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  4. Vector autoregression: Useful in rare diseases? Predicting organ response patterns in a rare case of secondary AA amyloidosis
 
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2023
Journal Article
Title

Vector autoregression: Useful in rare diseases? Predicting organ response patterns in a rare case of secondary AA amyloidosis

Abstract
Background: Statistical analyses of clinical data are a cornerstone in understanding pathomechanisms of disorders. In rare disorders, cross-sectional datasets of sufficient size are usually not available. Taking AA amyloidosis as an example of a life-threatening rare disorder resulting from of uncontrolled chronic inflammation, we propose techniques from time series analysis to predict organ response to treatment. The advantage of time-series analysis is that it solely relies on temporal variation and therefore allows analyzing organ response to treatment even when the cross-sectional dimension is small.
Methods: The joint temporal interdependence of inflammatory activity and organ response was modelled multivariately using vector autoregression (VAR) based on a unique 4.5 year spanning data set of routine laboratory, imaging data (e.g., 18F-Florbetaben-PET/CT) and functional investigations of a 68-year-old patient with multi-organ involvement of AA amyloidosis due to ongoing inflammatory activity of a malignant paraganglioma in stable disease for >20 years and excellent response to tocilizumab). Results: VAR analysis showed that alterations in inflammatory activity forecasted alkaline phosphatase (AP). AP levels, but not inflammatory activity at the previous measurement time point predicted proteinuria. Conclusion: We demonstrate the feasibility and value of time series analysis for obtaining clinically reliable information when the rarity of a disease prevents conventional prognostic modelling approaches. We illustrate the comparative utility of blood, functional and imaging markers to monitor the development and regression of AA amyloidosis.
Author(s)
Ihne-Schubert, Sandra M.
Universitätsklinikum Würzburg, Interdisziplinäres Amyloidosezentrum Nordbayern
Kircher, Malte
Universität Augsburg, Medizinische Fakultät
Werner, Rudolf A.
Universitätsklinikum Würzburg, Abteilung für Nuklearmedizin
Lapa, Constantin
Universität Augsburg, Medizinische Fakultät
Einsele, Hermann
Universitätsklinikum Würzburg, Interdisziplinäres Amyloidosezentrum Nordbayern
Geier, Andreas
Universitätsklinikum Würzburg, Interdisziplinäres Amyloidosezentrum Nordbayern
Schubert, Torben  orcid-logo
Fraunhofer-Institut für System- und Innovationsforschung ISI  
Journal
PLoS one. Online journal  
Open Access
DOI
10.1371/journal.pone.0289921
10.24406/publica-1805
File(s)
Vector_autoregression_Useful_in_rare_diseases.pdf (1.36 MB)
Rights
CC BY 4.0: Creative Commons Attribution
Language
English
Fraunhofer-Institut für System- und Innovationsforschung ISI  
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