Context Of Rare Diseases Research Articles

The impact of music on health and wellbeing of children and young people with rare diseases in healthcare settings: A scoping review

Interest in the applications of music in health, social care and community settings are growing worldwide. Rare diseases are a major challenge for public health, particularly in paediatric populations. Previous research has demonstrated music and music medicine benefit children and young people’s health and wellbeing; however, this is under-researched in the paediatric rare disease context. This scoping review was conducted to explore music therapy and music medicine as tools to support children with rare diseases’ health and wellbeing within healthcare settings. The review investigated the current research on how music is used for children and young people with rare diseases and complex conditions and synthesised the resulting evidence. Results from this review suggest that music therapy and music medicine are beneficial for the health and wellbeing of children with rare diseases and complex conditions, including reduced anxiety, stress and pain during clinical procedures, and increased communication, social and coping skills and enhanced quality of life.

Accurate detection of shared genetic architecture from GWAS summary statistics in the small-sample context.

Assessment of the genetic similarity between two phenotypes can provide insight into a common genetic aetiology and inform the use of pleiotropy-informed, cross-phenotype analytical methods to identify novel genetic associations. The genetic correlation is a well-known means of quantifying and testing for genetic similarity between traits, but its estimates are subject to comparatively large sampling error. This makes it unsuitable for use in a small-sample context. We discuss the use of a previously published nonparametric test of genetic similarity for application to GWAS summary statistics. We establish that the null distribution of the test statistic is modelled better by an extreme value distribution than a transformation of the standard exponential distribution. We show with simulation studies and real data from GWAS of 18 phenotypes from the UK Biobank that the test is to be preferred for use with small sample sizes, particularly when genetic effects are few and large, outperforming the genetic correlation and another nonparametric statistical test of independence. We find the test suitable for the detection of genetic similarity in the rare disease context.

Stress, Coping, and Physical Health in Caregiving.

Informal caregivers experience a great deal of stress due to care-related duties and responsibilities. Caregiving stress has the ability to impact caregivers' physical health, but has been largely understudied in caregivers of children with a chronic illness. In this study, we examine the associations of stress to both caregiver self-rated health and biomarkers of the hypothalamic-pituitary-adrenal (HPA) axis and immune systems (arginine vasopressin, c-reactive protein, tumor necrosis factor alpha). We also examine whether coping style (proactive, avoidant, support coping) buffers the links of stress to health across two different stressor contexts: caregiving for a child with a rare or undiagnosed disease (n = 101) and caregiving for a typically developing child (n = 69). Results indicated perceived stress was linked to worse self-rated health, however, stress was only linked to biological markers of health for caregivers of typically developing children. Results also suggest that coping style may moderate some of the links of stress to health, as proactive coping was linked to lower arginine vasopressin. However, models also suggested the role of coping style may differ based on caregiving context, as support coping was linked to better health only for caregivers of typically developing children, and more proactive coping overall was observed in the rare disease context. Future research should continue to examine how stress and coping interact within different caregiving contexts to protect caregiver health and well-being.

The unique challenges of clinical trials in rare disease: A regulatory writer’s perspective

Designing clinical trials in rare diseases comes with a specific set of challenges including limited knowledge around the natural history of a disease, small sample size available for trial participation, regulatory guidance that is not calibrated to the rare disease context, manufacturing and supply issues, and safety and financial risks. Here, we discuss some of these potential challenges and how, through proactive early engagement with key opinion leaders, regulatory bodies, and patient groups, a cohesive and strategic clinical development plan can be created to provide the strongest foundations when marketing approval is sought.

Creation of an ustekinumab external control arm for Crohn's disease using electronic health records data: A pilot study.

Randomized trials are the gold-standard for clinical evidence generation, but they can sometimes be limited by infeasibility and unclear generalizability to real-world practice. External control arm (ECA) studies may help address this evidence gaps by constructing retrospective cohorts that closely emulate prospective ones. Experience in constructing these outside the context of rare diseases or cancer is limited. We piloted an approach for developing an ECA in Crohn's disease using electronic health records (EHR) data. We queried EHR databases and manually screened records at the University of California, San Francisco to identify patients meeting the eligibility criteria of TRIDENT, a recently completed interventional trial involving an ustekinumab reference arm. We defined timepoints to balance missing data and bias. We compared imputation models by their impacts on cohort membership and outcomes. We assessed the accuracy of algorithmic data curation against manual review. Lastly, we assessed disease activity following treatment with ustekinumab. Screening identified 183 patients. 30% of the cohort had missing baseline data. Nonetheless, cohort membership and outcomes were robust to the method of imputation. Algorithms for ascertaining non-symptom-based elements of disease activity using structured data were accurate against manual review. The cohort consisted of 56 patients, exceeding planned enrollment in TRIDENT. 34% of the cohort was in steroid-free remission at week 24. We piloted an approach for creating an ECA in Crohn's disease from EHR data by using a combination of informatics and manual methods. However, our study reveals significant missing data when standard-of-care clinical data are repurposed. More work will be needed to improve the alignment of trial design with typical patterns of clinical practice, and thereby enable a future of more robust ECAs in chronic diseases like Crohn's disease.

