TY - JOUR
T1 - Adapting the Elixhauser comorbidity index for cancer patients
AU - Mehta, Hemalkumar B.
AU - Sura, Sneha D.
AU - Adhikari, Deepak
AU - Andersen, Clark R.
AU - Williams, Stephen B.
AU - Senagore, Anthony J.
AU - Kuo, Yong Fang
AU - Goodwin, James S.
N1 - Funding Information:
This study was supported by the Cancer Prevention and Research Institute of Texas (RP1607674), the National Cancer Institute (K05 CA134923), the Agency for Healthcare Research and Quality (R24 HS022134), and the National Center for Advancing Translational Sciences of the National Institutes of Health (Clinical and Translational Science Award–linked KL2 Mentored Career Development Award KL2TR001441).
Publisher Copyright:
© 2018 American Cancer Society
PY - 2018/5/1
Y1 - 2018/5/1
N2 - 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.
AB - 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.
KW - Charlson comorbidity score
KW - Elixhauser comorbidity score
KW - National Cancer Institute combined index
KW - comorbidity
KW - confounding control
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U2 - 10.1002/cncr.31269
DO - 10.1002/cncr.31269
M3 - Article
C2 - 29390174
AN - SCOPUS:85045765223
SN - 0008-543X
VL - 124
SP - 2018
EP - 2025
JO - Cancer
JF - Cancer
IS - 9
ER -