Alexander Sherman

Safety and efficacy of ceftriaxone for amyotrophic lateral sclerosis: A multi-stage, randomised, double-blind, placebo-controlled trial

BACKGROUND Glutamate excitotoxicity might contribute to the pathophysiology of amyotrophic lateral sclerosis. In animal models, decreased excitatory aminoacid transporter 2 (EAAT2) overexpression delays disease onset and prolongs survival, and ceftriaxone increases EAAT2 activity. We aimed to assess the safety and efficacy of ceftriaxone for amyotrophic lateral sclerosis in a combined phase 1, 2, and 3 clinical trial. METHODS This three-stage randomised, double-blind, placebo-controlled study was done at 59 clinical sites in the USA and Canada between Sept 4, 2006, and July 30, 2012. Eligible adult patients had amyotrophic lateral sclerosis, a vital capacity of more than 60% of that predicted for age and height, and symptom duration of less than 3 years. In stages 1 (pharmacokinetics) and 2 (safety), participants were randomly allocated (2:1) to ceftriaxone (2 g or 4 g per day) or placebo. In stage 3 (efficacy), participants assigned to ceftriaxone in stage 2 received 4 g ceftriaxone, participants assigned to placebo in stage 2 received placebo, and new participants were randomly assigned (2:1) to 4 g ceftriaxone or placebo. Participants, family members, and site staff were masked to treatment assignment. Randomisation was done by a computerised randomisation sequence with permuted blocks of 3. Participants received 2 g ceftriaxone or placebo twice daily through a central venous catheter administered at home by a trained caregiver. To minimise biliary side-effects, participants assigned to ceftriaxone also received 300 mg ursodeoxycholic acid twice daily and those assigned to placebo received matched placebo capsules. The coprimary efficacy outcomes were survival and functional decline, measured as the slope of Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R) scores. Analyses were by intention to treat. This study is registered with ClinicalTrials.gov, number NCT00349622. FINDINGS Stage 3 included 66 participants from stages 1 and 2 and 448 new participants. In total, 340 participants were randomly allocated to ceftriaxone and 173 to placebo. During stages 1 and 2, mean ALSFRS-R declined more slowly in participants who received 4 g ceftriaxone than in those on placebo (difference 0·51 units per month, 95% CI 0·02 to 1·00; p=0·0416), but in stage 3 functional decline between the treatment groups did not differ (0·09, -0·06 to 0·24; p=0·2370). No significant differences in survival between the groups were recorded in stage 3 (HR 0·90, 95% CI 0·71 to 1·15; p=0·4146). Gastrointestinal adverse events and hepatobiliary adverse events were more common in the ceftriaxone group than in the placebo group (gastrointestinal, 245 of 340 [72%] ceftriaxone vs 97 of 173 [56%] placebo, p=0·0004; hepatobiliary, 211 [62%] vs 19 [11%], p<0·0001). Significantly more participants who received ceftriaxone had serious hepatobiliary serious adverse events (41 participants [12%]) than did those who received placebo (0 participants). INTERPRETATION Despite promising stage 2 data, stage 3 of this trial of ceftriaxone in amyotrophic lateral sclerosis did not show clinical efficacy. The adaptive design allowed for seamless transition from one phase to another, and central venous catheter use in the home setting was shown to be feasible. FUNDING National Institute of Neurological Disorders and Stroke.

Crowdsourced analysis of clinical trial data to predict amyotrophic lateral sclerosis progression

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with substantial heterogeneity in its clinical presentation. This makes diagnosis and effective treatment difficult, so better tools for estimating disease progression are needed. Here, we report results from the DREAM-Phil Bowen ALS Prediction Prize4Life challenge. In this crowdsourcing competition, competitors developed algorithms for the prediction of disease progression of 1,822 ALS patients from standardized, anonymized phase 2/3 clinical trials. The two best algorithms outperformed a method designed by the challenge organizers as well as predictions by ALS clinicians. We estimate that using both winning algorithms in future trial designs could reduce the required number of patients by at least 20%. The DREAM-Phil Bowen ALS Prediction Prize4Life challenge also identified several potential nonstandard predictors of disease progression including uric acid, creatinine and surprisingly, blood pressure, shedding light on ALS pathobiology. This analysis reveals the potential of a crowdsourcing competition that uses clinical trial data for accelerating ALS research and development.

Roadmap and standard operating procedures for biobanking and discovery of neurochemical markers in ALS

Abstract Despite major advances in deciphering the neuropathological hallmarks of amyotrophic lateral sclerosis (ALS), validated neurochemical biomarkers for monitoring disease activity, earlier diagnosis, defining prognosis and unlocking key pathophysiological pathways are lacking. Although several candidate biomarkers exist, translation into clinical application is hindered by small sample numbers, especially longitudinal, for independent verification. This review considers the potential routes to the discovery of neurochemical markers in ALS, and provides a consensus statement on standard operating procedures that will facilitate multicenter collaboration, validation and ultimately clinical translation.

