The Rare Diseases Clinical Research Network's organization and approach to observational research and health outcomes research

One-food versus 4-food elimination diet for pediatric eosinophilic esophagitis: A multisite randomized trial

BACKGROUND

A 6-food elimination diet in pediatric eosinophilic esophagitis (EoE) is difficult to implement and may negatively affect quality of life (QoL). Less restrictive elimination diets may balance QoL and efficacy.

OBJECTIVE

We performed a multisite, randomized comparative efficacy trial of a 1-food (milk) elimination diet (1FED) versus 4-food (milk, egg, wheat, soy) elimination diet (4FED) in pediatric EoE.

METHODS

Patients aged 6 to 17 years with histologically active and symptomatic EoE were randomized 1:1 to 1FED or 4FED for 12 weeks. Primary end point was symptom improvement by Pediatric Eosinophilic Esophagitis Symptom Score (PEESS). Secondary end points were proportion experiencing histologic remission (<15 eosinophils per high-power field); change in histologic features (histology scoring system), endoscopic severity (endoscopic reference score), transcriptome (EoE diagnostic panel), and QoL scores; and predictors of remission.

RESULTS

Sixty-three patients were randomly assigned to 1FED (n = 38) and 4FED (n = 25). In 4FED versus 1FED, mean PEESS improved -25.0 versus -14.5 (P = .04), but remission rates (41% vs 44%; P = 1.00), histology scoring system (-0.25 vs -0.29; P = .77), endoscopic reference score (-1.10 vs -0.58; P = .47), and QoL scores were similar between groups. The EoE transcriptome normalized in those with histologic response to both diets. Baseline peak eosinophil count predicted remission (odds ratio, 0.975 [95% confidence interval, 0.953-0.999], P = .04; cutoff ≤42 eosinophils per high-power field). The 4FED withdrawal rate (32%) exceeded that of 1FED (11%) (P = .0496).

CONCLUSIONS

Although 4FED moderately improved symptoms compared with 1FED, the histologic, endoscopic, QoL, and transcriptomic outcomes were similar in both groups. 1FED is a reasonable first-choice therapy for pediatric EoE, given its effects, tolerability, and relative simplicity.

Towards cross-application model-agnostic federated cohort discovery

OBJECTIVES

To demonstrate that 2 popular cohort discovery tools, Leaf and the Shared Health Research Information Network (SHRINE), are readily interoperable. Specifically, we adapted Leaf to interoperate and function as a node in a federated data network that uses SHRINE and dynamically generate queries for heterogeneous data models.

MATERIALS AND METHODS

SHRINE queries are designed to run on the Informatics for Integrating Biology & the Bedside (i2b2) data model. We created functionality in Leaf to interoperate with a SHRINE data network and dynamically translate SHRINE queries to other data models. We randomly selected 500 past queries from the SHRINE-based national Evolve to Next-Gen Accrual to Clinical Trials (ENACT) network for evaluation, and an additional 100 queries to refine and debug Leaf's translation functionality. We created a script for Leaf to convert the terms in the SHRINE queries into equivalent structured query language (SQL) concepts, which were then executed on 2 other data models.

RESULTS AND DISCUSSION

91.1% of the generated queries for non-i2b2 models returned counts within 5% (or ±5 patients for counts under 100) of i2b2, with 91.3% recall. Of the 8.9% of queries that exceeded the 5% margin, 77 of 89 (86.5%) were due to errors introduced by the Python script or the extract-transform-load process, which are easily fixed in a production deployment. The remaining errors were due to Leaf's translation function, which was later fixed.

CONCLUSION

Our results support that cohort discovery applications such as Leaf and SHRINE can interoperate in federated data networks with heterogeneous data models.

Leveraging a global, federated, real-world data network to optimize investigator-initiated pediatric clinical trials: the TriNetX Pediatric Collaboratory Network

Objective

Clinical research networks facilitate collaborative research, but data sharing remains a common barrier.

Materials and Methods

The TriNetX platform provides real-time access to electronic health record (EHR)-derived, anonymized data from 173 healthcare organizations (HCOs) and tools for queries and analysis. In 2022, 4 pediatric HCOs worked with TriNetX leadership to found the Pediatric Collaboratory Network (PCN), facilitated via a multi-institutional data-use agreement (DUA). The DUA enables collaborative study design and execution, with institutional review board-approved transfer of complete datasets for further analyses on a per-protocol basis.

Results and Discussion

Of the 41.2 million children with TriNetX records, the PCN represents nearly 10%. The PCN assisted several early-career investigators to bring study concepts from conception to an international scientific meeting presentation and journal submission.

Conclusion

The PCN facilitates EHR vendor-agnostic multicenter pediatric research on the global TriNetX platform. Continued growth of the PCN will advance knowledge in pediatric health.