Bayesian Strategies in Rare Diseases.

Bayesian strategies for planning and analyzing clinical trials have become a viable choice, especially in rare diseases where drug development faces many challenges and stakeholders are interested in innovations that may help overcome them. Disease natural history and clinical outcomes occurrence and variability are often poorly understood. Standard trial designs are not optimized to obtain adequate safety and efficacy data from small numbers of patients. Bayesian methods are well-suited for adaptive trials, with an accelerated learning curve. Using Bayesian statistics can be advantageous in that design choices and their consequences are considered carefully, continuously monitored, and updated where necessary, which ultimately provides a natural and principled way of seamlessly combining prior clinical information with data, within a solid decision theoretical framework. In this article, we introduce the Bayesian option in the rare disease context to support clinical decision-makers in selecting the best choice for their drug development project. Many researchers in drug development show reluctance to using Bayesian statistics, and the top-two reported barriers are insufficient knowledge of Bayesian approaches and a lack of clarity or guidance from regulators. Here we introduce concepts of borrowing, extrapolation, adaptation, and modeling and illustrate them with examples that have been discussed or developed with regulatory bodies to show how Bayesian strategies can be applied to drug development in rare diseases.

Management of PTLD After Hematopoietic Stem Cell Transplantation: Immunological Perspectives.

Post-transplant lymphoproliferative disorders (PTLDs) are life-threatening complications of iatrogenic immune impairment after allogeneic hematopoietic stem cell transplantation (HSCT). In the pediatric setting, the majority of PTLDs are related to the Epstein–Barr virus (EBV) infection, and present as B-cell lymphoproliferations. Although considered rare events, PTLDs have been increasingly observed with the widening application of HSCT from alternative sources, including cord blood and HLA-haploidentical stem cell grafts, and the use of novel agents for the prevention and treatment of rejection and graft-vs.-host disease. The higher frequency initially paralleled a poor outcome, due to limited therapeutic options, and scarcity of controlled trials in a rare disease context. In the last 2 decades, insight into the relationship between EBV and the immune system, and advances in early diagnosis, monitoring and treatment have changed the approach to the management of PTLDs after HSCT, and significantly ameliorated the prognosis. In this review, we summarize literature on the impact of combined viro-immunologic assessment on PTLD management, describe the various strategies for PTLD prevention and preemptive/curative treatment, and discuss the potential of novel immune-based therapies in the containment of this malignant complication.

Defining Coordinated Care for People with Rare Conditions: A Scoping Review.

Introduction:To coordinate care effectively for rare conditions, we need to understand what coordinated care means. This review aimed to define coordinated care and identify components of coordinated care within the context of rare diseases; by drawing on evidence from chronic conditions.Methods:A systematic scoping review. We included reviews that reported or defined and outlined components of coordinated care for chronic or rare conditions. Thematic analysis was used to develop a definition and identify components or care coordination. Stakeholder consultations (three focus groups with patients, carers and healthcare professionals with experience of rare conditions) were held to further explore the relevance of review findings for rare conditions.Results:We included 154 reviews (n = 139 specific to common chronic conditions, n = 3 specific to rare conditions, n = 12 both common/rare conditions). A definition of coordination was developed. Components were identified and categorised by those that: may need to be coordinated, inform how to coordinate care, have multiple roles, or that contextualise coordination.Conclusions:Coordinated care is multi-faceted and has both generic and context-specific components. Findings outline many ways in which care may be coordinated for both rare and common chronic conditions. Findings can help to develop and eventually test different ways of coordinating care for people with rare and common chronic conditions.

Response-adaptive designs for binary responses: How to offer patient benefit while being robust to time trends?

Response‐adaptive randomisation (RAR) can considerably improve the chances of a successful treatment outcome for patients in a clinical trial by skewing the allocation probability towards better performing treatments as data accumulates. There is considerable interest in using RAR designs in drug development for rare diseases, where traditional designs are not either feasible or ethically questionable. In this paper, we discuss and address a major criticism levelled at RAR: namely, type I error inflation due to an unknown time trend over the course of the trial. The most common cause of this phenomenon is changes in the characteristics of recruited patients—referred to as patient drift. This is a realistic concern for clinical trials in rare diseases due to their lengthly accrual rate. We compute the type I error inflation as a function of the time trend magnitude to determine in which contexts the problem is most exacerbated. We then assess the ability of different correction methods to preserve type I error in these contexts and their performance in terms of other operating characteristics, including patient benefit and power. We make recommendations as to which correction methods are most suitable in the rare disease context for several RAR rules, differentiating between the 2‐armed and the multi‐armed case. We further propose a RAR design for multi‐armed clinical trials, which is computationally efficient and robust to several time trends considered.

