To what degree are orphan drugs patient-centered? A review of the current state of clinical research in rare diseases

Critical path activities in clinical trial setup and conduct: How to avoid bottlenecks and accelerate clinical trials

Most clinical trials are delayed due to scientific and/or operational challenges. Any effort to minimize delays can generate value for patients and sponsors. This article reviews critical path process steps commonly identified by practitioners, such as during protocol development, site contracting, or patient recruitment. Commonly considered measures, such as adding more trial sites or countries, were contrasted with less frequented measures, such as evidence-based feasibility or real-world evidence analysis, to help validate assumptions before clinical trial initiation. In a broad analysis, we integrated a literature review with a practitioner survey into a framework to help decision makers on the most critical process steps when setting up or conducting clinical trials in order to bring critical treatments to patients faster.

Patient-reported outcomes validated in phase 3 clinical trials: a targeted literature review

BACKGROUND

Regulatory guidance advises validation of patient-reported outcome (PRO) instruments prior to use in pivotal clinical studies, which may then be used to generate critical patient-centered evidence and support labelling claims. This targeted literature review aimed to determine if PRO instruments psychometrically validated in a phase 3 trial setting could support label claims from the same phase 3 study (i.e. PRO data were generated as an endpoint).

METHODS

A targeted search of published studies (1 January 2006-3 June 2021) using the MEDLINE database identified PRO instruments validated during phase 3 trials. The search included instrument terms (e.g. patient-reported outcome measures, questionnaire, survey) and validation terms (e.g. reproducibility, minimal important difference), without filtering for therapeutic indications. Results were limited to phase 3 clinical trials or validation studies. The PROLABELS database was used to identify PROs validated in phase 3 trials and accepted in labelling claims.

RESULTS

Of 355 references identified, 68 studies with PRO psychometric validation in phase 3 studies were selected, covering 78 instruments. Of these, 20 were novel PRO instruments and 58 were existing instruments being validated for a new therapeutic indication/population. The psychometric properties most frequently validated were internal consistency reliability, known-group validity, responsiveness, minimal important difference, and concurrent validity. Five novel instruments obtained ten labelling claims for seven drugs/products.

CONCLUSIONS

These results suggest that quantitative validation of novel PRO instruments, and existing PROs for new indications, can occur within the context of phase 3 trials, and these PROs can also support label claims.

How do patients and other members of the public engage with the orphan drug development? A narrative qualitative synthesis

BACKGROUND

The diversity of patient experiences of orphan drug development has until recently been overlooked, with the existing literature reporting the experience of some patients and not others. The current evidence base (the best available current research) is dominated by quantitative surveys and patient reported outcome measures defined by researchers. Where research that uses qualitative methods of data collection and analysis has been conducted, patient experiences have been studied using content analysis and automatic textual analysis, rather than in-depth qualitative analytical methods. Systematic reviews of patient engagement in orphan drug development have also excluded qualitative studies. The aim of this paper is to review qualitative literature about how patients and other members of the public engage with orphan drug development.

METHODS

We conducted a systematic search of qualitative papers describing a range of patient engagement practices and experiences were identified and screened. Included papers were appraised using a validated tool (CASP), supplemented by reporting guidance (COREQ), by two independent researchers.

RESULTS

262 papers were identified. Thirteen papers reported a range of methods of qualitative data collection. Many conflated patient and public involvement and engagement (PPIE) with qualitative research. Patients were typically recruited via their physician or patient organisations. We identified an absence of overarching philosophical or methodological frameworks, limited details of informed consent processes, and an absence of recognisable methods of data analysis. Our narrative synthesis suggests that patients and caregivers need to be involved in all aspects of trial design, including the selection of clinical endpoints that capture a wider range of outcomes, the identification of means to widen access to trial participation, the development of patient facing materials to optimise their decision making, and patients included in the dissemination of trial results.

CONCLUSIONS

This narrative qualitative synthesis identified the explicit need for methodological rigour in research with patients with rare diseases (e.g. appropriate and innovative use of qualitative methods or PPIE, rather than their conflation); strenuous efforts to capture the perspectives of under-served, under-researched or seldom listened to communities with experience of rare diseases (e.g. creative recruitment and wider adoption of post-colonial practices); and a re-alignment of the research agenda (e.g. the use of co-design to enable patients to set the agenda, rather than respond to what they are being offered).