Advancing rare disease measurement through the Rare Disease Clinical Outcome Assessment Consortium

There is a significant unmet need to develop and evaluate new treatments for people living with one of approximately 8000 rare diseases. Well-known difficulties in conducting clinical trials (e.g., small samples, wide geographic distribution, heterogeneous symptoms) and developing products for these rare indications persist. Identifying outcomes in rare disease clinical trials remains a hurdle that contributes to the challenges for drug and gene therapy development due to uncertainty about what aspects of a condition to measure for safety and efficacy and often with no regulatory approval precedent. To accelerate rare disease treatments by advancing outcomes measurement, the US Food and Drug Administration (FDA) funded a cooperative agreement to establish the Rare Disease COA Consortium (RD-COAC) in 2019. The RD-COAC officially launched on January 1, 2022, with the mission to enable pre-competitive, multi-stakeholder collaboration aimed at identifying scientifically sound tools and methodologies for collecting clinically meaningful and patient-centric outcomes data in treatment trials for rare diseases. The RD-COAC has four complementary workstreams to advance COA measurement for rare disease clinical trials: (1) Rare Disease COA Resource; (2) Advancing COA Measurement Topic-Focused Working Groups; (3) Rare Disease Discussion Sessions for pre-competitive collaboration and shared learnings among RD-COAC members; and (4) Dissemination. This review provides an overview of the RD-COAC's activities to date, as well as future directions and opportunities to collaborate.

The Rare Diseases Clinical Research Network: a model for clinical trial readiness

Background

The current road to developing treatments for rare diseases is often slow, expensive, and riddled with risk. Change is needed to improve the process, both in how we think about rare disease treatment development and the infrastructure we build to support ongoing science. The National Institutes of Health (NIH)-supported Rare Diseases Clinical Research Network (RDCRN) was established to advance the diagnosis, management, and treatment of rare diseases and to promote highly collaborative, multi-site, patient-centric, translational, and clinical research. The current iteration of the RDCRN intends to build upon and enhance successful approaches within the network while identifying innovative methods to fill gaps and address needs in the approach to the rare disease treatment development process through innovation, collaboration, and clinical trial readiness.

Objective

The objective of this paper is to provide an overview of the productivity and influence of the RDCRN since it was first established 20 years ago.

Design and methods

Using a suite of tools available to NIH staff that provides access to a comprehensive, curated, extensively linked data set of global grants, patents, publications, clinical trials, and FDA-approved drugs, a series of queries were executed that conducted bibliometric, co-author, and co-occurrence analysis.

Results

The results demonstrate that the entire RDCRN consortia and network has been highly productive since its inception. They have produced 2763 high-quality publications that have been cited more than 100,000 times, expanded international networks, and contributed scientifically to eight FDA-approved treatments for rare diseases.

Conclusion

The RDCRN program has successfully addressed some significant challenges while developing treatments for rare diseases. However, looking to the future and being agile in facing new challenges that arise as science progresses is important.

Advancing brain network models to reconcile functional neuroimaging and clinical research

Functional magnetic resonance imaging (fMRI) captures information on brain function beyond the anatomical alterations that are traditionally visually examined by neuroradiologists. However, the fMRI signals are complex in addition to being noisy, so fMRI still faces limitations for clinical applications. Here we review methods that have been proposed as potential solutions so far, namely statistical, biophysical and decoding models, with their strengths and weaknesses. We especially evaluate the ability of these models to directly predict clinical variables from their parameters (predictability) and to extract clinically relevant information regarding biological mechanisms and relevant features for classification and prediction (interpretability). We then provide guidelines for useful applications and pitfalls of such fMRI-based models in a clinical research context, looking beyond the current state of the art. In particular, we argue that the clinical relevance of fMRI calls for a new generation of models for fMRI data, which combine the strengths of both biophysical and decoding models. This leads to reliable and biologically meaningful model parameters, which thus fulfills the need for simultaneous interpretability and predictability. In our view, this synergy is fundamental for the discovery of new pharmacological and interventional targets, as well as the use of models as biomarkers in neurology and psychiatry.

Global Regulatory and Public Health Initiatives to Advance Pediatric Drug Development for Rare Diseases

The literature thoroughly describes the challenges of pediatric drug development for rare diseases. This includes (1) generating interest from sponsors, (2) small numbers of children affected by a particular disease, (3) difficulties with study design, (4) lack of definitive outcome measures and assessment tools, (5) the need for additional safeguards for children as a vulnerable population, and (6) logistical hurdles to completing trials, especially with the need for longer term follow-up to establish safety and efficacy. There has also been an increasing awareness of the need to engage patients and their families in drug development processes and to address inequities in access to pediatric clinical trials. The year 2020 ushered in yet another challenge-the COVID-19 pandemic. The pediatric drug development ecosystem continues to evolve to meet these challenges. This article will focus on several key factors including recent regulatory approaches and public health policies to facilitate pediatric rare disease drug development, emerging trends in product development (biologics, molecularly targeted therapies), innovations in trial design/endpoints and data collection, and current efforts to increase patient engagement and promote equity. Finally, lessons learned from COVID-19 about building adaptable pediatric rare disease drug development processes will be discussed.

