Modelling the Time Taken to Experience a Type 2 Diabetes Related Complication Using a Survival Tree in Order to Advise General Practitioners

Christopher J. Steele, Adele H. Marshall, Anne Kouvonen, Frank Kee, Reijo Sund

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Type 2 diabetes (T2D) is a major public health problem. The prevalence of the disease is growing at an alarming rate and the sharp increase in T2D shows no signs of slowing down. The increased number of T2D cases worldwide has caused a simultaneous increase in the number of T2D related complications. This paper demonstrates how a survival tree based approach can be used to enable predictions to be made concerning when an individual is expected to experience a complication of T2D. A survival tree is used to identify cohorts of individuals with significantly different survival distributions from T2D to complication. By fitting appropriate survival distributions to the individual leaves of the tree, the expected time until complication can be calculated for each group of individuals. Survival trees were built for death, stroke/acute myocardial infarction (AMI) and amputation/coronary revascularisation.
Original languageEnglish
Title of host publicationIEEE 29th International Symposium on Computer-Based Medical Systems, CBMS 2016: Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages271-272
Number of pages2
ISBN (Electronic)978-1-4673-9036-1
ISBN (Print)978-1-4673-9037-8
DOIs
Publication statusPublished - 18 Aug 2016

Publication series

NameIEEE 29th International Symposium on Computer-Based Medical Systems (CBMS)
PublisherIEEE
ISSN (Electronic)2372-9198

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    Steele, C. J., Marshall, A. H., Kouvonen, A., Kee, F., & Sund, R. (2016). Modelling the Time Taken to Experience a Type 2 Diabetes Related Complication Using a Survival Tree in Order to Advise General Practitioners. In IEEE 29th International Symposium on Computer-Based Medical Systems, CBMS 2016: Proceedings (pp. 271-272). (IEEE 29th International Symposium on Computer-Based Medical Systems (CBMS)). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CBMS.2016.69