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Publication Abstract

Authors: Tammemagi CM, Neslund-Dudas C, Simoff M, Kvale P

Title: In lung cancer patients, age, race-ethnicity, gender and smoking predict adverse comorbidity, which in turn predicts treatment and survival.

Journal: J Clin Epidemiol 57(6):597-609

Date: 2004 Jun

Abstract: OBJECTIVE: This study evaluates the relationship between sociodemographic/exposure factors and comorbidity, and their impact on lung cancer treatment and survival. STUDY AND DESIGN SETTING: Data for 1,155 patients were abstracted from the Josephine Ford Cancer Center Tumor Registry and medical records. Associations were analyzed by linear, logistic, and Cox regression. RESULTS: Approximately 88% of patients had > or = 1 of 56 comorbidities assessed. In multivariate analysis, comorbidity count was associated with older age, pack-years smoked, heavy alcohol use, lower socioeconomic status (SES), and female gender. Approximately 63% of patients had > or = 1 of 18 adverse prognostic comorbidities (AC), and significant independent predictors of AC were age, pack-years, African-American race/ethnicity, and gender. In multivariate analysis, comorbidity count and AC predicted nonreceipt of surgery in localized disease (OR(> or = 1 vs. 0 AC)=0.38, 95% 0.18, 0.81) and chemotherapy in advanced disease (OR > or = 1 vs. 0 AC)=0.72, 95% 0.51, 1.00). In adjusted analysis, comorbidity predicted survival in localized (hazard ratio (HR)(> or = 2 vs. 0 AC)=2.99, 95% CI 1.75, 5.10) and advanced lung cancer (HR(> or = 2 vs. 0 AC)=1.56, 95% CI 1.25, 1.94). CONCLUSION: Comorbidity has important deleterious effects on lung cancer outcomes and significant predictors of comorbidity included age, smoking, race/ethnicity, SES, alcohol, and gender.

Last Modified: 03 Sep 2013