4 histological cohorts. RESULTS: In part 2 with 209 patients, no significant difference in progression-free survival between ontuxizumab plus G/D (4.3 months; 95% confidence interval [CI], 2.7-6.3 months) and the placebo plus G/D (5.6 months; 95% CI, 2.6-8.3 months) was observed (P = .67; hazard ratio [HR], 1.07; 95% CI, 0.77-1.49). Similarly, there was no significant difference in median overall survival between the 2 groups: 18.3 months for the ontuxizumab plus G/D group (95% CI, 16.2-21.1 months) and 21.1 months for the placebo plus G/D group (95% CI, 14.2 months to not reached; P = .32; HR, 1.23; 95% CI, 0.82-1.82). No significant differences between the treatment groups occurred for any efficacy parameter by sarcoma cohort. The combination of ontuxizumab plus G/D was generally well tolerated. CONCLUSIONS: Ontuxizumab plus G/D showed no enhanced activity over chemotherapy alone in soft-tissue sarcomas, whereas the safety profile of the combination was consistent with G/D alone.

Using Bayesian adaptive designs to improve phase III trials: a respiratory care example.

BACKGROUND: Bayesian adaptive designs can improve the efficiency of trials, and lead to trials that can produce high quality evidence more quickly, with fewer patients and lower costs than traditional methods. The aim of this work was to determine how Bayesian adaptive designs can be constructed for phase III clinical trials in critical care, and to assess the influence that Bayesian designs would have on trial efficiency and study results. METHODS: We re-designed the High Frequency OSCillation in Acute Respiratory distress syndrome (OSCAR) trial using Bayesian adaptive design methods, to allow for the possibility of early stopping for success or futility. We constructed several alternative designs and studied their operating characteristics via simulation. We then performed virtual re-executions by applying the Bayesian adaptive designs using the OSCAR data to demonstrate the practical applicability of the designs. RESULTS: We constructed five alternative Bayesian adaptive designs and identified a preferred design based on the simulated operating characteristics, which had similar power to the original design but recruited fewer patients on average. The virtual re-executions showed the Bayesian sequential approach and original OSCAR trial yielded similar trial conclusions. However, using a Bayesian sequential design could have led to a reduced sample size and earlier completion of the trial. CONCLUSIONS: Using the OSCAR trial as an example, this case study found that Bayesian adaptive designs can be constructed for phase III critical care trials. If the OSCAR trial had been run using one of the proposed Bayesian adaptive designs, it would have terminated at a smaller sample size with fewer deaths in the trial, whilst reaching the same conclusions. We recommend the wider use of Bayesian adaptive approaches in phase III clinical trials. TRIAL REGISTRATION: OSCAR Trial registration ISRCTN, ISRCTN10416500 . Retrospectively registered 13 June 2007.

Phase 3 adaptive trial design options in treatment of complicated urinary tract infection.

New antimicrobial drugs for treatment of complicated urinary tract infection (cUTI) are generally assessed in randomized, double-blind, noninferiority clinical trials. Robust historical data for the active comparator inform on treatment effect estimation, yet typically do not substitute for the active comparator data in the proposed trial. We report design options for a phase 3 trial of cUTI using a Bayesian hierarchical model and historical data from 2 well-executed phase 3 registrational trials of doripenem. The methodology is directly applicable to other phase 3 noninferiority settings. In addition to the research design application, we provide a novel methodology for assessing the robustness of type I error control. The model borrows heavily from the prior data when the current active comparator parameter estimate approximated the historical estimate. In contrast, the model had restricted borrowing when the 2 estimates were very different. The alternative trial design, with or without the inclusion of futility stopping criteria, provides a framework for future cUTI phase 3 trials.

Conditional Power: How Likely Is Trial Success?

This JAMA Guide to Statistics and Methods article examines conditional power, calculated while a trial is ongoing and based on both the currently observed data and an assumed treatment effect for future patients.

Use of historical control data for assessing treatment effects in clinical trials.

Clinical trials rarely, if ever, occur in a vacuum. Generally, large amounts of clinical data are available prior to the start of a study, particularly on the current study's control arm. There is obvious appeal in using (i.e., 'borrowing') this information. With historical data providing information on the control arm, more trial resources can be devoted to the novel treatment while retaining accurate estimates of the current control arm parameters. This can result in more accurate point estimates, increased power, and reduced type I error in clinical trials, provided the historical information is sufficiently similar to the current control data. If this assumption of similarity is not satisfied, however, one can acquire increased mean square error of point estimates due to bias and either reduced power or increased type I error depending on the direction of the bias. In this manuscript, we review several methods for historical borrowing, illustrating how key parameters in each method affect borrowing behavior, and then, we compare these methods on the basis of mean square error, power and type I error. We emphasize two main themes. First, we discuss the idea of 'dynamic' (versus 'static') borrowing. Second, we emphasize the decision process involved in determining whether or not to include historical borrowing in terms of the perceived likelihood that the current control arm is sufficiently similar to the historical data. Our goal is to provide a clear review of the key issues involved in historical borrowing and provide a comparison of several methods useful for practitioners.

An adaptive, phase II, dose-finding clinical trial design to evaluate L-carnitine in the treatment of septic shock based on efficacy and predictive probability of subsequent phase III success.

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.