Literature DB >> 31438056

A Dashboard for Latent Class Trajectory Modeling: Application in Rheumatoid Arthritis.

Beatrice Amico1, Arianna Dagliati2,3, Darren Plant4, Anne Barton4,5, Niels Peek2,5, Nophar Geifman2.   

Abstract

A key trend in current medical research is a shift from a one-size-fit-all to precision treatment strategies, where the focus is on identifying narrow subgroups of the population that would benefit from a given intervention. Precision medicine will greatly benefit from accessible tools that clinicians can use to identify such subgroups, and to generate novel inferences about the patient population they are treating. We present a novel dashboard app that enables clinician users to explore patient subgroups with varying longitudinal treatment response, using latent class mixed modeling. The dashboard was developed in R Shiny. We present results of our approach applied to an observational study of patients with moderate to severe rheumatoid arthritis (RA) on first-line biologic treatment.

Entities:  

Keywords:  Medical Informatics Applications; Precision Medicine; Rheumatoid Arthritis

Mesh:

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Year:  2019        PMID: 31438056     DOI: 10.3233/SHTI190356

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  2 in total

1.  Do traditional BMI categories capture future obesity? A comparison with trajectories of BMI and incidence of cancer.

Authors:  Charlotte Watson; Dr Nophar Geifman
Journal:  AMIA Annu Symp Proc       Date:  2021-01-25

2.  Distinct patterns of disease activity over time in patients with active SLE revealed using latent class trajectory models.

Authors:  John A Reynolds; Jennifer Prattley; Nophar Geifman; Mark Lunt; Caroline Gordon; Ian N Bruce
Journal:  Arthritis Res Ther       Date:  2021-07-29       Impact factor: 5.156

  2 in total

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