Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Oct:108:105323.
doi: 10.1016/j.ebiom.2024.105323. Epub 2024 Sep 12.

Prognostic clinical and biological markers for amyotrophic lateral sclerosis disease progression: validation and implications for clinical trial design and analysis

Michael Benatar  1 , Eric A Macklin  2 , Andrea Malaspina  3 , Mary-Louise Rogers  4 , Eran Hornstein  5 , Vittoria Lombardi  3 , Danielle Renfrey  4 , Stephanie Shepheard  4 , Iddo Magen  5 , Yahel Cohen  5 , Volkan Granit  6 , Jeffrey M Statland  7 , Jeannine M Heckmann  8 , Rosa Rademakers  9 , Caroline A McHutchison  10 , Leonard Petrucelli  11 , Corey T McMillan  12 , Joanne Wuu  13 ; CReATe Consortium PGB1 Study Investigators
Collaborators, Affiliations

Prognostic clinical and biological markers for amyotrophic lateral sclerosis disease progression: validation and implications for clinical trial design and analysis

Michael Benatar et al. EBioMedicine. 2024 Oct.

Abstract

Background: With increasing recognition of the value of incorporating prognostic markers into amyotrophic lateral sclerosis (ALS) trial design and analysis plans, there is a pressing need to understand which among the prevailing clinical and biochemical markers have real value, and how they can be optimally used.

Methods: A subset of patients with ALS recruited through the multi-center Phenotype-Genotype-Biomarker study (clinicaltrials.gov: NCT02327845) was identified as "trial-like" based on meeting common trial eligibility criteria. Clinical phenotyping was performed by evaluators trained in relevant assessments. Serum neurofilament light (NfL) and phosphorylated neurofilament heavy (pNfH), urinary p75ECD, plasma microRNA-181, and an array of biochemical and clinical measures were evaluated for their prognostic value. Associations with functional progression were estimated by random-slopes mixed models of ALS functional rating scale-revised (ALSFRS-R) score. Associations with survival were estimated by log-rank test and Cox proportional hazards regression. Potential sample size savings from adjusting for given biomarkers in a hypothetical trial were estimated.

Findings: Baseline serum NfL is a powerful prognostic biomarker, predicting survival and ALSFRS-R rate of decline. Serum NfL <40 pg/mL and >100 pg/mL correspond to future ALSFRS-R slopes of ∼0.5 and ∼1.5 points/month, respectively. Serum NfL also adds value to the best available clinical predictors, encapsulated by the European Network to Cure ALS (ENCALS) predictor score. In models of functional decline, the addition of NfL yields ∼25% sample size saving above those achieved by inclusion of either clinical predictors or ENCALS score alone. The prognostic value of serum pNfH, urinary p75ECD, and plasma miR-181ab is more limited.

Interpretation: Among the multitude of biomarkers considered, only blood NfL adds value to the ENCALS prediction model and should be incorporated into analysis plans for all ongoing and future ALS trials. Defined thresholds of NfL might also be used in trial design, for enrichment or stratified randomisation, to improve trial efficiency.

Funding: NIH (U01-NS107027, U54-NS092091). ALSA (16-TACL-242).

Keywords: ALS clinical trials; Context-of-use; Neurofilament; Prognostic biomarkers.

