The PRO-ACT database: design, initial analyses, and predictive features

Sex Differences in Amyotrophic Lateral Sclerosis Survival and Progression: A Multidimensional Analysis

OBJECTIVE

To investigate sex-related differences in amyotrophic lateral sclerosis (ALS) prognosis and their contributing factors.

METHODS

Our primary cohort was the Piemonte and Aosta Register for ALS (PARALS); the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) and the Answer ALS databases were used for validation. Survival analyses were conducted accounting for age and onset site. The roles of forced vital capacity and weight decline were explored through a causal mediation analysis. Survival and disease progression rates were also evaluated after propensity score matching.

RESULTS

The PARALS cohort included 1,890 individuals (44.8% women). Men showed shorter survival when stratified by onset site (spinal onset HR 1.20, 95% CI 1.00-1.44, p = 0.0439; bulbar onset HR 1.36, 95% CI 1.09-1.70, p = 0.006917), although women had a steeper functional decline (+0.10 ALSFRS-R points/month, 95% CI 0.07-0.15, p < 0.00001) regardless of onset site. Instead, men showed worse respiratory decline (-4.2 forced vital capacity%/month, 95% CI -6.3 to -2.2, p < 0.0001) and faster weight loss (-0.15 kg/month, 95% CI -0.25 to -0.05, p = 0.0030). Causal mediation analysis showed that respiratory function and weight loss were pivotal in sex-related survival differences. Analysis of patients from PRO-ACT (n = 1,394, 40.9% women) and Answer ALS (n = 849, 37.2% women) confirmed these trends.

INTERPRETATION

The shorter survival in men is linked to worse respiratory function and weight loss rather than a faster disease progression. These findings emphasize the importance of considering sex-specific factors in understanding ALS pathophysiology and designing tailored therapeutic strategies. ANN NEUROL 2024;96:159-169.

Safety and efficacy of arimoclomol in patients with early amyotrophic lateral sclerosis (ORARIALS-01): a randomised, double-blind, placebo-controlled, multicentre, phase 3 trial

BACKGROUND

Amyotrophic lateral sclerosis is a progressive neurodegenerative disorder leading to muscle weakness and respiratory failure. Arimoclomol, a heat-shock protein-70 (HSP70) co-inducer, is neuroprotective in animal models of amyotrophic lateral sclerosis, with multiple mechanisms of action, including clearance of protein aggregates, a pathological hallmark of sporadic and familial amyotrophic lateral sclerosis. We aimed to evaluate the safety and efficacy of arimoclomol in patients with amyotrophic lateral sclerosis.

METHODS

ORARIALS-01 was a multinational, randomised, double-blind, placebo-controlled, parallel-group trial done at 29 centres in 12 countries in Europe and North America. Patients were eligible if they were aged 18 years or older and met El Escorial criteria for clinically possible, probable, probable laboratory-supported, definite, or familial amyotrophic lateral sclerosis; had an ALS Functional Rating Scale-Revised score of 35 or more; and had slow vital capacity at 70% or more of the value predicted on the basis of the participant's age, height, and sex. Patients were randomly assigned (2:1) in blocks of 6, stratified by use of a stable dose of riluzole or no riluzole use, to receive oral arimoclomol citrate 1200 mg/day (400 mg three times per day) or placebo. The Randomisation sequence was computer generated centrally. Investigators, study personnel, and study participants were masked to treatment allocation. The primary outcome was the Combined Assessment of Function and Survival (CAFS) rank score over 76 weeks of treatment. The primary outcome and safety were analysed in the modified intention-to-treat population. This trial is registered with ClinicalTrials.gov, NCT03491462, and is completed.

FINDINGS

Between July 31, 2018, and July 17, 2019, 287 patients were screened, 245 of whom were enrolled in the trial and randomly assigned. The modified intention-to-treat population comprised 239 patients (160 in the arimoclomol group and 79 in the placebo group): 151 (63%) were male and 88 (37%) were female; mean age was 57·6 years (SD 10·9). CAFS score over 76 weeks did not differ between groups (mean 0·51 [SD 0·29] in the arimoclomol group vs 0·49 [0·28] in the placebo group; p=0·62). Cliff's delta comparing the two groups was 0·039 (95% CI -0·116 to 0·194). Proportions of participants who died were similar between the treatment groups: 29 (18%) of 160 patients in the arimoclomol group and 18 (23%) of 79 patients in the placebo group. Most deaths were due to disease progression. The most common adverse events were gastrointestinal. Adverse events were more often deemed treatment-related in the arimoclomol group (104 [65%]) than in the placebo group (41 [52%]) and more often led to treatment discontinuation in the arimoclomol group (26 [16%]) than in the placebo group (four [5%]).

INTERPRETATION

Arimoclomol did not improve efficacy outcomes compared with placebo. Although available biomarker data are insufficient to preclude future strategies that target the HSP response, safety data suggest that a higher dose of arimoclomol would not have been tolerated.

FUNDING

Orphazyme.

A Model-Based Economic Evaluation of Hypothetical Treatments for Amyotrophic Lateral Sclerosis in the UK: Implications for Pricing of New and Emerging Health Technologies

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a devastating disease which leads to loss of muscle function and paralysis. Historically, clinical drug development has been unsuccessful, but promising disease-modifying therapies (DMTs) may be on the horizon.

OBJECTIVES

The aims of this study were to estimate survival, quality-adjusted life-years (QALYs) and costs under current care, and to explore the conditions under which new therapies might be considered cost effective.

METHODS

We developed a health economic model to evaluate the cost effectiveness of future ALS treatments from a UK National Health Service and Personal Social Services perspective over a lifetime horizon using data from the ALS-CarE study. Costs were valued at 2021/22 prices. Two hypothetical interventions were evaluated: a DMT which delays progression and mortality, and a symptomatic therapy which improves utility only. Sensitivity analysis was conducted to identify key drivers of cost effectiveness.

RESULTS

Starting from King's stage 2, patients receiving current care accrue an estimated 2.27 life-years, 0.75 QALYs and lifetime costs of £68,047. Assuming a 50% reduction in progression rates and a UK-converted estimate of the price of edaravone, the incremental cost-effectiveness ratio for a new DMT versus current care is likely to exceed £735,000 per QALY gained. Symptomatic therapies may be more likely to achieve acceptable levels of cost effectiveness.

CONCLUSIONS

Regardless of efficacy, DMTs may struggle to demonstrate cost effectiveness, even at a low price. The cost effectiveness of DMTs is likely to be strongly influenced by drug price, the magnitude and durability of relative treatment effects, treatment starting/stopping rules and any additional utility benefits over current care.

ALSFRS-R decline rate prior to baseline is not useful for stratifying subsequent progression of functional decline

OBJECTIVE

One of the difficulties in developing a novel drug for patients with amyotrophic lateral sclerosis (ALS) is the significant variation in the clinical course. To control this variation, a 12-week run-in period is used in some clinical trials. Based on the Amyotrophic Lateral Sclerosis Functional Rating Scale Revised (ALSFRS-R) change during the run-in period, only moderate progressors are selected in some clinical trials. Some reports showed that the ALSFRS-R progression rate was associated with survival. However, it is unclear whether the ALSFRS-R change in the run-in period is a useful prognostic factor of the ALSFRS-R change from baseline. In addition, we explore the inclusion criteria that could control the variability in ALS-function progression without setting a run-in period.

METHODS

We utilized the Japanese and US ALS registry databases (JaCALS and PRO-ACT). Patients were classified into three populations (rapid, moderate, and slow progressors) based on the ALSFRS-R change prior to baseline. We also classified patients into three prognostic populations based on the ALSFRS-R change from baseline. We confirmed whether each of the three populations were matched with their respective three prognostic populations.

RESULTS

Our data showed that the three groups classified by the ALSFRS-R change during the 12 weeks prior to baseline or by the rate of progression from onset to baseline did not accord with the three prognostic groups.

CONCLUSIONS

Our results showed that the ALSFRS-R change in the run-in period or from onset to baseline is not useful for stratifying subsequent progression of functional decline in clinical trials.

Predicting amyotrophic lateral sclerosis (ALS) progression with machine learning

OBJECTIVE

To predict ALS progression with varying observation and prediction window lengths, using machine learning (ML).

METHODS

We used demographic, clinical, and laboratory parameters from 5030 patients in the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database to model ALS disease progression as fast (at least 1.5 points decline in ALS Functional Rating Scale-Revised (ALSFRS-R) per month) or non-fast, using Extreme Gradient Boosting (XGBoost) and Bayesian Long Short Term Memory (BLSTM). XGBoost identified predictors of progression while BLSTM provided a confidence level for each prediction.

RESULTS

ML models achieved area under receiver-operating-characteristics curve (AUROC) of 0.570-0.748 and were non-inferior to clinician assessments. Performance was similar with observation lengths of a single visit, 3, 6, or 12 months and on a holdout validation dataset, but was better for longer prediction lengths. 21 important predictors were identified, with the top 3 being days since disease onset, past ALSFRS-R and forced vital capacity. Nonstandard predictors included phosphorus, chloride and albumin. BLSTM demonstrated higher performance for the samples about which it was most confident. Patient screening by models may reduce hypothetical Phase II/III clinical trial sizes by 18.3%.

CONCLUSION

Similar accuracies across ML models using different observation lengths suggest that a clinical trial observation period could be shortened to a single visit and clinical trial sizes reduced. Confidence levels provided by BLSTM gave additional information on the trustworthiness of predictions, which could aid decision-making. The identified predictors of ALS progression are potential biomarkers and therapeutic targets for further research.