The Impact of Artificial Intelligence in the Odyssey of Rare Diseases

Emerging machine learning (ML) technologies have the potential to significantly improve the research and treatment of rare diseases, which constitute a vast set of diseases that affect a small proportion of the total population. Artificial Intelligence (AI) algorithms can help to quickly identify patterns and associations that would be difficult or impossible for human analysts to detect. Predictive modeling techniques, such as deep learning, have been used to forecast the progression of rare diseases, enabling the development of more targeted treatments. Moreover, AI has also shown promise in the field of drug development for rare diseases with the identification of subpopulations of patients who may be most likely to respond to a particular drug. This review aims to highlight the achievements of AI algorithms in the study of rare diseases in the past decade and advise researchers on which methods have proven to be most effective. The review will focus on specific rare diseases, as defined by a prevalence rate that does not exceed 1-9/100,000 on Orphanet, and will examine which AI methods have been most successful in their study. We believe this review can guide clinicians and researchers in the successful application of ML in rare diseases.

Impact of Potential Symptoms and Risks Associated with Acid Sphingomyelinase Deficiency on Patients and Caregivers: A Best-Worst Scaling Study

Purpose

Acid sphingomyelinase deficiency (ASMD) is a rare, progressive, and potentially fatal disease affecting major organs; its symptoms present heterogeneously. Data on the most bothersome symptoms for patients with ASMD types B or A/B and their caregivers or parents are limited. We conducted a survey to quantify the relative impact of potential ASMD symptoms and risks for patients and parents/caregivers.

Patients and Methods

Twenty respondents, recruited via National Niemann-Pick Disease Foundation (United States) and Niemann-Pick United Kingdom, took a preference survey: 11 patients who had a self-reported diagnosis of ASMD types B or A/B and 9 parents who had a child with ASMD types B or A/B. Using object-case best-worst scaling, we explored the most and least bothersome among a set of 15 ASMD symptoms/risks selected based on clinical input and qualitative research with patients and caregivers. In 15 experimentally designed questions containing five items each, respondents ranked the symptoms/risks, irrespective of their experiences with them. Data were analyzed using a conditional multinomial logit model.

Results

Patients reported constant abdominal pain, severe pain in bones and joints, and severe fatigue to be the most bothersome potential symptoms or risks, followed by a chance of bleeding in the spleen. The next most bothersome potential symptom was constant shortness of breath. Easy bruising and noticeable abdominal enlargement were among the least bothersome symptoms. The most bothersome symptom for parents was bleeding in the spleen.

Conclusion

Patients and parents had similar perceptions of the most bothersome potential symptoms/risks. Despite the small sample size typical of rare disease studies, understanding patient preferences is important for such diseases and can inform shared decision-making.

Regulatory Considerations Toward Orphan Drug Designation and Orphan Drug Exclusivity in the United States and European Union: Structural Similarity, Clinical Superiority/Significant Benefit, and Case Studies

The U.S. Food and Drug Administration and European Commission have developed successful orphan drug legislation to promote the research, development, and marketing approval of drugs to treat rare diseases. Central to these regulations are the concepts of structural similarity and clinical superiority/significant benefit to achieve orphan drug exclusivity. However, differences in health authority expectations remain regarding the qualification for an orphan drug designation, defining structural similarity, and demonstrating clinical superiority/significant benefit. These differences can create sponsor company uncertainty regarding the approvability of products (e.g., blocking risk by an existing orphan product) and divergent orphan drug decisions among health authorities. A comprehensive assessment of current regulations, case studies in exclusivities, and recommendations for improvement are presented.

