Adapting the Elixhauser comorbidity index for cancer patients

• Published in: Cancer Vol. 124; no. 9; pp. 2018 - 2025
• Main Authors: Mehta, Hemalkumar B., Sura, Sneha D., Adhikari, Deepak, Andersen, Clark R., Williams, Stephen B., Senagore, Anthony J., Kuo, Yong‐Fang, Goodwin, James S.
• Format: Journal Article
• Language: English
• Published: United States Wiley Subscription Services, Inc 01.05.2018
• Subjects: Breast cancer; Cancer; Charlson comorbidity score; Colorectal cancer; Colorectal carcinoma; Comorbidity; confounding control; Elixhauser comorbidity score; Government programs; Health care; Health risk assessment; Lung cancer; Mortality; National Cancer Institute combined index; Oncology; Patients; Prostate cancer; Regression models; Survival; Training; Elixhauser comorbidity score; comorbidity; confounding control; National Cancer Institute combined index; Charlson comorbidity score
• ISSN: 0008-543X; 1097-0142; 1045-7410; 1097-0142
• DOI: 10.1002/cncr.31269

BACKGROUND This study was designed to adapt the Elixhauser comorbidity index for 4 cancer‐specific populations (breast, prostate, lung, and colorectal) and compare 3 versions of the Elixhauser comorbidity score (individual comorbidities, summary comorbidity score, and cancer‐specific summary comorbidity score) with 3 versions of the Charlson comorbidity score for predicting 2‐year survival with 4 types of cancer. METHODS This cohort study used Texas Cancer Registry–linked Medicare data from 2005 to 2011 for older patients diagnosed with breast (n = 19,082), prostate (n = 23,044), lung (n = 26,047), or colorectal cancer (n = 16,693). For each cancer cohort, the data were split into training and validation cohorts. In the training cohort, competing risk regression was used to model the association of Elixhauser comorbidities with 2‐year noncancer mortality, and cancer‐specific weights were derived for each comorbidity. In the validation cohort, competing risk regression was used to compare 3 versions of the Elixhauser comorbidity score with 3 versions of the Charlson comorbidity score. Model performance was evaluated with c statistics. RESULTS The 2‐year noncancer mortality rates were 14.5% (lung cancer), 11.5% (colorectal cancer), 5.7% (breast cancer), and 4.1% (prostate cancer). Cancer‐specific Elixhauser comorbidity scores (c = 0.773 for breast cancer, c = 0.772 for prostate cancer, c = 0.579 for lung cancer, and c = 0.680 for colorectal cancer) performed slightly better than cancer‐specific Charlson comorbidity scores (ie, the National Cancer Institute combined index; c = 0.762 for breast cancer, c = 0.767 for prostate cancer, c = 0.578 for lung cancer, and c = 0.674 for colorectal cancer). Individual Elixhauser comorbidities performed best (c = 0.779 for breast cancer, c = 0.783 for prostate cancer, c = 0.587 for lung cancer, and c = 0.687 for colorectal cancer). CONCLUSIONS The cancer‐specific Elixhauser comorbidity score performed as well as or slightly better than the cancer‐specific Charlson comorbidity score in predicting 2‐year survival. If the sample size permits, using individual Elixhauser comorbidities may be the best way to control for confounding in cancer outcomes research. Cancer 2018;124:2018‐25. © 2018 American Cancer Society. The Elixhauser comorbidity score has been adapted for cancer patients and it performs equally as well as or slightly better than the cancer‐specific Charlson comorbidity score (ie, the National Cancer Institute combined index).