Giving Breath to Motor Neurons: Noninvasive Mechanical Ventilation Slows Disease Progression in Amyotrophic Lateral Sclerosis

OBJECTIVE

Noninvasive mechanical ventilation (NIMV) improves amyotrophic lateral sclerosis (ALS) quality of life and survival. However, data about its effect on disease progression are still lacking. Here, we test whether NIMV use changed the rate of functional decline among ALS patients.

METHODS

In this retrospective observational study, we included 448 ALS patients followed up at the ALS Center in Turin, Italy, who underwent NIMV during the disease course. The primary outcome was the change in functional decline after NIMV initiation adjusting for covariates. Functional decline was based on the nonrespiratory items of the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R).

RESULTS

NIMV initiation resulted in a slower functional decline (mean improvement = 0.16 points per month, 95% confidence interval = 0.12-0.19, p < 0.001), with consistent effects observed across various demographic factors, including sex, age at diagnosis, and disease duration before NIMV initiation. This finding was replicated using the PRO-ACT (Pooled Resource Open-Access ALS Clinical Trials) dataset. The favorable impact of NIMV on ALSFRS-R progression was evident independently of disease stages. Notably, NIMV benefits were not dose-dependent but were particularly prominent for nighttime respiratory support.

INTERPRETATION

NIMV significantly influences the rate of motor progression in ALS, and this effect is not determined by the nonlinearity of ALSFRS-R trajectory. The functional decline slowed following NIMV initiation, independently of the site of disease onset or disease severity at the time of NIMV initiation. Our findings underscore the importance of timely NIMV initiation for all ALS patients and highlight the need to consider NIMV-induced slowing of disease progression when evaluating clinical trial outcomes. ANN NEUROL 2024;95:817-822.

Timing and impact of percutaneous endoscopic gastrostomy insertion in patients with amyotrophic lateral sclerosis: a comprehensive analysis

Dysphagia is common in amyotrophic lateral sclerosis (ALS) patients, often requiring percutaneous endoscopic gastrostomy (PEG) for enteral nutrition. We retrospectively analyzed data from 188 Korean patients with ALS who underwent PEG tube insertion at five-time points: symptom onset (t1), diagnosis (t2), recommended time for gastrostomy (t3), PEG insertion (t4), and one-year post-insertion (t5). The recommended time point for gastrostomy (T-rec for gastrostomy) was defined as the earlier time point between a weight loss of more than 10% and advanced dysphagia indicated by the ALSFRS-R swallowing subscore of 2 or less. The T-rec for gastrostomy was reached at 22 months after symptom onset, followed by PEG insertion at 30 months, resulting in an 8-month delay. During the delay, the ALSFRS-R declined most rapidly at 1.7 points/month, compared to 0.8 points/month from symptom onset to diagnosis, 0.7 points/month from diagnosis to T-rec for gastrostomy, and 0.6 points/month after the PEG insertion. It is crucial to discuss PEG insertion before significant weight loss or severe dysphagia occurs and minimize the delay between the recommended time for gastrostomy and the actual PEG insertion. A stratified and individualized multidisciplinary team approach with careful symptom monitoring and proactive management plans, including early PEG insertion, should be prioritized to improve patient outcomes.

Ensemble-imbalance-based classification for amyotrophic lateral sclerosis prognostic prediction: identifying short-survival patients at diagnosis

Prognosticating Amyotrophic Lateral Sclerosis (ALS) presents a formidable challenge due to patients exhibiting different onset sites, progression rates, and survival times. In this study, we have developed and evaluated Machine Learning (ML) algorithms that integrate Ensemble and Imbalance Learning techniques to classify patients into Short and Non-Short survival groups based on data collected during diagnosis. We aimed to identify individuals at high risk of mortality within 24 months of symptom onset through analysis of patient data commonly encountered in daily clinical practice. Our Ensemble-Imbalance approach underwent evaluation employing six ML algorithms as base classifiers. Remarkably, our results outperformed those of individual algorithms, achieving a Balanced Accuracy of 88% and a Sensitivity of 96%. Additionally, we used the Shapley Additive Explanations framework to elucidate the decision-making process of the top-performing model, pinpointing the most important features and their correlations with the target prediction. Furthermore, we presented helpful tools to visualize and compare patient similarities, offering valuable insights. Confirming the obtained results, our approach could aid physicians in devising personalized treatment plans at the time of diagnosis or serve as an inclusion/exclusion criterion in clinical trials.

Feasibility assessment of using the MiToS staging system for conducting economic evaluation in amyotrophic lateral sclerosis

OBJECTIVES

This study assessed the feasibility of using the Milano-Torino staging (MiToS) system for conducting economic evaluation to measure health outcomes in amyotrophic lateral sclerosis (ALS).

METHODS

A Markov model was developed using the MiToS system and evaluated with a hypothetical treatment versus standard of care. Health utilities and transition probabilities were derived from the literature. Four-time horizons (1, 5, 10, and 20 years) were examined. Treatment effects of 20-35% relative risk reduction (RRR) of progressing to the next MiToS stage were assessed. Three patient distribution scenarios were tested: (1) all patients began in stage 0; (2) patient distribution based on real-world TONiC study; (3) distribution based on the PRO-ACT database. Health outcomes (quality-adjusted life-years [QALYs], life-years [LYs]) were reported with a 3% discount rate.

RESULTS

A time horizon of 10 years fully captured treatment benefits: incremental QALYs were 0.28-0.60, 0.21-0.45, and 0.26-0.55 for scenarios 1-3, respectively; incremental LYs were 0.56-1.17, 0.46-0.97, and 0.53-1.11, respectively.

CONCLUSION

MiToS-based staging can be used for conducting economic analyses in ALS. Estimated incremental QALY and LY gains were meaningful within the context of ALS, for hypothetical treatments with RRR of 20-35%.

Describing and characterising variability in ALS disease progression

BACKGROUND, OBJECTIVES

Decrease in the revised ALS Functional Rating Scale (ALSFRS-R) score is currently the most widely used measure of disease progression. However, it does not sufficiently encompass the heterogeneity of ALS. We describe a measure of variability in ALSFRS-R scores and demonstrate its utility in disease characterization.

METHODS

We used 5030 ALS clinical trial patients from the Pooled Resource Open-Access ALS Clinical Trials database to calculate variability in disease progression employing a novel measure and correlated variability with disease span. We characterized the more and less variable populations and designed a machine learning model that used clinical, laboratory and demographic data to predict class of variability. The model was validated with a holdout clinical trial dataset of 84 ALS patients (NCT00818389).

RESULTS

Greater variability in disease progression was indicative of longer disease span on the patient-level. The machine learning model was able to predict class of variability with accuracy of 60.1-72.7% across different time periods and yielded a set of predictors based on clinical, laboratory and demographic data. A reduced set of 16 predictors and the holdout dataset yielded similar accuracy.

DISCUSSION

This measure of variability is a significant determinant of disease span for fast-progressing patients. The predictors identified may shed light on pathophysiology of variability, with greater variability in fast-progressing patients possibly indicative of greater compensatory reinnervation and longer disease span. Increasing variability alongside decreasing rate of disease progression could be a future aim of trials for faster-progressing patients.

Higher Glycemic Index and Glycemic Load Diet Is Associated with Slower Disease Progression in Amyotrophic Lateral Sclerosis

OBJECTIVE

High-caloric diets may slow the progression of amyotrophic lateral sclerosis; however, key macronutrients have not been identified. We examined whether dietary macronutrients are associated with the rate of progression and length of survival among the prospective cohort study participants.

METHODS

Participants with a confirmed diagnosis of sporadic amyotrophic lateral sclerosis enrolled in the Multicenter Cohort Study of Oxidative Stress were included (n = 304). We evaluated baseline macronutrient intake assessed by food frequency questionnaire in relation to change in revised amyotrophic lateral sclerosis functional rating scale total-score, and tracheostomy-free survival using linear regression and Cox proportional hazard models. Baseline age, sex, disease duration, diagnostic certainty, body mass index, bulbar onset, revised amyotrophic lateral sclerosis functional rating scale total-score, and forced vital capacity were included as covariates.

RESULTS

Baseline higher glycemic index and load were associated with less decline of revised amyotrophic lateral sclerosis functional rating scale total score at 3-month follow-up (β = -0.13, 95% CI -0.2, -0.01, p = 0.03) and (β = -0.01, 95% CI -0.03, -0.0007, p = 0.04), respectively. Glycemic index second-quartile, third-quartile, and fourth-quartile groups were associated with less decline at 3 months by 1.9 (95% CI -3.3, -0.5, p = 0.008), 2.0 (95% CI -3.3, -0.6, p = 0.006), and 1.6 (95% CI -3.0, -0.2, p = 0.03) points compared with the first-quartile group; the glycemic load fourth-quartile group had 1.4 points less decline compared with the first-quartile group (95% CI -2.8, 0.1, p = 0.07). Higher glycemic index was associated with a trend toward longer tracheostomy-free survival (HR 0.97, 95% CI 0.93, 1.00, p = 0.07).

INTERPRETATION

Higher dietary glycemic index and load are associated with slower disease progression in amyotrophic lateral sclerosis. ANN NEUROL 2024;95:217-229.

