Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Describing complex disease progression using joint latent class models
  for multivariate longitudinal markers and clinical endpoints   Neurodegenerative diseases are characterized by numerous markers of
progression and clinical endpoints. For instance, Multiple System Atrophy
(MSA), a rare neurodegenerative synucleinopathy, is characterized by various
combinations of progressive autonomic failure and motor dysfunction, and a very
poor prognosis. Describing the progression of such complex and
multi-dimensional diseases is particularly difficult. One has to simultaneously
account for the assessment of multivariate markers over time, the occurrence of
clinical endpoints, and a highly suspected heterogeneity between patients. Yet,
such description is crucial for understanding the natural history of the
disease, staging patients diagnosed with the disease, unraveling subphenotypes,
and predicting the prognosis. Through the example of MSA progression, we show
how a latent class approach can help describe complex disease progression
measured by multiple repeated markers and clinical endpoints, and identify
subphenotypes for exploring new pathological hypotheses. The joint latent class
model includes class-specific multivariate mixed models to handle multivariate
repeated biomarkers possibly summarized into latent dimensions and
class-and-cause-specific proportional hazard models to handle time-to-event
data. Maximum likelihood estimation is made available in the lcmm R package. In
the French MSA cohort comprising data of 598 patients during up to 13 years,
five subphenotypes of MSA were identified that differ by the sequence and shape
of biomarkers degradation, and the associated risk of death. In posterior
analyses, the five subphenotypes were used to explore the association between
clinical progression and external imaging and fluid biomarkers, while properly
accounting for the uncertainty in the subphenotypes membership.

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The categories of this paper are: math
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The categories of this paper are: eess
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The categories of this paper are: solv-int
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The categories of this paper are: cmp-lg
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The categories of this paper are: chao-dyn
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The categories of this paper are: alg-geom
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The categories of this paper are: hep-lat
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The categories of this paper are: math-ph
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The categories of this paper are: quant-ph
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The categories of this paper are: ao-sci
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The categories of this paper are: acc-phys
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The categories of this paper are: astro-ph
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The categories of this paper are: adap-org
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The categories of this paper are: patt-sol
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The categories of this paper are: q-bio
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The categories of this paper are: supr-con