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InterPreT cancer survival: A dynamic web interactive prediction cancer survival tool for health-care professionals and cancer epidemiologists.

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posted on 2018-09-10, 13:57 authored by Sarwar Islam Mozumder, Paul W. Dickman, Mark J. Rutherford, Paul C. Lambert
BACKGROUND: There are a variety of ways for quantifying cancer survival with each measure having advantages and disadvantages. Distinguishing these measures and how they should be interpreted has led to confusion among scientists, the media, health care professionals and patients. This motivates the development of tools to facilitate communication and interpretation of these statistics. METHODS: "InterPreT Cancer Survival" is a newly developed, publicly available, online interactive cancer survival tool targeted towards health-care professionals and epidemiologists (http://interpret.le.ac.uk). It focuses on the correct interpretation of commonly reported cancer survival measures facilitated through the use of dynamic interactive graphics. Statistics presented are based on parameter estimates obtained from flexible parametric relative survival models using large population-based English registry data containing information on survival across 6 cancer sites; Breast, Colon, Rectum, Stomach, Melanoma and Lung. RESULTS: Through interactivity, the tool improves understanding of various measures and how survival or mortality may vary by age and sex. Routine measures of cancer survival are reported, however, individualised estimates using crude probabilities are advocated, which is more appropriate for patients or health care professionals. The results are presented in various interactive formats facilitating understanding of individual risk and differences between various measures. CONCLUSIONS: "InterPreT Cancer Survival" is presented as an educational tool which engages the user through interactive features to improve the understanding of commonly reported cancer survival statistics. The tool has received positive feedback from a Cancer Research UK patient sounding board and there are further plans to incorporate more disease characteristics, e.g. stage.

History

Citation

Cancer Epidemiology, 2018, 56, pp. 46-52

Author affiliation

/Organisation/COLLEGE OF LIFE SCIENCES/School of Medicine/Department of Health Sciences

Version

  • AM (Accepted Manuscript)

Published in

Cancer Epidemiology

Publisher

Elsevier

issn

1877-7821

eissn

1877-783X

Acceptance date

2018-07-14

Copyright date

2018

Available date

2019-07-20

Publisher version

https://www.sciencedirect.com/science/article/pii/S187778211830198X?via=ihub

Notes

The online interactive cancer survival prediction tool, InterPreT, can be accessed via http://interpret.le.ac.uk. The web tool is compatible with most web browsers excluding Internet Explorer (e.g. Chrome, Firefox, Edge and Safari). We highly encourage readers to use the tool whilst reading the paper.;The file associated with this record is under embargo until 12 months after publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.

Language

en

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