Time-restricted ketogenic diet in amyotrophic lateral sclerosis: a case study

Amyotrophic lateral sclerosis (ALS) is an incurable neurodegenerative disorder. The most devastating variant is bulbar-onset ALS, which portends a median survival of 24 months from the onset of symptoms. Abundant evidence indicates that neuron metabolism and mitochondrial function are impaired in ALS. Metabolic strategies, particularly fasting and ketogenic diet protocols, alter neuron metabolism and mitochondria function in a manner that may mitigate the symptoms of this disorder. We report the case of a 64-year-old man with a 21-month history of progressive, deteriorating bulbar-onset ALS, with an associated pseudobulbar affect, who implemented a time-restricted ketogenic diet (TRKD) for 18 months. During this time, he improved in ALS-related function (7% improvement from baseline), forced expiratory volume (17% improvement), forced vital capacity (13% improvement), depression (normalized), stress levels (normalized), and quality of life (19% improvement), particularly fatigue (23% improvement). His swallowing impairment and neurocognitive status remained stable. Declines were measured in physical function, maximal inspiratory pressure, and maximal expiratory pressure. Weight loss was attenuated and no significant adverse effects occurred. This case study represents the first documented occurrence of a patient with ALS managed with either a fasting or ketogenic diet protocol, co-administered as a TRKD. We measured improved or stabilized ALS-related function, forced expiratory volume, forced vital capacity, swallowing, neurocognitive status, mood, and quality of life. Measurable declines were restricted to physical function, maximal inspiratory pressure, and maximal expiratory pressure. Now over 45 months since symptom onset, our patient remains functionally independent and dedicated to his TRKD.

Individualized predictions for clinical milestone in amyotrophic lateral sclerosis: A multialgorithmic approach

Objective

The phenotypic heterogeneity and complex disease trajectory complicate the ability to predict specific clinical milestone for individual patients with amyotrophic lateral sclerosis (ALS). Here we developed individualized prediction models to estimate the time to the loss of autonomy in swallowing function.

Methods

Utilizing the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database, we built three models of distinct time-to-event prediction algorithms: accelerated failure time (AFT), cox proportional hazard (COX) and random survival forest (RSF) for an individualized risk assessment of the swallowing milestone. The target variable was defined as the time to a decline in the ALSFRS-R swallowing item score to 1 or below, indicating a need for supplementary tube feeding.

Results

Internal cross-validation revealed the median concordance index (C-index) of 0.851 (IQR, 0.842-0.859) for AFT, 0.850 (0.841-0.859) for COX and 0.846 (0.839-0.854) for RSF, and all models demonstrated good distributional calibration with predicted and observed event probabilities closely matched across different time intervals. For external validation with a registry dataset with characteristics different from PRO-ACT, the discriminative power was replicated with comparable C-indices for all models, whereas the calibration revealed a left-skewed distribution suggesting a bias towards overestimation of event probabilities in real-world data. While all models were effective at stratifying patients, the results of RSF model, unlike AFT and COX, did not match well with the KM curves of the corresponding risk groups, supporting the importance of nuanced understanding of data structure and algorithmic properties.

Conclusion

Our models are implemented into a web application which could be applied to individualized counselling, management and clinical trial design for gastrostomy intervention. Further studies for model optimization will advance personalized care in patients with ALS.

Analysis of sodium phenylbutyrate and taurursodiol survival effect in ALS using external controls

OBJECTIVE

Sodium phenylbutyrate and taurursodiol (PB and TURSO) was evaluated in amyotrophic lateral sclerosis (ALS) in the CENTAUR trial encompassing randomized placebo-controlled and open-label extension phases. On intent-to-treat (ITT) survival analysis, median overall survival (OS) was 4.8 months longer and risk of death 36% lower in those originally randomized to an initial 6-month double-blind period of PB and TURSO versus placebo. To estimate PB and TURSO treatment effect without placebo-to-active crossover, we performed a post hoc survival analysis comparing PB and TURSO-randomized participants from CENTAUR and a propensity score-matched, PB and TURSO-naïve external control cohort from the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database.

METHODS

Clinical trial control participants from the PRO-ACT database who met prespecified eligibility criteria were propensity score matched 1:1 with PB and TURSO-randomized CENTAUR participants using prognostically significant covariates in ALS.

RESULTS

Baseline characteristics including propensity score-matched covariates were generally well balanced between CENTAUR PB and TURSO (n = 89) and PRO-ACT external control (n = 85) groups. Estimated median (IQR) OS was 23.54 (14.56-39.32) months in the CENTAUR PB and TURSO group and 13.15 (9.83-19.20) months in the PRO-ACT external control group; hazard of death was 52% lower in the former group (hazard ratio, 0.48; 95% CI, 0.31-0.72; p = 0.00048).

INTERPRETATION

This analysis suggests potentially greater survival benefit with PB and TURSO in ALS without placebo-to-active crossover than seen on ITT analysis in CENTAUR. Analyses using well-matched external controls may provide additional context for evaluating survival effects in future ALS trials.

Induced pluripotent stem cells-based disease modeling, drug screening, clinical trials, and reverse translational research for amyotrophic lateral sclerosis

It has been more than 10 years since the hopes for disease modeling and drug discovery using induced pluripotent stem cell (iPSC) technology boomed. Recently, clinical trials have been conducted with drugs identified using this technology, and some promising results have been reported. For amyotrophic lateral sclerosis (ALS), a devastating neurodegenerative disease, several groups have identified candidate drugs, ezogabine (retigabine), bosutinib, and ropinirole, using iPSCs-based drug discovery, and clinical trials using these drugs have been conducted, yielding interesting results. In our previous study, an iPSCs-based drug repurposing approach was utilized to show the potential of ropinirole hydrochloride (ROPI) in reducing ALS-specific pathological phenotypes. Recently, a phase 1/2a trial was conducted to investigate the effects of ropinirole on ALS further. This double-blind, randomized, placebo-controlled study confirmed the safety and tolerability of and provided evidence of its ability to delay disease progression and prolong the time to respiratory failure in ALS patients. Furthermore, in the reverse translational research, in vitro characterization of patient-derived iPSCs-motor neurons (MNs) mimicked the therapeutic effects of ROPI in vivo, suggesting the potential application of this technology to the precision medicine of ALS. Interestingly, RNA-seq data showed that ROPI treatment suppressed the sterol regulatory element-binding protein 2-dependent cholesterol biosynthesis pathway. Therefore, this pathway may be involved in the therapeutic effect of ROPI on ALS. The possibility that this pathway may be involved in the therapeutic effect of ALS was demonstrated. Finally, new future strategies for ALS using iPSCs technology will be discussed in this paper.

Interaction of sex and onset site on the disease trajectory of amyotrophic lateral sclerosis

BACKGROUND

Studies showed the impact of sex and onset site (spinal or bulbar) on disease onset and survival in ALS. However, they mainly result from cross-sectional or survival analysis, and the interaction of sex and onset site on the different proxies of disease trajectory has not been fully investigated.

METHODS

We selected all patients with repeated observations in the PRO-ACT database. We divided them into four groups depending on their sex and onset site. We estimated a multivariate disease progression model, named ALS Course Map, to investigate the combined temporal changes of the four sub-scores of the revised ALS functional rating scale (ALSFRSr), the forced vital capacity (FVC), and the body mass index (BMI). We then compared the progression rate, the estimated age at onset, and the relative progression of the outcomes across each group.

RESULTS

We included 1438 patients from the PRO-ACT database. They were 51% men with spinal onset, 12% men with bulbar onset, 26% women with spinal onset, and 11% women with bulbar onset. We showed a significant influence of both sex and onset site on the ALSFRSr progression. The BMI decreased 8.9 months earlier (95% CI [3.9, 13.8]) in women than men, after correction for the onset site. Among patients with bulbar onset, FVC was impaired 2.6 months earlier (95% CI [0.6, 4.6]) in women.

CONCLUSION

Using a multivariable disease modelling approach, we showed that sex and onset site are important drivers of the progression of motor function, BMI, and FVC decline.

Efficacy and Safety of Ravulizumab, a Complement C5 Inhibitor, in Adults With Amyotrophic Lateral Sclerosis: A Randomized Clinical Trial

Importance

Additional therapies for amyotrophic lateral sclerosis (ALS) are urgently needed. Immune-mediated complement activation may be involved in ALS pathogenesis as evidenced by the upregulation of terminal components; thus, complement inhibition could potentially slow progression.

Objective

To evaluate the safety and efficacy of the terminal complement C5 inhibitor ravulizumab in adults with ALS.

Design, Setting, and Participants

This double-blind, placebo-controlled, parallel-group, multinational, randomized, phase 3 clinical trial was conducted from March 30, 2020, to October 17, 2021, in 81 ALS specialty centers across 17 countries. A preplanned, unmasked, nonbinding interim futility analysis was conducted when 33% of participants had completed week 26, wherein a conditional power of less than 10% would halt the trial. A total of 478 individuals were screened, and 96 were excluded. Inclusion criteria were weight of 40 kg or more, fulfillment of the El Escorial diagnostic criteria, and a minimal prestudy Revised Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS-R) progression score of -0.3 points per month.

Interventions

Study treatment consisted of placebo or a weight-based dose of intravenous ravulizumab every 8 weeks until week 42. Participants could continue standard-of-care treatment.

Main Outcomes and Measures

The primary end point was change from baseline in ALSFRS-R score at week 50 based on the Combined Assessment of Function and Survival (CAFS).