Novel clinical trial design and analytic methods to tackle challenges in therapeutic development in rare diseases

While only a fraction of the worldwide population may have a particular rare disorder, millions of people worldwide are affected across the over 6,000 rare disorders and do not have a safe and effective approved therapy to help them live or manage complications from the disorder. Challenges to clinical development of new therapies in rare disorders include difficulty in powering and recruiting into a study in small and often heterogenous population, scarcity of natural history data informing critical design elements such as endpoint selection and study duration, and ethical and recruitment challenges in randomizing patients to a placebo arm. In this review, we describe some existing and novel strategies to tackle these challenges, by efficient utilization of available resources. We discuss the role of natural history studies and endpoint selection as they remain critical features that apply across designs and disorders. We also review some novel clinical trial designs including incorporating external control and/or longitudinal measures, master protocol designs, and adaptive designs. Additionally, we review some analytic strategies that are often associated with these designs, such as the use of causal inference methods, and Bayesian methods. We hope this review will raise awareness of these novel approaches and encourage their use in studies of rare diseases.

Accrual-Monitoring Practices for Various Disease Trials among AACI Member Cancer Centers

Progress in the management of rare diseases, including rare cancers, is dependent upon clinical trials; however, as many as 32% of rare-disease trials go uncompleted or unpublished due to insufficient accrual. Monitoring practices may differ between institutions. We sought to survey the regulatory standards for various trial types among major U.S. cancer centers. A 10-question survey was designed using Qualtrics assessment software. The survey was sent via email to an internal server of member institutions of the Association of American Cancer Institutes (AACI). Of 103 AACI centers, 31% completed the survey (n = 32). Respondents differed in their definitions of a rare disease, minimum expectations for rare tumor studies, and frequency of accrual monitoring by their institutional Protocol Review and Monitoring Committee. Seventy-three percent of respondents did not close trials based on low accrual. Strategies to optimize accrual included investigator incentives for high accrual and penalties for low accrual in 37% and 13% of respondents, respectively.

The Rare Disease Research Scholars Program: A training curriculum for clinical researchers with mixed methods evaluation study

Rare disease clinician investigators are essential to ensure appropriate diagnosis, care, and treatment for the rapidly growing rare disease population. As these researchers are spread across many specialties, learning the unique skill set for rare disease research (RDR) can be a hurdle and may hinder progress in the field. The need for an RDR focused training program for investigators in many specialties and backgrounds was identified in a needs assessment of trainees in the NIH funded Rare Diseases Clinical Research Network. Based on this information, the Rare Disease Research Scholars Program (RDRSP) was developed. We describe the needs assessment, curriculum creation, scholar recruitment, and outcome evaluation based on four years of programmatic data (2015–2019). This one year-long RDRSP uses a blended approach that includes in-person, web-based, synchronous and asynchronous learning. We evaluated the RDRSP using quantitative and qualitative approaches. Quantitative measures included pre and post questionnaires about knowledge, self-efficacy, and intent to remain in RDR. Data were analyzed using descriptive statistics and a paired t-test. Qualitative semi-structured interviews explored the RDR scholars’ perceptions of the RDRSP; thematic analysis examined the textual data. Quantitative pre- and post-measures were statistically significant in the following areas: 1) improved knowledge content in RDR, 2) enhanced self-efficacy in clinical research, and 3) intent to remain in the field of RDR. Qualitative data analysis found the program supported the development of the scholar’s research skills as well as ‘soft-skills’. By combining training of skills unique to RDR with the more general topics of leadership, mentorship and collaboration among participants in diverse specialties, we created a program that supports the development of the next generation of rare disease clinician investigators and serves as a model for training in other niche research areas.

Randomized and non-randomized designs for causal inference with longitudinal data in rare disorders

In the United States, approximately 7000 rare diseases affect 30 million patients, and only 10% of these diseases have existing therapies. Sound study design and causal inference methods are essential to demonstrate the therapeutic efficacy, safety, and effectiveness of new therapies. In the rare diseases setting, several factors challenge the use of typical parallel control designs: the small patient population size, genotypic and phenotypic diversity, and the complexity and incomplete understanding of the disorder’s progression. Repeated measures, when spaced appropriately relative to disease progression and exploited in design and analysis, can increase study power and reduce variability in treatment effect estimation. This paper reviews these longitudinal designs and draws the parallel between some new and existing randomized studies in rare diseases and their less well-known controlled observational study designs. We show that self-controlled randomized crossover and N-of-1 designs have similar considerations as the observational case series and case-crossover designs. Also, randomized sequential designs have similar considerations to longitudinal cohort studies using sequential matching or weighting to control confounding. We discuss design and analysis considerations for valid causal inference and illustrate them with examples of analyses in multiple rare disorders, including urea cycle disorder and cystic fibrosis.