Knowledge Representation and Management, It’s Time to Integrate!

Summary Objectives: To select, present, and summarize the best papers published in 2016 in the field of Knowledge Representation and Management (KRM). Methods: A comprehensive and standardized review of the medical informatics literature was performed based on a PubMed query. Results: Among the 1,421 retrieved papers, the review process resulted in the selection of four best papers focused on the integration of heterogeneous data via the development and the alignment of terminological resources. In the first article, the authors provide a curated and standardized version of the publicly available US FDA Adverse Event Reporting System. Such a resource will improve the quality of the underlying data, and enable standardized analyses using common vocabularies. The second article describes a project developed in order to facilitate heterogeneous data integration in the i2b2 framework. The originality is to allow users integrate the data described in different terminologies and to build a new repository, with a unique model able to support the representation of the various data. The third paper is dedicated to model the association between multiple phenotypic traits described within the Human Phenotype Ontology (HPO) and the corresponding genotype in the specific context of rare diseases (rare variants). Finally, the fourth paper presents solutions to annotation-ontology mapping in genome-scale data. Of particular interest in this work is the Experimental Factor Ontology (EFO) and its generic association model, the Ontology of Biomedical AssociatioN (OBAN). Conclusion: Ontologies have started to show their efficiency to integrate medical data for various tasks in medical informatics: electronic health records data management, clinical research, and knowledge-based systems development.

Finding patients using similarity measures in a rare diseases-oriented clinical data warehouse: Dr. Warehouse and the needle in the needle stack

ObjectiveIn the context of rare diseases, it may be helpful to detect patients with similar medical histories, diagnoses and outcomes from a large number of cases with automated methods. To reduce the time to find new cases, we developed a method to find similar patients given an index case leveraging data from the electronic health records. Materials and methodsWe used the clinical data warehouse of a children academic hospital in Paris, France (Necker-Enfants Malades), containing about 400,000 patients. Our model was based on a vector space model (VSM) to compute the similarity distance between an index patient and all the patients of the data warehouse. The dimensions of the VSM were built upon Unified Medical Language System concepts extracted from clinical narratives stored in the clinical data warehouse. The VSM was enhanced using three parameters: a pertinence score (TF-IDF of the concepts), the polarity of the concept (negated/not negated) and the minimum number of concepts in common. We evaluated this model by displaying the most similar patients for five different rare diseases: Lowe Syndrome (LOWE), Dystrophic Epidermolysis Bullosa (DEB), Activated PI3K delta Syndrome (APDS), Rett Syndrome (RETT) and Dowling Meara (EBS-DM), from the clinical data warehouse representing 18, 103, 21, 84 and 7 patients respectively. ResultsThe percentages of index patients returning at least one true positive similar patient in the Top30 similar patients were 94% for LOWE, 97% for DEB, 86% for APDS, 71% for EBS-DM and 99% for RETT. The mean number of patients with the exact same genetic diseases among the 30 returned patients was 51%. ConclusionThis tool offers new perspectives in a translational context to identify patients for genetic research. Moreover, when new molecular bases are discovered, our strategy will help to identify additional eligible patients for genetic screening.

Knowledge Representation and Management, It's Time to Integrate!

Objectives: To select, present, and summarize the best papers published in 2016 in the field of Knowledge Representation and Management (KRM). Methods: A comprehensive and standardized review of the medical informatics literature was performed based on a PubMed query. Results: Among the 1,421 retrieved papers, the review process resulted in the selection of four best papers focused on the integration of heterogeneous data via the development and the alignment of terminological resources. In the first article, the authors provide a curated and standardized version of the publicly available US FDA Adverse Event Reporting System. Such a resource will improve the quality of the underlying data, and enable standardized analyses using common vocabularies. The second article describes a project developed in order to facilitate heterogeneous data integration in the i2b2 framework. The originality is to allow users integrate the data described in different terminologies and to build a new repository, with a unique model able to support the representation of the various data. The third paper is dedicated to model the association between multiple phenotypic traits described within the Human Phenotype Ontology (HPO) and the corresponding genotype in the specific context of rare diseases (rare variants). Finally, the fourth paper presents solutions to annotation-ontology mapping in genome-scale data. Of particular interest in this work is the Experimental Factor Ontology (EFO) and its generic association model, the Ontology of Biomedical AssociatioN (OBAN). Conclusion: Ontologies have started to show their efficiency to integrate medical data for various tasks in medical informatics: electronic health records data management, clinical research, and knowledge-based systems development.

