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Updated: May 21, 2026
10:46
A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Likelihood-based modeling of covariate-specific time-dependent receiver operating characteristic curves
Ainesh Sewak1, Vanda Inácio2, Joanne Wuu3
1Department of Clinical Research, Universität Bern, Bern, Switzerland.
Statistical Methods in Medical Research
|May 20, 2026
Summary
A new framework improves prognostic biomarker accuracy in amyotrophic lateral sclerosis (ALS) by accounting for patient differences over time. This aids in better disease prognosis and clinical trial design for ALS treatments.
Area of Science:
- Biostatistics
- Neurology
- Biomarker Discovery
Background:
- Prognostic biomarker accuracy is crucial for disease management but challenged by patient heterogeneity in observational studies.
- Factors like age, onset site, and genetics in amyotrophic lateral sclerosis (ALS) affect survival and biomarker levels, complicating prognostic assessment.
- Existing time-dependent methods for censored outcomes often lack covariate adjustment, limiting their applicability.
Purpose of the Study:
- To introduce the nonparanormal prognostic biomarker (NPB) framework for modeling joint biomarker and event time distributions.
- To enable estimation of covariate-specific time-dependent receiver operating characteristic (tdROC) curves and summary measures.
- To evaluate serum neurofilament light as a prognostic biomarker in ALS using the NPB framework.
Main Methods:
- Developed the nonparanormal prognostic biomarker (NPB) framework to jointly model biomarker levels and event times.
- Incorporated covariate adjustment within the modeling framework to account for patient heterogeneity.
- Applied the NPB framework to analyze time-dependent prognostic accuracy of serum neurofilament light in ALS patients.
Main Results:
- The NPB framework successfully models the joint distribution of biomarkers and event times, adjusting for covariates.
- Prognostic accuracy of serum neurofilament light in ALS was shown to vary significantly over time and across patient subgroups.
- Demonstrated the ability to estimate covariate-specific tdROC curves, revealing nuanced prognostic performance.
Conclusions:
- The NPB framework provides a robust method for evaluating prognostic biomarkers in the presence of covariates and time-dependent effects.
- This approach enhances risk stratification accuracy for conditions like ALS.
- The NPB framework can inform and improve the design of clinical trials for neurodegenerative diseases.
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