Results

A total of 382 participants were randomly assigned 2:1 to receive ravulizumab (n = 255; mean [SD] age, 58.6 [10.6] years; 94 female [36.9%] and 161 male [63.1%]) or placebo (n = 127; mean [SD] age, 58.0 [11.0] years; 58 female [45.7%] and 69 male [54.3%]). The interim analysis showed that the observed mean change from baseline in ALSFRS-R at week 50 was -14.67 points (SE, 0.89 points; 95% CI, -16.42 to -12.91 points) for ravulizumab and -13.33 points (SE, 1.22 points; 95% CI, -15.72 to -10.93 points) for placebo, with no significant difference between the groups (mean [SE] difference, -1.34 [1.46] points; 95% CI, -4.21 to 1.53 points). Based on these data, the trial was terminated for futility. The primary analysis at week 50 showed no significant difference in CAFS between groups (mean [SE], 5.5 [10.8] points; 95% CI, -15.7 to 26.6 points; P = .61). Overall incidence rates for treatment-emergent adverse events were similar for ravulizumab (204 participants [80.0%]) and placebo (108 participants [85.0%]).

Conclusions and Relevance

This trial rapidly showed that terminal complement C5 inhibition with ravulizumab did not slow functional decline in participants with ALS and that the safety profiles of ravulizumab and placebo were similar. Highly effective, novel treatments are critically needed to slow functional decline and extend survival in patients with ALS.

Trial Registration

ClinicalTrials.gov Identifier: NCT04248465.

Addressing Outcome Measure Variability in Myasthenia Gravis Clinical Trials

An increasing number of clinical trials are enrolling patients with myasthenia gravis (MG). A lack of standardization in the performance of outcome measures leads to confusion among site research teams and is a source of variability in clinical trial data. MGNet, the NIH-supported Rare Disease Clinical Research Network for MG, views standardization of MG outcome measures as a critical need. To address this issue, a group of experts summarized key outcome measures used in MG clinical trials and a symposium was convened to address issues contributing to outcome measure variability. Consensus recommendations resulted in changes to outcome measure instructions and, in some cases, modifications to specific instruments. Recommended changes were posted for public commentary before finalization. Changes to the MG-Activities of Daily Living, MG-Quality of Life-15r, and MG-Impairment Index were limited to adding details to the administration instructions. Recommendations for proper positioning of participants and how to score items that could not be performed because of non-MG reasons were provided for the MG Composite. The Quantitative MG (QMG) score required the most attention, and changes were made both to the instructions and the performance of certain items resulting in the QMG-Revised. The Postintervention Status was believed to have a limited role in clinical trials, except for the concept of minimal manifestation status. As a next step, training materials and revised source documents, which will be freely available to study teams, will be created and posted on the MGNet website. Further studies are needed to validate changes made to the QMG-Revised.

Design and Statistical Innovations in a Platform Trial for Amyotrophic Lateral Sclerosis

Platform trials allow efficient evaluation of multiple interventions for a specific disease. The HEALEY ALS Platform Trial is testing multiple investigational products in parallel and sequentially in persons with amyotrophic lateral sclerosis (ALS) with the goal of rapidly identifying novel treatments to slow disease progression. Platform trials have considerable operational and statistical efficiencies compared with typical randomized controlled trials due to their use of shared infrastructure and shared control data. We describe the statistical approaches required to achieve the objectives of a platform trial in the context of ALS. This includes following regulatory guidance for the disease area of interest and accounting for potential differences in outcomes of participants within the shared control (potentially due to differences in time of randomization, mode of administration, and eligibility criteria). Within the HEALEY ALS Platform Trial, the complex statistical objectives are met using a Bayesian shared parameter analysis of function and survival. This analysis serves to provide a common integrated estimate of treatment benefit, overall slowing in disease progression, as measured by function and survival while accounting for potential differences in the shared control group using Bayesian hierarchical modeling. Clinical trial simulation is used to provide a better understanding of this novel analysis method and complex design. ANN NEUROL 2023;94:547-560.

Dynamic effects of prognostic factors and individual survival prediction for amyotrophic lateral sclerosis disease

OBJECTIVE

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease affecting motor neurons, with broad heterogeneity in disease progression and survival in different patients. Therefore, an accurate prediction model will be crucial to implement timely interventions and prolong patient survival time.

METHODS

A total of 1260 ALS patients from the PRO-ACT database were included in the analysis. Their demographics, clinical variables, and death reports were included. We constructed an ALS dynamic Cox model through the landmarking approach. The predictive performance of the model at different landmark time points was evaluated by calculating the area under the curve (AUC) and Brier score.

RESULTS

Three baseline covariates and seven time-dependent covariates were selected to construct the ALS dynamic Cox model. For better prognostic analysis, this model identified dynamic effects of treatment, albumin, creatinine, calcium, hematocrit, and hemoglobin. Its prediction performance (at all landmark time points, AUC ≥ 0.70 and Brier score ≤ 0.12) was better than that of the traditional Cox model, and it predicted the dynamic 6-month survival probability according to the longitudinal information of individual patients.

INTERPRETATION

We developed an ALS dynamic Cox model with ALS longitudinal clinical trial datasets as the inputs. This model can not only capture the dynamic prognostic effect of both baseline and longitudinal covariates but also make individual survival predictions in real time, which are valuable for improving the prognosis of ALS patients and providing a reference for clinicians to make clinical decisions.

Split-elbow sign in the PRO-ACT and Southern Italy ALS cohorts: a potential marker of disease severity and lower motor neuron involvement?

INTRODUCTION

Split phenomena in ALS refers to the preferential dysfunction of some groups of muscles over others. The split-elbow sign (SE) is characterized by the predominant weakness of the biceps compared to the triceps, but available results are conflicting.

OBJECTIVES

To evaluate the prevalence of the SE in two independent cohorts: the randomized controlled trial-based PRO-ACT cohort (n = 500) and a monocentric cohort of patients with ALS from Southern Italy (n = 144); to investigate the demographic and clinical variables associated with the SE sign.

METHODS

Wilcoxon signed-rank test was used to compare biceps with triceps power in the same limb measured by hand-held dynamometry in the PRO-ACT cohort and Medical Research Council (MRC) in our cohort. Each limb was considered independently and not paired within the same individual. The arm where the triceps was stronger than the biceps was defined SE + , whereas the arm where the biceps was stronger than the triceps was considered SE-. A backward stepwise multivariate logistic regression was used to analyze the relationship between clinical and demographic variables and SE. PENN Upper Motor Neuron and Devine scales were used to evaluate the different upper (UMN) and lower (LMN) motor neuron impairments between the SE + and SE- arms.

RESULTS

In both cohorts, the biceps were on average stronger than the triceps, and the SE sign was present in 41% of the PRO-ACT cohort and just 30% of the Southern Italy cohort. The multivariate logistic regression revealed that older age (OR: 1.45; p = 0.01), male gender (OR: 1.55; p = 0.002), spinal onset (OR: 1.59; p = 0.007), and higher disease severity (OR: 1.70; p = 0.001) were significant predictors of the SE sign in the PRO-ACT cohort. Conversely, in Southern Italy patients, only a lower ALSFRS-R score was a significant determinant of the SE (OR: 8.47; p = 0.008). Finally, SE + arms exhibited a significantly higher median Devine sub-score compared to SE- [1 vs 0, p = < 0.05], while arms SE- showed a significantly higher median PUMNS sub-score [2 vs 0; p = < 0.05)].

CONCLUSION

In our study, most patients with ALS do not show SE. Patients with SE are more likely older, males, with spinal onset, a higher degree of disease severity, and predominant and wider LMN impairment.

Wearable device and smartphone data quantify ALS progression and may provide novel outcome measures

Amyotrophic lateral sclerosis (ALS) therapeutic development has largely relied on staff-administered functional rating scales to determine treatment efficacy. We sought to determine if mobile applications (apps) and wearable devices can be used to quantify ALS disease progression through active (surveys) and passive (sensors) data collection. Forty ambulatory adults with ALS were followed for 6-months. The Beiwe app was used to administer the self-entry ALS functional rating scale-revised (ALSFRS-RSE) and the Rasch Overall ALS Disability Scale (ROADS) surveys every 2-4 weeks. Each participant used a wrist-worn activity monitor (ActiGraph Insight Watch) or an ankle-worn activity monitor (Modus StepWatch) continuously. Wearable device wear and app survey compliance were adequate. ALSFRS-R highly correlated with ALSFRS-RSE. Several wearable data daily physical activity measures demonstrated statistically significant change over time and associations with ALSFRS-RSE and ROADS. Active and passive digital data collection hold promise for novel ALS trial outcome measure development.

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.

Statistical analysis plan for the motor neuron disease systematic multi-arm adaptive randomised trial (MND-SMART)

BACKGROUND

MND-SMART is a platform, multi-arm, multi-stage, multi-centre, randomised controlled trial recruiting people with motor neuron disease. Initially, the treatments memantine and trazodone will each be compared against placebo, but other investigational treatments will be introduced into the trial later. The co-primary outcomes are the Amyotrophic Lateral Sclerosis Functional Rating Scale Revised (ALS-FRS-R) functional outcome, which is assessed longitudinally, and overall survival.

METHODS

Initially in MND-SMART, participants are randomised 1:1:1 via a minimisation algorithm to receive placebo or one of the two investigational treatments with up to 531 to be randomised in total. The comparisons between each research arm and placebo will be conducted in four stages, with the opportunity to cease further randomisations to poorly performing research arms at the end of stages 1 or 2. The final ALS-FRS-R analysis will be at the end of stage 3 and final survival analysis at the end of stage 4. The estimands for the co-primary outcomes are described in detail. The primary analysis of ALS-FRS-R at the end of stages 1 to 3 will involve fitting a normal linear mixed model to the data to calculate a mean difference in rate of ALS-FRS-R change between each research treatment and placebo. The pairwise type 1 error rate will be controlled, because each treatment comparison will generate its own distinct and separate interpretation. This publication is based on a formal statistical analysis plan document that was finalised and signed on 18 May 2022.

