Using qualitative methods to guide clinical trial design: Parent recommendations for intervention modification in Type 1 diabetes.

2011 ◽  
Vol 25 (6) ◽  
pp. 868-872 ◽  
Author(s):  
Maureen Monaghan ◽  
Risa E. Sanders ◽  
Katherine Patterson Kelly ◽  
Fran R. Cogen ◽  
Randi Streisand
Keyword(s):  
Clinical Trial ◽  
Type 1 Diabetes ◽  
Qualitative Methods ◽  
Trial Design ◽  
Clinical Trial Design

scholarly journals Challenges to Reshape the Future of Type 1 Diabetes Research

2018 ◽  
Vol 103 (8) ◽  
pp. 2838-2842 ◽  
Author(s):  
David Bleich ◽  
David H Wagner
Keyword(s):  
Type 1 Diabetes ◽  
T Cell ◽  
Trial Design ◽  
Evidence Synthesis ◽  
Clinical Trial Design ◽  
Preventive Treatment ◽  
Diabetes Research ◽  
Knowledge Gaps ◽  
Disease Stratification

Abstract Context Immunotherapy trials to prevent type 1 diabetes have been unsuccessful for >15 years. Understanding pitfalls and knowledge gaps in the immunology of type 1 diabetes should lead us in new directions that will yield better trial outcomes. A proposal is made for precision medicine trial design in future type 1 diabetes studies. Evidence Acquisition High-quality peer-reviewed basic science and clinical research trials for type 1 diabetes were used in this Perspective article. Type 1 diabetes publications were reviewed from 2000 to 2018 by using Google Scholar and PubMed reference databases. Evidence Synthesis Personalized medicine for type 1 diabetes should recognize that each individual has phenotypic and genotypic quirks that distinguish them from other study participants. A uniform protocol for antigen-specific immunotherapy has consistently failed to prevent disease. An alternative approach using molecular tools to personalize the preventive treatment strategy might be a road forward for type 1 diabetes research. Assumptions or lack of knowledge about disease stratification (not all type 1 diabetes is the same disease), individualized antigen-specific T cells, regulatory T-cell populations, and T-cell receptor rearrangement are just a few aspects of immunology that require integration with clinical trial design. Conclusions The type 1 diabetes research community continues to bring forward novel immunotherapy trials to prevent disease, but this approach is unlikely to succeed until several fundamental aspects of clinical immunology are recognized and addressed. Here, we identify several knowledge gaps that could rectify type 1 diabetes trial design and lead to future success.

scholarly journals Hierarchical Bayesian modelling of disease progression to inform clinical trial design in centronuclear myopathy

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Eve Fouarge ◽  
◽  
Arnaud Monseur ◽  
Bruno Boulanger ◽  
Mélanie Annoussamy ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Natural History ◽  
Bayesian Statistics ◽  
Trial Design ◽  
Clinical Trial Design ◽  
Threshold Probability ◽  
Congenital Diseases ◽  
Type 1 Error ◽  
Rate Of Response

Abstract Background Centronuclear myopathies are severe rare congenital diseases. The clinical variability and genetic heterogeneity of these myopathies result in major challenges in clinical trial design. Alternative strategies to large placebo-controlled trials that have been used in other rare diseases (e.g., the use of surrogate markers or of historical controls) have limitations that Bayesian statistics may address. Here we present a Bayesian model that uses each patient’s own natural history study data to predict progression in the absence of treatment. This prospective multicentre natural history evaluated 4-year follow-up data from 59 patients carrying mutations in the MTM1 or DNM2 genes. Methods Our approach focused on evaluation of forced expiratory volume in 1 s (FEV1) in 6- to 18-year-old children. A patient was defined as a responder if an improvement was observed after treatment and the predictive probability of such improvement in absence of intervention was less than 0.01. An FEV1 response was considered clinically relevant if it corresponded to an increase of more than 8%. Results The key endpoint of a clinical trial using this model is the rate of response. The power of the study is based on the posterior probability that the rate of response observed is greater than the rate of response that would be observed in the absence of treatment predicted based on the individual patient’s previous natural history. In order to appropriately control for Type 1 error, the threshold probability by which the difference in response rates exceeds zero was adapted to 91%, ensuring a 5% overall Type 1 error rate for the trial. Conclusions Bayesian statistical analysis of natural history data allowed us to reliably simulate the evolution of symptoms for individual patients over time and to probabilistically compare these simulated trajectories to actual observed post-treatment outcomes. The proposed model adequately predicted the natural evolution of patients over the duration of the study and will facilitate a sufficiently powerful trial design that can cope with the disease’s rarity. Further research and ongoing dialog with regulatory authorities are needed to allow for more applications of Bayesian statistics in orphan disease research.

