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.

Futility in Clinical Trials.

This JAMA Guide to Statistics and Methods discusses the early stopping of clinical trials for futility due to lack of evidence supporting the desired benefit, evidence of harm, or practical issues that make successful completion unlikely.

Evaluation of dose-dependent treatment effects after mid-trial dose escalation in biomarker, clinical, and cognitive outcomes for gantenerumab or solanezumab in dominantly inherited Alzheimer's disease.

Introduction: While the Dominantly Inherited Alzheimer Network Trials Unit (DIAN-TU) was ongoing, external data suggested higher doses were needed to achieve targeted effects; therefore, doses of gantenerumab were increased 5-fold, and solanezumab was increased 4-fold. We evaluated to what extent mid-trial dose increases produced a dose-dependent treatment effect. Methods: Using generalized linear mixed effects (LME) models, we estimated the annual low- and high-dose treatment effects in clinical, cognitive, and biomarker outcomes. Results: Both gantenerumab and solanezumab demonstrated dose-dependent treatment effects (significant for gantenerumab, non-significant for solanezumab) in their respective target amyloid biomarkers (Pittsburgh compound B positron emission tomography standardized uptake value ratio and cerebrospinal fluid amyloid beta 42), with gantenerumab demonstrating additional treatment effects in some downstream biomarkers. No dose-dependent treatment effects were observed in clinical or cognitive outcomes. Conclusions: Mid-trial dose escalation can be implemented as a remedy for an insufficient initial dose and can be more cost effective and less burdensome to participants than starting a new trial with higher doses, especially in rare diseases. Highlights: We evaluated the dose-dependent treatment effect of two different amyloid-specific immunotherapies.Dose-dependent treatment effects were observed in some biomarkers.No dose-dependent treatment effects were observed in clinical/cognitive outcomes, potentially due to the fact that the modified study may not have been powered to detect such treatment effects in symptomatic subjects at a mild stage of disease exposed to high (or maximal) doses of medication for prolonged durations.

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.

PET-CR as a potential surrogate endpoint in untreated DLBCL: meta-analysis and implications for clinical trial design.

This study's focus is the association of end-of-therapy (EOT) PET results with progression-free (PFS) and overall survival (OS) in patients with diffuse large B-cell lymphoma receiving first-line chemoimmunotherapy. We develop a Bayesian hierarchical model for predicting PFS and OS from EOT PET-complete response (PET-CR) using a literature-based meta-analysis of 20 treatment arms and a substudy of 4 treatment arms in 3 clinical trials for which we have patient-level data. The PET-CR rate in our substudy was 72%. The modeled estimates for hazard ratio (PET-CR/non-PET-CR) were 0.13 for PFS (95% CI 0.10, 0.16) and 0.10 for OS (CI 0.07, 0.12). Hazard ratios varied little by patient subtype and were confirmed by the overall meta-analysis. We link these findings to designing future clinical trials and show how our model can be used in adapting the sample size of a trial to accumulating results regarding treatment benefits on PET-CR and a survival endpoint.

Application of Bayesian methods to accelerate rare disease drug development: scopes and hurdles.

BACKGROUND: Design and analysis of clinical trials for rare and ultra-rare disease pose unique challenges to the practitioners. Meeting conventional power requirements is infeasible for diseases where sample sizes are inherently very small. Moreover, rare disease populations are generally heterogeneous and widely dispersed, which complicates study enrollment and design. Leveraging all available information in rare and ultra-rare disease trials can improve both drug development and informed decision-making processes. MAIN TEXT: Bayesian statistics provides a formal framework for combining all relevant information at all stages of the clinical trial, including trial design, execution, and analysis. This manuscript provides an overview of different Bayesian methods applicable to clinical trials in rare disease. We present real or hypothetical case studies that address the key needs of rare disease drug development highlighting several specific Bayesian examples of clinical trials. Advantages and hurdles of these approaches are discussed in detail. In addition, we emphasize the practical and regulatory aspects in the context of real-life applications. CONCLUSION: The use of innovative trial designs such as master protocols and complex adaptive designs in conjunction with a Bayesian approach may help to reduce sample size, select the correct treatment and population, and accurately and reliably assess the treatment effect in the rare disease setting.

Epidemiology of out-of-hospital pediatric airway management in the 2019 national emergency medical services information system data set.

OBJECTIVE: Airway management is an important priority in the care of critically ill children. We sought to provide updated estimates of the epidemiology of pediatric out-of-hospital airway management and ventilation interventions in the United States. METHODS: We used data from the 2019 National Emergency Medical Services Information System (NEMSIS) data set. We performed a descriptive analysis of all patients < 18 years receiving one or more of the following: bag-valve-mask ventilation (BVM), tracheal intubation (TI), supraglottic airway (SGA) insertion, continuous positive airway pressure (CPAP), bilevel positive airway pressure (BiPAP) and surgical airway placement. We determined success and complication rates for each airway procedure. RESULTS: Among 1,148,943 pediatric patient care encounters, airway and ventilation interventions occurred in 22,637 (1,970 per 100,000 pediatric Emergency Medical Services (EMS) activations), including 64% <11 years old, 56.1% male, 16.9% cardiac arrest, 16.6% injured, and 83.9% in urban areas. Airway interventions included: BVM 3,997 (17.7% of pediatric airway encounters), TI 3,165 (14.0%), SGA 582 (2.6%), CPAP/BiPAP 331 (1.5%) and surgical airway 29 (0.1%). TI success was 75.2% (95% CI 73.7-76.7%) and lowest for the 0-1 month age group (56.8%; 49.2-64.2%). SGA success was 88.0% (95% CI 85.1-90.6%). Vomiting was the most common airway complication (n = 223, 1%). CONCLUSIONS: BVM and advanced airway management occur in 1 of every 51 pediatric EMS encounters. BVM is the most commonly prehospital pediatric airway management technique, followed by TI and SGA insertion. These data provide contemporary perspectives of pediatric prehospital airway management.

