| Title |
A Dashboard for Latent Class Trajectory Modeling: Application in Rheumatoid Arthritis.
|
|---|---|
| Published in |
Studies in health technology and informatics, August 2019
|
| DOI | 10.3233/shti190356 |
| Pubmed ID | |
| Authors |
Beatrice Amico, Arianna Dagliati, Darren Plant, Anne Barton, Niels Peek, Nophar Geifman |
| 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. |
Login to access the Attention Digest and the Sentiment Analysis related to this output.
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 40% |
| United States | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Scientists | 1 | 20% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 11 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Professor | 2 | 18% |
| Student > Ph. D. Student | 2 | 18% |
| Researcher | 2 | 18% |
| Other | 1 | 9% |
| Student > Postgraduate | 1 | 9% |
| Other | 0 | 0% |
| Unknown | 3 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 4 | 36% |
| Biochemistry, Genetics and Molecular Biology | 1 | 9% |
| Agricultural and Biological Sciences | 1 | 9% |
| Immunology and Microbiology | 1 | 9% |
| Engineering | 1 | 9% |
| Other | 0 | 0% |
| Unknown | 3 | 27% |