scholarly journals Status and Recommendations for Incorporating Biomarkers for Cutaneous Neurofibromas into Clinical Research

Neurology ◽  
2021 ◽  
pp. 10.1212/WNL.0000000000012426
Author(s):  
Deeann Wallis ◽  
Anat Stemmer-Rachamimov ◽  
Sarah Adsit ◽  
Bruce Korf ◽  
Dominique Pichard ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Working Group ◽  
Trial Design ◽  
Clinical Trial Design ◽  
Predictive Biomarkers ◽  
Neurofibromatosis Type ◽  
Proteomic Data ◽  
Group A ◽  
Existing Data

Objective:To summarize existing biomarker data for cutaneous neurofibroma (cNF) and inform the incorporation of biomarkers into clinical trial design for cNFs.Methods:The cNF working group, a subgroup of the Response Evaluation in Neurofibromatosis and Schwannomatosis (REiNS) consortium, was formed to review and inform clinical trial design for cNFs. Between June 2018 and February 2020, the cNF working group performed a review of existing data on genetic biomarkers for cNFs in the setting of Neurofibromatosis Type 1 (NF1). We also reviewed criteria for successful biomarker application in the clinic. The group then met during a series of meetings to develop a consensus report.Results:Our systematic literature review of existing data revealed a lack of validated biomarkers for cNFs. In our report, we summarize the existing signaling, genomic, transcriptomic, histopathologic and proteomic data relevant to cNF. Finally, we make recommendations for incorporating exploratory aims for predictive biomarkers in clinical trials through biobanking samples.Conclusion:These recommendations are intended to provide both researchers and clinicians with best practices for clinical trial design to aid in the identification of clinically validated biomarkers for cNF.

Liraglutide as an Additional Treatment to Insulin in Patients with Type 1 Diabetes Mellitus—A 52-Week Randomized Double-Blinded Placebo-Controlled Clinical Trial

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 3-LB ◽  
Author(s):  
PARESH DANDONA ◽  
HUSAM GHANIM ◽  
NITESH D. KUHADIYA ◽  
TANVI SHAH ◽  
JEANNE M. HEJNA ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Clinical Trial ◽  
Type 1 Diabetes ◽  
Type 1 Diabetes Mellitus ◽  
Additional Treatment ◽  
Controlled Clinical Trial ◽  
Double Blinded

Integrating radiomics into clinical trial design

2019 ◽  
Vol 63 (4) ◽  
Author(s):  
Jessica J. Waninger ◽  
Michael D. Green ◽  
Catherine Cheze Le Rest ◽  
Benjamin Rosen ◽  
Issam El Naqa
Keyword(s):  
Clinical Trial ◽  
Trial Design ◽  
Clinical Trial Design

scholarly journals Pump It Up! A randomized clinical trial to optimize insulin pump self-management behaviors in adolescents with type 1 diabetes

2021 ◽  
Vol 102 ◽  
pp. 106279
Author(s):  
Holly K. O'Donnell ◽  
Tim Vigers ◽  
Suzanne Bennett Johnson ◽  
Laura Pyle ◽  
Nancy Wright ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Type 1 Diabetes ◽  
Randomized Clinical Trial ◽  
Insulin Pump ◽  
Self Management ◽  
Management Behaviors

scholarly journals X-change symposium: status and future of modern radiation oncology—from technology to biology

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Stefanie Corradini ◽  
Maximilian Niyazi ◽  
Dirk Verellen ◽  
Vincenzo Valentini ◽  
Seán Walsh ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Radiation Oncology ◽  
Trial Design ◽  
Rapid Development ◽  
Clinical Trial Design ◽  
Current Status ◽  
Treatment Modalities ◽  
Special Treatment ◽  
Image Guided Radiotherapy

AbstractFuture radiation oncology encompasses a broad spectrum of topics ranging from modern clinical trial design to treatment and imaging technology and biology. In more detail, the application of hybrid MRI devices in modern image-guided radiotherapy; the emerging field of radiomics; the role of molecular imaging using positron emission tomography and its integration into clinical routine; radiation biology with its future perspectives, the role of molecular signatures in prognostic modelling; as well as special treatment modalities such as brachytherapy or proton beam therapy are areas of rapid development. More clinically, radiation oncology will certainly find an important role in the management of oligometastasis. The treatment spectrum will also be widened by the rational integration of modern systemic targeted or immune therapies into multimodal treatment strategies. All these developments will require a concise rethinking of clinical trial design. This article reviews the current status and the potential developments in the field of radiation oncology as discussed by a panel of European and international experts sharing their vision during the “X-Change” symposium, held in July 2019 in Munich (Germany).

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