DISCUSSION

In developing the statistical analysis plan, we had to carefully consider several issues such as multiple testing, estimand specification, interim analyses, and statistical analysis of the repeated measurements of ALS-FRS-R. This analysis plan attempts to balance multiple factors, including minimisation of bias, maximising power and precision, and deriving clinically interpretable summaries of treatment effects.

TRIAL REGISTRATION

EudraCT Number, 2019-000099-41. Registered 2 October 2019, https://www.clinicaltrialsregister.eu/ctr-search/search?query=mnd-smart ClinicalTrials.gov, NCT04302870 . Registered 10 March 2020.

Long-term survival benefits of intrathecal autologous bone marrow-derived mesenchymal stem cells (Neuronata-R®: lenzumestrocel) treatment in ALS: Propensity-score-matched control, surveillance study

Objective

Neuronata-R® (lenzumestrocel) is an autologous bone marrow-derived mesenchymal stem cell (BM-MSC) product, which was conditionally approved by the Korean Ministry of Food and Drug Safety (KMFDS, Republic of Korea) in 2013 for the treatment of amyotrophic lateral sclerosis (ALS). In the present study, we aimed to investigate the long-term survival benefits of treatment with intrathecal lenzumestrocel.

Methods

A total of 157 participants who received lenzumestrocel and whose symptom duration was less than 2 years were included in the analysis (BM-MSC group). The survival data of placebo participants from the Pooled-Resource Open-Access ALS Clinical Trials (PROACT) database were used as the external control, and propensity score matching (PSM) was used to reduce confounding biases in baseline characteristics. Adverse events were recorded during the entire follow-up period after the first treatment.

Results

Survival probability was significantly higher in the BM-MSC group compared to the external control group from the PROACT database (log-rank, p < 0.001). Multivariate Cox proportional hazard analysis showed a significantly lower hazard ratio for death in the BM-MSC group and indicated that multiple injections were more effective. Additionally, there were no serious adverse drug reactions found during the safety assessment, lasting a year after the first administration.

Conclusion

The results of the present study showed that lenzumestrocel treatment had a long-term survival benefit in real-world ALS patients.

Drug discovery and amyotrophic lateral sclerosis: Emerging challenges and therapeutic opportunities

Amyotrophic lateral sclerosis (ALS) is characterized by the degeneration of upper and lower motor neurons (MNs) leading to paralysis and, ultimately, death by respiratory failure 3-5 years after diagnosis. Edaravone and Riluzole, the only drugs currently approved for ALS treatment, only provide mild symptomatic relief to patients. Extraordinary progress in understanding the biology of ALS provided new grounds for drug discovery. Over the last two decades, mitochondria and oxidative stress (OS), iron metabolism and ferroptosis, and the major regulators of hypoxia and inflammation - HIF and NF-κB - emerged as promising targets for ALS therapeutic intervention. In this review, we focused our attention on these targets to outline and discuss current advances in ALS drug development. Based on the challenges and the roadblocks, we believe that the rational design of multi-target ligands able to modulate the complex network of events behind the disease can provide effective therapies in a foreseeable future.

The contribution of brain banks to knowledge discovery in amyotrophic lateral sclerosis: A systematic review

Over the past decade, considerable efforts have been made to accelerate pathophysiological understanding of fatal neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS) with brain banks at the forefront. In addition to exploratory disease mechanisms, brain banks have aided our understanding with regard to clinical diagnosis, genetics and cell biology. Across neurodegenerative disorders, the impact of brain tissue in ALS research has yet to be quantified. This review aims to outline (i) how postmortem tissues from brain banks have influenced our understanding of ALS over the last 15 years, (ii) correlate the location of dedicated brain banks with the geographical prevalence of ALS, (iii) identify the frequency of features reported from postmortem studies and (iv) propose common reporting standards for materials obtained from dedicated brain banks. A systematic review was conducted using PubMed and Web of Science databases using key words. From a total of 1439 articles, 73 articles were included in the final review, following PRISMA guidelines. Following a thematic analysis, articles were categorised into five themes; clinico-pathological (13), genetic (20), transactive response DNA binding protein 43 (TDP-43) pathology (12), non-TDP-43 neuronal pathology (nine) and extraneuronal pathology (19). Research primarily focused on the genetics of ALS, followed by protein pathology. About 63% of the brain banks were in the United States of America and United Kingdom. The location of brain banks overall aligned with the incidence of ALS worldwide with 88% of brain banks situated in Europe and North America. An overwhelming lack of consistency in reporting and replicability was observed, strengthening the need for a standardised reporting system. Overall, postmortem material from brain banks generated substantial new knowledge in areas of genetics and proteomics and supports their ongoing role as an important research tool.

Effectiveness of herbal medicine on patients with amyotrophic lateral sclerosis: Analysis of the PRO-ACT data using propensity score matching

BACKGROUND

Patients with amyotrophic lateral sclerosis (ALS) have restricted pharmacotherapy options and thus resort to herbal medicines (HMs), despite limited and conflicting evidence. Therefore, use of HMs needs to be assessed in patients with ALS.

PURPOSE

This study aimed to evaluate the benefits of HMs in ALS and to describe the characteristics of HM users.

STUDY DESIGN

The correlation between HMs and prognosis was determined based on data obtained from the largest ALS database with high-quality clinical trials. Propensity score (PS) matching was used to address confounding and selection bias.

METHODS

In total, 321 and 231 HM users with at least a 4-week HM prescription were identified and PS-matched with non-HM users at a 1:1 ratio based on predefined confounders. Time-to-event models with censoring at 12 or 18 months were established for survival analyses. For evaluating activity limitation and respiratory function, 320 and 376 HM users were included, respectively, and analyzed using multivariate analysis of variance (MANOVA).

RESULTS

The profiles of 321 HM users indicated a better condition compared with that of non-HM users before PS-matching, including higher weight (median [IQR], 77.90 [21.8] kg vs. 74.00 [21.2] kg, p < 0.01), higher body mass index (26.00 [5.4] vs. 25.20 [5.8], p < 0.01), more percentage of limb onset (261 [81.3%] vs. 2366 [67.2%], p < 0.01), and slower progression (0.47 [0.5] vs. 0.51 [0.5], p = 0.03). HM did not significantly affect survival at 12 months (adjusted hazard ratio [HR] 0.71, 95% confidence interval [CI] 0.49-1.03; log-rank p = 0.069), but it significantly prolonged survival at 18 months (adjusted HR 0.74, 95% CI 0.56-0.98; log-rank p = 0.038). After imputation of missing data, MANOVA revealed significant effectiveness of HMs in improving activity limitation (Pillai trace, 0.0195; p = 0.03).

CONCLUSION

PS-based methods eliminated baseline differences between HM and non-HM users. Overall, the use of HM to treat patients with ALS is favored based on their association with prolonged overall survival within 18 months and improved activity limitation.

Early initiation of riluzole may improve absolute survival in amyotrophic lateral sclerosis

INTRODUCTION/AIMS

Riluzole improves survival in amyotrophic lateral sclerosis (ALS), but optimal time and duration of treatment are unknown. The aim of this study was to examine if timing of riluzole initiation and duration of treatment modified its effect on survival.

METHODS

Patients from the PRO-ACT dataset with information on ALS Functional Rating Scale, time from onset to enrollment (TFOE), and riluzole use were selected for analysis. Survival from enrollment was the outcome. Multivariable Cox proportional hazard models were examined for interactions between riluzole and TFOE. Inverse probability of treatment weighting (IPTW) was used to assess average treatment effect.

RESULTS

Of 4778 patients, 3446 (72.1%) had received riluzole. In unadjusted analyses, riluzole improved median survival significantly (22.6 vs. 20.2 months, log-rank p < 0.001). In multivariable analyses, no significant interaction between TFOE and riluzole was found. Riluzole effect was uniform during follow-up. By IPTW, estimated riluzole hazard ratio was 0.798 (95% confidence interval 0.686-0.927). Delaying riluzole initiation by 1 y (6 to 18 months from onset) may translate to reducing median survival from onset by 1.9 months (40.1 to 38.2 months).

DISCUSSION

Riluzole appears to reduce risk of death uniformly, regardless of time from onset to treatment, and duration of treatment. Earlier treatment with riluzole may be associated with greater absolute survival gain from onset. Early diagnosis of ALS will facilitate early treatment and is expected to improve survival.

A novel quantitative indicator for disease progression rate in amyotrophic lateral sclerosis

OBJECTIVE

The current study sought to develop a new indicator for disease progression rate in amyotrophic lateral sclerosis (ALS).

METHODS

We used a nonparametric method to score diverse patterns of decline in the percentage of predicted forced vital capacity (%FVC) in patients with ALS. This involved 6317 longitudinal %FVC data sets from 920 patients in the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database volunteered by PRO-ACT Consortium members. To assess the utility of the derived scores as a disease indicator, we examined changes over time, the association with prognosis, and correlation with the Risk Profile of the Treatment Research Initiative to Cure ALS (TRICALS). Our local cohort (n = 92) was used for external validation.

RESULTS

We derived scores ranging from 35 to 106 points to construct the FVC Decline Pattern scale (FVC-DiP). Individuals' FVC-DiP scores were determined from a single measurement of %FVC and disease duration at assessment. Although the %FVC declined over the disease course (p < 0.0001), the FVC-DiP remained relatively stable. Low FVC-DiP scores were associated with rapid disease progression. Using our cohort, we demonstrated an association between FVC-DiP and the survival prognosis, the stability of the FVC-DiP per individual, and a correlation between FVC-DiP scores and the TRICALS Risk Profile (r² = 0.904, p < 0.0001).