Model organisms contribute to diagnosis and discovery in the undiagnosed diseases network: current state and a future vision

Decreased sequencing costs have led to an explosion of genetic and genomic data. These data have revealed thousands of candidate human disease variants. Establishing which variants cause phenotypes and diseases, however, has remained challenging. Significant progress has been made, including advances by the National Institutes of Health (NIH)-funded Undiagnosed Diseases Network (UDN). However, 6000-13,000 additional disease genes remain to be identified. The continued discovery of rare diseases and their genetic underpinnings provides benefits to affected patients, of whom there are more than 400 million worldwide, and also advances understanding the mechanisms of more common diseases. Platforms employing model organisms enable discovery of novel gene-disease relationships, help establish variant pathogenicity, and often lead to the exploration of underlying mechanisms of pathophysiology that suggest new therapies. The Model Organism Screening Center (MOSC) of the UDN is a unique resource dedicated to utilizing informatics and functional studies in model organisms, including worm (Caenorhabditis elegans), fly (Drosophila melanogaster), and zebrafish (Danio rerio), to aid in diagnosis. The MOSC has directly contributed to the diagnosis of challenging cases, including multiple patients with complex, multi-organ phenotypes. In addition, the MOSC provides a framework for how basic scientists and clinicians can collaborate to drive diagnoses. Customized experimental plans take into account patient presentations, specific genes and variant(s), and appropriateness of each model organism for analysis. The MOSC also generates bioinformatic and experimental tools and reagents for the wider scientific community. Two elements of the MOSC that have been instrumental in its success are (1) multidisciplinary teams with expertise in variant bioinformatics and in human and model organism genetics, and (2) mechanisms for ongoing communication with clinical teams. Here we provide a position statement regarding the central role of model organisms for continued discovery of disease genes, and we advocate for the continuation and expansion of MOSC-type research entities as a Model Organisms Network (MON) to be funded through grant applications submitted to the NIH, family groups focused on specific rare diseases, other philanthropic organizations, industry partnerships, and other sources of support.

The practice of active patient involvement in rare disease research using ICT: experiences and lessons from the RUDY JAPAN project

BACKGROUND

The role of patients in medical research is changing, as more emphasis is being placed on patient involvement, and patient reported outcomes are increasingly contributing to clinical decision-making. Information and communication technology provides new opportunities for patients to actively become involved in research. These trends are particularly noticeable in Europe and the US, but less obvious in Japan. The aim of this study was to investigate the practice of active involvement of patients in medical research in Japan by utilizing a digital platform, and to analyze the outcomes to clarify what specific approaches could be put into practice.

METHODS

We developed the RUDY JAPAN system, an ongoing rare disease medical research platform, in collaboration with the Rare and Undiagnosed Diseases Study (RUDY) project in the UK. After 2 years of preparation, RUDY JAPAN was launched in December 2017. Skeletal muscle channelopathies were initially selected as target diseases, and hereditary angioedema was subsequently added. Several approaches for active patient involvement were designed through patient-researcher collaboration, namely the Steering Committee, questionnaire development, dynamic consent, and other communication strategies. We analyzed our practices and experiences focusing on how each approach affected and contributed to the research project.

RESULTS

RUDY JAPAN has successfully involved patients in this research project in various ways. While not a part of the initial decision-making phase to launch the project, patients have increasingly been involved since then. A high level of patient involvement was achieved through the Steering Committee, a governance body that has made a major contribution to RUDY JAPAN, and the process of the questionnaire development. The creation of the Patient Network Forum, website and newsletter cultivated dialogue between patients and researchers. The registry itself allowed patient participation through data input and control of data usage through dynamic consent.

CONCLUSIONS

We believe the initial outcomes demonstrate the feasibility and utility of active patient involvement in Japan. The collaboration realized through RUDY JAPAN was enabled by digital technologies. It allowed busy patients and researchers to find the space to meet and work together for the Steering Committee, questionnaire development and various communication activities. While the practice of active patient involvement in Japan is still in its early stages, this research confirms its viability if the right conditions are in place. (331 words).

Developments in evidence creation for treatments of inborn errors of metabolism

Inborn errors of metabolism (IEM) represent the first group of genetic disorders, amenable to causal therapies. In addition to traditional medical diet and cofactor treatments, new treatment strategies such as enzyme replacement and small molecule therapies, solid organ transplantation, and cell-and gene-based therapies have become available. Inherent to the rare nature of the single conditions, generating high-quality evidence for these treatments in clinical trials and under real-world conditions has been challenging. Guidelines developed with standardized methodologies have contributed to improve the practice of care and long-term clinical outcomes. Adaptive trial designs allow for changes in sample size, group allocation and trial duration as the trial proceeds. n-of-1 studies may be used in small sample sized when participants are clinically heterogeneous. Multicenter observational and registry-based clinical trials are promoted via international research networks. Core outcome and standard data element sets will enhance comparative analysis of clinical trials and observational studies. Patient-centered outcome-research as well as patient-led research initiatives will further accelerate the development of therapies for IEM.

The Collaborative Network Approach: a model for advancing patient-centric research for Castleman disease and other rare diseases

There are ∼7000 rare diseases affecting 30 000 000 individuals in the U.S.A. 95% of these rare diseases do not have a single Food and Drug Administration-approved therapy. Relatively, limited progress has been made to develop new or repurpose existing therapies for these disorders, in part because traditional funding models are not as effective when applied to rare diseases. Due to the suboptimal research infrastructure and treatment options for Castleman disease, the Castleman Disease Collaborative Network (CDCN), founded in 2012, spearheaded a novel strategy for advancing biomedical research, the 'Collaborative Network Approach'. At its heart, the Collaborative Network Approach leverages and integrates the entire community of stakeholders - patients, physicians and researchers - to identify and prioritize high-impact research questions. It then recruits the most qualified researchers to conduct these studies. In parallel, patients are empowered to fight back by supporting research through fundraising and providing their biospecimens and clinical data. This approach democratizes research, allowing the entire community to identify the most clinically relevant and pressing questions; any idea can be translated into a study rather than limiting research to the ideas proposed by researchers in grant applications. Preliminary results from the CDCN and other organizations that have followed its Collaborative Network Approach suggest that this model is generalizable across rare diseases.

