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Validation and Recalibration of Two Multivariable Prognostic Models for Survival and Independence in Acute Stroke

Sim, Julius; Teece, Lucy; Dennis, Martin S.; Roffe, Christine

Validation and Recalibration of Two Multivariable Prognostic Models for Survival and Independence in Acute Stroke Thumbnail


Authors

Lucy Teece

Martin S. Dennis



Abstract

Introduction
Various prognostic models have been developed for acute stroke, including one based on age and five binary variables (‘six simple variables’ model; SSVMod) and one based on age plus scores on the National Institutes of Health Stroke Scale (NIHSSMod). The aims of this study were to externally validate and recalibrate these models, and to compare their predictive ability in relation to both survival and independence.

Methods
Data from a large clinical trial of oxygen therapy (n = 8003) were used to determine the discrimination and calibration of the models, using C-statistics, calibration plots, and Hosmer-Lemeshow statistics. Methods of recalibration in the large and logistic recalibration were used to update the models.

Results
For discrimination, both models functioned better for survival (C-statistics between .802 and .837) than for independence (C-statistics between .725 and .735). Both models showed slight shortcomings with regard to calibration, over-predicting survival and under-predicting independence; the NIHSSMod performed slightly better than the SSVMod. For the most part, there were only minor differences between ischaemic and haemorrhagic strokes. Logistic recalibration successfully updated the models for a clinical trial population.

Conclusions
Both prognostic models performed well overall in a clinical trial population. The choice between them is probably better based on clinical and practical considerations than on statistical considerations.

Journal Article Type Article
Acceptance Date Mar 30, 2016
Publication Date May 26, 2016
Publicly Available Date Mar 28, 2024
Journal PLoS One
Print ISSN 1932-6203
Publisher Public Library of Science
Volume 11
Issue 5
Article Number ARTN e0153527
DOI https://doi.org/10.1371/journal.pone.0153527
Keywords prognostic models, stroke
Publisher URL http://dx.doi.org/10.1371/journal.pone.0153527

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