CONCLUSIONS

FVC-DiP scores reflected patterns of declining %FVC over the natural course of ALS and indicated the disease progression rate. The FVC-DiP may enable easy assessment of disease progression patterns and could be used for assessing treatment efficacy.

Longitudinal comparison of the self-entry Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-RSE) and Rasch-Built Overall Amyotrophic Lateral Sclerosis Disability Scale (ROADS) as outcome measures in people with amyotrophic lateral sclerosis

INTRODUCTION/AIMS

Improved functional outcome measures in amyotrophic lateral sclerosis (ALS) would aid ALS trial design and help hasten drug discovery. We evaluate the longitudinal performance of the Rasch-Built Overall Amyotrophic Lateral Sclerosis Disability Scale (ROADS) compared to the Amyotrophic Lateral Sclerosis Functional Rating Scale Revised for Self-Entry (ALSFRS-RSE) as patient reported outcomes of functional status in people with ALS.

METHODS

Participants completed the ROADS and the ALSFRS-RSE questionnaires at baseline, 3-, 6-, and 12- mo using Research Electronic Data Capture as part of a prospective, longitudinal, remote, online survey study of fatigue in ALS from 9/2020 to 12/2021. The scales were compared cross-sectionally (at baseline) and longitudinally. Correlation coefficients, coefficients of variation, and descriptive statistics were assessed.

RESULTS

A total of 182 adults with ALS consented to the study. This volunteer sample was comprised of predominantly White, non-Hispanic, non-smoking participants. Consented participant survey completion was approximately 90% at baseline and greater than 40% at 12 mo. The ALSFRS-RSE and the ROADS had high, significant agreement at 3 and 6 mo by Cohen's kappa ≥71% (p < 0.001); the number of functional increases or plateaus on the two scales were not significantly different; and the coefficient of variation of functional decline was similar at the 6-month mark, though higher for the ROADS at 3 mo and lower at 12 mo.

DISCUSSION

Although the ROADS performed similarly to the ALSFRS-RSE in an observational cohort, it has psychometric advantages, such as Rasch-modeling and unidimensionality. It merits further investigation as a patient reported outcome of overall disability and efficacy outcome measure in ALS trials.

Combination of ciprofloxacin/celecoxib as a novel therapeutic strategy for ALS

OBJECTIVE

This study aimed to evaluate the safety and tolerability of a fixed-dose co-formulation of ciprofloxacin and celecoxib (PrimeC) in patients with amyotrophic lateral sclerosis (ALS), and to examine its effects on disease progression and ALS-related biomarkers.

METHODS

In this proof of concept, open-label, phase IIa study of PrimeC in 15 patients with ALS, participants were administered PrimeC thrice daily for 12 months. The primary endpoints were safety and tolerability. Exploratory endpoints included disease progression outcomes such as forced vital capacity, revised ALS functional rating scale, and effect on algorithm-predicted survival. In addition, indications of a biological effect were assessed by selected biomarker analyses, including TDP-43 and LC3 levels in neuron-derived exosomes (NDEs), and serum neurofilaments.

RESULTS

Four participants experienced adverse events (AEs) related to the study drug. None of these AEs were unexpected, and most were mild or moderate (69%). Additionally, no serious AEs were related to the study drug. One participant tested positive for COVID-19 and recovered without complications, and no other abnormal laboratory investigations were found. Participants' survival compared to their predictions showed no safety concerns. Biomarker analyses demonstrated significant changes associated with PrimeC in neural-derived exosomal TDP-43 levels and levels of LC3, a key autophagy marker.

INTERPRETATION

This study supports the safety and tolerability of PrimeC in ALS. Biomarker analyses suggest early evidence of a biological effect. A placebo-controlled trial is required to disentangle the biomarker results from natural progression and to evaluate the efficacy of PrimeC for the treatment of ALS. Summary for social media if publishedTwitter handles: @NeurosenseT, @ShiranZimri•What is the current knowledge on the topic? ALS is a severe neurodegenerative disease, causing death within 2-5 years from diagnosis. To date there is no effective treatment to halt or significantly delay disease progression.•What question did this study address? This study assessed the safety, tolerability and exploratory efficacy of PrimeC, a fixed dose co-formulation of ciprofloxacin and celecoxib in the ALS population.•What does this study add to our knowledge? This study supports the safety and tolerability of PrimeC in ALS, and exploratory biomarker analyses suggest early insight for disease related-alteration.•How might this potentially impact the practice of neurology? These results set the stage for a larger, placebo-controlled study to examine the efficacy of PrimeC, with the potential to become a new drug candidate for ALS.

Identifying patterns in amyotrophic lateral sclerosis progression from sparse longitudinal data

The clinical presentation of amyotrophic lateral sclerosis (ALS), a fatal neurodegenerative disease, varies widely across patients, making it challenging to determine if potential therapeutics slow progression. We sought to determine whether there were common patterns of disease progression that could aid in the design and analysis of clinical trials. We developed an approach based on a mixture of Gaussian processes to identify clusters of patients sharing similar disease progression patterns, modeling their average trajectories and the variability in each cluster. We show that ALS progression is frequently nonlinear, with periods of stable disease preceded or followed by rapid decline. We also show that our approach can be extended to Alzheimer's and Parkinson's diseases. Our results advance the characterization of disease progression of ALS and provide a flexible modeling approach that can be applied to other progressive diseases.

Deep learning methods to predict amyotrophic lateral sclerosis disease progression

Amyotrophic lateral sclerosis (ALS) is a highly complex and heterogeneous neurodegenerative disease that affects motor neurons. Since life expectancy is relatively low, it is essential to promptly understand the course of the disease to better target the patient’s treatment. Predictive models for disease progression are thus of great interest. One of the most extensive and well-studied open-access data resources for ALS is the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) repository. In 2015, the DREAM-Phil Bowen ALS Prediction Prize4Life Challenge was held on PRO-ACT data, where competitors were asked to develop machine learning algorithms to predict disease progression measured through the slope of the ALSFRS score between 3 and 12 months. However, although it has already been successfully applied in several studies on ALS patients, to the best of our knowledge deep learning approaches still remain unexplored on the ALSFRS slope prediction in PRO-ACT cohort. Here, we investigate how deep learning models perform in predicting ALS progression using the PRO-ACT data. We developed three models based on different architectures that showed comparable or better performance with respect to the state-of-the-art models, thus representing a valid alternative to predict ALS disease progression.

Analysis of routine blood parameters in patients with amyotrophic lateral sclerosis and evaluation of a possible correlation with disease progression—a multicenter study

Objective

Amyotrophic lateral sclerosis (ALS) pathogenesis is still unclear, its course is considerably variable, and prognosis is hard to determine. Despite much research, there is still a lack of easily accessible markers predicting prognosis. We investigated routine blood parameters in ALS patients regarding correlations with disease severity, progression rate, and survival. Additionally, we analyzed disease and patients' characteristics relating to baseline blood parameter levels.

Methods

We analyzed creatine kinase (CK), albumin (ALB), creatinine (CREA), total cholesterol (TC), high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), and triglycerides (TG) levels around time of diagnosis in 1,084 ALS patients. We carried out linear regression analyses including disease and patients' characteristics with each blood parameter to detect correlations with them. Linear regression models were performed for ALSFRS-R at study entry, its retrospectively defined rate of decay and prospectively collected progression rate. Different survival analysis methods were used to examine associations between blood parameters and survival.

Results

We found higher CK (p-value 0.001), ALB (p-value <0.001), CREA (p-value <0.001), and HDL levels (p-value 0.044) at time of diagnosis being associated with better functional status according to ALSFRS-R scores at study entry. Additionally, higher CREA levels were associated with lower risk of death (p-value 0.003).

Conclusions

Our results indicate potential of CK, ALB, CREA, and HDL as disease severity or progression markers, and may also provide clues to ALS pathogenesis. However, these values are highly dependent on other variables, and further careful, longitudinal analyses will be necessary to prove the relevance of our findings.

Motor Neuron Disease Systematic Multi-Arm Adaptive Randomised Trial (MND-SMART): a multi-arm, multi-stage, adaptive, platform, phase III randomised, double-blind, placebo-controlled trial of repurposed drugs in motor neuron disease

INTRODUCTION

Motor neuron disease (MND) is a rapidly fatal neurodegenerative disease. Despite decades of research and clinical trials there remains no cure and only one globally approved drug, riluzole, which prolongs survival by 2-3 months. Recent improved mechanistic understanding of MND heralds a new translational era with many potential targets being identified that are ripe for clinical trials. Motor Neuron Disease Systematic Multi-Arm Adaptive Randomised Trial (MND-SMART) aims to evaluate the efficacy of drugs efficiently and definitively in a multi-arm, multi-stage, adaptive trial. The first two drugs selected for evaluation in MND-SMART are trazodone and memantine.

METHODS AND ANALYSIS

Initially, up to 531 participants (177/arm) will be randomised 1:1:1 to oral liquid trazodone, memantine and placebo. The coprimary outcome measures are the Amyotrophic Lateral Sclerosis Functional Rating Scale Revised (ALSFRS-R) and survival. Comparisons will be conducted in four stages. The decision to continue randomising to arms after each stage will be made by the Trial Steering Committee who receive recommendations from the Independent Data Monitoring Committee. The primary analysis of ALSFRS-R will be conducted when 150 participants/arm, excluding long survivors, have completed 18 months of treatment; if positive the survival effect will be inferentially analysed when 113 deaths have been observed in the placebo group. The trial design ensures that other promising drugs can be added for evaluation in planned trial adaptations. Using this novel trial design reduces time, cost and number of participants required to definitively (phase III) evaluate drugs and reduces exposure of participants to potentially ineffective treatments.

