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Vasta R, Koumantakis E, Canosa A, Manera U, Grassano M, Palumbo F, Cabras S, Matteoni E, Di Pede F, De Mattei F, Vergnano F, Mandrioli J, Simonini C, Martinelli I, De Marchi F, Mazzini L, Moglia C, Calvo A, Chiò A. Phosphatemia is an Independent Prognostic Factor in Amyotrophic Lateral Sclerosis. Ann Neurol 2025. [PMID: 40285624 DOI: 10.1002/ana.27252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2024] [Revised: 04/07/2025] [Accepted: 04/10/2025] [Indexed: 04/29/2025]
Abstract
OBJECTIVE The objective of this study was to evaluate the prognostic value of several muscle damage biomarkers. METHODS Data from Piemonte and Valle d'Aosta Amyotrophic Lateral Sclerosis (PARALS) were considered for this study. Survival was defined as the time from diagnosis to death, tracheostomy, or the censoring date. Blood levels of potassium, creatinine, creatine kinase, phosphorus, aspartate aminotransferase (AST) and alanine aminotransferase (ALT) diagnosis were evaluated as potential prognostic biomarkers. A Cox model was developed for each biomarker and adjusted for sex, onset age, onset site, and diagnostic delay. Significant findings from PARALS were evaluated in the Pooled Resource Open-Access Amyotrophic Lateral Sclerosis Clinical Trials (PRO-ACT) database. Additionally, a joint model was constructed to evaluate the prognostic role of phosphatemia slope over time using longitudinal data from PRO-ACT. RESULTS A total of 1,444 and 1,023 patients were included in the PARALS and PRO-ACT cohorts, respectively. Only creatinine (hazard ratio [HR] = 0.65, 95% confidence interval [CI] = 0.50-0.85) and phosphorus (HR = 1.14, 95% CI = 1.04-1.24) showed a significant association with survival in the PARALS cohort. These findings were further validated in the PRO-ACT cohort (creatinine HR = 0.21, 95% CI = 0.13-0.35, p < 0.0001; phosphorus HR = 2.35, 95% CI = 1.13-4.88, p = 0.02). Longitudinal data from the PRO-ACT database showed that an increase of 0.1 mmol/l per month in phosphate levels was also associated with a HR of 8.26 (95% CI = 1.07-96.6, p = 0.044). INTERPRETATION Creatininemia was confirmed as a prognostic marker in amyotrophic lateral sclerosis (ALS). Additionally, both phosphatemia levels at diagnosis and its rate of change over time were identified as a potential prognostic marker for ALS. As with other blood biomarkers, phosphate levels are cost-effective and minimally invasive to measure, supporting their potential use in clinical trials. ANN NEUROL 2025.
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Affiliation(s)
- Rosario Vasta
- ALS Center, Department of Neuroscience "Rita Levi Montalcini", University of Turin, Turin, Italy
| | - Emanuele Koumantakis
- Department of Public Health and Pediatrics, University of Turin, Turin, Italy
- Department of Clinical and Biological Sciences, University of Turin, Turin, Italy
| | - Antonio Canosa
- ALS Center, Department of Neuroscience "Rita Levi Montalcini", University of Turin, Turin, Italy
- Neurology 1, AOU Città Della Salute e Della Scienza di Torino, Turin, Italy
- National Research Council, Institute of Cognitive Science and Technologies, Rome, Italy
| | - Umberto Manera
- ALS Center, Department of Neuroscience "Rita Levi Montalcini", University of Turin, Turin, Italy
- Neurology 1, AOU Città Della Salute e Della Scienza di Torino, Turin, Italy
| | - Maurizio Grassano
- ALS Center, Department of Neuroscience "Rita Levi Montalcini", University of Turin, Turin, Italy
| | - Francesca Palumbo
- ALS Center, Department of Neuroscience "Rita Levi Montalcini", University of Turin, Turin, Italy
| | - Sara Cabras
- ALS Center, Department of Neuroscience "Rita Levi Montalcini", University of Turin, Turin, Italy
