Factors Associated With Early Motor Function Trajectories in DMD After Glucocorticoid Initiation: Post Hoc Analysis of the FOR-DMD Trial.

BACKGROUND AND OBJECTIVES: Clinical trials in Duchenne muscular dystrophy (DMD) require 3-6 months of stable glucocorticoids, and the primary outcome is explored at 48-52 weeks. The factors that influence the clinical outcome assessment (COA) trajectories soon after glucocorticoid initiation are relevant for the design and analysis of clinical trials of novel drugs. We describe early COA trajectories, associated factors, and the time from glucocorticoid initiation to COA peak. METHODS: This was a prospective 18-month analysis of the Finding the Optimum Corticosteroid Regimen for Duchenne Muscular Dystrophy study. Four COAs were investigated: rise from supine velocity (RFV), 10-meter walk/run velocity (10MWRV), North Star Ambulatory Assessment (NSAA) total score, and 6-minute walk test distance (6MWT). The relationships of baseline age (4-5 vs 6-7 years), COA baseline performance, genotype, and glucocorticoid regimen (daily vs intermittent) with the COA trajectories were evaluated using linear mixed-effects models. RESULTS: One hundred ninety-six glucocorticoid-naïve boys with DMD aged 4-7 years were enrolled. The mean age at baseline was 5.9 ± 1.0 years, 66% (n = 130) were on daily regimens, 55% (n = 107) showed a 6MWT distance >330 metres; 41% (n = 78) showed RFV >0.2 rise/s; 76% (n = 149) showed 10MWRV >0.142 10m/s, and 41.0% (n = 79) showed NSAA total score >22 points. Mean COA trajectories differed by age at glucocorticoid initiation (p < 0.01 for RFV, 10MWRV, and NSAA; p < 0.05 for 6MWT) and regimen (p < 0.01 for RFV, 10MWRV, and NSAA). Boys younger than 6 years reached their peak performance 12-18 months after glucocorticoid initiation. Boys aged 6 years or older on a daily regimen peaked between months 9 and 12 and those on an intermittent regimen by 9 months. The baseline COA performance was associated with the NSAA (p < 0.01) and the 6MWT trajectory in boys younger than 6 years on a daily regimen (p < 0.01). Differences in the mean trajectories by genotype were not significant. DISCUSSION: Glucocorticoid regimen, age, duration of glucocorticoid exposure, and baseline COA performance need to be considered in the design and analysis of clinical trials in young boys with DMD.

Developing a Natural History Model for Duchenne Muscular Dystrophy.

BACKGROUND: The aim of this study was to pool multiple data sets to build a patient-centric, data-informed, natural history model (NHM) for Duchenne muscular dystrophy (DMD) to estimate disease trajectory across patient lifetime under current standard of care in future economic evaluations. The study was conducted as part of Project HERCULES, a multi-stakeholder collaboration to develop tools to support health technology assessments of new treatments for DMD. METHODS: Health states were informed by a review of NHMs for DMD and input from clinicians, patients and caregivers, and defined using common outcomes in clinical trials and real-world practice. The primary source informing the NHM was the Critical Path Institute Duchenne Regulatory Science Consortium (D-RSC) database. This was supplemented with expert input obtained via an elicitation exercise, and a systematic literature review and meta-analysis of mortality data. RESULTS: The NHM includes ambulatory, transfer and non-ambulatory phases, which capture loss of ambulation, ability to weight bear and upper body and respiratory function, respectively. The NHM estimates patients spend approximately 9.5 years in ambulatory states, 1.5 years in the transfer state and the remainder of their lives in non-ambulatory states. Median predicted survival is 34.8 years (95% CI 34.1-35.8). CONCLUSION: The model includes a detailed disease pathway for DMD, including the clinically and economically important transfer state. The NHM may be used to estimate the current trajectory of DMD in economic evaluations of new treatments, facilitating inclusion of a lifetime time horizon, and will help identify areas for further research.

Modeling the multi-state natural history of rare diseases with heterogeneous individual patient data: A simulation study.

Multi-state survival models are used to represent the natural history of a disease, forming the basis of a health technology assessment comparing a novel treatment to current practice. Constructing such models for rare diseases is problematic, since evidence sources are typically much sparser and more heterogeneous. This simulation study investigated different one-stage and two-stage approaches to meta-analyzing individual patient data (IPD) in a multi-state survival setting when the number and size of studies being meta-analyzed are small. The objective was to assess methods of different complexity to see when they are accurate, when they are inaccurate and when they struggle to converge due to the sparsity of data. Biologically plausible multi-state IPD were simulated from study- and transition-specific hazard functions. One-stage frailty and two-stage stratified models were estimated, and compared to a base case model that did not account for study heterogeneity. Convergence and the bias/coverage of population-level transition probabilities to, and lengths of stay in, each state were used to assess model performance. A real-world application to Duchenne Muscular Dystrophy, a neuromuscular rare disease, was conducted, and a software demonstration is provided. Models not accounting for study heterogeneity were consistently out-performed by two-stage models. Frailty models struggled to converge, particularly in scenarios of low heterogeneity, and predictions from models that did converge were also subject to bias. Stratified models may be better suited to meta-analyzing disparate sources of IPD in rare disease natural history/economic modeling, as they converge more consistently and produce less biased predictions of lengths of stay.

