Summary
Background: Systems medicine is a new approach for the development and selection of treatment
strategies for patients with complex diseases. It is often referred to as the application
of systems biology methods for decision making in patient care. For systems medicine
computer applications, many different data sources have to be integrated and included
into models. This is a challenging task for Medical Informatics since the approach
exceeds traditional systems like Electronic Health Records. To prioritize research
activities for systems medicine applications, it is necessary to get an overview over
modelling methods and data sources already used in this field.
Objectives: We performed a systematic literature review with the objective to capture current
use of 1) modelling methods and 2) data sources in systems medicine related research projects.
Methods: We queried the MEDLINE and ScienceDirect databases for papers associated with the
search term systems medicine and related terms. Papers were screened and assessed in full text in a two-step process
according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses
(PRISMA) statement guidelines.
Results: The queries returned 698 articles of which 34 papers were finally included into the
study. A multitude of modelling approaches such as machine learning and network analysis
was identified and classified. Since these approaches are also used in other domains,
no methods specific for systems medicine could be identified. Omics data are the most
widely used data types followed by clinical data. Most studies only include a rather
limited number of data sources.
Conclusions: Currently, many different modelling approaches are used in systems medicine. Thus,
highly flexible modular solutions are necessary for systems medicine clinical applications.
However, the number of data sources included into the models is limited and most projects
currently focus on prognosis. To leverage the potential of systems medicine further,
it will be necessary to focus on treatment strategies for patients and consider a
broader range of data.
Keywords
Systems medicine - systematic literature review - data sources - models - medical
informatics