Assessing disease experience across the life span for individuals with osteogenesis imperfecta: challenges and opportunities for patient-reported outcomes (PROs) measurement: a pilot study

Background

Patient reported outcome (PRO) information is crucial for establishing better patient-provider communication, improving shared decision-making between clinicians and patients, assessing patient responses to therapeutic interventions, and increasing satisfaction with care. We used the Brittle Bones Disease Consortium (BBDC) Contact Registry for People with OI, managed by the Rare Disease Clinical Research Network (RDCRN) to (1) to evaluate the construct validity of the Patient-Reported Outcome Measurement Information System® (PROMIS®) to record important components of the disease experience among individuals with OI; and (2) explore the feasibility of using a registry to recruit individuals with OI to report on health status. Our long-term goal is to enhance communication of health and disease management findings back to the OI community, especially those who do not have access to major OI clinical centers.

Results

We demonstrated the construct validity of PROMIS instruments in OI. Our results confirm that the scores from most domains differ significantly from the general US population: individuals with OI have worse symptom burden and functioning. We found no excessive floor or ceiling effects. Our study demonstrates that the BBDC Contact Registry can be used to recruit participants for online health status surveys. However, there are numerous challenges that must be addressed: lack of self-knowledge of OI type, under-representation of men, limited ethnic diversity, and imperfect questionnaire completion rates.

Conclusion

Our pilot study demonstrated the feasibility of using a contact registry to recruit respondents from the OI community and to obtain analyzable PROMIS data regarding disease experience. Because the results differ from the general population and avoid excessive floor and ceiling effects, PROMIS instruments can be used to assess response to therapeutic interventions in individuals with OI. Future directions will include (1) development and validation of an OI-specific patient-based classification system that aggregates persons with similar clinical characteristics and risks for complications to identify treatment needs; and (2) integrating these PRO tools into routine patient care and research studies.

Electronic supplementary material

The online version of this article (10.1186/s13023-019-1004-x) contains supplementary material, which is available to authorized users.

National information system for rare diseases with an approach to data architecture: A systematic review

The study aims to systematically review literature on the rare diseases information system to identify architecture of this system from a data perspective. The search for relevant English language articles, based on keywords in title, abstract, Mesh and Emtree terms, was done in Pubmed and Embase (from 1980 to June 2017), Scopus, Science Direct and Cochran (from 1980 to July 2017). Articles were selected if they addressed data architecture of information systems with a focus on rare disease, and if at least one of their objectives dealt with design, implementation, and development of rare diseases information systems. Thirty-five studies met the inclusion criteria. The findings were categorized into six groups. This first group addressed organizations acting as data generators, data users, and data governors. The second group was related to data sources and databases. Datasets and data elements formed the third group of findings, including common datasets, specific datasets, and complementary datasets. The fourth group of findings was in relation to data standards. Data sharing and interactions among relevant bodies included the fifth group of the findings. The last group of findings was pertinent to procedures and criteria used for checking the quality of data, as cross review checking was a main procedure assessing the accuracy, consistency, and completeness of data. Design and development of an integrated information system for rare diseases considering data architecture principles in practice could help eliminating issues with management of rare diseases through facilitating sharing information and experiences.

Using a meta-narrative literature review and focus groups with key stakeholders to identify perceived challenges and solutions for generating robust evidence on the effectiveness of treatments for rare diseases

INTRODUCTION

For many rare diseases, strong analytic study designs for evaluating the efficacy and effectiveness of interventions are challenging to implement because of small, geographically dispersed patient populations and underlying clinical heterogeneity. The objective of this study was to integrate perspectives from published literature and key rare disease stakeholders to better understand the perceived challenges and proposed methodological approaches to research on clinical interventions for rare diseases.

METHODS

We used a meta-narrative literature review and focus group interviews with key rare disease stakeholders to better understand the perceived challenges in generating and synthesizing treatment effectiveness evidence, and to describe various research methods for mitigating these identified challenges. Data from both components of this study were synthesized narratively according to research paradigms that emerged from our data.

RESULTS

Results from our meta-narrative literature review and focus group interviews revealed three fundamental challenges in generating robust treatment effectiveness evidence for rare diseases: i) limitations in recruiting a sufficient sample size to achieve planned statistical power; ii) inability to account for clinical heterogeneity and assess treatment effects across a clinical spectrum; and iii) reliance on short-term, surrogate outcomes whose clinical relevance is often unclear. We mapped these challenges and associated solutions to three interrelated research paradigms: i) explanatory evidence generation; ii) comparative effectiveness/pragmatic evidence generation; and iii) patient-oriented evidence generation. Within each research paradigm, numerous criticisms and potential solutions have been described with respect to overcoming these challenges from a research study design perspective.