Literature Review on Health Emigration in Rare Diseases-A Machine Learning Perspective

The article deals with one of the effects of health inequalities and gaps in access to treatments for rare diseases, namely health-driven emigration. The purpose of the paper is to systematize knowledge about the phenomenon of health emigration observed among families affected by rare diseases, for which reimbursed treatment is available, but only in selected countries. The topic proved to be niche; the issue of "health emigration in rare diseases" is an area for exploration. Therefore, the further analysis used text mining and machine learning methods based on a database selected based on keywords related to this issue. The results made it possible to systematize the guesses made by researchers in management and economic fields, to identify the most common keywords and thematic clusters around the perspective of the patient, drug manufacturer and treatment reimbursement decision-maker, and the perspective integrating all the others. Since the topic of health emigration was not directly addressed in the selected sources, the authors attempted to define the related concepts and discussed the importance of this phenomenon in managing the support system in rare diseases. Thus, they indicated directions for further research in this area.

Improving Interpretation of Evidence Relating to Quality of Life in Health Technology Assessments of Rare Disease Treatments

Rare diseases are often severe, debilitating, life-limiting conditions, many of which occur in childhood. These complex conditions have a wide range of clinical manifestations that have a substantial impact on the lives of patients, carers and families and often produce heterogeneous clinical outcomes. Therefore, the evaluation of quality-of-life (QoL) impacts is important. In health technology assessment (HTA), patient-reported outcome measures (PROMs) and/or health state utility values (HSUVs) are used to determine QoL impacts of new treatments, but their use in rare diseases is challenging due to small and heterogeneous populations and limited disease knowledge. This paper describes challenges associated with the use of patient-reported outcomes (PROs)/HSUVs to evaluate QoL in HTA of rare disease treatments (RDTs) and identifies five recommendations to ensure appropriate interpretation of QoL impacts. These were derived from mixed methods research (literature reviews, appraisal document analyses, appraisal committee observations and interviews) examining the use of PROs/HSUVs in HTA of RDTs. They highlight that HTAs of RDTs must (1) understand the QoL impacts of the disease and of treatments; (2) critically assess PRO data, recognising the nuances in development and administration of PROMs/HSUVs, considering what is feasible and what matters most to the patient population; (3) recognise that lack of significant effect on a PRO does not imply no QoL benefit; (4) use different forms of evidence to understand QoL impacts, such as patient input; and (5) provide methodological guidance to capture QoL impacts on patients/carers.

Patient-Centered Core Impact Sets: What They are and Why We Need Them

A quote attributed to Mark Twain states, “What gets us into trouble is not what we don’t know. It’s what we know for sure that just ain’t so.” The growing focus on patient centricity has revealed a misalignment between what patients report as important to them about their disease and/or treatment, and the data collected in research and care. Decisions across healthcare are made using an evidence base most stakeholders acknowledge is inadequate. Patients might report that what is important to them are everyday life impacts, concepts that can be very different from the more typical clinical outcomes we often track. In this paper, we encourage expanding current thinking to all “impacts,” not only health outcomes, but also the other equally (and sometimes more important) concerns patients report as important to them. We propose that a patient-centered core impact set be developed for each disease or condition of interest, and/or subpopulation of patients. A patient-centered core impact set begins with gathering from patients and caregivers an inventory of all impacts disease and treatments have on a patient’s (and carers’ and families’) life. Then, through a formal prioritization process, a core set of impacts is derived, inclusive of but extending beyond relevant health outcomes. We offer several recommendations on how to move the goal of a patient-centered core impact set forward through collaboration, leadership, and establishment of a patient-centered core impact set development blueprint with supporting tools.

Understanding disease symptoms and impacts and producing qualitatively-derived severity stages for MPS IIIA: a mixed methods approach

Background

MPS IIIA is a rare, degenerative pediatric genetic disease characterized by symptoms impacting cognition, mobility and behavior; the mean age of death is around 15 years of age. Currently, there are no approved therapies for MPS IIIA.

Methods

A two-year, multi-center, prospective, descriptive cohort study was conducted to document the natural history course of MPS IIIA. In the context of this study, semi-structured interviews were performed with parents of children at study entry and one year later. Interview transcripts were analyzed using thematic analysis methods to identity concepts of interest to children and parents, identify what factors impacted parents’ burden the most, and develop qualitatively-derived disease severity stages. Children were sorted into these stages according to the symptoms their parents described at the entry interview. This sorting was compared quantitatively to the sorting of children at baseline according to the child’s calendar age and their BSID development quotient (DQ).

