Title:
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Multiple imputation of missing data and prognostic survival modelling for incident patients starting dialysis in England, Wales and Northern Ireland
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Background
The UK Renal Registry (UKRR) collects data, performs clinical audit and reports on
achievement of clinical standards and outcomes for patients on renal replacement
therapy (RRT). Mortality predictions for patients starting dialysis are important,
especially for elderly patients with an increased risk of death. Studies have shown
that patients who are considering starting dialysis, do want prognostic information
to aid informed decision making. The main aim of the prognostic model developed
in this research, is to provide realistic and objective prognostic information to
clinicians when discussing prognosis with patients in preparation for starting
dialysis.
Methods
The research described in this thesis investigates the application of multiple
imputation by chained equations for handling of missing data in the UKRR database
and the development of the prognostic model in the 20 complete imputed data sets.
Internal validation was based on a non-randomly geographical split of renal centres
and the prognostic model was externally validated in the Australia and New
Zealand Dialysis and Transplant Registry (ANZDATA) data.
Main results
Prognostic model discrimination at 1 year after start of dialysis was good
(c-statistic=0.79). The results from the prognostic model in terms of calibration,
discrimination and variance explained did not dilute much over follow-up time. The
geographical internal validation showed very good calibration and discrimination
with little degradation of model fit compared to the full dataset. Although the
predictive ability of the externally validated prognostic sub-model in the ANZDATA
cohort was reasonable, calibration . in the 2 most at risk patient groups was not
adequate.
Recommendations
The transportability of the prognostic model developed in the UKRR data was not
proven in the external validation and it is not advisable to use the prognostic model
in populations other than the UK. The prognostic model will need to be calibrated
before use in other populations.
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