CONCLUSIONS

Over time, discussions about clinical research for interventions for rare diseases have moved beyond methodological approaches to overcome challenges related to explanatory evidence generation, with increased recognition of the importance of pragmatic and patient-oriented evidence. Future directions for our work include developing a framework to expand current evidence synthesis practices to take into consideration many of the concepts discussed in this paper.

Genomic medicine for kidney disease

Technologies such as next-generation sequencing and chromosomal microarray have advanced the understanding of the molecular pathogenesis of a variety of renal disorders. Genetic findings are increasingly used to inform the clinical management of many nephropathies, enabling targeted disease surveillance, choice of therapy, and family counselling. Genetic analysis has excellent diagnostic utility in paediatric nephrology, as illustrated by sequencing studies of patients with congenital anomalies of the kidney and urinary tract and steroid-resistant nephrotic syndrome. Although additional investigation is needed, pilot studies suggest that genetic testing can also provide similar diagnostic insight among adult patients. Reaching a genetic diagnosis first involves choosing the appropriate testing modality, as guided by the clinical presentation of the patient and the number of potential genes associated with the suspected nephropathy. Genome-wide sequencing increases diagnostic sensitivity relative to targeted panels, but holds the challenges of identifying causal variants in the vast amount of data generated and interpreting secondary findings. In order to realize the promise of genomic medicine for kidney disease, many technical, logistical, and ethical questions that accompany the implementation of genetic testing in nephrology must be addressed. The creation of evidence-based guidelines for the utilization and implementation of genetic testing in nephrology will help to translate genetic knowledge into improved clinical outcomes for patients with kidney disease.

An overview of the impact of rare disease characteristics on research methodology

Background

About 30 million individuals in the United States are living with a rare disease, which by definition have a prevalence of 200,000 or fewer cases in the United States ([National Organization for Rare Disorders], [About NORD], [2016]). Disease heterogeneity and geographic dispersion add to the difficulty of completing robust studies in small populations. Improving the ability to conduct research on rare diseases would have a significant impact on population health. The purpose of this paper is to raise awareness of methodological approaches that can address the challenges to conducting robust research on rare diseases.

Approach

We conducted a landscape review of available methodological and analytic approaches to address the challenges of rare disease research. Our objectives were to: 1. identify algorithms for matching study design to rare disease attributes and the methodological approaches applicable to these algorithms; 2. draw inferences on how research communities and infrastructure can contribute to the efficiency of research on rare diseases; and 3. to describe methodological approaches in the rare disease portfolio of the Patient-Centered Outcomes Research Institute (PCORI), a funder promoting both rare disease research and research infrastructure.

Results

We identified three algorithms for matching study design to rare disease or intervention characteristics (Gagne, et.al, BMJ 349:g6802, 2014); (Gupta, et.al, J Clin Epidemiol 64:1085-1094, 2011); (Cornu, et. al, Orphet J Rare Dis 8:48,2012) and summarized the applicable methodological and analytic approaches. From this literature we were also able to draw inferences on how an effective research infrastructure can set an agenda, prioritize studies, accelerate accrual, catalyze patient engagement and terminate poorly performing studies. Of the 24 rare disease projects in the PCORI portfolio, 11 are randomized controlled trials (RCTs) using standard designs. Thirteen are observational studies using case-control, prospective cohort, or natural history designs. PCORI has supported the development of 9 Patient-Powered Research Networks (PPRNs) focused on rare diseases.

Conclusion

Matching research design to attributes of rare diseases and interventions can facilitate the completion of RCTs that are adequately powered. An effective research infrastructure can improve efficiency and avoid waste in rare disease research. Our review of the PCORI research portfolio demonstrates that it is feasible to conduct RCTs in rare disease. However, most of these studies are using standard RCT designs. This suggests that use of a broader array of methodological approaches to RCTs --such as adaptive trials, cross-over trials, and early escape designs can improve the productivity of robust research in rare diseases.

Creating a multi-center rare disease consortium - the Consortium of Eosinophilic Gastrointestinal Disease Researchers (CEGIR)

 Eosinophilic gastrointestinal disorders (EGIDs) affect various segments of the gastrointestinal tract. Since these disorders are rare, collaboration is essential to enroll subjects in clinical studies and study the broader population. The Rare Diseases Clinical Research Network (RDCRN), a program of the National Center for Advancing Translational Sciences (NCATS), funded the Consortium of Eosinophilic Gastrointestinal Disease Researchers (CEGIR) in 2014 to advance the field of EGIDs. CEGIR facilitates collaboration among various centers, subspecialties, patients, professional organizations and patient-advocacy groups and includes 14 clinical sites. It has successfully initiated two large multi-center clinical studies looking to refine EGID diagnoses and management. Several pilot studies are underway that focus on various aspects of EGIDs including novel therapeutic interventions, diagnostic and monitoring methods, and the role of the microbiome in pathogenesis. CEGIR currently nurtures five physician-scholars through a career training development program and has published more than 40 manuscripts since its inception. This review focuses on CEGIR's operating model and progress and how it facilitates a framework for exchange of ideas and stimulates research and innovation. This consortium provides a model for progress on other potential clinical areas.