The PRO-ACT database Design, initial analyses, and predictive features

Objective: To pool data from completed amyotrophic lateral sclerosis (ALS) clinical trials and create an open-access resource that enables greater understanding of the phenotype and biology of ALS. Methods: Clinical trials data were pooled from 16 completed phase II/III ALS clinical trials and one observational study. Over 8 million de-identified longitudinally collected data points from over 8,600 individuals with ALS were standardized across trials and merged to create the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) database. This database includes demographics, family histories, and longitudinal clinical and laboratory data. Mixed effects models were used to describe the rate of disease progression measured by the Revised ALS Functional Rating Scale (ALSFRS-R) and vital capacity (VC). Cox regression models were used to describe survival data. Implementing Bonferroni correction, the critical p value for 15 different tests was p = 0.003. Results: The ALSFRS-R rate of decline was 1.02 (±2.3) points per month and the VC rate of decline was 2.24% of predicted (±6.9) per month. Higher levels of uric acid at trial entry were predictive of a slower drop in ALSFRS-R (p = 0.01) and VC (p < 0.0001), and longer survival (p = 0.02). Higher levels of creatinine at baseline were predictive of a slower drop in ALSFRS-R (p = 0.01) and VC (p < 0.0001), and longer survival (p = 0.01). Finally, higher body mass index (BMI) at baseline was associated with longer survival (p < 0.0001). Conclusion: The PRO-ACT database is the largest publicly available repository of merged ALS clinical trials data. We report that baseline levels of creatinine and uric acid, as well as baseline BMI, are strong predictors of disease progression and survival.

Being PRO-ACTive: What can a Clinical Trial Database Reveal About ALS?

Advancing research and clinical care, and conducting successful and cost-effective clinical trials requires characterizing a given patient population. To gather a sufficiently large cohort of patients in rare diseases such as amyotrophic lateral sclerosis (ALS), we developed the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) platform. The PRO-ACT database currently consists of >8600 ALS patient records from 17 completed clinical trials, and more trials are being incorporated. The database was launched in an open-access mode in December 2012; since then, >400 researchers from >40 countries have requested the data. This review gives an overview on the research enabled by this resource, through several examples of research already carried out with the goal of improving patient care and understanding the disease. These examples include predicting ALS progression, the simulation of future ALS clinical trials, the verification of previously proposed predictive features, the discovery of novel predictors of ALS progression and survival, the newly identified stratification of patients based on their disease progression profiles, and the development of tools for better clinical trial recruitment and monitoring. Results from these approaches clearly demonstrate the value of large datasets for developing a better understanding of ALS natural history, prognostic factors, patient stratification, and more. The increasing use by the community suggests that further analyses of the PRO-ACT database will continue to reveal more information about this disease that has for so long defied our understanding.

Infrastructure resources for clinical research in amyotrophic lateral sclerosis

Abstract Clinical trial networks, shared clinical databases, and human biospecimen repositories are examples of infrastructure resources aimed at enhancing and expediting clinical and/or patient oriented research to uncover the etiology and pathogenesis of amyotrophic lateral sclerosis (ALS), a rapidly progressive neurodegenerative disease that leads to the paralysis of voluntary muscles. The current status of such infrastructure resources, as well as opportunities and impediments, were discussed at the second Tarrytown ALS meeting held in September 2011. The discussion focused on resources developed and maintained by ALS clinics and centers in North America and Europe, various clinical trial networks, U.S. government federal agencies including the National Institutes of Health (NIH), the Agency for Toxic Substances and Disease Registry (ATSDR) and the Centers for Disease Control and Prevention (CDC), and several voluntary disease organizations that support ALS research activities. Key recommendations included 1) the establishment of shared databases among individual ALS clinics to enhance the coordination of resources and data analyses; 2) the expansion of quality-controlled human biospecimen banks; and 3) the adoption of uniform data standards, such as the recently developed Common Data Elements (CDEs) for ALS clinical research. The value of clinical trial networks such as the Northeast ALS (NEALS) Consortium and the Western ALS (WALS) Consortium was recognized, and strategies to further enhance and complement these networks and their research resources were discussed.

Urate Levels Predict Survival in ALS: Analysis of the Expanded PRO-ACT Database

Introduction: Urate has been identified as a predictor of amyotrophic lateral sclerosis (ALS) survival in some but not all studies. Here we leverage the recent expansion of the Pooled Resource Open‐Access ALS Clinical Trials (PRO‐ACT) database to study the association between urate levels and ALS survival. Methods: Pooled data of 1,736 ALS participants from the PRO‐ACT database were analyzed. Cox proportional hazards regression models were used to evaluate associations between urate levels at trial entry and survival. Results: After adjustment for potential confounders (i.e., creatinine and body mass index), there was an 11% reduction in risk of reaching a survival endpoint during the study with each 1‐mg/dL increase in uric acid levels (adjusted hazard ratio 0.89, 95% confidence interval 0.82–0.97, P < 0.01). Discussion: Our pooled analysis provides further support for urate as a prognostic factor for survival in ALS and confirms the utility of the PRO‐ACT database as a powerful resource for ALS epidemiological research. Muscle Nerve 57: 430–434, 2018