- School of Advanced Studies, Center for Neuroscience, University of Camerino, Camerino, Italy
| | - Enrico Matteoni
- ALS Center, Department of Neuroscience "Rita Levi Montalcini", University of Turin, Turin, Italy
| | - Francesca Di Pede
- ALS Center, Department of Neuroscience "Rita Levi Montalcini", University of Turin, Turin, Italy
| | - Filippo De Mattei
- ALS Center, Department of Neuroscience "Rita Levi Montalcini", University of Turin, Turin, Italy
| | - Filippo Vergnano
- ALS Center, Department of Neuroscience "Rita Levi Montalcini", University of Turin, Turin, Italy
| | - Jessica Mandrioli
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
- Department of Neurosciences, Azienda Ospedaliero-Universitaria Di Modena, Modena, Italy
| | - Cecilia Simonini
- Department of Neurosciences, Azienda Ospedaliero-Universitaria Di Modena, Modena, Italy
| | - Ilaria Martinelli
- Department of Neurosciences, Azienda Ospedaliero-Universitaria Di Modena, Modena, Italy
| | - Fabiola De Marchi
- ALS Center, Department of Neurology, Azienda Ospedaliero Universitaria Maggiore Della Carità, University of Piemonte Orientale, Novara, Italy
| | - Letizia Mazzini
- ALS Center, Department of Neurology, Azienda Ospedaliero Universitaria Maggiore Della Carità, University of Piemonte Orientale, Novara, Italy
| | - Cristina Moglia
- ALS Center, Department of Neuroscience "Rita Levi Montalcini", University of Turin, Turin, Italy
- Neurology 1, AOU Città Della Salute e Della Scienza di Torino, Turin, Italy
| | - Andrea Calvo
- ALS Center, Department of Neuroscience "Rita Levi Montalcini", University of Turin, Turin, Italy
- Neurology 1, AOU Città Della Salute e Della Scienza di Torino, Turin, Italy
| | - Adriano Chiò
- ALS Center, Department of Neuroscience "Rita Levi Montalcini", University of Turin, Turin, Italy
- Neurology 1, AOU Città Della Salute e Della Scienza di Torino, Turin, Italy
- National Research Council, Institute of Cognitive Science and Technologies, Rome, Italy
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Wu H, Erenay FS, Özaltın OY, Dalgıç ÖO, Sır MY, He QM, Crum BA, Pasupathy KS. Prognostic factors affecting ALS progression through disease tollgates. J Neurol 2024; 272:69. [PMID: 39680215 DOI: 10.1007/s00415-024-12819-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 09/11/2024] [Accepted: 09/28/2024] [Indexed: 12/17/2024]
Abstract
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.
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Affiliation(s)
- Haoran Wu
- School of Business, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - F Safa Erenay
- Department of Management Sciences and Engineering, University of Waterloo, Waterloo, ON, Canada
| | - Osman Y Özaltın
- E.P. Fitts Department of Industrial & Systems Engineering, NC State University, Raleigh, NC, USA
| | | | - Mustafa Y Sır
- Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Rochester, USA
| | - Qi-Ming He
- Department of Management Sciences and Engineering, University of Waterloo, Waterloo, ON, Canada
| | - Brian A Crum
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
| | - Kalyan S Pasupathy
- Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Rochester, USA
- Biomedical & Health Information Sciences, University of Illinois at Chicago, Chicago, IL, USA
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Kuan LH, Parnianpour P, Kushol R, Kumar N, Anand T, Kalra S, Greiner R. Accurate personalized survival prediction for amyotrophic lateral sclerosis patients. Sci Rep 2023; 13:20713. [PMID: 38001260 PMCID: PMC10673879 DOI: 10.1038/s41598-023-47935-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 11/20/2023] [Indexed: 11/26/2023] Open
Abstract
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.