Results

22 parents in France, Germany, the Netherlands and the UK were interviewed. Children ranged in age from 28 to 105 months (mean 61.4 months). The conceptual models for children’s symptoms and impacts and parents’ impacts provided a detailed and comprehensive picture of what it is like for children of various ages and their parents to live with MPS IIIA. Four factors were identified as mediating the burden perceived by parents: state support, family support, time since diagnosis, and parent coping strategy. Four disease stages were developed, accounting for both the presence and the severity of MPS IIIA symptoms. The comparison of children’s sorting into these stages with the BSID DQ and the child’s calendar age showed strong statistical associations.

Conclusions

The findings of this qualitative research embedded in a natural history study add to the current understanding of MPS IIIA as a complex disease that impacts every aspect of the lives of children and their families. This study demonstrates the unique potential of mixed methods research in rare diseases to address some of the current limitations of more traditional quantitative approaches by providing an individualized, detailed understanding of the patient experience.

Advances in orphan drug development: Time to change the status and stereotype

Rare diseases remain a challenge for many of the countries in the world. The millions of people collectively suffering from rare diseases, in the context of raging COVID-19 pandemics globally, require an innovative and recent solution from different stakeholders. Regulatory bodies such as the Food and Drug Administration and the European Medicines Agency have come up with many different approaches including financial assistance to prompt drug development and approval. Novel approaches pertinent to clinical trials of such drugs such as patient centricity, early interaction with regulatory bodies, and establishing clinical outcome of interest have been experimented. Various international organizations including cross-country collaborators have initiated various projects or consortiums to bridge the gap between knowledge and practice. The challenges remain more pivotal in developing countries such as India, which has adopted few noteworthy initiatives by involving relevant stakeholders in the presence of limited resources, infrastructures, and a nascent regulatory framework. Therefore, it is imperative to revisit the key aspects of orphan drug development to fulfill the unmet needs of such patients suffering from various rare diseases.

Colocating Wound Care for Patients with Sickle Cell Ulcers in a Hematology Clinic

OBJECTIVE

Leg ulcers affect 15% of people with sickle cell disease. However, wound centers typically treat few people with this condition, which makes it difficult to concentrate clinical expertise or support the scientific study of this orphan disease. This article describes an initiative to increase engagement in care through a partnership between wound healing and hematology leadership that led to colocating wound services within a sickle cell clinic.

METHODS

Via a retrospective chart review, the authors collected records of all adult patients with sickle cell disease who received wound care in the last decade, including 7 years of wound center data and 3 years of data from the colocated services. Patient and visit characteristics were analyzed using descriptive analytics.

RESULTS

The general wound center had previously treated 35 patients with sickle cell ulcers over 7 years. In contrast, colocated services engaged 56 patients within 3 years, including 20 who transferred care and 36 new patients. The majority of patients at the colocated site were women, unlike at the wound center (58% vs 47%, P = .07). Results indicated that 36% of patients healed initial wounds, and 45% had new wound occurrences.

CONCLUSIONS

Colocation successfully increases the number of patients with sickle cell ulcers who will engage in wound care at a single site, laying the foundation for clinical studies to improve the evidence base for this difficult-to-treat condition.

Establishing a second-generation artificial intelligence-based system for improving diagnosis, treatment, and monitoring of patients with rare diseases

Patients with rare diseases are a major challenge for healthcare systems. These patients face three major obstacles: late diagnosis and misdiagnosis, lack of proper response to therapies, and absence of valid monitoring tools. We reviewed the relevant literature on first-generation artificial intelligence (AI) algorithms which were designed to improve the management of chronic diseases. The shortage of big data resources and the inability to provide patients with clinical value limit the use of these AI platforms by patients and physicians. In the present study, we reviewed the relevant literature on the obstacles encountered in the management of patients with rare diseases. Examples of currently available AI platforms are presented. The use of second-generation AI-based systems that are patient-tailored is presented. The system provides a means for early diagnosis and a method for improving the response to therapies based on clinically meaningful outcome parameters. The system may offer a patient-tailored monitoring tool that is based on parameters that are relevant to patients and caregivers and provides a clinically meaningful tool for follow-up. The system can provide an inclusive solution for patients with rare diseases and ensures adherence based on clinical responses. It has the potential advantage of not being dependent on large datasets and is a dynamic system that adapts to ongoing changes in patients' disease and response to therapy.

