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BMC Health Serv Res. 2016 Nov 22;16(1):671.

Effects of longitudinal changes in Charlson comorbidity on prognostic survival model performance among newly diagnosed patients with hypertension.

Author information

1
Measurement and Evaluation, Mosaic Primary Care Network, Calgary, AB, Canada.
2
Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
3
O'Brien Institute for Public Health, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
4
Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada.
5
Libin Cardiovascular Institute of Alberta, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
6
Alberta Health Services, Calgary, AB, Canada.
7
Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada. hquan@ucalgary.ca.
8
O'Brien Institute for Public Health, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada. hquan@ucalgary.ca.
9
University of Calgary, 3E23 3rd fl TRW, 3280 Hospital Drive NW, Calgary, T2N 4Z6, AB, Canada. hquan@ucalgary.ca.

Abstract

BACKGROUND:

To assess the use of updated comorbidity information over time on ability to predict mortality among adults with newly diagnosed hypertension.

METHODS:

We studied adults 18 years and older with an incident diagnosis of hypertension from Alberta, Canada. We compared the prognostic performance of Cox regression models using Charlson comorbidities as time-invariant covariates at baseline (TIC) versus models including Charlson comorbidities as time-varying covariates (TVC) using Akaike Information Criterion (AIC) for testing goodness of fit.

RESULTS:

The strength of the association between important prognostic clinical variables and mortality varied by modeling technique; for example, myocardial infarction was less strongly associated with mortality in the TIC model (Hazard Ratio 1.07; 95% Confidence Interval (CI): 1.05 to 1.1) than in the TVC model (HR 1.20; 95% CI: 1.18 to 1.22). All TVC models slightly outperformed TIC models, regardless of the method used to adjust for comorbid conditions (individual Charlson Comorbidities, count of comorbidities or indices). The TVC model including all 17 Charlson comorbidities as individual independent variables showed the best fit and performance.

CONCLUSION:

Accounting for changes in patient comorbidity status over time more accurately captures a patient's health risk and slightly improves predictive model fit and performance than traditional methods using TIC assessment.

KEYWORDS:

Charlson; Comorbidity; Hypertension; Longitudinal change; Model performance

PMID:
27876047
PMCID:
PMC5120518
DOI:
10.1186/s12913-016-1910-8
[Indexed for MEDLINE]
Free PMC Article

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