Critical Factors in Planning a Pediatric Prehospital Airway Trial.

Objective: The objective of this study was to assess factors influencing the design of a pediatric prehospital airway management trial, including minimum clinically significant differences for three clinical subgroups. Methods: We conducted a virtual consensus-conference among U.S. emergency medical services (EMS) agency medical directors and researchers in the Fall of 2020. This included (1) a preconference survey, (2) an interactive live videoconference, and (3) a postconference survey. Participants were identified through co-investigator relationships and by surveying "The Eagles," a consortium of medical directors from large urban EMS systems and, subsequently, through follow up email contact based on survey responses. Results: Twenty-seven of the 34 (80%) EMS agencies we invited responded to the prewebinar survey. Of the 27 agencies, 27 (100%) use BMV, 19 (70%) use endotracheal intubation (ETI), 21 (78%) use supraglottic airways (SGA). SGA use included 14 (52%) who use the iGel, 8 (30%) who use the King laryngeal tube (LT), and 2 (7%) who use a laryngeal mask airway (LMA). Three agencies use more than one of the available SGAs. Twenty (74%) of the EMS agencies indicated they had access to an SGA suitable for pediatric patients, and 9 (33%) agencies have access to pediatric video laryngoscopy. The majority of agencies indicated that the minimum clinically significant difference for survival to change practice was 1% for cardiac arrest patients with a baseline survival assumption of 7%, 4% for respiratory failure with a baseline survival assumption of 73%, and 3% for trauma with a baseline survival assumption of 42%. Overall, these agencies responded that BVM vs. SGA is the most important comparison that would change their practice. Conclusions: This virtual consensus conference provided a new perspective on current airway management practice and identified specific factors likely to drive change in pediatric prehospital airway management. This information will be leveraged in future trial design to ensure impactful clinical trials.

Design of a novel clinical trial of prehospital pediatric airway management.

Emergency Medical Services personnel are often the first to intervene in the care of critically ill children. Airway management is a fundamental step in prehospital resuscitation, yet there is significant variation in current prehospital airway management practices. Our objective is to present a methodologic approach to determine the optimal strategy for prehospital pediatric airway management. We describe the conceptual premise for the Pediatric Prehospital Airway Resuscitation Trial, a novel Bayesian adaptive sequential platform trial. We developed an innovative design to enable comparison of the three predominant prehospital pediatric airway techniques (bag-mask-ventilation, supraglottic airway insertion, and endotracheal intubation) in three distinct disease groups (cardiac arrest, major trauma, and other respiratory failure). We used a Bayesian statistical approach to provide flexible modeling that can adapt based on prespecified rules according to accumulating trial data with patient enrollment continuing until stopping rules are met. The approach also allows the comparison of multiple interventions in sequence across the different disease states. This Bayesian hierarchical model will be the primary analysis method for the Pediatric Prehospital Airway Resuscitation Trial. The model integrates information across subgroups, a technique known as "borrowing" to generate accurate global and subgroup-specific estimates of treatment effects and enables comparisons of airway intervention arms within the overarching trial. We will use this Bayesian hierarchical linear model that adjusts for subgroup to estimate treatment effects within each subgroup. The model will predict a patient-centered score of 30-day intensive care unit-free survival using arm, subgroup, and emergency medical services agency as predictors. The novel approach of Pediatric Prehospital Airway Resuscitation Trial will provide a feasible method to determine the optimal strategy for prehospital pediatric airway management and may transform the design of future prehospital resuscitation trials.

ICU-free days as a more sensitive primary outcome for clinical trials in critically ill pediatric patients.

BACKGROUND: Our objective was to assess the association between intensive care unit (ICU)-free days and patient outcomes in pediatric prehospital care and to evaluate whether ICU-free days is a more sensitive outcome measure for emergency medical services research in this population. METHODS: This study used data from a previous pediatric prehospital trial. The original study enrolled patients ≤12 years of age and compared bag-valve-mask-ventilation (BVM) versus endotracheal intubation (ETI) during prehospital resuscitation. For the current study, we defined ICU-free days as 30 minus the number of days in the ICU (range, 0-30 days) and assigned 0 ICU-free days for death within 30 days. We compared ICU-free days between the original study treatment groups (BVM vs ETI) and with the original trial outcomes of survival to hospital discharge and Pediatric Cerebral Performance Category (PCPC). RESULTS: Median ICU-free days for the BVM group (n = 404) versus ETI group (n = 416) was not statistically different: 0 ICU-free days (interquartile range, 0-10) versus 0 (0-0), P = 0.219. Median ICU-free days were greater for BVM group in 3 subgroups: foreign body aspiration 30 (0-30) versus 0 (0-21), P = 0.028; child maltreatment 0 (0-14.2) versus 0 (0-0), P = 0.004; and respiratory arrest 25 (1-29) versus 7.5 (0-27.7), P = 0.015. In the original trial, neither survival nor PCPC demonstrated differences in all 3 subgroups-survival was greater with BVM for child maltreatment and respiratory arrest and favorable PCPC was greater with BVM for foreign body aspiration. Overall, in the current study, patients with more ICU-free days also had greater survival to hospital discharge and more favorable PCPC scores. CONCLUSIONS: This initial study of the association between ICU-free days and patient outcomes during prehospital pediatric resuscitation appears to support the use of ICU-free days as a clinical endpoint in this population. ICU-free days may be more sensitive than either mortality or PCPC alone while capturing aspects of both measures.