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Affiliation(s)
- Li-Hao Kuan
- Department of Computing Science, University of Alberta, Edmonton, Canada.
| | - Pedram Parnianpour
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada
| | - Rafsanjany Kushol
- Department of Computing Science, University of Alberta, Edmonton, Canada
| | - Neeraj Kumar
- Alberta Machine Intelligence Institute, Edmonton, Alberta, Canada
| | - Tanushka Anand
- Division of Neurology, Department of Medicine, University of Alberta, Edmonton, Canada
| | - Sanjay Kalra
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada
- Division of Neurology, Department of Medicine, University of Alberta, Edmonton, Canada
| | - Russell Greiner
- Department of Computing Science, University of Alberta, Edmonton, Canada
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada
- Alberta Machine Intelligence Institute, Edmonton, Alberta, Canada
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Milella G, Introna A, Mezzapesa DM, D'Errico E, Fraddosio A, Ucci M, Zoccolella S, Simone IL. Clinical Profiles and Patterns of Neurodegeneration in Amyotrophic Lateral Sclerosis: A Cluster-Based Approach Based on MR Imaging Metrics. AJNR Am J Neuroradiol 2023; 44:403-409. [PMID: 36958798 PMCID: PMC10084907 DOI: 10.3174/ajnr.a7823] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 02/20/2023] [Indexed: 03/25/2023]
Abstract
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.
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Affiliation(s)
- G Milella
- From the Neurology Unit (G.M., A.I., D.M.M., E.D., A.F., M.U., I.L.S.), Department of Basic Medical Sciences, Neurosciences and Sense Organs, University of Bari "Aldo Moro," Bari, Italy
| | - A Introna
- From the Neurology Unit (G.M., A.I., D.M.M., E.D., A.F., M.U., I.L.S.), Department of Basic Medical Sciences, Neurosciences and Sense Organs, University of Bari "Aldo Moro," Bari, Italy
| | - D M Mezzapesa
- From the Neurology Unit (G.M., A.I., D.M.M., E.D., A.F., M.U., I.L.S.), Department of Basic Medical Sciences, Neurosciences and Sense Organs, University of Bari "Aldo Moro," Bari, Italy
| | - E D'Errico
- From the Neurology Unit (G.M., A.I., D.M.M., E.D., A.F., M.U., I.L.S.), Department of Basic Medical Sciences, Neurosciences and Sense Organs, University of Bari "Aldo Moro," Bari, Italy
| | - A Fraddosio
- From the Neurology Unit (G.M., A.I., D.M.M., E.D., A.F., M.U., I.L.S.), Department of Basic Medical Sciences, Neurosciences and Sense Organs, University of Bari "Aldo Moro," Bari, Italy
| | - M Ucci
- From the Neurology Unit (G.M., A.I., D.M.M., E.D., A.F., M.U., I.L.S.), Department of Basic Medical Sciences, Neurosciences and Sense Organs, University of Bari "Aldo Moro," Bari, Italy
| | - S Zoccolella
- Azienda Sanitaria Locale Bari (S.Z.), San Paolo Hospital, Bari, Italy
| | - I L Simone
- From the Neurology Unit (G.M., A.I., D.M.M., E.D., A.F., M.U., I.L.S.), Department of Basic Medical Sciences, Neurosciences and Sense Organs, University of Bari "Aldo Moro," Bari, Italy
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Dawson B, McConvey K, Gofton TE. When to initiate palliative care in neurology. HANDBOOK OF CLINICAL NEUROLOGY 2022; 190:105-125. [PMID: 36055710 DOI: 10.1016/b978-0-323-85029-2.00011-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
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?
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Affiliation(s)
- Benjamin Dawson
- Department of Clinical Neurologic Sciences, Western University, London, ON, Canada
| | - Kayla McConvey
- Department of Clinical Neurologic Sciences, Western University, London, ON, Canada
| | - Teneille E Gofton
- Department of Clinical Neurologic Sciences, Western University, London, ON, Canada.
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