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

peer-reviewed
Erstveröffentlichung
2021-08-26Authors
Witzel, Simon
Frauhammer, Felix
Steinacker, Petra
Devos, David
Pradat, Pierre‑François
Wissenschaftlicher Artikel
Published in
Translational Neurodegeneration ; 10 (2021). - Art.-Nr. 31. - eISSN 2047-9158
Link to original publication
https://dx.doi.org/10.1186/s40035-021-00257-yInstitutions
UKU. Klinik für NeurologieExternal cooperations
Universität HeidelbergUniversité de Lille
Sorbonne Université
Hôpital Universitaire Pitié-Salpêtrière
Deutsches Zentrum für Neurodegenerative Erkrankungen
Document version
published version (publisher's PDF)Abstract
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.
Project uulm
Efficacy, Safety and Tolerability of High Lipid and Calorie Supplementation in Amyotrophic Lateral Sclerosis / Universität Ulm / NCT02306590
Publication funding
Open-Access-Förderung durch die Medizinische Fakultät der Universität Ulm
Is supplemented by
https://translationalneurodegeneration.biomedcentral.com/articles/10.1186/s40035-021-00257-y#Sec16Subject headings
[GND]: Myatrophische Lateralsklerose | Neurofilament[MeSH]: Amyotrophic lateral sclerosis | Intermediate filaments
[Free subject headings]: Neurofilament light | Prediction model | Disease progression | Statistical power
[DDC subject group]: DDC 610 / Medicine & health
Metadata
Show full item recordDOI & citation
Please use this identifier to cite or link to this item: http://dx.doi.org/10.18725/OPARU-42020
Witzel, Simon et al. (2022): Neurofilament light and heterogeneity of disease progression in amyotrophic lateral sclerosis: development and validation
of a prediction model to improve interventional trials. Open Access Repositorium der Universität Ulm und Technischen Hochschule Ulm. http://dx.doi.org/10.18725/OPARU-42020
Citation formatter >