Risk stratification of cancer survivors: a quantitative method using clinical attendance patterns for colorectal, Hodgkin’s disease and multiple myeloma.


Year:

Session type:

Katie Harris1, Kimberley Edwards1, Ashley Woolmore2, James Wells2, Catherine Boyle3, Tom Farrell1, Haley Nai1, Eva Morris5, James Thomas5, David Forman4
1University of Leeds, Leeds, United Kingdom,2Monitor, London, United Kingdom,3Macmillan, London, United Kingdom,4IARC, Lyon, France,5NYRCIS, Leeds, United Kingdom

Background

As cancer cases continue to rise and deaths fall, the population of survivors grows. The requirements of cancer survivors vary.  Cancer survivorship may be examined by considering the post-treatment clinical attendance patterns(NHS ‘footprints’) for entire populations of survivors, for specific cancer types.

Method

NHS footprint is a concept that is not directly measurable. It may be, however, described by a combination of features that are observed; such as the number, duration and interval between hospital episodes.

Structural equation modelling will be applied to data that has been sourced from the NCIN hosted National Cancer Data Repository, linking cancer registry data with Hospital Episode Statistics data, for patients diagnosed in the Northern and Yorkshire region with colorectal cancer (C) in Q1 2001 and myeloma (M) and Hodgkin’s (H) in 2001. Differences in NHS footprint due to stage at diagnosis, treatment and co-morbidities will be investigated; and related to survival outcome for each cancer site.

Results

The total duration of inpatient hospital stays (median days) for those who survive (24C; 82M; 24H) varies significantly from those who die (44C; 63M; 93H), respectively (p<0.01). The total number of episodes (median days) of episodes also varies, by cancer site, for survivors (10C; 32M; 16H) and non-survivors (8C; 11M; 25H) (p<0.01).  Five year survival rates for these groups are: 41%C; 22%M and 79%H.

Structural equation modelling will identify “types” of survivors for each cancer site. It is expected patients will range from those who are completely cured with no further impact on the health service; to frequent users due to necessary follow ups, late effects, and co-morbidities; and probably a range in between.   

Conclusion

This study contributes to risk stratification of cancer survivorship, illustrating differences cancer sites’ NHS footprints. This work will facilitate identification of different support requirements for cancer patients, plus associated co-morbidities.