Introduction: Molecular genomics of cancer: Linking diagnostic testing and clinical therapy

For many physicians, genetic testing in any form falls within the category of esoteric testing. The concept that gene mutations or copy number abnormalities are only understood by a limited number of specialists, and that the data may only be relevant within the context of rare disease, is prevalent throughout many medical practices. In light of the most recent data from both the bench and the bedside, this mindset is woefully antiquated in oncology. Moving forward, a clear understanding of the utility of multi-gene molecular testing in informing the diagnosis and treatment of cancer patients within specific disease subtypes is essential for improving outcomes. Due to the vast breadth of medical education, physician exposure to advanced molecular technologies and applications is often limited. Organizations like the National Coalition for Health Care Professional Education in Genetics and other groups tasked with the goal of educating health care professionals have been poorly funded and unable to expand content to the understanding of somatic cancer mutations. This review has been written with the intent of serving as a general primer for clinical oncologists and pathologists alike, who are entrusted with providing the highest standard of care to their patients. This review highlights key advances in genomic medicine in solid tumors, central nervous system neoplasia, and hematologic malignancies with a particular emphasis on diagnostic testing and clinical reporting. Nucleic acid is the input for all genomic testing, thus it is the opinion of these authors that practical implementation of genomic medicine requires institutional revisions to traditional approaches of pathologic diagnoses and specimen handling. Particular emphasis is required to integrate both specimen and molecular data, and the willingness to interpret complex data sets in their entirety, rather than as a series of individual tests, data sets, or abnormalities. Advances in genetics and genomics technologies have demonstrated a lag of nearly a decade from the time of discovery of a new technological advancement such as fluorescence in situ hybridization, microarray, or next generation sequencing to widespread clinical use. It is uncertain what technologies will surpass next generation sequencing, but for now, it is clear that

SP0194 Leveraging an Innovative TRIAL Design for A Rare Disease Context: the Cohort Multiple RCT (CMRCT) Design

Pragmatic randomized controlled trials (RCTs) are considered the gold standard for determining the effectiveness of interventions in actual clinical practice. Traditionally designed pragmatic RCTs have high internal validity, but have...

The Scleroderma Patient-centered Intervention Network (SPIN) Cohort: protocol for a cohort multiple randomised controlled trial (cmRCT) design to support trials of psychosocial and rehabilitation interventions in a rare disease context

IntroductionPsychosocial and rehabilitation interventions are increasingly used to attenuate disability and improve health-related quality of life (HRQL) in chronic diseases, but are typically not available for patients with rare diseases....

Achieving the “triple aim” for inborn errors of metabolism: a review of challenges to outcomes research and presentation of a new practice-based evidence framework

Across all areas of health care, decision makers are in pursuit of what Berwick and colleagues have called the “triple aim”: improving patient experiences with care, improving health outcomes, and managing health system impacts. This is challenging in a rare disease context, as exemplified by inborn errors of metabolism. There is a need for evaluative outcomes research to support effective and appropriate care for inborn errors of metabolism. We suggest that such research should consider interventions at both the level of the health system (e.g., early detection through newborn screening, programs to provide access to treatments) and the level of individual patient care (e.g., orphan drugs, medical foods). We have developed a practice-based evidence framework to guide outcomes research for inborn errors of metabolism. Focusing on outcomes across the triple aim, this framework integrates three priority themes: tailoring care in the context of clinical heterogeneity; a shift from “urgent care” to “opportunity for improvement”; and the need to evaluate the comparative effectiveness of emerging and established therapies. Guided by the framework, a new Canadian research network has been established to generate knowledge that will inform the design and delivery of health services for patients with inborn errors of metabolism and other rare diseases.Genet Med 2013:15(6):415–422

BRINGING GENETICS INTO THE CLASSROOM: A Practice-Based Approach

Abstract GENETICS, once thought of only in the context of rare diseases, is now recognized as an integral component of many common diseases. In the near future, genetic predisposition to cancer and heart disease may be identified at an early age, allowing for individualized prevention and management plans (2). Nurses must be prepared to identify and effectively respond to clients' genetic health concerns and help them manage new genetic information. TO DO THIS, NURSES MUST HAVE THE NECESSARY GENETICS EDUCATION (3–7). THE CONCEPT OF INFORMED CONSENT can serve as an example of how to reframe a well-established principle inherent in the delivery of health care and in research involving human subjects within a “GENETIC FRAMEWORK” and thus integrate genetic content. Nurses must be prepared to identify and effectively respond to clients' genetic concerns and help them manage new genetic information. To do this, they need genetics education. This article describes an innovative, case-study-based genetics educati...