Disease trajectory browser for exploring temporal, population-wide disease progression patterns in 7.2 million Danish patients

Troels Siggaard, Roc Reguant, Isabella F. Jørgensen, Amalie D. Haue, Mette Lademann, Alejandro Aguayo-Orozco, Jessica X. Hjaltelin, Anders Boeck Jensen, Karina Banasik, Søren Brunak

Research output: Contribution to journalArticlepeer-review

61 Scopus citations

Abstract

We present the Danish Disease Trajectory Browser (DTB), a tool for exploring almost 25 years of data from the Danish National Patient Register. In the dataset comprising 7.2 million patients and 122 million admissions, users can identify diagnosis pairs with statistically significant directionality and combine them to linear disease trajectories. Users can search for one or more disease codes (ICD-10 classification) and explore disease progression patterns via an array of functionalities. For example, a set of linear trajectories can be merged into a disease trajectory network displaying the entire multimorbidity spectrum of a disease in a single connected graph. Using data from the Danish Register for Causes of Death mortality is also included. The tool is disease-agnostic across both rare and common diseases and is showcased by exploring multimorbidity in Down syndrome (ICD-10 code Q90) and hypertension (ICD-10 code I10). Finally, we show how search results can be customized and exported from the browser in a format of choice (i.e. JSON, PNG, JPEG and CSV).

Original languageEnglish
Article number4952
JournalNature Communications
Volume11
Issue number1
DOIs
StatePublished - 1 Dec 2020

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