Measuring health-related quality of life in patients with rare disease

Background

There has been a growing emphasis on health-related quality of life (HRQoL) as an important outcome in rare disease drug development, although its assessment may be useful outside the drug development context, including in clinical applications or natural history studies. Central to assessing quality of life in health research is utilizing outcome measures that capture symptoms and impacts of the disease and treatment that are important and relevant to patients. Identifying and implementing valid and reliable tools to measure HRQoL in rare diseases poses unique challenges that often require creative solutions.

Main body

In this commentary, we explore some of the challenges in HRQoL assessment in rare disease, propose solutions, and consider regulatory issues. Some of the solutions discussed entail the use of item banks, adapting existing measures from phenotypically similar disease contexts, use of multi-domain measurement indices, and adapting methods for assessing content validity of existing measures. Current regulatory considerations are discussed and resources outlined.

Conclusion

Quality of life may be the most important endpoint for patients with rare diseases, and the challenges of valid assessment require effort and innovative thinking specific to each context to improve measurement and clinical outcomes.

Health-related quality of life in adults with osteogenesis imperfecta

Patient-reported outcome measures (PROMs) are increasingly utilized as endpoints in clinical trials. The Short Form Health Survey-12 (SF-12v2) is a generic PROM for adults. We sought to evaluate the validity of SF-12v2 in adults with osteogenesis imperfecta (OI). Physical and mental health-related quality of life (HRQoL) were assessed in a large cohort of adults in a multicenter, observational, natural history study. Physical HRQoL scores were correlated with the Gillette Functional Assessment Questionnaire (GFAQ). We calculated sample sizes required in clinical trials with crossover and parallel-group designs to detect clinically meaningful changes in physical HRQoL. Three hundred and two adults with OI types I, III, and IV were enrolled. Physical HRQoL scores in the study population were lower than population norms. Physical HRQoL scores moderately correlated with GFAQ for OI types I and IV. We found no correlations between mental and physical HRQoL. From a clinical trial readiness perspective, we show that SF-12v2 reliably measures physical function in adults with OI and can be utilized in crossover trials to detect meaningful physical HRQoL changes with small sample sizes. This study shows that SF-12v2 can be used to measure changes in physical HRQoL in response to interventions in OI.

The Use of Patient-Reported Outcome Measures in Rare Diseases and Implications for Health Technology Assessment

Background

Patient-reported outcome measures (PROMs) are used in health technology assessment (HTA) to measure patient experiences with disease and treatment, allowing a deeper understanding of treatment impact beyond clinical endpoints. Developing and administering PROMs for rare diseases poses unique challenges because of small patient populations, disease heterogeneity, lack of natural history knowledge, and short-term studies.

Objective

This research aims to identify key factors to consider when using different types of PROMs in HTA for rare disease treatments (RDTs).

Methods

A scoping review of scientific and grey literature was conducted, with no date or publication type restrictions. Information on the advantages of and the challenges and potential solutions when using different types of PROMs for RDTs, including psychometric properties, was extracted and synthesized.

Results

Of 79 records from PubMed, 32 were included, plus 12 records from the grey literature. PROMs for rare diseases face potential data collection and psychometric challenges resulting from small patient populations and disease heterogeneity. Generic PROMs are comparable across diseases but not sensitive to disease specificities. Disease-specific instruments are sensitive but do not exist for many rare diseases and rarely provide the utility values required by some HTA bodies. Creating new PROMs is time and resource intensive. Potential solutions include pooling data (multi-site/international data collection), using computer-assisted technology, or using generic and disease-specific PROMs in a complementary way.

Conclusions

PROMs are relevant in HTA for RDTs but pose a number of difficulties. A deeper understanding of the potential advantages of and the challenges and potential solutions for each can help manage these difficulties.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40271-020-00493-w.