ETHICS AND DISSEMINATION

MND-SMART was approved by the West of Scotland Research Ethics Committee on 2 October 2019. (REC reference: 19/WS/0123) Results of the study will be submitted for publication in a peer-reviewed journal and a summary provided to participants.

TRIAL REGISTRATION NUMBERS

European Clinical Trials Registry (2019-000099-41); NCT04302870.

Considerations for Amyotrophic Lateral Sclerosis (ALS) Clinical Trial Design

Thoughtful clinical trial design is critical for efficient therapeutic development, particularly in the field of amyotrophic lateral sclerosis (ALS), where trials often aim to detect modest treatment effects among a population with heterogeneous disease progression. Appropriate outcome measure selection is necessary for trials to provide decisive and informative results. Investigators must consider the outcome measure's reliability, responsiveness to detect change when change has actually occurred, clinical relevance, and psychometric performance. ALS clinical trials can also be performed more efficiently by utilizing statistical enrichment techniques. Innovations in ALS prediction models allow for selection of participants with less heterogeneity in disease progression rates without requiring a lead-in period, or participants can be stratified according to predicted progression. Statistical enrichment can reduce the needed sample size and improve study power, but investigators must find a balance between optimizing statistical efficiency and retaining generalizability of study findings to the broader ALS population. Additional progress is still needed for biomarker development and validation to confirm target engagement in ALS treatment trials. Selection of an appropriate biofluid biomarker depends on the treatment mechanism of interest, and biomarker studies should be incorporated into early phase trials. Inclusion of patients with ALS as advisors and advocates can strengthen clinical trial design and study retention, but more engagement efforts are needed to improve diversity and equity in ALS research studies. Another challenge for ALS therapeutic development is identifying ways to respect patient autonomy and improve access to experimental treatment, something that is strongly desired by many patients with ALS and ALS advocacy organizations. Expanded access programs that run concurrently to well-designed and adequately powered randomized controlled trials may provide an opportunity to broaden access to promising therapeutics without compromising scientific integrity or rushing regulatory approval of therapies without adequate proof of efficacy.

Identifying and predicting amyotrophic lateral sclerosis clinical subgroups: a population-based machine-learning study

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is known to represent a collection of overlapping syndromes. Various classification systems based on empirical observations have been proposed, but it is unclear to what extent they reflect ALS population substructures. We aimed to use machine-learning techniques to identify the number and nature of ALS subtypes to obtain a better understanding of this heterogeneity, enhance our understanding of the disease, and improve clinical care.

METHODS

In this retrospective study, we applied unsupervised Uniform Manifold Approximation and Projection [UMAP]) modelling, semi-supervised (neural network UMAP) modelling, and supervised (ensemble learning based on LightGBM) modelling to a population-based discovery cohort of patients who were diagnosed with ALS while living in the Piedmont and Valle d'Aosta regions of Italy, for whom detailed clinical data, such as age at symptom onset, were available. We excluded patients with missing Revised ALS Functional Rating Scale (ALSFRS-R) feature values from the unsupervised and semi-supervised steps. We replicated our findings in an independent population-based cohort of patients who were diagnosed with ALS while living in the Emilia Romagna region of Italy.

FINDINGS

Between Jan 1, 1995, and Dec 31, 2015, 2858 patients were entered in the discovery cohort. After excluding 497 (17%) patients with missing ALSFRS-R feature values, data for 42 clinical features across 2361 (83%) patients were available for the unsupervised and semi-supervised analysis. We found that semi-supervised machine learning produced the optimum clustering of the patients with ALS. These clusters roughly corresponded to the six clinical subtypes defined by the Chiò classification system (ie, bulbar, respiratory, flail arm, classical, pyramidal, and flail leg ALS). Between Jan 1, 2009, and March 1, 2018, 1097 patients were entered in the replication cohort. After excluding 108 (10%) patients with missing ALSFRS-R feature values, data for 42 clinical features across 989 patients were available for the unsupervised and semi-supervised analysis. All 1097 patients were included in the supervised analysis. The same clusters were identified in the replication cohort. By contrast, other ALS classification schemes, such as the El Escorial categories, Milano-Torino clinical staging, and King's clinical stages, did not adequately label the clusters. Supervised learning identified 11 clinical parameters that predicted ALS clinical subtypes with high accuracy (area under the curve 0·982 [95% CI 0·980-0·983]).

INTERPRETATION

Our data-driven study provides insight into the ALS population substructure and confirms that the Chiò classification system successfully identifies ALS subtypes. Additional validation is required to determine the accuracy and clinical use of these algorithms in assigning clinical subtypes. Nevertheless, our algorithms offer a broad insight into the clinical heterogeneity of ALS and help to determine the actual subtypes of disease that exist within this fatal neurodegenerative syndrome. The systematic identification of ALS subtypes will improve clinical care and clinical trial design.

FUNDING

US National Institute on Aging, US National Institutes of Health, Italian Ministry of Health, European Commission, University of Torino Rita Levi Montalcini Department of Neurosciences, Emilia Romagna Regional Health Authority, and Italian Ministry of Education, University, and Research.

TRANSLATIONS

For the Italian and German translations of the abstract see Supplementary Materials section.

Body composition in amyotrophic lateral sclerosis subjects and its effect on disease progression and survival

BACKGROUND

Motor neuron degeneration and malnutrition alter body composition in amyotrophic lateral sclerosis (ALS). Resulting losses of weight, fat mass (FM), and fat-free mass (FFM) shorten survival. Nutritional management relies on body weight or BMI; neither reliably indicates malnutrition nor differentiates body compartments.

OBJECTIVES

We aimed to 1) develop an equation to compute FM and FFM using clinical data, validated against DXA; and 2) examine the effect of computed FM and FFM on disease course and survival.

METHODS

We studied 364 ALS patients from 3 cohorts. In Cohort #1 we used logistic regression on clinical and demographic data to create an equation (test cohort). In Cohort #2 we validated FM and FFM computed using this equation against DXA (validation cohort). In Cohort #3, we examined the effect of computed body composition on disease course and survival.

RESULTS

In Cohort #1 (n = 29) the model incorporated sex, age, BMI, and bulbar-onset to create an equation to estimate body fat: % body fat = 1.73 - [19.80*gender (1 if male or 0 if female)] + [0.25*weight (kg)] + [0.95*BMI (kg/m2)] - (5.20*1 if bulbar-onset or *0 if limb-onset). In Cohort #2 (n = 104), body composition using this equation, compared to other published equations, showed the least variance from DXA values. In Cohort #3 (n = 314), loss of body composition over 6 mo was greater in males. Adjusted survival was predicted by low baseline FM (HR: 1.39; 95% CI: 1.07, 1.80), and loss of FM (HR: 1.87; 95% CI: 1.30, 2.69) and FFM (HR: 1.73; 95% CI: 1.20, 2.49) over 6 mo.

CONCLUSIONS

Our equation broadens the traditional nutritional evaluation in clinics and reliably estimates body composition. Measuring body composition could target FM as a focus for nutritional management to ensure adequate energy intake and complement measures, such as the ALS functional rating scale-revised score and forced vital capacity, currently used.

Predicting dysphagia onset in patients with ALS: the ALS dysphagia risk score

Purpose: For patients diagnosed with ALS, dysphagia can result in aspiration, malnutrition, and mortality. The purpose of this study was to develop a clinical prediction model capable of identifying patients with ALS at imminent risk for developing swallowing complications. Methods: A retrospective cohort study using the Pooled Resource Open-Access ALS Clinical Trials Database (PRO-ACT) was conducted. After dividing the PRO-ACT database into development and validation cohorts with dysphagia defined from the ALS Functional Rating Scale (ALSFRS), a multivariable Cox proportional hazards regression model estimated the probability of dysphagia at 3, 6, and 12-months with subsequent evaluation of model discrimination and calibration. Results: With 2057 participants in the development cohort and 1891 in the validation cohort, the Cox model included 7 clinical variables: spinal-onset; bulbar, fine and gross motor ALSFRS subscale scores; respiratory impairment; functional progression rate; and time from diagnosis. The cumulative incidence of dysphagia was 18% at 3-months, 29% at 6-months, and 45% at 12-months. The mean predicted probability of dysphagia development ranged from 4.5% in the bottommost risk decile to 40% in the topmost decile at 3 months, 10%-72% at 6 months, and 25%-93% at 12 months. In the validation cohort, the model had good discrimination and calibration with an optimism corrected c-statistic of 0.70 and calibration slope of 0.96. Conclusions: The ALS dysphagia risk score can be used to identify patients with ALS at high risk for self-reported dysphagia development who would benefit from a comprehensive swallowing assessment and proactive dysphagia management strategies.

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.

Causal associations of genetic factors with clinical progression in amyotrophic lateral sclerosis

BACKGROUND AND OBJECTIVE

Recent advances in the genetic causes of ALS reveals that about 10% of ALS patients have a genetic origin and that more than 30 genes are likely to contribute to this disease. However, four genes are more frequently associated with ALS: C9ORF72, TARDBP, SOD1, and FUS. The relationship between genetic factors and ALS progression rate is not clear. In this study, we carried out a causal analysis of ALS disease with a genetics perspective in order to assess the contribution of the four mentioned genes to the progression rate of ALS.