Experience With Direct-to-Patient Recruitment for Enrollment Into a Clinical Trial in a Rare Disease: A Web-Based Study

Background

The target sample size for clinical trials often necessitates a multicenter (center of excellence, CoE) approach with associated added complexity, cost, and regulatory requirements. Alternative recruitment strategies need to be tested against this standard model.

Objectives

The aim of our study was to test whether a Web-based direct recruitment approach (patient-centric, PC) using social marketing strategies provides a viable option to the CoE recruitment method.

Methods

PC recruitment and Web-based informed consent was compared with CoE recruitment for a randomized controlled trial (RCT) of continuing versus stopping low-dose prednisone for maintenance of remission of patients with granulomatosis with polyangiitis (GPA).

Results

The PC approach was not as successful as the CoE approach. Enrollment of those confirmed eligible by their physician was 10 of 13 (77%) and 49 of 51 (96%) in the PC and CoE arms, respectively (P=.05). The two approaches were not significantly different in terms of eligibility with 34% of potential participants in the CoE found to be ineligible as compared with 22% in the PC arm (P=.11) nor in provider acceptance, 22% versus 26% (P=.78). There was no difference in the understanding of the trial as reflected in the knowledge surveys of individuals in the PC and CoE arms.

Conclusions

PC recruitment was substantially less successful than that achieved by the CoE approach. However, the PC approach was good at confirming eligibility and was as acceptable to providers and as understandable to patients as the CoE approach. The PC approach should be evaluated in other clinical settings to get a better sense of its potential.

From promising molecules to orphan drugs: Early clinical drug development

Phase-1 (also known as "First-in-Man") clinical trials initiate the early clinical development of possible new medicines. Patient participation in this early phase of clinical trials is rather limited. After successful phase 1 trials, further phase 2 and phase 3 clinical trials in patients may lead to a marketing authorization. In the first 15 years of the European Union Orphan Drug Directive, 4.5% of the orphan drug applications were authorized. However, for many of these orphan drugs, no phase 1 studies were required, as these products were already well known pharmaceutical substances, with a clearly defined pharmacological profile. Furthermore, for 19 orphan drugs, already authorized by the European Medicines Agency (EMA), the original rare indication was extended to another rare disease and no phase 1 trials were needed. Phase 1 studies need to be performed in a sufficient number of volunteers even for medicinal products intended for a very limited number of patients.

Facilitating Clinical Studies in Rare Diseases

In recent years, there have been many scientific advances and new collaborations for rare diseases research and, ultimately, the health of patients living with rare diseases. However, for too many rare diseases, there still is no effective treatment, and our understanding of the incidence, prevalence, and underlying etiology is incomplete. To facilitate the studies needed to answer the many open questions there is a great need for the active involvement of all stakeholders, most importantly of patient groups. Also, the creation of streamlined infrastructure for performing multi-site clinical studies is critical, as is the engagement of multi-disciplinary teams with shared focus on a group of diseases. Another essential component of such efforts is to collect standardized data so that downstream meta-analyses and data sharing can be facilitated. To ensure high-quality protocols and datasets, a central data management and coordinating center is important. Since there are more than 6000 rare diseases, instead of focusing on single rare disease, it is more impactful to create platforms and methods that can support a group of rare diseases.

Administrative Claims Data for Economic Analyses in Hematopoietic Cell Transplantation: Challenges and Opportunities

There is an increasing need for the development of approaches to measure quality, costs, and resource utilization patterns among allogeneic hematopoietic cell transplantation (HCT) patients. Administrative claims data provide an opportunity to examine service utilization and costs, particularly from the payer's perspective. However, because administrative claims data are primarily designed for reimbursement purposes, challenges arise when using it for research. We use a case study with data derived from the 2007 to 2011 Truven Health MarketScan Research database to discuss opportunities and challenges for the use of administrative claims data to examine the costs and service utilization of allogeneic HCT and chemotherapy alone for patients with acute myeloid leukemia (AML). Starting with a cohort of 29,915 potentially eligible patients with a diagnosis of AML, we were able to identify 211 patients treated with HCT and 774 treated with chemotherapy alone where we were sufficiently confident of the diagnosis and treatment path to allow analysis. Administrative claims data provide an avenue to meet the need for health care costs, resource utilization, and outcome information. However, when using these data, a balance between clinical knowledge and applied methods is critical to identifying a valid study cohort and accurate measures of costs and resource utilization.

The partnership of patient advocacy groups and clinical investigators in the rare diseases clinical research network

BACKGROUND

Among the unique features of the Rare Diseases Clinical Research Network (RDCRN) Program is the requirement for each Consortium to include patient advocacy groups (PAGs) as research partners. This development has transformed the work of the RDCRN and is a model for collaborative research. This article outlines the roles patients and PAGs play in the RDCRN and reports on the PAGs' impact on the Network's success.

METHODS

Principal Investigators from the 17 RDCRN Consortia and 28 representatives from 76 PAGs affiliated with these Consortia were contacted by email to provide feedback via an online RDCRN survey. Impact was measured in the key areas of 1) Research logistics; 2) Outreach and communication; and 3) Funding and in-kind support. Rating choices were: 1-very negative, 2-somewhat negative, 3-no impact, 4-somewhat positive, and 5-very positive.

