Background: Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease with variable clinical progression. While median survival is 2–4 years, 5–15% of individuals survive for longer. Methods: We conducted a retrospective, observational study using a population-based ALS register in Lombardy, Italy, to identify the clinical characteristics of long-term ALS survivors (≥10 years). Incident cases included in two periods (1998–2002 and 2008–2012) were considered. Results: A total of 828 ALS cases were included. Median survival for the entire cohort was 2.2 years (IQR 1.1–4.4). However, long-term survival was observed in 7% of individuals at 10 years, and 3% at 15 years. Long-survivors had a median survival of 13.4 years, significantly longer than the 1.9 years of non-long-survivors (IQR 1.0–3.6). Long-survivors were younger at disease onset and diagnosis, had longer diagnostic delay, and were more likely to have had a spinal onset. The cohort also showed a higher proportion of males among long-term survivors (75% vs. 59%). No significant difference in survival was observed between the two examined periods. Conclusions: Our findings suggest that long-term ALS survival is likely influenced by a complex interplay of clinical, genetic, and environmental factors, along with the intrinsic rate of motor neuron degeneration.

In this study, we explore the feasibility and efficacy of leveraging Sanbot Elf – a humanoid intelligent assistive robot – integrated with artificial intelligence (AI), specifically the Vivaldi AI system, for functional assessment in amyotrophic lateral sclerosis (ALS) patients. Our investigation involves evaluating and comparing the performance of the Sanbot Elf in administering the ALS Functional Rating Scale–Revised (ALSFRS-R) to that of human operators, using a structured format where patients respond with either “yes” or “no” answers. This approach is intentionally adopted to minimize ambiguity in patient responses. Patients were given the option to respond either verbally or by utilizing the touchscreen display, particularly beneficial for those experiencing dysarthria or hypophonia. In addition, we examined patient emotional responses to this novel approach. A cohort of 28 ALS patients participated in the study, with a subset undergoing longitudinal follow-up assessments. Our results demonstrate strong agreement between human and robotic administrations of the ALSFRS-R, indicating the potential for AI-enabled robotics to accurately assess ALS functional status. Furthermore, the patients’ feedback underscores their acceptability of this technology as a supportive tool in healthcare settings. Our findings also highlight the potential benefits of employing robotic devices with algorithmic capabilities, such as the binary tree method, in hospitals. Moreover, such integration has the potential to alleviate operators’ workload. Importantly, this research contributes to the burgeoning field of AI-enabled healthcare operations, highlighting the promising role of robotic systems in enhancing functional assessment and management of ALS.

Introduction/Aims: Study of clinical milestones, particularly intermediate events like loss of ambulation, in large amyotrophic lateral sclerosis (ALS) cohorts is limited. Here, we leverage the ALS Natural History Consortium dataset to evaluate the time‐to‐event for several outcomes and prognostic factors that predict risk. Methods: Longitudinal data from 1950 participants were used in time‐to‐event analyses based on time from diagnosis. Outcomes were gastrostomy, loss of ambulation, loss of useful speech, non‐invasive ventilation (NIV) usage, and death equivalent (death or mechanical ventilation). Median times‐to‐event were calculated along with Kaplan–Meier curves. Cox proportional hazards models for each outcome estimated (through adjusted hazard ratios [HR]) the impact of several prognostic factors, including sex, region of onset, age at diagnosis, and the initial rate of change (delta‐FRS) in ALS Functional Rating Scale‐Revised (ALSFRS‐R) scores. Results: Estimated median times‐to‐event for clinical outcomes ranged from 1.44 to 6.21 years, with a median time to death equivalent of 2.12 years. A higher delta‐FRS was the greatest risk factor for all outcomes (HRs between 2.01 and 3.05). Limb onset decreased risk of loss of speech, NIV use, gastrostomy, and death equivalent (HRs 0.41–0.78). Older age at diagnosis increased risk of gastrostomy, NIV use, and death equivalent (HRs 1.08–1.27). Discussion: These findings further inform expectations of time to various outcomes, especially rarely investigated intermediate events, and their risk factors. The importance of progression rate supports other recent findings, highlighting delta‐FRS as a key prognostic factor with potential utility in clinical trial designs.

Tofersen is a gene-targeted therapy for superoxide dismutase 1 (SOD1)-associated amyotrophic lateral sclerosis (ALS), but neurofilament light chain (NfL) may not fully capture the biological response to treatment. We performed a multicentre retrospective longitudinal study including 24 patients with SOD1-ALS treated with intrathecal tofersen at four Italian referral centres between 2022 and 2025. Cerebrospinal fluid (CSF) and serum biomarkers were assessed at baseline, month 3, month 6, and last available administration using single-molecule array assays to quantify NfL, glial fibrillary acidic protein (GFAP), ubiquitin C-terminal hydrolase L1 (UCHL-1), and total tau. NfL decreased after treatment initiation in both CSF and serum, providing the clearest pharmacodynamic signal. In contrast, CSF GFAP increased progressively over follow-up, while CSF total tau and UCHL-1 rose mainly at later timepoints; serum GFAP, total tau, and UCHL-1 also showed increases during follow-up. ALS Functional Rating Scale-Revised trajectories were broadly stable, whereas disease progression rate was lower at last follow-up than at baseline. Greater reductions in CSF NfL were observed in pathogenic versus uncertain SOD1 variants, and early serum NfL and UCHL-1 changes were associated with longer-term changes in disease progression. These findings suggest that longitudinal multi-analyte profiling may refine biological response stratification beyond NfL alone in tofersen-treated SOD1-ALS.