Short-Form Charlson Comorbidity Index for Assessment of Perioperative Mortality After Radical Cystectomy
Standard
Short-Form Charlson Comorbidity Index for Assessment of Perioperative Mortality After Radical Cystectomy. / Dell'Oglio, Paolo; Tian, Zhe; Leyh-Bannurah, Sami-Ramzi; Trudeau, Vincent; Larcher, Alessandro; Moschini, Marco; Di Trapani, Ettore; Capitanio, Umberto; Briganti, Alberto; Montorsi, Francesco; Saad, Fred; Karakiewicz, Pierre I.
In: J NATL COMPR CANC NE, Vol. 15, No. 3, 03.2017, p. 327-333.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
Harvard
APA
Vancouver
Bibtex
}
RIS
TY - JOUR
T1 - Short-Form Charlson Comorbidity Index for Assessment of Perioperative Mortality After Radical Cystectomy
AU - Dell'Oglio, Paolo
AU - Tian, Zhe
AU - Leyh-Bannurah, Sami-Ramzi
AU - Trudeau, Vincent
AU - Larcher, Alessandro
AU - Moschini, Marco
AU - Di Trapani, Ettore
AU - Capitanio, Umberto
AU - Briganti, Alberto
AU - Montorsi, Francesco
AU - Saad, Fred
AU - Karakiewicz, Pierre I
N1 - Copyright © 2017 by the National Comprehensive Cancer Network.
PY - 2017/3
Y1 - 2017/3
N2 - Background: The Deyo adaptation of the Charlson comorbidity index (DaCCI), which relies on 17 comorbid condition groupings, represents one of the most frequently used baseline comorbidity assessment tools in retrospective database studies. However, this index is not specific for patients with bladder cancer (BCa) treated with radical cystectomy (RC). The goal of this study was to develop a short-form of the original DaCCI (DaCCI-SF) that may specifically predict 90-day mortality after RC, with equal or better accuracy.Patients and Methods:Between 2000 and 2009, we identified 7,076 patients in the SEER-Medicare database with stage T1 through T4 nonmetastatic BCa treated with RC. We randomly divided the population into development (n=6,076) and validation (n=1,000) cohorts. Within the development cohort, logistic regression models tested the ability to predict 90-day mortality with various iterations of the DaCCI-SF, wherein <17 original comorbid condition groupings were included after adjusting for age, sex, race, T stage, and N stage. We relied on the Akaike information criterion to identify the most parsimonious and informative set of comorbid condition groupings. Accuracy of the DaCCI and the DaCCI-SF was tested in the external validation cohort.Results:Within the development cohort, the most parsimonious and informative model resulted in the inclusion of 3 of the 17 (17.6%) original comorbid condition groupings: congestive heart failure, cerebrovascular disease, and chronic pulmonary disease. Within the validation cohort, the accuracy was 68.4% for the DaCCI versus 69.7% for the DaCCI-SF. Higher accuracy of the DaCCI-SF was confirmed in subgroup analyses performed according to age (≤75 vs >75 years), stage (organ-confined vs non-organ-confined), type of diversion (ileal-conduit vs non-ileal-conduit), and treatment period.Conclusions:DaCCI-SF relies on 17.6% of the original comorbid condition groupings and provides higher accuracy for predicting 90-day mortality after RC compared with the original DaCCI, especially in most contemporary patients.
AB - Background: The Deyo adaptation of the Charlson comorbidity index (DaCCI), which relies on 17 comorbid condition groupings, represents one of the most frequently used baseline comorbidity assessment tools in retrospective database studies. However, this index is not specific for patients with bladder cancer (BCa) treated with radical cystectomy (RC). The goal of this study was to develop a short-form of the original DaCCI (DaCCI-SF) that may specifically predict 90-day mortality after RC, with equal or better accuracy.Patients and Methods:Between 2000 and 2009, we identified 7,076 patients in the SEER-Medicare database with stage T1 through T4 nonmetastatic BCa treated with RC. We randomly divided the population into development (n=6,076) and validation (n=1,000) cohorts. Within the development cohort, logistic regression models tested the ability to predict 90-day mortality with various iterations of the DaCCI-SF, wherein <17 original comorbid condition groupings were included after adjusting for age, sex, race, T stage, and N stage. We relied on the Akaike information criterion to identify the most parsimonious and informative set of comorbid condition groupings. Accuracy of the DaCCI and the DaCCI-SF was tested in the external validation cohort.Results:Within the development cohort, the most parsimonious and informative model resulted in the inclusion of 3 of the 17 (17.6%) original comorbid condition groupings: congestive heart failure, cerebrovascular disease, and chronic pulmonary disease. Within the validation cohort, the accuracy was 68.4% for the DaCCI versus 69.7% for the DaCCI-SF. Higher accuracy of the DaCCI-SF was confirmed in subgroup analyses performed according to age (≤75 vs >75 years), stage (organ-confined vs non-organ-confined), type of diversion (ileal-conduit vs non-ileal-conduit), and treatment period.Conclusions:DaCCI-SF relies on 17.6% of the original comorbid condition groupings and provides higher accuracy for predicting 90-day mortality after RC compared with the original DaCCI, especially in most contemporary patients.
KW - Aged
KW - Aged, 80 and over
KW - Comorbidity
KW - Cystectomy
KW - Female
KW - Humans
KW - Male
KW - Mortality
KW - Neoplasm Metastasis
KW - Neoplasm Staging
KW - Population Surveillance
KW - SEER Program
KW - United States
KW - Urinary Bladder Neoplasms
KW - Journal Article
M3 - SCORING: Journal article
C2 - 28275033
VL - 15
SP - 327
EP - 333
JO - J NATL COMPR CANC NE
JF - J NATL COMPR CANC NE
SN - 1540-1405
IS - 3
ER -
