title: Effects of longitudinal changes in Charlson comorbidity on prognostic survival model performance among newly diagnosed patients with hypertension.
abstract: To assess the use of updated comorbidity information over time on ability to predict mortality among adults with newly diagnosed hypertension.
  
  
  
  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.
  
  
  
  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.
  
  
  
  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.
authors.affiliation: Measurement and Evaluation, Mosaic Primary Care Network, Calgary, AB, Canada.
authors.forename: Peter
authors.initials: P
authors.lastname: Rymkiewicz
authors.affiliation: Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.|O'Brien Institute for Public Health, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
authors.forename: Pietro
authors.initials: P
authors.lastname: Ravani
authors.affiliation: Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.|O'Brien Institute for Public Health, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
authors.forename: Brenda R
authors.initials: BR
authors.lastname: Hemmelgarn
authors.affiliation: Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada.
authors.forename: Finlay A
authors.initials: FA
authors.lastname: McAlister
authors.affiliation: O'Brien Institute for Public Health, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
authors.forename: Danielle A
authors.initials: DA
authors.lastname: Southern
authors.affiliation: Libin Cardiovascular Institute of Alberta, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
authors.forename: Robin
authors.initials: R
authors.lastname: Walker
authors.affiliation: Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.|Alberta Health Services, Calgary, AB, Canada.
authors.forename: Guanmin
authors.initials: G
authors.lastname: Chen
authors.affiliation: Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada. hquan@ucalgary.ca.|O'Brien Institute for Public Health, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada. hquan@ucalgary.ca.|University of Calgary, 3E23 3rd fl TRW, 3280 Hospital Drive NW, Calgary, T2N 4Z6, AB, Canada. hquan@ucalgary.ca.
authors.forename: Hude
authors.initials: H
authors.lastname: Quan
mesh_terms: D000328:Adult; D000368:Aged; D000416:Alberta / Q000453:epidemiology; D015897:Comorbidity; D005260:Female; D006801:Humans; D006973:Hypertension / Q000453:epidemiology* / Q000401:mortality; D008297:Male; D008875:Middle Aged; D011379:Prognosis; D016016:Proportional Hazards Models; D016019:Survival Analysis; D055815:Young Adult
keywords: Charlson; Comorbidity; Hypertension; Longitudinal change; Model performance