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Neurofilament light and heterogeneity of disease progression in amyotrophic lateral sclerosis: development and validation of a prediction model to improve interventional trials

BACKGROUND: Interventional trials in amyotrophic lateral sclerosis (ALS) suffer from the heterogeneity of the disease as it considerably reduces statistical power. We asked if blood neurofilament light chains (NfL) could be used to anticipate disease progression and increase trial power. METHODS: In...

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Autores principales: Witzel, Simon, Frauhammer, Felix, Steinacker, Petra, Devos, David, Pradat, Pierre-François, Meininger, Vincent, Halbgebauer, Steffen, Oeckl, Patrick, Schuster, Joachim, Anders, Simon, Dorst, Johannes, Otto, Markus, Ludolph, Albert C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8390195/
https://www.ncbi.nlm.nih.gov/pubmed/34433481
http://dx.doi.org/10.1186/s40035-021-00257-y
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author Witzel, Simon
Frauhammer, Felix
Steinacker, Petra
Devos, David
Pradat, Pierre-François
Meininger, Vincent
Halbgebauer, Steffen
Oeckl, Patrick
Schuster, Joachim
Anders, Simon
Dorst, Johannes
Otto, Markus
Ludolph, Albert C.
author_facet Witzel, Simon
Frauhammer, Felix
Steinacker, Petra
Devos, David
Pradat, Pierre-François
Meininger, Vincent
Halbgebauer, Steffen
Oeckl, Patrick
Schuster, Joachim
Anders, Simon
Dorst, Johannes
Otto, Markus
Ludolph, Albert C.
author_sort Witzel, Simon
collection PubMed
description BACKGROUND: Interventional trials in amyotrophic lateral sclerosis (ALS) suffer from the heterogeneity of the disease as it considerably reduces statistical power. We asked if blood neurofilament light chains (NfL) could be used to anticipate disease progression and increase trial power. METHODS: In 125 patients with ALS from three independent prospective studies—one observational study and two interventional trials—we developed and externally validated a multivariate linear model for predicting disease progression, measured by the monthly decrease of the ALS Functional Rating Scale Revised (ALSFRS-R) score. We trained the prediction model in the observational study and tested the predictive value of the following parameters assessed at diagnosis: NfL levels, sex, age, site of onset, body mass index, disease duration, ALSFRS-R score, and monthly ALSFRS-R score decrease since disease onset. We then applied the resulting model in the other two study cohorts to assess the actual utility for interventional trials. We analyzed the impact on trial power in mixed-effects models and compared the performance of the NfL model with two currently used predictive approaches, which anticipate disease progression using the ALSFRS-R decrease during a three-month observational period (lead-in) or since disease onset (ΔFRS). RESULTS: Among the parameters provided, the NfL levels (P < 0.001) and the interaction with site of onset (P < 0.01) contributed significantly to the prediction, forming a robust NfL prediction model (R = 0.67). Model application in the trial cohorts confirmed its applicability and revealed superiority over lead-in and ΔFRS-based approaches. The NfL model improved statistical power by 61% and 22% (95% confidence intervals: 54%–66%, 7%–29%). CONCLUSION: The use of the NfL-based prediction model to compensate for clinical heterogeneity in ALS could significantly increase the trial power. NCT00868166, registered March 23, 2009; NCT02306590, registered December 2, 2014. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40035-021-00257-y.
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spelling pubmed-83901952021-08-27 Neurofilament light and heterogeneity of disease progression in amyotrophic lateral sclerosis: development and validation of a prediction model to improve interventional trials Witzel, Simon Frauhammer, Felix Steinacker, Petra Devos, David Pradat, Pierre-François Meininger, Vincent Halbgebauer, Steffen Oeckl, Patrick Schuster, Joachim Anders, Simon Dorst, Johannes Otto, Markus Ludolph, Albert C. Transl Neurodegener Research BACKGROUND: Interventional trials in amyotrophic lateral sclerosis (ALS) suffer from the heterogeneity of the disease as it considerably reduces statistical power. We asked if blood neurofilament light chains (NfL) could be used to anticipate disease progression and increase trial power. METHODS: In 125 patients with ALS from three independent prospective studies—one observational study and two interventional trials—we developed and externally validated a multivariate linear model for predicting disease progression, measured by the monthly decrease of the ALS Functional Rating Scale Revised (ALSFRS-R) score. We trained the prediction model in the observational study and tested the predictive value of the following parameters assessed at diagnosis: NfL levels, sex, age, site of onset, body mass index, disease duration, ALSFRS-R score, and monthly ALSFRS-R score decrease since disease onset. We then applied the resulting model in the other two study cohorts to assess the actual utility for interventional trials. We analyzed the impact on trial power in mixed-effects models and compared the performance of the NfL model with two currently used predictive approaches, which anticipate disease progression using the ALSFRS-R decrease during a three-month observational period (lead-in) or since disease onset (ΔFRS). RESULTS: Among the parameters provided, the NfL levels (P < 0.001) and the interaction with site of onset (P < 0.01) contributed significantly to the prediction, forming a robust NfL prediction model (R = 0.67). Model application in the trial cohorts confirmed its applicability and revealed superiority over lead-in and ΔFRS-based approaches. The NfL model improved statistical power by 61% and 22% (95% confidence intervals: 54%–66%, 7%–29%). CONCLUSION: The use of the NfL-based prediction model to compensate for clinical heterogeneity in ALS could significantly increase the trial power. NCT00868166, registered March 23, 2009; NCT02306590, registered December 2, 2014. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40035-021-00257-y. BioMed Central 2021-08-26 /pmc/articles/PMC8390195/ /pubmed/34433481 http://dx.doi.org/10.1186/s40035-021-00257-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Witzel, Simon
Frauhammer, Felix
Steinacker, Petra
Devos, David
Pradat, Pierre-François
Meininger, Vincent
Halbgebauer, Steffen
Oeckl, Patrick
Schuster, Joachim
Anders, Simon
Dorst, Johannes
Otto, Markus
Ludolph, Albert C.
Neurofilament light and heterogeneity of disease progression in amyotrophic lateral sclerosis: development and validation of a prediction model to improve interventional trials
title Neurofilament light and heterogeneity of disease progression in amyotrophic lateral sclerosis: development and validation of a prediction model to improve interventional trials
title_full Neurofilament light and heterogeneity of disease progression in amyotrophic lateral sclerosis: development and validation of a prediction model to improve interventional trials
title_fullStr Neurofilament light and heterogeneity of disease progression in amyotrophic lateral sclerosis: development and validation of a prediction model to improve interventional trials
title_full_unstemmed Neurofilament light and heterogeneity of disease progression in amyotrophic lateral sclerosis: development and validation of a prediction model to improve interventional trials
title_short Neurofilament light and heterogeneity of disease progression in amyotrophic lateral sclerosis: development and validation of a prediction model to improve interventional trials
title_sort neurofilament light and heterogeneity of disease progression in amyotrophic lateral sclerosis: development and validation of a prediction model to improve interventional trials
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8390195/
https://www.ncbi.nlm.nih.gov/pubmed/34433481
http://dx.doi.org/10.1186/s40035-021-00257-y
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