King's college progression rate at first clinical evaluation: A new measure of disease progression in amyotrophic lateral sclerosis

Prognostic factors affecting ALS progression through disease tollgates

BACKGROUND AND OBJECTIVES

Understanding factors affecting the timing of critical clinical events in ALS progression.

METHODS

We captured ALS progression based on the timing of critical events (tollgates), by augmenting 6366 patients' data from the PRO-ACT database with tollgate-passed information using classification. Time trajectories of passing ALS tollgates after the first visit were derived using Kaplan-Meier analyses. The significant prognostic factors were found using log-rank tests. Decision-tree-based classifications identified significant ALS phenotypes characterized by the list of body segments involved at the first visit.

RESULTS

Standard (e.g., gender and onset type) and tollgate-related (phenotype and initial tollgate level) prognostic factors affect the timing of ALS tollgates. For instance, by the third year after the first visit, 80-100% of bulbar-onset patients vs. 43-48% of limb-onset patients, and 65-73% of females vs. 42-49% of males lost the ability to talk and started using a feeding tube. Compared to the standard factors, tollgate-related factors had a stronger effect on ALS progression. The initial impairment level significantly impacted subsequent ALS progression in a segment while affected segment combinations further characterized progression speed. For instance, patients with normal speech (Tollgate Level 0) at the first visit had less than a 10% likelihood of losing speech within a year, while for patients with Tollgate Level 1 (affected speech), this likelihood varied between 23 and 53% based on additional segment (leg) involvement.

CONCLUSIONS

Tollgate- and phenotype-related factors have a strong effect on the timing of ALS tollgates. All factors should be jointly considered to better characterize patient groups with different progression aggressiveness.

Accurate personalized survival prediction for amyotrophic lateral sclerosis patients

Amyotrophic Lateral Sclerosis (ALS) is a rapidly progressive neurodegenerative disease. Accurately predicting the survival time for ALS patients can help patients and clinicians to plan for future treatment and care. We describe the application of a machine-learned tool that incorporates clinical features and cortical thickness from brain magnetic resonance (MR) images to estimate the time until a composite respiratory failure event for ALS patients, and presents the prediction as individual survival distributions (ISDs). These ISDs provide the probability of survival (none of the respiratory failures) at multiple future time points, for each individual patient. Our learner considers several survival prediction models, and selects the best model to provide predictions. We evaluate our learned model using the mean absolute error margin (MAE-margin), a modified version of mean absolute error that handles data with censored outcomes. We show that our tool can provide helpful information for patients and clinicians in planning future treatment.

Clinical Profiles and Patterns of Neurodegeneration in Amyotrophic Lateral Sclerosis: A Cluster-Based Approach Based on MR Imaging Metrics

BACKGROUND AND PURPOSE

The previous studies described phenotype-associated imaging findings in amyotrophic lateral sclerosis (ALS) with a prior categorization of patients based on clinical characteristics. We investigated the natural segregation of patients through a radiologic cluster-based approach without a priori patient categorization using 3 well-known prognostic MR imaging biomarkers in ALS, namely bilateral precentral and paracentral gyrus cortical thickness and medulla oblongata volume. We aimed to identify clinical/prognostic features that are cluster-associated.

MATERIALS AND METHODS

Bilateral precentral and paracentral gyri and medulla oblongata volume were calculated using FreeSurfer in 90 patients with amyotrophic lateral sclerosis and 25 healthy controls. A 2-step cluster analysis was performed using precentral and paracentral gyri (averaged pair-wise) and medulla oblongata volume.

RESULTS

We identified 3 radiologic clusters: 28 (31%) patients belonged to "cluster-1"; 51 (57%), to "cluster 2"; and 11 (12%), to "cluster 3." Patients in cluster 1 showed statistically significant cortical thinning of the analyzed cortical areas and lower medulla oblongata volume compared with subjects in cluster 2 and cluster 3, respectively. Patients in cluster 3 exhibited significant cortical thinning of both paracentral and precentral gyri versus those in cluster 2, and this latter cluster showed lower medulla oblongata volume than cluster 3. Patients in cluster 1 were characterized by older age, higher female prevalence, greater disease severity, higher progression rate, and lower survival compared with patients in clusters 2 and 3.

CONCLUSIONS

Patients with amyotrophic lateral sclerosis spontaneously segregate according to age and sex-specific patterns of neurodegeneration. Some patients with amyotrophic lateral sclerosis showed an early higher impairment of cortical motor neurons with relative sparing of bulbar motor neurons (cluster 3), while others expressed an opposite pattern (cluster 2). Moreover, 31% of patients showed an early simultaneous impairment of cortical and bulbar motor neurons (cluster 1), and they were characterized by higher disease severity and lower survival.

When to initiate palliative care in neurology

Life-limiting and life-threatening neurologic conditions often progress slowly. Patients live with a substantial symptom burden over a long period of time, and there is often a high degree of functional and cognitive impairment. Because of this, the most appropriate time to initiate neuropalliative care is often difficult to identify. Further challenges to the incorporation of neuropalliative care include communication barriers, such as profound dysarthria or language impairments, and loss of cognitive function and decision-making capacity that prevent shared decision making and threaten patient autonomy. As a result, earlier initiation of at least some components of palliative care is paramount to ensuring patient-centered care while the patient is still able to communicate effectively and participate as fully as possible in their medical care. For these reasons, neuropalliative care is also distinct from palliative care in oncology, and there is a growing evidence base to guide timely initiation and integration of neuropalliative care. In this chapter, we will focus on when to initiate palliative care in patients with life-limiting, life-threatening, and advanced neurologic conditions. We will address three main questions, which patients with neurologic conditions will benefit from initiation of palliative care, what aspects of neurologic illness are most amenable to neuropalliative care, and when to initiate neuropalliative care?