METHODS

In this work, we applied a novel causal learning model to the CRESLA dataset which is a longitudinal clinical dataset of ALS patients including genetic information of such patients. This study aims to discover the relationship between four mentioned genes and ALS progression rate from a causation perspective using machine learning and probabilistic methods.

RESULTS

The results indicate a meaningful association between genetic factors and ALS progression rate with causality viewpoint. Our findings revealed that causal relationships between ALSFRS-R items associated with bulbar regions have the strongest association with genetic factors, especially C9ORF72; and other three genes have the greatest contribution to the respiratory ALSFRS-R items with a causation point of view.

CONCLUSIONS

The findings revealed that genetic factors have a significant causal effect on the rate of ALS progression. Since C9ORF72 patients have higher proportion compared to those carrying other three gene mutations in the CRESLA cohort, we need a large multi-centric study to better analyze SOD1, TARDBP and FUS contribution to the ALS clinical progression. We conclude that causal associations between ALSFRS-R clinical factors is a suitable predictor for designing a prognostic model of ALS.

Cx43 hemichannels contribute to astrocyte-mediated toxicity in sporadic and familial ALS

Our results demonstrate that connexin 43 hemichannels are the conduits for amyotrophic lateral sclerosis (ALS) astrocyte-mediated motor neuron toxicity and disease spread, acting as a common mechanism that can target both familial ALS and sporadic ALS populations. Furthermore, our present work provides proof of principle that tonabersat, as a drug already studied in clinical trials for other indications, could serve as a potential ALS therapeutic.

Connexin 43 (Cx43) gap junctions and hemichannels mediate astrocyte intercellular communication in the central nervous system under normal conditions and contribute to astrocyte-mediated neurotoxicity in amyotrophic lateral sclerosis (ALS). Here, we show that astrocyte-specific knockout of Cx43 in a mouse model of ALS slows disease progression both spatially and temporally, provides motor neuron (MN) protection, and improves survival. In addition, Cx43 expression is up-regulated in human postmortem tissue and cerebrospinal fluid from ALS patients. Using human induced pluripotent stem cell–derived astrocytes (hiPSC-A) from both familial and sporadic ALS, we establish that Cx43 is up-regulated and that Cx43-hemichannels are enriched at the astrocyte membrane. We also demonstrate that the pharmacological blockade of Cx43-hemichannels in ALS astrocytes using GAP 19, a mimetic peptide blocker, and tonabersat, a clinically tested small molecule, provides neuroprotection of hiPSC-MN and reduces ALS astrocyte-mediated neuronal hyperexcitability. Extending the in vitro application of tonabersat with chronic administration to SOD1^G93A mice results in MN protection with a reduction in reactive astrocytosis and microgliosis. Taking these data together, our studies identify Cx43 hemichannels as conduits of astrocyte-mediated disease progression and a pharmacological target for disease-modifying ALS therapies.

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.

Qualitative measures that assess functional disability and quality of life in ALS

BACKGROUND

Selection of appropriate trial endpoints and outcome measures is particularly important in rare disease and rapidly progressing disease such as amyotrophic lateral sclerosis (ALS) where the challenges to conducting clinical trials, are substantial: patient and disease heterogeneity, limited understanding of exact disease pathophysiology, and lack of robust and available biomarkers. To address these challenges in ALS, the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised version (ALSFRS-R) was developed and has become a key primary endpoint in ALS clinical trials to assess functional disability and disease progression, often replacing survival as a primary outcome. However, increased understanding of the ALS disease journey and improvements in assistive technology for ALS patients have exposed issues with the ALSFRS-R, including non-linearity, multidimensionality and floor and ceiling effects that could challenge its continued utility as a primary outcome measure in ALS clinical trials. Recently, other qualitative scale measures of functioning disability have been developed to help address these issues. With this in mind, we conducted a literature search aimed at identifying both established and promising new measures for potential use in clinical trials.

METHODS

We searched PubMed, Google, Google Scholar, and the reference sections of key studies to identify papers that discussed qualitative measures of functional status for potential use in ALS studies. We also searched clinicaltrials.gov to identify functional status and health-related quality of life (HRQoL) measures that have been used in ALS interventional studies.

RESULTS

In addition to the ALSFRS-R, we identified several newer qualitative scales including ALSFRS-EX, ALS-MITOS, CNS-BFS, DALS-15, MND-DS, and ROADS. Strengths and limitations of each measure were identified and discussed, along with their potential to act as a primary or secondary outcome to assess patient functional status in ALS clinical trials.

CONCLUSION

This paper serves as a reference guide for researchers deciding which qualitative measures to use as endpoints in their ALS clinical trials to assess functional status. This paper also discusses the importance of including ALS HRQoL and ALS cognitive screens in future clinical trials to assess the value of a new ALS therapy more comprehensively.

Can Innovative Trial Designs in Orphan Diseases Drive Advancement of Treatments for Common Neurological Diseases?

Global regulatory agencies have transformed their approach to approvals in their processes for formal review of the safety and efficacy of new drugs. Opportunities for innovation have expanded because of the COVID-19 pandemic. Several regulatory-led initiatives have progressed rapidly during the past year including patient-focused drug development, model-informed drug development, Real World Evidence, and complex innovative trial designs. Collectively, these initiatives have accelerated the rate of approvals. Despite demands to focus on urgent needs imposed by the COVID-19 pandemic, the number of new drug approvals over the past year, particularly for rare diseases, has outpaced expectations. Advancing therapeutics for nervous system disorders requires adaptive strategies that align with rapid developments in the field. Three relentlessly progressive diseases, Amyotrophic Lateral Sclerosis (ALS), Duchenne Muscular Dystrophy (DMD), and Parkinson's disease are in urgent need of new treatments. Herein, we propose new regulatory initiatives including innovative trial designs and patient-focused drug development that accelerate clinical trial conduct while meeting critical regulatory requirements for therapeutic approval.

OUP accepted manuscript

The routine clinical integration of individualized objective markers of disease activity in those diagnosed with the neurodegenerative disorder amyotrophic lateral sclerosis is a key requirement for therapeutic development. A large, multicentre, clinic-based, longitudinal cohort was used to systematically appraise the leading candidate biofluid biomarkers in the stratification and potential therapeutic assessment of those with amyotrophic lateral sclerosis. Incident patients diagnosed with amyotrophic lateral sclerosis (n = 258), other neurological diseases (n = 80) and healthy control participants (n = 101), were recruited and followed at intervals of 3–6 months for up to 30 months. Cerebrospinal fluid neurofilament light chain and chitotriosidase 1 and blood neurofilament light chain, creatine kinase, ferritin, complement C3 and C4 and C-reactive protein were measured. Blood neurofilament light chain, creatine kinase, serum ferritin, C3 and cerebrospinal fluid neurofilament light chain and chitotriosidase 1 were all significantly elevated in amyotrophic lateral sclerosis patients. First-visit plasma neurofilament light chain level was additionally strongly associated with survival (hazard ratio for one standard deviation increase in log₁₀ plasma neurofilament light chain 2.99, 95% confidence interval 1.65–5.41, P = 0.016) and rate of disability progression, independent of other prognostic factors. A small increase in level was noted within the first 12 months after reported symptom onset (slope 0.031 log₁₀ units per month, 95% confidence interval 0.012–0.049, P = 0.006). Modelling the inclusion of plasma neurofilament light chain as a therapeutic trial outcome measure demonstrated that a significant reduction in sample size and earlier detection of disease-slowing is possible, compared with using the revised Amyotrophic Lateral Sclerosis Functional Rating Scale. This study provides strong evidence that blood neurofilament light chain levels outperform conventional measures of disease activity at the group level. The application of blood neurofilament light chain has the potential to radically reduce the duration and cost of therapeutic trials. It might also offer a first step towards the goal of more personalized objective disease activity monitoring for those living with amyotrophic lateral sclerosis.

Plasma Uric Acid Helps Predict Cognitive Impairment in Patients With Amyotrophic Lateral Sclerosis

Objective: Uric acid as an antioxidant plays an important role in neurodegenerative disease. Our objective is to investigate the relationship between plasma uric acid and cognitive impairment in patients with amyotrophic lateral sclerosis (ALS).

Methods: In this cross-sectional study, 124 ALS patients were screened by the Edinburgh Cognitive and Behavioral Screen (ECAS) and classified according to the revised Strong's criteria. Additionally, based on total ECAS cut-off score patients were categorized into those with cognitive impairment (ALS-cie) and those without cognitive impairment (ALS-ncie), and clinical data and uric acid level were compared between the two groups. Parameters with significant differences were further included in a multivariate linear regression analysis with ECAS score as a dependent variable. Hold-out validation was performed to evaluate the fitness of regression model.

Results: Up to 60% of ALS patients showed cognitive or/and behavioral impairment. The ALS-cie group had lower education level (p < 0.001), older age at symptom onset (p = 0.001), older age at testing (p = 0.001), and lower plasma uric acid (p = 0.01). Multivariate analysis showed increased uric acid (β = 0.214, p = 0.01), lower age at testing (β = −0.378, p < 0.001), and higher education level (β = 0.424, p < 0.001) could predict higher ECAS score (F = 19.104, R² = 0.381, p < 0.0001). Validation analysis showed that predicted ECAS score was significantly correlated with raw ECAS score in both the training set (rs = 0.621, p < 0.001) and the testing set (rs = 0.666, p < 0.001).

Conclusions: Cognitive impairment was a common feature in our Chinese ALS patients. Plasma uric acid might help evaluate the risk of cognitive impairment in ALS patients when combined with education level and age at testing.