RESULTS

Twenty-seven of the PAGs (96 %) disseminate information about the RDCRN within the patient community. The Consortium Principal Investigators also reported high levels of PAG involvement. Sixteen (94 %) Consortium Principal Investigators and 25 PAGs (89 %) reported PAGs participation in protocol review, study design, Consortium conference calls, attending Consortium meetings, or helping with patient recruitment.

CONCLUSIONS

PAGs are actively involved in shaping Consortia's research agendas, help ensure the feasibility and success of research protocols by assisting with study design and patient recruitment, and support training programs. This extensive PAG-Investigator partnership in the RDCRN has had a strongly positive impact on the success of the Network.

Developing methodology for the creation of clinical practice guidelines for rare diseases: A report from RARE-Bestpractices

Rare diseases are a global public health priority; they can cause significant morbidity and mortality, can gravely affect quality of life, and can confer a social and economic burden on families and communities. These conditions are, by their nature, encountered very infrequently by clinicians. Thus, clinical practice guidelines are potentially very helpful in supporting clinical decisions, health policy and resource allocation. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) system is a structured and transparent approach to developing and presenting summaries of evidence, grading its quality, and then transparently interpreting the available evidence to make recommendations in health care. GRADE has been adopted widely. However, its use in creating guidelines for rare diseases – which are often plagued by a paucity of high quality evidence – has not yet been explored. RARE-Bestpractices is a project to create and populate a platform for sharing best practices for management of rare diseases. A major aim of this project is to ensure that European Union countries have the capacity to produce high quality clinical practice guidelines for rare diseases. On February 12, 2013 at the Istituto Superiore di Sanità, in Rome, Italy, the RARE-Bestpractices group held the first of a series of 2 workshops to discuss methodology for creating clinical practice guidelines, and explore issues specific to rare diseases. This paper summarizes key results of the first workshop, and explores how the current GRADE approach might (or might not) work for rare diseases. Avenues for future research are also identified.

Biomedical Data Sharing and Reuse: Attitudes and Practices of Clinical and Scientific Research Staff

Background

Significant efforts are underway within the biomedical research community to encourage sharing and reuse of research data in order to enhance research reproducibility and enable scientific discovery. While some technological challenges do exist, many of the barriers to sharing and reuse are social in nature, arising from researchers’ concerns about and attitudes toward sharing their data. In addition, clinical and basic science researchers face their own unique sets of challenges to sharing data within their communities. This study investigates these differences in experiences with and perceptions about sharing data, as well as barriers to sharing among clinical and basic science researchers.

Methods

Clinical and basic science researchers in the Intramural Research Program at the National Institutes of Health were surveyed about their attitudes toward and experiences with sharing and reusing research data. Of 190 respondents to the survey, the 135 respondents who identified themselves as clinical or basic science researchers were included in this analysis. Odds ratio and Fisher’s exact tests were the primary methods to examine potential relationships between variables. Worst-case scenario sensitivity tests were conducted when necessary.

Results and Discussion

While most respondents considered data sharing and reuse important to their work, they generally rated their expertise as low. Sharing data directly with other researchers was common, but most respondents did not have experience with uploading data to a repository. A number of significant differences exist between the attitudes and practices of clinical and basic science researchers, including their motivations for sharing, their reasons for not sharing, and the amount of work required to prepare their data.

Conclusions

Even within the scope of biomedical research, addressing the unique concerns of diverse research communities is important to encouraging researchers to share and reuse data. Efforts at promoting data sharing and reuse should be aimed at solving not only technological problems, but also addressing researchers’ concerns about sharing their data. Given the varied practices of individual researchers and research communities, standardizing data practices like data citation and repository upload could make sharing and reuse easier.

Rare disease registries classification and characterization: a data mining approach

BACKGROUND

The European Commission and Patients Organizations identify rare disease registries (RDRs) as strategic instruments to develop research and improve knowledge in the field of rare diseases. Interoperability between RDRs is needed for research activities, validation of therapeutic treatments, and public health actions. Sharing and comparing information requires a uniform and standardized way of data collection, so levels of interconnection between RDRs with similar aims and/or nature of data should be identified. The objective of this study is to define a classification and characterization of RDRs in order to identify different profiles and informative needs.

METHODS

Exploratory statistical analyses (cluster analysis and random forest) were applied to data derived from the EPIRARE project ('Building Consensus and Synergies for the EU Rare Disease Patient Registration') survey on the activities and needs of RDRs.

RESULTS

The cluster analysis identified 3 main typologies of RDRs: public health, clinical and genetic research, and treatment registries. The analysis of the most informative variables, identified by the random forest method, led to the characterization of 3 types of RDRs and the definition of different profiles and informative needs.

CONCLUSIONS

These results represent a useful source of information to facilitate the harmonization and interconnection of RDRs in accordance with the different profiles identified. It could help sharing the information between RDRs with similar profiles and, whenever possible, interconnections between registries with different profiles.