PubMed Disclaimer

Conflict of interest statement

Declaration of interests MB reports grants from the NIH (U01NS107027, U54NS092091) and the ALS Association (16-TACL-242) in support of this work. He is also an unpaid member of the Board of Trustees for the ALS Association. He has served as a consultant to Alector, Alexion, Annexon, Arrowhead, Biogen, Cartesian, Denali, Eli Lilly, Horizon, Immunovant, Novartis, Roche, Sanofi, Takeda, UCB, and UniQure. EAM reports grants from the NIH (U01NS107027, U54NS092091). He also serves as a consultant to Annexon, Biogen, Bial Biotech, Cortexyme, Chase Therapeutics, Enterin, nQ Medical, Partner Therapeutics, Stoparkinson Healthcare, and UCB. He has served on DSMBs for NeuroSense Therapeutics, Novartis, and Sanofi. AM reports grants from the NIH (U01NS107027). He has also provided consulting services to Roche, Pfizer, and Accure Therapeutics. MLR reports support from grants from the NIH (U01NS107027, U54NS092091) and FightMND. EH has nothing to declare. VL has nothing to declare. DR has nothing to declare. SS has nothing to declare. IM has nothing to declare. YC has nothing to declare. VG currently is an employee of Biohaven Pharmaceutical Inc. JS receives research funding from the NIH < MDA, FSHD Society, Friends of FSH Research, and FSHD Canada. He also serves as a consultant or on scientific advisory boards for Avidity, Fulcrum, Dyne, Armatus, Epic Bio, Roche, Lupin, and Entrada. JH has nothing to declare. RR reports grants from the NIH (U54NS092091) in support of this work. She is also an unpaid member of the Medical Advisory Board of the Association for Frontotemporal Dementias (AFTD) and a paid member of the Scientific Advisory Board of the Kissick Family Foundation FTD Grant Program. CAM reports funding from the ALS Association and the NIH (U54NS092091). LP reports support from the Mayo Clinic Foundation and grants from the National Institute on Aging (5P30AG0062677, U19AG063911) the National Institute of Neurological Disorders and Stroke (U54NS123743, R35NS097273, P01NS084974) and Target ALS Foundation. CM reports grants from the NIH (AG066597, AG076411, AG066152, AG072979, NS109260, NS092091), Department of Defense, and support from the Penn Institute on Aging, Decrane Family PPA Fund, and Newhouse Fund.2. JW reports funding from the NIH (U01NS107027, U54NS092091) and the ALS Association (16-TACL-242) in support of this work. The CReATe Consortium (U54NS092091) is part of the NIH Rare Diseases Clinical Research Network (RDCRN), an initiative of the Office of Rare Diseases Research (ORDR), NCATS. This Consortium is funded through a collaboration between NCATS and the NINDS. This work was also supported by a Clinical Trial Readiness grant (U01NS107027) from NINDS and by a grant from the ALS Association to support the CReATe Biorepository (grant ID 16-TACL-242).

Figures

Fig. 1
Fig. 1
ALSFRS-R slope and its relationship to baseline NfL. (a) Random slopes model of ALSFRS-R over time, with errors bars showing 95% confidence intervals (CI). Faint grey dotted line illustrates the linear estimate of change in ALSFRS-R over time. (b) Relationship between baseline serum NfL (measured in duplicate) and future rate of progression of the ALSFRS-R (Spearman correlation coefficient = −0.57, 95% CI −0.66 to −0.47, p < 0.0001) among n = 203 study participants. The straight orange line shows the linear prediction. The bent blue line represents a partial-linear spline with knots chosen post-hoc at 40 and 100 pg/mL. The smooth green curve is a smoothing spline through the empirical Bayes slope estimates.
Fig. 2
Fig. 2
Longitudinal biomarker trajectories. Longitudinal trajectories of (a) serum NfL; (b) serum pNfH; and (c) urinary p75ECD. Y-axis shows percent change in each biomarker compared to baseline, plotted on a log scale. The faint grey dotted line illustrates the linear estimate of biomarker change over time. Error bars represent 95% confidence intervals (CI), widened at later time points due to participant attrition over time and fewer biomarker data available. NfL and pNfH were measured in duplicate; p75ECD quantified with a median of 3 replicates. Single NfL and pNfH values from the 18-month visit of a single participant have been excluded (see footnote to Table 3 for detailed explanation).
Fig. 3
Fig. 3
Kaplan–Meier survival curves. Permanent assisted ventilation (PAV)- and tracheostomy-free survival for (a) the ENCALS predictor score, divided into quartiles; (b) ΔFRS, divided into quartiles; (c) baseline serum NfL, divided into quartiles; and (d) baseline plasma miR-181ab dichotomised at the median value of 24,590 UMI. The range of values for each clinical or biological marker within a defined quartile, as well as the number of observations at each time point, are shown below each KM plot. Shading represents pointwise log–log confidence intervals.
See this image and copyright information in PMC

Update of

References

    1. Benatar M., Boylan K., Jeromin A., et al. ALS biomarkers for therapy development: state of the field and future directions. Muscle Nerve. 2016;53(2):169–182. - PMC - PubMed
    1. Witzel S., Frauhammer F., Steinacker P., et al. Neurofilament light and heterogeneity of disease progression in amyotrophic lateral sclerosis: development and validation of a prediction model to improve interventional trials. Transl Neurodegener. 2021;10(1):31. - PMC - PubMed
    1. Westeneng H.J., Debray T.P.A., Visser A.E., et al. Prognosis for patients with amyotrophic lateral sclerosis: development and validation of a personalised prediction model. Lancet Neurol. 2018;17(5):423–433. - PubMed
    1. Benatar M., Zhang L., Wang L., et al. Validation of serum neurofilaments as prognostic and potential pharmacodynamic biomarkers for ALS. Neurology. 2020;95(1):e59–e69. - PMC - PubMed
    1. Miller T.M., Cudkowicz M.E., Genge A., et al. Trial of antisense oligonucleotide tofersen for SOD1 ALS. N Engl J Med. 2022;387(12):1099–1110. - PubMed

Associated data