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

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

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

Abstract 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.http://deepblue.lib.umich.edu/bitstream/2027.42/173792/1/13023_2022_Article_2342.pd

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

Disease progression models of familial frontotemporal lobar degeneration and the temporal ordering of biomarker changes in an international cohort

Background: Clinical trials are underway to treat familial frontotemporal lobar degeneration (f-FTLD). This is a rare disease, and a limited number of mutation carriers have been identified; thus, efficient trial design is critical. Multimodal, latent disease progression models (DPM) can estimate time to symptom onset and define the temporal ordering of biomarker changes. DPMs can also be leveraged to select endpoints and potentially supplement analyses by integrating historical data. Recent draft FDA guidance for gene therapy trials in neurological disease supports these novel approaches to clinical trials. Method: Participants included 1,049 members of families affected by f-FTLD, due to mutations in GRN, MAPT, or C9orf72 genes, who were enrolled in ALLFTD or GENFI. A Bayesian repeated measures model incorporated multimodal data to estimate disease progression, conditional on latent disease age (proximity to symptom onset), in 677 mutations carriers (GRN (n=233), MAPT (n=151) and C9orf72 (n=293)). Family members without pathogenic mutations were used as the reference group. Mean follow-up was 1.1 (SD=1.1) years. Jointly modeled longitudinal variables included neuropsychological scores, CDR®+NACC-FTLD Box Score, MRI volumes of brain regions affected by f-FTLD, and plasma levels of neurofilament light chain (NfL). Result: Disease progression curves were similar across ALLFTD and GENFI cohorts. Plasma NfL elevations occurred earliest, up to 10 years before symptom onset, and NfL was the most powerful endpoint in the asymptomatic stage. MRI abnormalities occurred next, closer to symptom onset. The earliest MRI changes relative to symptom onset were observed in C9orf72+. GRN mutation carriers showed the most rapid acceleration in all biomarkers, and this acceleration occurred in close proximity to symptom onset. Neuropsychological measures and CDR®+NACC-FTLD Box Score were among the most promising endpoints in the symptomatic stage. Trial simulations indicated that using latent disease age as an enrollment criterion would allow some asymptomatic mutation carriers to be enrolled without sacrificing power. Conclusion: Similarity in disease progression across ALLFTD and GENFI participants suggests these models will apply to international trials. Model-derived estimates of disease progression curves indicate that endpoint selection should be specific to disease stage and mutation, and DPMs would facilitate greater participant enrollment

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

A trial of gantenerumab or solanezumab in dominantly inherited Alzheimer’s disease

International audienceDominantly inherited Alzheimer's disease (DIAD) causes predictable biological changes decades before the onset of clinical symptoms, enabling testing of interventions in the asymptomatic and symptomatic stages to delay or slow disease progression. We conducted a randomized, placebo-controlled, multi-arm trial of gantenerumab or solanezumab in participants with DIAD across asymptomatic and symptomatic disease stages. Mutation carriers were assigned 3:1 to either drug or placebo and received treatment for 4-7 years. The primary outcome was a cognitive end point; secondary outcomes included clinical, cognitive, imaging and fluid biomarker measures. Fifty-two participants carrying a mutation were assigned to receive gantenerumab, 52 solanezumab and 40 placebo. Both drugs engaged their Aβ targets but neither demonstrated a beneficial effect on cognitive measures compared to controls. The solanezumab-treated group showed a greater cognitive decline on some measures and did not show benefits on downstream biomarkers. Gantenerumab significantly reduced amyloid plaques, cerebrospinal fluid total tau, and phospho-tau181 and attenuated increases of neurofilament light chain. Amyloid-related imaging abnormalities edema was observed in 19.2% (3 out of 11 were mildly symptomatic) of the gantenerumab group, 2.5% of the placebo group and 0% of the solanezumab group. Gantenerumab and solanezumab did not slow cognitive decline in symptomatic DIAD. The asymptomatic groups showed no cognitive decline; symptomatic participants had declined before reaching the target doses

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

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