Incorporation of patient and public involvement in statistical methodology research: development of an animation.

BACKGROUND: Patient and Public Involvement and Engagement (PPIE) is important to all aspects of health research. However, there are few examples of successful PPIE in statistical methodology research. One of the reasons for this relates to challenges in the identification of individuals interested in statistical methodology research projects, and ambiguities over the importance of PPIE to these projects. METHODS: This project was conducted between August 2022 and August 2023. The aim is to report the process of the development of an accessible animation to describe what statistical methodology is and the importance of PPIE in statistical methodology research projects. For this, we combined storyboarding and scriptwriting with feedback from PPIE members and researchers. RESULTS: After three stages that incorporated feedback from the relevant stakeholders, we produced a final animation about PPIE in statistical methodology. The resulting animation used minimal text, simple animation techniques and was of short duration (< 3 min) to optimise the communication of the key messages clearly and effectively. CONCLUSIONS: The resulting animation provides a starting point for members of the public to learn about PPIE in statistical methodology research and for methodologists who wish to conduct PPIE. We recommend further work to explore ways in which members of the public can be more meaningfully involved in methodology research.

Patient and public involvement and engagement (PPIE) is when members of the public are directly involved in carrying out research projects. This is important because we as researchers want to make sure we are focusing on what matters most to patients, so that the research has as large an impact as possible. PPIE has typically been used in more applied research projects, such as clinical trials, but is equally as important in statistical methodology research, where we focus on making sure the statistical tools that we use in the applied projects are as good as possible. The aim of this project was to create a short animation that helps to explain the importance of PPIE in statistical methodology research projects. Researchers sometimes incorrectly assume that PPIE is less important in these projects as this type of research has a less obvious benefit to patients. The animation helps to further explain these concepts. It describes what statistical methodology research is and why involving members of the public is still important. This paper explains the process of developing the animation, including receiving feedback from members of the public to make sure the animation is accessible to as many people as possible. The result is a short, 3-min animation that is free to view on the NIHR website. This can be used by other researchers to help them when recruiting members of the public to their research projects.

Natural history of Duchenne muscular dystrophy in the United Kingdom: A descriptive study using the Clinical Practice Research Datalink.

BACKGROUND: Duchenne muscular dystrophy (DMD) is a rare, muscle-degenerative disease predominantly affecting males. Natural history models capture the full disease pathway under current care and combine with estimates of new interventions' effects to assess cost-effectiveness by health technology decision-makers. These models require mortality estimates throughout a patient's lifetime, but rare disease datasets typically contain relatively few patients with short follow-ups. Alternative (published) sources of mortality data may therefore be required. METHODS: The Clinical Practice Research Datalink (CPRD) was evaluated as a source of mortality and natural history data for future economic evaluations of health technologies for DMD and rare diseases in general in the UK population. This retrospective longitudinal cohort study provides flexible parametric estimates of mortality rates and survival probabilities in the current UK DMD population through primary/secondary records in the CPRD since 1990. It also investigates clinically significant milestones such as corticosteroid use, spinal surgery, and cardiomyopathy in these patients. RESULTS: A total of 1121 male patients were included in the study, observed from 0.7 to 48.9 years. Median life expectancy was 25.64 years (95% confidence interval 24.73, 26.47), consistent with previous global estimates. This has improved to 26.47 (25.16, 27.89) years in patients born after 1990. The median ages at corticosteroid initiation, spinal surgery, ventilation, and cardiomyopathy diagnosis were 6.06 years (5.77, 6.29), 14.79 years (14.29, 15.09), 16.97 years (16.50, 18.31), and 15.26 years (14.22, 16.70), respectively. CONCLUSIONS: Estimates of mortality in UK-based DMD patients are age-specific in a uniquely large and nationally representative sample from the CPRD.

Incorporation of patient and public involvement in statistical methodology research: a survey assessing current practices and attitudes of researchers.

BACKGROUND: Patient and public involvement (PPI) ensures that research is designed and conducted in a manner that is most beneficial to the individuals whom it will impact. It has an undisputed place in applied research and is required by many funding bodies. However, PPI in statistical methodology research is more challenging and work is needed to identify where and how patients and the public can meaningfully input in this area. METHODS: A descriptive cross-sectional research study was conducted using an online questionnaire, which asked statistical methodologists about themselves and their experience conducting PPI, either to inform a grant application or during a funded statistical methodology project. The survey included both closed-text responses, which were reported using summary statistics, and open-ended questions for which common themes were identified. RESULTS: 119 complete responses were recorded. Individuals who completed the survey displayed an even range of ages, career lengths and positions, with the majority working in academia. 40.3% of participants reported undertaking PPI to inform a grant application and the majority reported that the inclusion of PPI was received positively by the funder. Only 21.0% of participants reported undertaking PPI during a methodological project. 31.0% of individuals thought that PPI was "very" or "extremely" relevant to statistical methodology research, with 45.5% responding "somewhat" and 24.4% answering "not at all" or "not very". Arguments for including PPI were that it can provide the motivation for research and shape the research question. Negative opinions included that it is too technical for the public to understand, so they cannot have a meaningful impact. CONCLUSIONS: This survey found that the views of statistical methodologists on the inclusion of PPI in their research are varied, with some individuals having particularly strong opinions, both positive and negative. Whilst this is clearly a divisive topic, one commonly identified theme was that many researchers are willing to try and incorporate meaningful PPI into their research but would feel more confident if they had access to resources such as specialised training, guidelines, and case studies.

Patient and public involvement (or PPI) means researchers working in partnership with patients and the public in any part of research. It can include helping decide what the research question is, how to pass on results to the public, and telling researchers what areas are most important to patients and the public. Statistical methods are the tools we use to analyse data. Statistical methodology research involves making sure these tools use our healthcare data in the best way. PPI is essential in health research and is becoming more common in statistical methodology research. But it can be hard to know how to include patients and the public in statistical methodology research. It may seem complex and not directly related to patients. This paper describes the results from a survey we did about the experiences of researchers who have carried out PPI for statistical methodology research. We asked them what they think about it, and how it affects their research. We also asked if they feel confident including PPI in their research, and whether they are given enough help. Researchers had different views about PPI for statistical methodology research. Some people thought PPI was very important in their research, but others weren't sure. Many people said that they would like more help such as training and guidelines to help them do better PPI in the future.

An Approach to a Patient With Primary Hyperparathyroidism and a Suspected Ectopic Parathyroid Adenoma.

Primary hyperparathyroidism (PHPT) is characterized by hypercalcemia driven by excess parathyroid hormone (PTH) secretion. PHPT is a common endocrine condition with a prevalence of 1 to 7 cases per 1000 adults. PHPT typically presents in the fifth or sixth decade and shows significant female preponderance. Solitary hyperfunctioning parathyroid adenomas account for 85% to 90% of PHPT cases. The remaining 10% to 15% include cases of multiglandular disease (multiple adenomas or hyperplasia) and, rarely, parathyroid carcinoma (1%). Ectopic parathyroid adenomas may arise due to abnormal embryological migration of the parathyroid glands and can be difficult to localize preoperatively, making surgical cure challenging on the first attempt. The potential existence of multiglandular disease should be considered in all patients in whom preoperative localization fails to identify a target adenoma or following unsuccessful parathyroidectomy. Risk factors for multiglandular disease include underlying genetic syndromes (eg, MEN1/2A), lithium therapy, or previous radiotherapy. In addition to multifocal disease, the possibility of an ectopic parathyroid gland should also be considered in patients requiring repeat parathyroid surgery. In this article, we use illustrative clinical vignettes to discuss the approach to a patient with primary hyperparathyroidism (PHPT) and a suspected ectopic parathyroid adenoma.

Life Expectancy in Duchenne Muscular Dystrophy: Reproduced Individual Patient Data Meta-analysis.

BACKGROUND AND OBJECTIVES: Duchenne muscular dystrophy (DMD) is a rare progressive disease that is often diagnosed in early childhood and leads to considerably reduced life expectancy; because of its rarity, research literature and patient numbers are limited. To fully characterize the natural history, it is crucial to obtain appropriate estimates of the life expectancy and mortality rates of patients with DMD. METHODS: A systematic review of the published literature on mortality in DMD up to July 2020 was undertaken, specifically focusing on publications in which Kaplan-Meier (KM) survival curves with age as a timescale were presented. These were digitized, and individual patient data (IPD) were reconstructed. The pooled IPD were analyzed with the KM estimator and parametric survival analysis models. Estimates were also stratified by birth cohort. RESULTS: Of 1,177 articles identified, 14 publications met the inclusion criteria and provided data on 2,283 patients, of whom 1,049 had died. Median life expectancy was 22.0 years (95% confidence interval [CI] 21.2, 22.4). Analyses stratified by 3 time periods in which patients were born showed markedly increased life expectancy in more recent patient populations; patients born after 1990 have a median life expectancy of 28.1 years (95% CI 25.1, 30.3). DISCUSSION: This article presents a full overview of mortality across the lifetime of a patient with DMD and highlights recent improvements in survival. In the absence of large-scale prospective cohort studies or trials reporting mortality data for patients with DMD, extraction of IPD from the literature provides a viable alternative to estimating life expectancy for this patient population.