title: Temporal disease trajectories condensed from population-wide registry data covering 6.2 million patients.
abstract: A key prerequisite for precision medicine is the estimation of disease progression from the current patient state. Disease correlations and temporal disease progression (trajectories) have mainly been analysed with focus on a small number of diseases or using large-scale approaches without time consideration, exceeding a few years. So far, no large-scale studies have focused on defining a comprehensive set of disease trajectories. Here we present a discovery-driven analysis of temporal disease progression patterns using data from an electronic health registry covering the whole population of Denmark. We use the entire spectrum of diseases and convert 14.9 years of registry data on 6.2 million patients into 1,171 significant trajectories. We group these into patterns centred on a small number of key diagnoses such as chronic obstructive pulmonary disease (COPD) and gout, which are central to disease progression and hence important to diagnose early to mitigate the risk of adverse outcomes. We suggest such trajectory analyses may be useful for predicting and preventing future diseases of individual patients.
authors: 1] Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Kemitorvet, Building 208, DK-2800 Kgs. Lyngby, Denmark [2] NNF Center for Protein Research, University of Copenhagen, Blegdamsvej 3B, DK-2200 Copenhagen, Denmark.
authors: Anders Boeck
authors: AB
authors: Jensen
authors: 1] NNF Center for Protein Research, University of Copenhagen, Blegdamsvej 3B, DK-2200 Copenhagen, Denmark [2] Department of Internal Medicine, University of New Mexico, MSC10 5550, 1 University of New Mexico, Albuquerque, New Mexico 87131, USA.
authors: Pope L
authors: PL
authors: Moseley
authors: 1] Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Kemitorvet, Building 208, DK-2800 Kgs. Lyngby, Denmark [2] Department of Internal Medicine, University of New Mexico, MSC10 5550, 1 University of New Mexico, Albuquerque, New Mexico 87131, USA [3] Department of Rheumatology and Inflammation Research, University of Gothenburg, Box 480, SE-40530 Gothenburg, Sweden.
authors: Tudor I
authors: TI
authors: Oprea
authors: NNF Center for Protein Research, University of Copenhagen, Blegdamsvej 3B, DK-2200 Copenhagen, Denmark.
authors: Sabrina Gade
authors: SG
authors: Ellesøe
authors: 1] Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Kemitorvet, Building 208, DK-2800 Kgs. Lyngby, Denmark [2] NNF Center for Protein Research, University of Copenhagen, Blegdamsvej 3B, DK-2200 Copenhagen, Denmark.
authors: Robert
authors: R
authors: Eriksson
authors: Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Copenhagen University Hospital, Boserupvej 2, DK-4000 Roskilde, Denmark.
authors: Henriette
authors: H
authors: Schmock
authors: NNF Center for Protein Research, University of Copenhagen, Blegdamsvej 3B, DK-2200 Copenhagen, Denmark.
authors: Peter Bjødstrup
authors: PB
authors: Jensen
authors: NNF Center for Protein Research, University of Copenhagen, Blegdamsvej 3B, DK-2200 Copenhagen, Denmark.
authors: Lars Juhl
authors: LJ
authors: Jensen
authors: 1] Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Kemitorvet, Building 208, DK-2800 Kgs. Lyngby, Denmark [2] NNF Center for Protein Research, University of Copenhagen, Blegdamsvej 3B, DK-2200 Copenhagen, Denmark.
authors: Søren
authors: S
authors: Brunak
mesh_terms: D002561:Cerebrovascular Disorders / Q000175:diagnosis; D015331:Cohort Studies; D003718:Denmark / Q000453:epidemiology; D003920:Diabetes Mellitus / Q000175:diagnosis; D019937:Diagnostic Techniques and Procedures; D003935:Diagnostic Techniques, Cardiovascular; D018450:Disease Progression; D006801:Humans; D008297:Male; D008490:Medical Informatics / Q000379:methods*; D011471:Prostatic Neoplasms / Q000175:diagnosis; D029424:Pulmonary Disease, Chronic Obstructive / Q000175:diagnosis; D012042:Registries / Q000706:statistics & numerical data*; D012189:Retrospective Studies