John N Melvan1, Manu S Sancheti2, Theresa Gillespie3, Dana C Nickleach4, Yuan Liu5, Kristin Higgins6, Suresh Ramalingam7, Joseph Lipscomb5, Felix G Fernandez8. 1. Department of Surgery, Emory University School of Medicine, Atlanta, GA. 2. Department of Surgery, Emory University School of Medicine, Atlanta, GA; Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA. 3. Department of Surgery, Emory University School of Medicine, Atlanta, GA; Department of Hematology and Medical Oncology, Emory University School of Medicine, Atlanta, GA; Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA. 4. Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA; IntrinsiQ, Burlington, MA. 5. Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA; Rollins School of Public Health, Emory University School of Medicine, Atlanta, GA. 6. Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA; Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA. 7. Department of Hematology and Medical Oncology, Emory University School of Medicine, Atlanta, GA; Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA. 8. Department of Surgery, