ALS clinical trials: do enrolled patients accurately represent the ALS population?

Patient engagement in research: lessons learned from CAPTURE ALS, a longitudinal observational ALS study

Objective: There are compelling ethical and practical reasons for patient engagement in research (PEIR), however, evidence for best practices remains limited. We investigated PEIR as implemented in CAPTURE ALS, a longitudinal observational study, from study inception through the first 2.5 years of operations. Methods: Data were drawn from three engagement initiatives: a community-led letter-writing campaign; consultation with patient and caregiver focus groups; and a study-embedded 'participant partner advisory council' (PPAC). Data were derived retrospectively from study documentation. We used the International Association of Public Participation (IAP2) participation spectrum as a framework for investigation. Results: 2401 letters from community members to the Canadian government affirmed study objectives and advocated for funding. Feedback from focus group consultation influenced study design and supported the study's data-sharing plan. PPAC collaboration shaped all aspects of the study. Contributions included: co-creation of governance documents, input on study protocols and public-facing communication, and development of engagement webinars for study participants and feedback surveys. Effective communication practices fostered collaboration and helped avoid tokenistic engagement. CAPTURE ALS encompassed all IAP2 participation levels. Conclusions: CAPTURE ALS was shaped by meaningful engagement initiatives over the course of the study. Lessons learned included: begin early and embed PEIR within research; build relationships and foster mutual learning; be flexible, open to adaptation, and seek diversity. Primary challenges included funding for early implementation, time needed to maintain relationships, and attrition due to disease progression. All IAP2 participation levels contributed to meaningful PEIR. 'Empowerment' was demonstrated through advocacy.

Novel approaches to motoneuron disease/ALS treatment using non-invasive brain and spinal stimulation: IFCN handbook chapter

Non-invasive brain stimulation techniques have been exploited in motor neuron disease (MND) with multifold objectives: to support the diagnosis, to get insights in the pathophysiology of these disorders and, more recently, to slow down disease progression. In this review, we consider how neuromodulation can now be employed to treat MND, with specific attention to amyotrophic lateral sclerosis (ALS), the most common form with upper motoneuron (UMN) involvement, taking into account electrophysiological abnormalities revealed by human and animal studies that can be targeted by neuromodulation techniques. This review article encompasses repetitive transcranial magnetic stimulation methods (including low-frequency, high-frequency, and pattern stimulation paradigms), transcranial direct current stimulation as well as experimental findings with the newer approach of trans-spinal direct current stimulation. We also survey and discuss the trials that have been performed, and future perspectives.

Effect of tauroursodeoxycholic acid on survival and safety in amyotrophic lateral sclerosis: a retrospective population-based cohort study

Background

Oral tauroursodeoxycholic acid (TUDCA) is a commercial drug currently tested in patients with amyotrophic lateral sclerosis (ALS) both singly and combined with sodium phenylbutyrate. This retrospective study aimed to investigate, in a real-world setting, whether TUDCA had an impact on the overall survival of patients with ALS who were treated with this drug compared to those patients who received standard care only.

Methods

This propensity score-matched study was conducted in the Emilia Romagna Region (Italy), which has had an ALS regional registry since 2009. Out of 627 patients with ALS diagnosed from January 1st, 2015 to June 30th, 2021 and recorded in the registry with available information on death/tracheostomy, 86 patients took TUDCA and were matched in a 1:2 ratio with patients who received only usual care according to age at onset, sex, phenotype, diagnostic latency, ALS Functional Rating Scale-Revised (ALSFRS-R) at first visit, disease progression rate at first visit, and BMI at diagnosis. The primary outcome was survival difference (time from onset of symptoms to tracheostomy/death) between TUDCA exposed and unexposed patients.

Findings

A total of 86 patients treated with TUDCA were matched to 172 patients who did not receive treatment. TUDCA-exposed patients were stratified based on dosage (less than or equal to 1000 mg/day or greater) and duration (less than or equal to 12 months or longer) of treatment. The median overall survival was 49.6 months (95% CI 41.7-93.5) among those treated with TUDCA and 36.2 months (95% CI 32.7-41.6) in the control group, with a reduced risk of death observed in patients exposed to a higher dosage (defined as ≥ 1000 mg/day) of TUDCA (HR 0.56; 95% CI 0.38-0.83; p = 0.0042) compared to both the control group and those with lower TUDCA dosages (defined as < 1000 mg/day). TUDCA was generally well-tolerated, except for a minority of patients (n = 7, 8.1%) who discontinued treatment due to side effects, primarily gastrointestinal and mild in severity; only 2 adverse events required hospital access but resolved without sequelae.

Interpretation

In this population-based exploratory study, patients with ALS who were treated with TUDCA may have prolonged survival compared to patients receiving standard care only. Additional prospective randomized studies are needed to confirm the efficacy and safety of this drug.

Funding

Emilia-Romagna Region.

Asynchronous online focus groups for research with people living with amyotrophic lateral sclerosis and family caregivers: usefulness, acceptability and lessons learned

BACKGROUND

People with amyotrophic lateral sclerosis (ALS) face disability- and travel-related barriers to research participation. We investigate the usefulness and acceptability of asynchronous, online focus groups (AOFGs) for research involving people affected by ALS (patients and family caregivers) and outline lessons learned.

METHODS

The ALS Talk Project, consisting of seven AOFGs and 100 participants affected by ALS, provided context for this investigation. Hosted on the secure itracks Board™ platform, participants interacted in a threaded web forum structure. Moderators posted weekly discussion questions and facilitated discussion. Data pertaining to methodology, participant interaction and experience, and moderator technique were analyzed using itracks and NVivo 12 analytics (quantitative) and conventional content analysis and the constant-comparative approach (qualitative).

RESULTS

There was active engagement within groups, with post lengths averaging 111.48 words and a complex network of branching interactions between participants. One third of participant responses included individual reflections without further interaction. Participants affirmed their co-group members, offered practical advice, and discussed shared and differing perspectives. Moderators responded to all posts, indicating presence and probing answers. AOFGs facilitated qualitative and quantitative data-gathering and flexible response to unanticipated events. Although total participation fell below 50% after 10-12 weeks, participants valued interacting with peers in an inclusive, confidential forum. Participants used a variety of personal devices, browsers, and operating systems when interacting on the online platform.

CONCLUSIONS

This methodological examination of AOFGs for patient-centred investigations involving people affected by ALS demonstrates their usefulness and acceptability, and advances knowledge of online research methodologies. Lessons learned include: early identification of research goals and participant needs is critical to selecting an AOFG platform; although duration longer than 10-12 weeks may be burdensome in this population, participants were positive about AOFGs; AOFGs offer real world flexibility enabling response to research challenges and opportunities; and, AOGFs can effectively foster safe spaces for sharing personal perspectives and discussing sensitive topics. With moderators playing an important role in fostering engagement, AOFGs facilitated rich data gathering and promoted reciprocity by fostering the exchange of ideas and interaction between peers. Findings may have implications for research involving other neurologically impaired and/or medically vulnerable populations.

Hybrid Controlled Clinical Trials Using Concurrent Registries in Amyotrophic Lateral Sclerosis: A Feasibility Study

Hybrid designs with both randomized arms and an external control cohort preserve key features of randomization and utilize external information to augment clinical trials. In this study, we propose to leverage high-quality, patient-level concurrent registries to enhance clinical trials and illustrate the impact on trial design for amyotrophic lateral sclerosis. The proposed methodology was evaluated in a randomized, placebo-controlled clinical trial. We used patient-level information from a well-defined, population-based registry, that was running parallel to the randomized clinical trial, to identify concurrently nonparticipating, eligible patients who could be matched with trial participants, and integrate them into the statistical analysis. We assessed the impact of the addition of the external controls on the treatment effect estimate, precision, and time to reach a conclusion. During the runtime of the trial, a total of 1,141 registry patients were alive; 473 (41.5%) of them fulfilled the eligibility criteria and 133 (11.7%) were enrolled in the study. A matched control population could be identified among the nonparticipating patients. Augmenting the randomized controls with matched external controls could have avoided unnecessary randomization of 17 patients (-12.8%) as well as reducing the study duration from 30.1 months to 22.6 months (-25.0%). Matching eligible external controls from a different calendar period led to bias in the treatment effect estimate. Hybrid trial designs utilizing a concurrent registry with rigorous matching can minimize bias due to a mismatch in calendar time and differences in standard of care, and may accelerate the development of new treatments.

Insight into Elderly ALS Patients in the Emilia Romagna Region: Epidemiological and Clinical Features of Late-Onset ALS in a Prospective, Population-Based Study

Few studies have focused on elderly (>80 years) amyotrophic lateral sclerosis (ALS) patients, who represent a fragile subgroup generally not included in clinical trials and often neglected because they are more difficult to diagnose and manage. We analyzed the clinical and genetic features of very late-onset ALS patients through a prospective, population-based study in the Emilia Romagna Region of Italy. From 2009 to 2019, 222 (13.76%) out of 1613 patients in incident cases were over 80 years old at diagnosis, with a female predominance (F:M = 1.18). Elderly ALS patients represented 12.02% of patients before 2015 and 15.91% from 2015 onwards (p = 0.024). This group presented with bulbar onset in 38.29% of cases and had worse clinical conditions at diagnosis compared to younger patients, with a lower average BMI (23.12 vs. 24.57 Kg/m²), a higher progression rate (1.43 vs. 0.95 points/month), and a shorter length of survival (a median of 20.77 vs. 36 months). For this subgroup, genetic analyses have seldom been carried out (25% vs. 39.11%) and are generally negative. Finally, elderly patients underwent less frequent nutritional- and respiratory-supporting procedures, and multidisciplinary teams were less involved at follow-up, except for specialist palliative care. The genotypic and phenotypic features of elderly ALS patients could help identify the different environmental and genetic risk factors that determine the age at which disease onset occurs. Since multidisciplinary management can improve a patient's prognosis, it should be more extensively applied to this fragile group of patients.

Low intensity exercise training in patients with amyotrophic lateral sclerosis - factors influencing eligibility and compliance to the clinical trial

BACKGROUND

To date, there are no evidence-based recommendations for physical therapy in amyotrophic lateral sclerosis (ALS). The reason is a low number of related clinical trials (CTs), restricted sample sizes and a high dropout rate. It may influence the profile of the participants, while the final results might not translate to the general ALS population.

OBJECTIVE

To analyze factors affecting the ALS patients' enrollment and retention to the study, and to describe a profile of participants as compared to the eligible group.

METHODS

A total of 104 ALS patients were offered participation in a CT of low-intensity exercises at home. Forty-six patients were recruited. Demographic and clinical data (El Escorial criteria, site of onset, diagnosis delay, disease duration, amyotrophic lateral sclerosis functional rating scale - revised [ALSFRS-R], Medical Research Council [MRC], hand-held dynamometry) were analyzed every 3 months.

RESULTS

Male gender, younger age and a higher ALSFRS predicted enrollment, while male gender, higher ALSFRS-R and MRC predicted retention in the study. A long commute to the study site and a fast disease progression were the main reasons influencing both enrollment and retention. Despite a high dropout rate, study participants were representative for the general ALS population.

CONCLUSION

The above demographic, clinical and logistic factors need to be considered when designing studies in ALS population.

Leveraging process mining for modeling progression trajectories in amyotrophic lateral sclerosis

BACKGROUND

Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease whose spreading and progression mechanisms are still unclear. The ability to predict ALS prognosis would improve the patients' quality of life and support clinicians in planning treatments. In this paper, we investigate ALS evolution trajectories using Process Mining (PM) techniques enriched to both easily mine processes and automatically reveal how the pathways differentiate according to patients' characteristics.

METHODS

We consider data collected in two distinct data sources, namely the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) dataset and a real-world clinical register (ALS-BS) including data of patients followed up in two tertiary clinical centers of Brescia (Italy). With a focus on the functional abilities progressively impaired as the disease progresses, we use two Process Discovery methods, namely the Directly-Follows Graph and the CareFlow Miner, to mine the population disease trajectories on the PRO-ACT dataset. We characterize the impairment trajectories in terms of patterns, timing, and probabilities, and investigate the effect of some patients' characteristics at onset on the followed paths. Finally, we perform a comparative study of the impairment trajectories mined in PRO-ACT versus ALS-BS.

RESULTS

We delineate the progression pathways on PRO-ACT, identifying the predominant disabilities at different stages of the disease: for instance, 85% of patients enter the trials without disabilities, and 48% of them experience the impairment of Walking/Self-care abilities first. We then test how a spinal onset increases the risk of experiencing the loss of Walking/Self-care ability as first impairment (52% vs. 27% of patients develop it as the first impairment in the spinal vs. the bulbar cohorts, respectively), as well as how an older age at onset corresponds to a more rapid progression to death. When compared, the PRO-ACT and the ALS-BS patient populations present some similarities in terms of natural progression of the disease, as well as some differences in terms of observed trajectories plausibly due to the trial scheduling and recruitment criteria.

CONCLUSIONS

We exploited PM to provide an overview of the evolution scenarios of an ALS trial population and to preliminary compare it to the progression observed in a clinical cohort. Future work will focus on further improving the understanding of the disease progression mechanisms, by including additional real-world subjects as well as by extending the set of events considered in the impairment trajectories.

The future of ALS diagnosis and staging: where do we go from here?

Amyotrophic lateral sclerosis (ALS) is a rare, progressive multi-system neurodegenerative disorder. Its clinical presentation varies considerably leading to delays in diagnosis, which has dire consequences in a disease where early intervention is key to optimize outcomes and limit care giver burden. There are a range of diagnostic criteria available to aid ALS diagnosis, as well staging methods to assess disease progression. However, they all suffer from inter-rater variability, complexity, and confusion in use. Such difficulties, when medical appointment times are limited and becoming more virtually based, have the potential to amplify uncertainty and errors in ALS diagnosis and prognosis. This review provides a clinical overview of the best way to balance the needs of evidence-based medicine and the patient. We focus on ALS diagnostic criteria and staging systems currently in use in clinical practice and explore factors that could enhance diagnostic efficiency and assessment of disease progression.

Patient perspectives on digital healthcare technology in care and clinical trials for motor neuron disease: an international survey

Introduction

To capture the patient’s attitude toward remote monitoring of motor neuron disease (MND) in care and clinical trials, and their concerns and preferences regarding the use of digital technology.

Methods

We performed an international multi-centre survey study in three MND clinics in The Netherlands, the United Kingdom, and Australia. The survey was co-developed by investigators and patients with MND, and sent to patients by e-mail or postal-mail. The main topics included: patients’ attitude towards remote care, participating in decentralized clinical trials, and preferences for and concerns with digital technology use.

Results

In total, 332 patients with MND participated. A majority of patients indicated they would be happy to self-monitor their health from home (69%), be remotely monitored by a multidisciplinary care team (75%), and would be willing to participate in clinical trials from home (65%). Patients considered respiratory function and muscle strength most valuable for home-monitoring. The majority of patients considered the use of at least three devices/apps (75%) once a week (61%) to be acceptable for home-monitoring. Fifteen percent of patients indicated they would not wish to perform home-measurements; reporting concerns about the burden and distress of home-monitoring, privacy and data security.

Conclusion

Most patients with MND exhibited a positive attitude toward the use of digital technology in both care and clinical trial settings. A subgroup of patients reported concerns with home-monitoring, which should be addressed in order to improve widespread adoption of remote digital technology in clinical MND care.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00415-022-11273-x.

Gold Coast criteria expand clinical trial eligibility in amyotrophic lateral sclerosis

INTRODUCTION/AIMS

Consensus criteria to formalize the diagnosis of amyotrophic lateral sclerosis (ALS) and refine clinical trial populations have evolved. The recently proposed Gold Coast consensus criteria are intended to simplify use and increase sensitivity. We aimed to evaluate the potential impact of these criteria on clinical trial eligibility.

METHODS

We performed a single-center, retrospective study of people diagnosed with ALS between 2016 and 2021 to determine the numbers of those meeting Gold Coast, revised El Escorial (rEEC) criteria, and Awaji criteria. We identified the proportion of those who would have been eligible for participation in three major ALS clinical trials if Gold Coast were used in place of rEEC definite/probable criteria. (rEEC D/P).

RESULTS

Two hundred six people with ALS were included in our study. 48.5% met Gold Coast criteria but not rEEC D/P. Using the Gold Coast criteria would result in higher rates of clinical trial eligibility after other inclusion criteria were met: 95.2% vs 42.5% (P < .001) in a phase III study of riluzole; 100% vs 31.0% (P = .002) in a phase III study of edaravone; and 95.6% vs 45.3% (P < .001) in an ongoing phase III study of sodium phenylbutyrate and taurursodiol. The sensitivity of the Gold Coast criteria (96.1%; 95% confidence interval [CI], 92.2%-98.2%) was significantly higher than that of rEEC D/P (47.6%; 95% CI, 40.6%-54.6%; for difference, χ²  = 117.6; P < .001).

DISCUSSION

Until robust biomarkers are available to diagnose ALS, consensus diagnostic criteria remain necessary. Gold Coast criteria would expand research and clinical trial eligibility and improve external validity of clinical trial results.

The landscape of neurophysiological outcome measures in ALS interventional trials: A systematic review

OBJECTIVE

We collated all interventional clinical trials in amyotrophic lateral sclerosis (ALS), which utilised at least one neurophysiological technique as a primary or secondary outcome measure. By identifying the strengths and limitations of these studies, we aim to guide study design in future trials.

METHODS

We conducted and reported this systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Eight databases were searched from inception. In total, 703 studies were retrieved for screening and eligibility assessment.

RESULTS

Dating back to 1986, 32 eligible interventional clinical trials were identified, recruiting a median of 30 patients per completed trial. The most widely employed neurophysiological techniques were electromyography, motor unit number estimation (including motor unit number index), neurophysiological index and transcranial magnetic stimulation (including resting motor threshold and short-interval intracortical inhibition). Almost 40% of trials reported a positive outcome with respect to at least one neurophysiological measure. The interventions targeted either ion channels, immune mechanisms or neuronal metabolic pathways.

CONCLUSIONS

Neurophysiology offers many promising biomarkers that can be utilised as outcome measures in interventional clinical trials in ALS. When selecting the most appropriate technique, key considerations include methodological standardisation, target engagement and logistical burden.

SIGNIFICANCE

Future trial design in ALS would benefit from a standardised, updated and easily accessible repository of neurophysiological outcome measures.

Machine Learning Solutions Applied to Amyotrophic Lateral Sclerosis Prognosis: A Review

The prognosis of Amyotrophic Lateral Sclerosis (ALS), a complex and rare disease, represents a challenging and essential task to better comprehend its progression and improve patients' quality of life. The use of Machine Learning (ML) techniques in healthcare has produced valuable contributions to the prognosis field. This article presents a systematic and critical review of primary studies that used ML applied to the ALS prognosis, searching for databases, relevant predictor biomarkers, the ML algorithms and techniques, and their outcomes. We focused on studies that analyzed biomarkers commonly present in the ALS disease clinical practice, such as demographic, clinical, laboratory, and imaging data. Hence, we investigate studies to provide an overview of solutions that can be applied to develop decision support systems and be used by a higher number of ALS clinical settings. The studies were retrieved from PubMed, Science Direct, IEEEXplore, and Web of Science databases. After completing the searching and screening process, 10 articles were selected to be analyzed and summarized. The studies evaluated and used different ML algorithms, techniques, datasets, sample sizes, biomarkers, and performance metrics. Based on the results, three distinct types of prediction were identified: Disease Progression, Survival Time, and Need for Support. The biomarkers identified as relevant in more than one study were the ALSFRS/ALSFRS-R, disease duration, Forced Vital Capacity, Body Mass Index, age at onset, and Creatinine. In general, the studies presented promissory results that can be applied in developing decision support systems. Besides, we discussed the open challenges, the limitations identified, and future research opportunities.

Epidemiological, Clinical and Genetic Features of ALS in the Last Decade: A Prospective Population-Based Study in the Emilia Romagna Region of Italy

Increased incidence rates of amyotrophic lateral sclerosis (ALS) have been recently reported across various Western countries, although geographic and temporal variations in terms of incidence, clinical features and genetics are not fully elucidated. This study aimed to describe demographic, clinical feature and genotype–phenotype correlations of ALS cases over the last decade in the Emilia Romagna Region (ERR). From 2009 to 2019, our prospective population-based registry of ALS in the ERR of Northern Italy recorded 1613 patients receiving a diagnosis of ALS. The age- and sex-adjusted incidence rate was 3.13/100,000 population (M/F ratio: 1.21). The mean age at onset was 67.01 years; women, bulbar and respiratory phenotypes were associated with an older age, while C9orf72-mutated patients were generally younger. After peaking at 70–75 years, incidence rates, among women only, showed a bimodal distribution with a second slight increase after reaching 90 years of age. Familial cases comprised 12%, of which one quarter could be attributed to an ALS-related mutation. More than 70% of C9orf72-expanded patients had a family history of ALS/fronto-temporal dementia (FTD); 22.58% of patients with FTD at diagnosis had C9orf72 expansion (OR 6.34, p = 0.004). In addition to a high ALS incidence suggesting exhaustiveness of case ascertainment, this study highlights interesting phenotype–genotype correlations in the ALS population of ERR.

Predicting functional impairment trajectories in amyotrophic lateral sclerosis: a probabilistic, multifactorial model of disease progression

Objective

To employ Artificial Intelligence to model, predict and simulate the amyotrophic lateral sclerosis (ALS) progression over time in terms of variable interactions, functional impairments, and survival.

Methods

We employed demographic and clinical variables, including functional scores and the utilisation of support interventions, of 3940 ALS patients from four Italian and two Israeli registers to develop a new approach based on Dynamic Bayesian Networks (DBNs) that models the ALS evolution over time, in two distinct scenarios of variable availability. The method allows to simulate patients’ disease trajectories and predict the probability of functional impairment and survival at different time points.

Results

DBNs explicitly represent the relationships between the variables and the pathways along which they influence the disease progression. Several notable inter-dependencies were identified and validated by comparison with literature. Moreover, the implemented tool allows the assessment of the effect of different markers on the disease course, reproducing the probabilistically expected clinical progressions. The tool shows high concordance in terms of predicted and real prognosis, assessed as time to functional impairments and survival (integral of the AU-ROC in the first 36 months between 0.80–0.93 and 0.84–0.89 for the two scenarios, respectively).

Conclusions

Provided only with measurements commonly collected during the first visit, our models can predict time to the loss of independence in walking, breathing, swallowing, communicating, and survival and it can be used to generate in silico patient cohorts with specific characteristics. Our tool provides a comprehensive framework to support physicians in treatment planning and clinical decision-making.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00415-022-11022-0.

Telehealth in long-term neurological conditions: the potential, the challenges and the key recommendations

Long-term neurological conditions (LTNCs) cause physical and psychological symptoms that have a significant impact on activities of daily living and quality of life. Multidisciplinary teams are effective at providing treatment for people with LTNCs; however, access to such services by people with disabilities can be difficult and as a result, good quality care is not universal. One potential solution is telehealth. This review describes the potential of telehealth to support people with LTNCs, the challenges of designing and implementing these systems, and the key recommendations for those involved in telehealth to facilitate connected services that can benefit patients, carers and healthcare professionals. These recommendations include understanding the problems posed by LTNCs and the needs of the end-user through a person-centred approach. We discuss how to work collaboratively and use shared learning, and consider how to effectively evaluate the intervention at every stage of the development process.

MiNDAUS partnership: a roadmap for the cure and management of motor Neurone disease

An innovative approach to patient management, evidence-based policy development, and clinical drug trials is required to provide personalized care and to improve the likelihood of finding an effective treatment for Motor Neurone Disease (MND). The MiNDAus Partnership builds on and extends existing national collaborations in a targeted approach to improve the standard and coordination of care for people living with MND in Australia, and to enhance the prospects of discovering a cure or treatment. Relationships have been developed between leading clinical and research groups as well as patient-centered organizations, care providers, and philanthropy with a shared vision. MiNDAus has established a corporate structure and meets at least biannually to decide on how best to progress research, drug development, and patient management. The key themes are; (i) empowering patients and their family carers to engage in self-management and ensure personalized service provision, treatment, and policy development, (ii) integration of data collection so as to better inform policy development, (iii) unifying patients and carers with advocacy groups, funding bodies, clinicians and academic institutions so as to inform policy development and research, (iv) coordination of research efforts and development of standardized national infrastructure for conducting innovative clinical MND trials that can be harmonized within Australia and with international trials consortia. Such a collaborative approach is required across stakeholders in order to develop innovative management guidelines, underpinned by necessary and evidence-based policy change recommendations, which, will ensure the best patient care until a cure is discovered.

A Road Map for Remote Digital Health Technology for Motor Neuron Disease

Despite recent and potent technological advances, the real-world implementation of remote digital health technology in the care and monitoring of patients with motor neuron disease has not yet been realized. Digital health technology may increase the accessibility to and personalization of care, whereas remote biosensors could optimize the collection of vital clinical parameters, irrespective of patients’ ability to visit the clinic. To facilitate the wide-scale adoption of digital health care technology and to align current initiatives, we outline a road map that will identify clinically relevant digital parameters; mediate the development of benefit-to-burden criteria for innovative technology; and direct the validation, harmonization, and adoption of digital health care technology in real-world settings. We define two key end products of the road map: (1) a set of reliable digital parameters to capture data collected under free-living conditions that reflect patient-centric measures and facilitate clinical decision making and (2) an integrated, open-source system that provides personalized feedback to patients, health care providers, clinical researchers, and caregivers and is linked to a flexible and adaptable platform that integrates patient data in real time. Given the ever-changing care needs of patients and the relentless progression rate of motor neuron disease, the adoption of digital health care technology will significantly benefit the delivery of care and accelerate the development of effective treatments.

Can amyotrophic lateral sclerosis progression really pause? A cohort study using the medical research council scale

Objective: To assess the frequency and predictors of plateaus in ALS progression as assessed by the Medical Research Council (MRC) Scale. Methods: All patients attending the ALS Center of Turin, with a diagnosis between 2007 and 2014 were considered. At each visit, muscle strength was evaluated in several muscles and assessed using the MRC scale. Concomitant ALSFRSr scores were retrieved. Plateaus were calculated as a stable overall MRC or ALSFRSr score lasting at least 6, 12 or 18 months. Results: According to MRC scale scores, 122 (22.8%), 71 (13.2%) and 59 (11.0%) patients experienced a plateau lasting at least 6, 12 and 18 months. ALSFRSr scores revealed similar estimates [134, (25.0%), 89 (16.6%) and 67 (12.5%), respectively]. Plateaus were more frequent at high scores and appeared a median of 24.6 months (IQR 6.7-47.7) after the diagnosis. Only the predominant upper motor neuron phenotype (OR 4.06, 95% CI 2-06-8.10, p-value <0.001) and diagnostic delay OR 1.03, 95% CI 1.01-10.5, p-value = 0.005) were significantly correlated with their appearance. Discussion: Plateaus in ALS progression as assessed using either ALSFRSr or MRC scale are not infrequent and should be expected especially in less aggressive phenotypes. Similar results were found both using the MRC scale and the ALSFRSr scores, suggesting a comparable reliability of these scales in grasping the disease progression.

Challenging the Established Order: Innovating Clinical Trials for Amyotrophic Lateral Sclerosis

Development of effective treatments for amyotrophic lateral sclerosis (ALS) has been hampered by disease heterogeneity, a limited understanding of underlying pathophysiology, and methodologic design challenges. We have evaluated 2 major themes in the design of pivotal, phase 3 clinical trials for ALS—(1) patient selection and (2) analytical strategy—and discussed potential solutions with the European Medicines Agency. Several design considerations were assessed using data from 5 placebo-controlled clinical trials (n = 988), 4 population-based cohorts (n = 5,100), and 2,436 placebo-allocated patients from the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database. The validity of each proposed design modification was confirmed by means of simulation and illustrated for a hypothetical setting. Compared to classical trial design, the proposed design modifications reduce the sample size by 30.5% and placebo exposure time by 35.4%. By making use of prognostic survival models, one creates a potential to include a larger proportion of the population and maximize generalizability. We propose a flexible design framework that naturally adapts the trial duration when inaccurate assumptions are made at the design stage, such as enrollment or survival rate. In case of futility, the follow-up time is shortened and patient exposure to ineffective treatments or placebo is minimized. For diseases such as ALS, optimizing the use of resources, widening eligibility criteria, and minimizing exposure to futile treatments and placebo is critical to the development of effective treatments. Our proposed design modifications could circumvent important pitfalls and may serve as a blueprint for future clinical trials in this population.

Diabetes Mellitus and Amyotrophic Lateral Sclerosis: A Systematic Review

BACKGROUND

Amyotrophic Lateral Sclerosis (ALS) is a degenerative disorder which affects the motor neurons. Growing evidence suggests that ALS may impact the metabolic system, including the glucose metabolism. Several studies investigated the role of Diabetes Mellitus (DM) as risk and/or prognostic factor. However, a clear correlation between DM and ALS has not been defined. In this review, we focus on the role of DM in ALS, examining the different hypotheses on how perturbations of glucose metabolism may interact with the pathophysiology and the course of ALS.

METHODS

We undertook an independent PubMed literature search, using the following search terms: ((ALS) OR (Amyotrophic Lateral Sclerosis) OR (Motor Neuron Disease)) AND ((Diabetes) OR (Glucose Intolerance) OR (Hyperglycemia)). Review and original articles were considered.

RESULTS

DM appears not to affect ALS severity, progression, and survival. Contrasting data suggested a protective role of DM on the occurrence of ALS in elderly and an opposite effect in younger subjects.

CONCLUSIONS

The actual clinical and pathophysiological correlation between DM and ALS is unclear. Large longitudinal prospective studies are needed. Achieving large sample sizes comparable to those of common complex diseases like DM is a challenge for a rare disease like ALS. Collaborative efforts could overcome this specific issue.

Relative effects of forced vital capacity and ALSFRS-R on survival in ALS

INTRODUCTION/AIM

Amyotrophic lateral sclerosis (ALS) is a degenerative neuromuscular disease with marked clinical heterogeneity. This heterogeneity can be partly captured by clinical measures, such as the forced vital capacity (FVC) and ALS Functional Rating Scale-Revised (ALSFRS-R). We aimed to further characterize the performance of these clinical measures, including their independence and additivity, in predicting mortality.

METHODS

We leveraged the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT ALS) database, which includes data from 23 clinical trials (n = 2050). The primary exposures were baseline FVC and ALSFRS-R. The primary outcome was 1-y mortality. We performed correlation analyses, survival analyses and assessed classification performance using receiver operator characteristic (ROC) curves.

RESULTS

FVC and ALSFRS-R were weakly correlated (r = 0.31, p < .001). A 1-SD increase in FVC (hazard ratio [HR]: 0.66; 95% confidence interval [CI]: 0.59-0.74) and ALSFRS-R (HR: 0.75; 95% CI: 0.68-0.82) were associated with reduced risk of 1-y mortality. ROC analyses showed optimal predictive cutoffs at 80% for FVC (area under the curve [AUC]: 0.69) and 38 for ALSFRS-R (AUC: 0.67). After stratifying patients based on these cutoffs, we found a marked reduction (HR: 0.25; 95% CI: 0.19-0.33) in incident mortality for patients in the high FVC and high ALSFRS-R group relative to the low FVC and low ALSFRS-R group.

DISCUSSION

ALSFRS-R and FVC are comparable predictors of survival that are only weakly correlated. When considered together, they synergistically predict survival. As such, consideration of both measures should be a routine part of prognostication in care of patients with ALS.

Modifiable Barriers for Recruitment and Retention of Older Adults Participants from Underrepresented Minorities in Alzheimer's Disease Research

Clinical Alzheimer's disease (AD) trials currently face a critical shortfall of thousands of eligible participants, which inflates the duration and cost of the clinical study as well as threatens the scientific merit of promising clinical interventions. This recruitment crisis is further compounded by the fact that underrepresented and marginalized populations-particularly those identifying as a racial or ethnic minority, those with low socioeconomic status, or living in rural areas-have been historically underrepresented in ongoing AD clinical trials despite overwhelming evidence that such populations are at increased risk for developing dementia. As a result of various recruitment barriers, current AD clinical studies frequently reflect a decreasingly representative segment of the US population, which threatens the overall generalizability of these findings. The current narrative review provides an updated examination and critique of common recruitment barriers and potential solutions, as well as a discussion of theoretical approaches that may address barriers disproportionately experienced by underrepresented communities. AD clinical researchers are encouraged to take purposive action aimed at increasing diversity of enrolled AD clinical trial cohorts by actively identifying and quantifying barriers to research participation-especially recruitment barriers and health disparities that disproportionately prevent underrepresented and marginalized populations from participating in research. Furthermore, researchers are encouraged to closely track which individuals who express interest in AD research ultimately enroll in research studies to examine whether AD research participation is appropriately representative of the intended population for whom these new and novel AD interventions are being designed.

Introduction to spasticity and related mouse models

Although spasticity is one of the most common causes of motor disability worldwide, its precise definition and pathophysiology remain elusive, which to date renders its experimental targeting tricky. At least in part, this difficulty is caused by heterogeneous phenotypes of spasticity-causing neurological disorders, all causing spasticity by involving upper motor neurons. The most common clinical symptoms are a series of rapid muscle contractions (clonus), an increased muscle tone (hypertonia), and augmented tendon reflex activity (hyperreflexia). This muscle overactivity is due to disturbed inhibition of spinal reflexes following upper motor neuron dysfunction. Despite a range of physical and pharmacological therapies ameliorating the symptoms, their targeted application remains difficult. Therefore, to date, spasticity impacts rehabilitative therapy, and no therapy exists that reverses the pathology completely. In contrast to the incidence and importance of spasticity, only very little pre-clinical work in animal models exists, and this research is focused on the cat or the rat spastic tail model to decipher altered reflexes and excitability of the motor neurons in the spinal cord. Meanwhile, the characterization of spasticity in clinically more relevant mouse models of neurological disorders, such as stroke, remains understudied. Here, we provide a brief introduction into the clinical knowledge and therapy of spasticity and an in-depth review of pre-clinical studies of spasticity in mice including the current experimental challenges for clinical translation.

A novel method for predicting the progression rate of ALS disease based on automatic generation of probabilistic causal chains

Causal discovery is considered as a major concept in biomedical informatics contributing to diagnosis, therapy, and prognosis of diseases. Probabilistic causality approaches in epidemiology and medicine is a common method for finding relationships between pathogen and disease, environment and disease, and adverse events and drugs. Bayesian Network (BN) is one of the common approaches for probabilistic causality, which is widely used in health-care and biomedical science. Since in many biomedical applications we deal with temporal dataset, the temporal extension of BNs called Dynamic Bayesian network (DBN) is used for such applications. DBNs define probabilistic relationships between parameters in consecutive time points in the form of a graph and have been successfully used in many biomedical applications. In this paper, a novel method was introduced for finding probabilistic causal chains from a temporal dataset with the help of entropy and causal tendency measures. In this method, first, Causal Features Dependency (CFD) matrix is created on the basis of parameters changes in consecutive events of a phenomenon, and then the probabilistic causal graph is constructed from this matrix based on entropy criteria. At the next step, a set of probabilistic causal chains of the corresponding causal graph is constructed by a novel polynomial-time heuristic. Finally, the causal chains are used for predicting the future trend of the phenomenon. The proposed model was applied to the Pooled Resource Open-Access Clinical Trials (PRO-ACT) dataset related to Amyotrophic Lateral Sclerosis (ALS) disease, in order to predict the progression rate of this disease. The results of comparison with Bayesian tree, random forest, support vector regression, linear regression, and multivariate regression show that the proposed algorithm can compete with these methods and in some cases outperforms other algorithms. This study revealed that probabilistic causality is an appropriate approach for predicting the future states of chronic diseases with unknown cause.

Critical design considerations for time-to-event endpoints in amyotrophic lateral sclerosis clinical trials

BACKGROUND

Funding and resources for low prevalent neurodegenerative disorders such as amyotrophic lateral sclerosis (ALS) are limited, and optimising their use is vital for efficient drug development. In this study, we review the design assumptions for pivotal ALS clinical trials with time-to-event endpoints and provide optimised settings for future trials.

METHODS

We extracted design settings from 13 completed placebo-controlled trials. Optimal assumptions were estimated using parametric survival models in individual participant data (n=4991). Designs were compared in terms of sample size, trial duration, drug use and costs.

RESULTS

Previous trials overestimated the hazard rate by 18.9% (95% CI 3.4% to 34.5%, p=0.021). The median expected HR was 0.56 (range 0.33-0.66). Additionally, we found evidence for an increasing mean hazard rate over time (Weibull shape parameter of 2.03, 95% CI 1.93 to 2.15, p<0.001), which affects the design and planning of future clinical trials. Incorporating accrual time and assuming an increasing hazard rate at the design stage reduced sample size by 33.2% (95% CI 27.9 to 39.4), trial duration by 17.4% (95% CI 11.6 to 23.3), drug use by 14.3% (95% CI 9.6 to 19.0) and follow-up costs by 21.2% (95% CI 15.6 to 26.8).

CONCLUSIONS

Implementing distributional knowledge and incorporating accrual at the design stage could achieve large gains in the efficiency of ALS clinical trials with time-to-event endpoints. We provide an open-source platform that helps investigators to make more accurate sample size calculations and optimise the use of their available resources.

Using telehealth in motor neuron disease to increase access to specialist multidisciplinary care: a UK-based pilot and feasibility study

OBJECTIVES

Care of patients with motor neuron disease (MND) in a specialist, multidisciplinary clinic is associated with improved survival, but access is not universal. We wanted to pilot and establish the feasibility of a definitive trial of a novel telehealth system (Telehealth in Motor neuron disease, TiM) in patients with MND.

DESIGN

An 18-month, single-centre, mixed-methods, randomised, controlled pilot and feasibility study.

INTERVENTION

TiM telehealth plus usual care versus usual care.

SETTING

A specialist MND care centre in the UK.

PARTICIPANTS

Patients with MND and their primary informal carers.

PRIMARY AND SECONDARY OUTCOME MEASURES

Recruitment, retention and data collection rates, clinical outcomes including participant quality of life and anxiety and depression.

RESULTS

Recruitment achieved the target of 40 patients and 37 carers. Participant characteristics reflected those attending the specialist clinic and included those with severe disability and those with limited experience of technology. Retention and data collection was good. Eighty per cent of patients and 82% of carer participants reported outcome measures were completed at 6 months. Using a longitudinal analysis with repeated measures of quality of life (QoL), a sample size of 131 per arm is recommended in a definitive trial. The methods and intervention were acceptable to participants who were highly motivated to participate to research. The low burden of participation and accessibility of the intervention meant barriers to participation were minimal. However, the study highlighted difficulties assessing the associated costs of the intervention, the challenge of recruitment in such a rare disease and the difficulties of producing rigorous evidence of impact in such a complex intervention.

CONCLUSION

A definitive trial of TiM is feasible but challenging. The complexity of the intervention and heterogeneity of the patient population means that a randomised controlled trial may not be the best way to evaluate the further development and implementation of the TiM.

TRIAL REGISTRATION NUMBER

ISRCTN26675465.

Implications of spirometric reference values for amyotrophic lateral sclerosis

Objective: Spirometry is commonly used as screening tool for respiratory insufficiency in neuromuscular diseases. Despite the well-known effects of reference standards on spirometric outcomes, its standardization is overlooked in current guidelines. We aim to illustrate the effect of spirometric reference values on prognostication, medical decision-making, and trial eligibility in the applied setting of amyotrophic lateral sclerosis (ALS). Methods: We selected 4,651 patients with 32,022 FVC measurements from the PRO-ACT dataset. The FVC estimates were standardized according to five reference standards: Knudson '76, Knudson '83, ECSC, NHANES III, and GLI-2012. (Generalized) linear mixed-effects and Cox proportional hazard models were used to evaluate longitudinal patterns and time-to-event outcomes. Results: The mean population %predicted FVC varied between 78.5% (95% CI 78.0-79.1) and 88.5% (95% CI 87.9-89.1). The unstandardized liters provided the worst fit on the survival data (AIC 20573, c-index 0.760), whereas the GLI provided the best fit (AIC 20374, c-index 0.780, p < 0.001). The mean population rate of decline in %predicted FVC could vary as much as 11.4% between reference standards. The median time-to-50% predicted FVC differed by 2.9 months between recent (14.5 months, 95% CI 14.4-16.1) and early reference standards (17.4 months, 95% CI 16.1-18.2). Conclusion: Independent of technique, device, or evaluator, spirometric reference values affect the utility of spirometry in ALS. Standardization of reference values is of the utmost importance to optimize clinical decision-making, improve prognostication, enhance between-center comparison and unify patient selection for clinical trials.

Design and analysis of a clinical trial using previous trials as historical control

BACKGROUND/AIMS

For single arm trials, a treatment is evaluated by comparing an outcome estimate to historically reported outcome estimates. Such a historically controlled trial is often analyzed as if the estimates from previous trials were known without variation and there is no trial-to-trial variation in their estimands. We develop a test of treatment efficacy and sample size calculation for historically controlled trials that considers these sources of variation.

METHODS

We fit a Bayesian hierarchical model, providing a sample from the posterior predictive distribution of the outcome estimand of a new trial, which, along with the standard error of the estimate, can be used to calculate the probability that the estimate exceeds a threshold. We then calculate criteria for statistical significance as a function of the standard error of the new trial and calculate sample size as a function of difference to be detected. We apply these methods to clinical trials for amyotrophic lateral sclerosis using data from the placebo groups of 16 trials.

RESULTS

We find that when attempting to detect the small to moderate effect sizes usually assumed in amyotrophic lateral sclerosis clinical trials, historically controlled trials would require a greater total number of patients than concurrently controlled trials, and only when an effect size is extraordinarily large is a historically controlled trial a reasonable alternative. We also show that utilizing patient level data for the prognostic covariates can reduce the sample size required for a historically controlled trial.

CONCLUSION

This article quantifies when historically controlled trials would not provide any sample size advantage, despite dispensing with a control group.

Accelerometry for remote monitoring of physical activity in amyotrophic lateral sclerosis: a longitudinal cohort study

Background

The extensive heterogeneity between patients with amyotrophic lateral sclerosis (ALS) complicates the quantification of disease progression. In this study, we determine the value of remote, accelerometer-based monitoring of physical activity in patients with ALS.

Methods

This longitudinal cohort study was conducted in a home-based setting; all study materials were sent by mail. Patients wore the ActiGraph during waking hours for 7 days every 2–3 months and provided information regarding their daily functioning (ALSFRS-R). We defined four accelerometer-based endpoints that either reflect the average daily activity or quantify the patient’s physical capacity.

Results

A total of 42 patients participated; the total valid monitoring period was 9288 h with a 93.0% adherence rate. At baseline, patients were active 27.9% (range 11.6–52.4%) of their time; this declined by 0.64% (95% 0.43–0.86, p < 0.001) per month. Accelerometer-based endpoints were strongly associated with the ALSFRS-R (r 0.78, 95% CI 0.63–0.92, p < 0.001), but showed less variability over time than the ALSFRS-R (coefficient of variation 0.64–0.81 vs. 1.06, respectively). Accelerometer-based endpoints could reduce sample size by 30.3% for 12-month trials and 44.6% for 18-month trials; for trials lasting less than 9 months, the ALSFRS-R resulted in smaller sample sizes.

Conclusion

Accelerometry is an objective method for quantifying disease progression, which could obtain real-world insights in the patient’s physical functioning and may personalize the delivery of care. In addition, remote monitoring provides patients with the opportunity to participate in clinical trials from home, paving the way to a patient-centric clinical trial model.

Incidence of frontotemporal lobar degeneration in Italy: The Salento-Brescia Registry study

OBJECTIVE

The goal of the present work, based on a collaborative research registry in Italy (the Salento-Brescia Registry), was to assess the incidence of frontotemporal lobar degeneration (FTLD) and to define the frequencies of different FTLD phenotypes in the general population.

METHODS

The study was conducted from January 1, 2017, to December 31, 2017, in 2 Italian provinces: Lecce (in Puglia) in the south (area 2,799.07 km², inhabitants 802,082) and Brescia (in Lombardy) in the north (area 4,785.62 km², inhabitants 1,262,678). During the study period, all new cases of FTLD (incident FTLD) were counted, and all patients' records were reviewed. The incidence was standardized to the Italian general population in 2017.

RESULTS

In the 2 provinces, 63 patients with FTLD were diagnosed. The incidence rate for FTLD was 3.05 (95% confidence interval [CI] 2.34-3.90) per 100,000 person-years (py), while the age-sex standardized incidence rate was 3.09 (95% CI 2.95-3.23) per 100,000 py. In the Italian population, the lifetime risk was 1:400. There was a progressive increase in FTLD incidence across age groups, reaching its peak in the 75- to 79-year-old group, with an incidence rate of 15.97 (95% CI 8.94-26.33) per 100,000 py. The behavioral variant of frontotemporal dementia was the most common phenotype (37%). No difference in crude incidence rate between the 2 provinces was observed.

CONCLUSION

FTLD is a more common form of dementia than previously recognized, with a risk spanning in a wide age range and with maximum incidence in the mid-70s. Improved knowledge of FTLD epidemiology will help to provide appropriate public health service policies.

Machine Learning in Amyotrophic Lateral Sclerosis: Achievements, Pitfalls, and Future Directions

Background: Amyotrophic Lateral Sclerosis (ALS) is a relentlessly progressive neurodegenerative condition with limited therapeutic options at present. Survival from symptom onset ranges from 3 to 5 years depending on genetic, demographic, and phenotypic factors. Despite tireless research efforts, the core etiology of the disease remains elusive and drug development efforts are confounded by the lack of accurate monitoring markers. Disease heterogeneity, late-stage recruitment into pharmaceutical trials, and inclusion of phenotypically admixed patient cohorts are some of the key barriers to successful clinical trials. Machine Learning (ML) models and large international data sets offer unprecedented opportunities to appraise candidate diagnostic, monitoring, and prognostic markers. Accurate patient stratification into well-defined prognostic categories is another aspiration of emerging classification and staging systems. Methods: The objective of this paper is the comprehensive, systematic, and critical review of ML initiatives in ALS to date and their potential in research, clinical, and pharmacological applications. The focus of this review is to provide a dual, clinical-mathematical perspective on recent advances and future directions of the field. Another objective of the paper is the frank discussion of the pitfalls and drawbacks of specific models, highlighting the shortcomings of existing studies and to provide methodological recommendations for future study designs. Results: Despite considerable sample size limitations, ML techniques have already been successfully applied to ALS data sets and a number of promising diagnosis models have been proposed. Prognostic models have been tested using core clinical variables, biological, and neuroimaging data. These models also offer patient stratification opportunities for future clinical trials. Despite the enormous potential of ML in ALS research, statistical assumptions are often violated, the choice of specific statistical models is seldom justified, and the constraints of ML models are rarely enunciated. Conclusions: From a mathematical perspective, the main barrier to the development of validated diagnostic, prognostic, and monitoring indicators stem from limited sample sizes. The combination of multiple clinical, biofluid, and imaging biomarkers is likely to increase the accuracy of mathematical modeling and contribute to optimized clinical trial designs.

Refining eligibility criteria for amyotrophic lateral sclerosis clinical trials

OBJECTIVE

To assess the effect of eligibility criteria on exclusion rates, generalizability, and outcome heterogeneity in amyotrophic lateral sclerosis (ALS) clinical trials and to assess the value of a risk-based inclusion criterion.

METHODS

A literature search was performed to summarize the eligibility criteria of clinical trials. The extracted criteria were applied to an incidence cohort of 2,904 consecutive patients with ALS to quantify their effects on generalizability and outcome heterogeneity. We evaluated the effect of a risk-based selection approach on trial design using a personalized survival prediction model.

RESULTS

We identified 38 trials. A large variability exists between trials in all patient characteristics for enrolled patients (p < 0.001), except for the proportion of men (p = 0.21). Exclusion rates varied widely (from 14% to 95%; mean 59.8%; 95% confidence interval 52.6%-66.7%). Stratification of the eligible populations into prognostic subgroups showed that eligibility criteria lead to exclusion of patients in all prognostic groups. Eligibility criteria neither reduce heterogeneity in survival time (from 22.0 to 20.5 months, p = 0.09) nor affect between-patient variability in functional decline (from 0.62 to 0.65, p = 0.25). In none of the 38 trials were the eligibility criteria found to be more efficient than the prediction model in optimizing sample size and eligibility rate.

CONCLUSIONS

The majority of patients with ALS are excluded from trial participation, which questions the generalizability of trial results. Eligibility criteria only minimally improve homogeneity in trial endpoints. An individualized risk-based criterion could be used to balance the gains in trial design and loss in generalizability.

Lunasin does not slow ALS progression: results of an open-label, single-center, hybrid-virtual 12-month trial

Objective: Lunasin, a soy peptide that reportedly alters histone acetylation in vitro, was associated with a single ALS reversal in the media. Following an ALSUntangled report, we sought to determine whether Lunasin altered histone acetylation and improved progression in people with ALS, and whether patient-centric trial design features might improve enrollment and retention. Methods: This single-center, year-long trial (NCT02709330) featured broad inclusion criteria, historical controls, primarily virtual data collection, and real-time results. Participants measured their own ALSFRS-R score, weight and perceived efficacy, and recorded these monthly on PatientsLikeMe. Blood tests at screening and month 1 assessed alterations in histone H3 and H4 acetylation. The protocol was published online, empowering patients outside the study to self-experiment. Results: Fifty participants enrolled in 5.5 months. Although this population had more advanced disease compared to other trials, retention and adherence were very high. There was no significant effect of Lunasin treatment on histone acetylation or disease progression. A cohort following our protocol outside the trial reported similar side effects and perceived effectiveness; however, their compliance with data entry was markedly lower. Conclusions: While Lunasin's lack of efficacy is disappointing, our novel trial design had the highest ALS trial enrollment rate ever recorded, with excellent retention and adherence. Low data density from patients who are self-experimenting outside a formal protocol casts doubt on the possibility of gathering useful information from unsupervised expanded access programs or "right to try" initiatives.

Using automated electronic medical record data extraction to model ALS survival and progression

BACKGROUND

To assess the feasibility of using automated capture of Electronic Medical Record (EMR) data to build predictive models for amyotrophic lateral sclerosis (ALS) outcomes.

METHODS

We used an Informatics for Integrating Biology and the Bedside search discovery tool to identify and extract data from 354 ALS patients from the University of Kansas Medical Center EMR. The completeness and integrity of the data extraction were verified by manual chart review. A linear mixed model was used to model disease progression. Cox proportional hazards models were used to investigate the effects of BMI, gender, and age on survival.

RESULTS

Data extracted from the EMR was sufficient to create simple models of disease progression and survival. Several key variables of interest were unavailable without including a manual chart review. The average ALS Functional Rating Scale - Revised (ALSFRS-R) baseline score at first clinical visit was 34.08, and average decline was - 0.64 per month. Median survival was 27 months after first visit. Higher baseline ALSFRS-R score and BMI were associated with improved survival, higher baseline age was associated with decreased survival.

CONCLUSIONS

This study serves to show that EMR-captured data can be extracted and used to track outcomes in an ALS clinic setting, potentially important for post-marketing research of new drugs, or as historical controls for future studies. However, as automated EMR-based data extraction becomes more widely used there will be a need to standardize ALS data elements and clinical forms for data capture so data can be pooled across academic centers.

Global, regional, and national burden of motor neuron diseases 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016

BACKGROUND

Understanding how prevalence, incidence, and mortality of motor neuron diseases change over time and by location is crucial for understanding the causes of these disorders and for health-care planning. Our aim was to produce estimates of incidence, prevalence, and disability-adjusted life-years (DALYs) for motor neuron diseases for 195 countries and territories from 1990 to 2016 as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016.

METHODS

The motor neuron diseases included in this study were amyotrophic lateral sclerosis, spinal muscular atrophy, hereditary spastic paraplegia, primary lateral sclerosis, progressive muscular atrophy, and pseudobulbar palsy. Incidence, prevalence, and DALYs were estimated using a Bayesian meta-regression model. We analysed 14 165 site-years of vital registration cause of death data using the GBD 2016 cause of death ensemble model. The 84 risk factors quantified in GBD 2016 were tested for an association with incidence or death from motor neuron diseases. We also explored the relationship between Socio-demographic Index (SDI; a compound measure of income per capita, education, and fertility) and age-standardised DALYs of motor neuron diseases.

FINDINGS

In 2016, globally, 330 918 (95% uncertainty interval [UI] 299 522-367 254) individuals had a motor neuron disease. Motor neuron diseases have caused 926 090 (881 566-961 758) DALYs and 34 325 (33 051-35 364) deaths in 2016. The worldwide all-age prevalence was 4·5 (4·1-5·0) per 100 000 people, with an increase in age-standardised prevalence of 4·5% (3·4-5·7) over the study period. The all-age incidence was 0·78 (95% UI 0·71-0·86) per 100 000 person-years. No risk factor analysed in GBD showed an association with motor neuron disease incidence. The largest age-standardised prevalence was in high SDI regions: high-income North America (16·8, 95% UI 15·8-16·9), Australasia (14·7, 13·5-16·1), and western Europe (12·9, 11·7-14·1). However, the prevalence and incidence were lower than expected based on SDI in high-income Asia Pacific.

INTERPRETATION

Motor neuron diseases have low prevalence and incidence, but cause severe disability with a high fatality rate. Incidence of motor neuron diseases has geographical heterogeneity, which is not explained by any risk factors quantified in GBD, suggesting other unmeasured risk factors might have a role. Between 1990 and 2016, the burden of motor neuron diseases has increased substantially. The estimates presented here, as well as future estimates based on data from a greater number of countries, will be important in the planning of services for people with motor neuron diseases worldwide.

FUNDING

Bill & Melinda Gates Foundation.

Riluzole and edaravone: A tale of two amyotrophic lateral sclerosis drugs

Over the past decades, a multitude of experimental drugs have been shown to delay disease progression in preclinical animal models of amyotrophic lateral sclerosis (ALS) but failed to show efficacy in human clinical trials or are still waiting for approval under Phase I-III trials. Riluzole, a glutamatergic neurotransmission inhibitor, is the only drug approved by the USA Food and Drug Administration for ALS treatment with modest benefits on survival. Recently, an antioxidant drug, edaravone, developed by Mitsubishi Tanabe Pharma was found to be effective in halting ALS progression during early stages. The newly approved drug edaravone is a force multiplier for ALS treatment. This short report provides an overview of the two drugs that have been approved for ALS treatment and highlights an update on the timeline of drug development, how clinical trials were done, the outcome of these trials, primary endpoint, mechanism of actions, dosing information, administration, side effects, and storage procedures. Moreover, we also discussed the pressing issues and challenges of ALS clinical trials and drug developments as well as future outlook.

DNA Damage Response and Repair, DNA Methylation, and Cell Death in Human Neurons and Experimental Animal Neurons Are Different

Neurological disorders affecting individuals in infancy to old age elude interventions for meaningful protection against neurodegeneration, and preclinical work has not translated to humans. We studied human neuron responses to injury and death stimuli compared to those of animal neurons in culture under similar settings of insult (excitotoxicity, oxidative stress, and DNA damage). Human neurons were differentiated from a cortical neuron cell line and the embryonic stem cell-derived H9 line. Mouse neurons were differentiated from forebrain neural stem cells and embryonic cerebral cortex; pig neurons were derived from forebrain neural stem cells. Mitochondrial morphology was different in human and mouse neurons. Human and mouse neurons challenged with DNA-damaging agent camptothecin showed different chromatin condensation, cell death, and DNA damage sensor activation. DNA damage accumulation and repair kinetics differed among human, mouse, and pig neurons. Promoter CpG island methylation microarrays showed significant differential DNA methylation in human and mouse neurons after injury. Therefore, DNA damage response, DNA repair, DNA methylation, and autonomous cell death mechanisms in human neurons and experimental animal neurons are different.

Referral bias in ALS epidemiological studies

Background

Despite concerns about the representativeness of patients from ALS tertiary centers as compared to the ALS general population, the extent of referral bias in clinical studies remains largely unknown. Using data from EURALS consortium we aimed to assess nature, extent and impact of referral bias.

Methods

Four European ALS population-based registries located in Ireland, Piedmont, Puglia, Italy, and Limousin, France, covering 50 million person-years, participated. Demographic and clinic characteristics of ALS patients diagnosed in tertiary referral centers were contrasted with the whole ALS populations enrolled in registries in the same geographical areas.

Results

Patients referred to ALS centers were younger (with difference ranging from 1.1 years to 2.4 years), less likely to present a bulbar onset, with a higher proportion of familial antecedents and a longer survival (ranging from 11% to 15%) when compared to the entire ALS population in the same geographic area.

Conclusions

A trend for referral bias is present in cohorts drawn from ALS referral centers. The magnitude of the possible referral bias in a particular tertiary center can be estimated through a comparison with ALS patients drawn from registry in the same geographic area. Studies based on clinical cohorts should be cautiously interpreted. The presence of a registry in the same area may improve the complete ascertainment in the referral center.

Riluzole and other prognostic factors in ALS: a population-based registry study in Italy

OBJECTIVE

In this prospective population-based registry study on ALS survival, we investigated the role of riluzole treatment, together with other clinical factors, on the prognosis in incident ALS cases in Emilia Romagna Region (ERR), Italy.

METHODS

A registry for ALS has been collecting all incident cases in ERR since 2009. Detailed clinical data from all patients diagnosed with ALS between 1.1.2009 and 31.12.2014 have been analyzed for this study, with last follow up date set at 31.12.2015.

RESULTS

During the 6 years of the study, there were 681 incident cases with a median tracheostomy-free survival of 40 months (95% CI 36-44) from onset and of 26 months (95% CI 24-30) from diagnosis; 573 patients (84.14%) were treated with riluzole, 207 (30.39%) patients underwent gastrostomy, 246 (36.12%) non invasive ventilation, and 103 (15.15%) invasive ventilation. Patients who took treatment for ≥ 75% of disease duration from diagnosis had a median survival of 29 months compared to 18 months in patients with < 75% treatment duration. In multivariable analysis, factors independently influencing survival were age at onset (HR 1.04, 95% CI 1.02-1.05, p < 0.001), dementia (HR 1.56, 95% CI 1.05-2.32, p = 0.027), degree of diagnostic certainty (HR 0.88, 95% CI 0.78-0.98, p = 0.021), gastrostomy (HR 1.46, 95% CI 1.14-1.88, p = 0.003), NIV (HR 1.43, 95% CI 1.12-1.82, p = 0.004), and weight loss at diagnosis (HR 1.05, 95% CI 1.03-1.07, p < 0.001), diagnostic delay (HR 0.98, 95% CI 0.97-0.99, p = 0.004), and % treatment duration (HR 0.98, 95% CI 0.98-0.99, p < 0.001).

CONCLUSIONS

Independently from other prognostic factors, patients who received riluzole for a longer period of time survived longer, but further population based studies are needed to verify if long-tem use of riluzole prolongs survival.

Urate levels predict survival in amyotrophic lateral sclerosis: Analysis of the expanded Pooled Resource Open-Access ALS clinical trials database

INTRODUCTION

Urate has been identified as a predictor of amyotrophic lateral sclerosis (ALS) survival in some but not all studies. Here we leverage the recent expansion of the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database to study the association between urate levels and ALS survival.

METHODS

Pooled data of 1,736 ALS participants from the PRO-ACT database were analyzed. Cox proportional hazards regression models were used to evaluate associations between urate levels at trial entry and survival.

RESULTS

After adjustment for potential confounders (i.e., creatinine and body mass index), there was an 11% reduction in risk of reaching a survival endpoint during the study with each 1-mg/dL increase in uric acid levels (adjusted hazard ratio 0.89, 95% confidence interval 0.82-0.97, P < 0.01).

DISCUSSION

Our pooled analysis provides further support for urate as a prognostic factor for survival in ALS and confirms the utility of the PRO-ACT database as a powerful resource for ALS epidemiological research. Muscle Nerve 57: 430-434, 2018.

Developing multidisciplinary clinics for neuromuscular care and research

Multidisciplinary care is considered the standard of care for both adult and pediatric neuromuscular disorders and has been associated with improved quality of life, resource utilization, and health outcomes. Multidisciplinary care is delivered in multidisciplinary clinics that coordinate care across multiple specialties by reducing travel burden and streamlining care. In addition, the multidisciplinary care setting facilitates the integration of clinical research, patient advocacy, and care innovation (e.g., telehealth). Yet, multidisciplinary care requires substantial commitment of staff time and resources. We calculated personnel costs in our ALS clinic in 2015 and found an average cost per patient visit of $580, of which only 45% was covered by insurance reimbursement. In this review, we will describe classic and emerging concepts in multidisciplinary care models for adult and pediatric neuromuscular disease. We will then explore the financial impact of multidisciplinary care with emphasis on sustainability and metrics to demonstrate quality and value. Muscle Nerve 56: 848-858, 2017.

Epidemiological and clinical factors impact on the benefit of riluzole in the survival rates of patients with ALS

ABSTRACT Objective To investigate the impact of epidemiological and clinical factors on the benefit of riluzole in patients with amyotrophic lateral sclerosis (ALS). Methods The survival rate of 578 patients with ALS (1999-2011) was analyzed by descriptive statistics and Kaplan-Meier curves. Considering the median of the sample survival time (19 months), patients were divided in two groups: below (B19) and above the median (A19). Kaplan-Meier curves compared the survival rates of patients treated with riluzole and with patients who did not take the medication. Results Riluzole increased the survival rates of patients with lower limb onset who were diagnosed after the first appointment in B19. Patients with bulbar onset and diagnosed on the first, or after the first appointment showed higher survival rates in A19. Males lived longer than females in both groups. Conclusion Epidemiological and clinical factors influenced the benefit of riluzole in the survival rates of patients with ALS.