A comparison of charlson and elixhauser comorbidity measures to predict colorectal cancer survival using administrative health data

Authors

  • Jessica R. Lieffers MSc, RD,

    1. Division of Human Nutrition, Department of Agricultural, Food & Nutritional Science, University of Alberta, Edmonton, Alberta, Canada
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  • Vickie E. Baracos PhD,

    1. Division of Palliative Care Medicine, Department of Oncology, University of Alberta, Edmonton, Alberta, Canada
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  • Marcy Winget PhD,

    1. School of Public Health, University of Alberta, Edmonton, Alberta, Canada
    2. Community Oncology, Alberta Health Services—Cancer Care, Edmonton, Alberta, Canada
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  • Konrad Fassbender PhD

    Corresponding author
    1. Division of Palliative Care Medicine, Department of Oncology, University of Alberta, Edmonton, Alberta, Canada
    • Division of Palliative Care Medicine, Department of Oncology, University of Alberta, Third Floor, Environmental Engineering Building, Edmonton, Alberta, Canada T6G 2M8
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    • Fax: (780) 492-2145


Abstract

BACKGROUND:

Cancer survival is related to features of the primary malignancy and concurrent presence of nonmalignant diseases (comorbidities), including weight-related conditions (obesity, weight loss). The Charlson and Elixhauser methods are 2 well-known methods that take comorbidities into account when explaining survival. They differ in both the number and categorization of comorbidities.

METHODS:

Cancer, comorbidity, and survival data were acquired from inpatient administrative hospital records in 574 colorectal cancer patients. Robust Poisson regression was used to analyze 2- and 3-year survival according to cancer features and comorbidities classified by the Charlson and Elixhauser methods. Data for weight-related conditions (body mass index, weight loss) and performance status were acquired upon a new patient visit to the regional cancer center. Discrimination was assessed with the concordance (c) statistic.

RESULTS:

A base model (age, sex, stage) had excellent discrimination (c-statistic, 0.824 [2-year survival] and 0.827 [3-year survival]). The addition of Charlson comorbidities did not outperform the base model (c-statistic, 0.831 [2-year survival] and 0.833 [3-year survival]). Elixhauser comorbidities added higher discrimination compared with the base model, both in stage and overall (c-statistic, 0.852 [2-year survival] and 0.854 [3-year survival]; P < .01). The greatest increase in the c-statistic contributed by the addition of the Elixhauser comorbidities occurred in stage II patients (increased from 0.683 to 0.838). Overall, the Elixhauser comorbidities outperformed the Charlson comorbidities (P < .05). The use of self-reported weight and performance status data significantly increased discrimination by the Elixhauser method in 2-year but not 3-year survival.

CONCLUSIONS:

The Elixhauser method is a superior comorbidity risk-adjustment model for colorectal cancer survival prediction. Cancer 2011. © 2010 American Cancer Society.

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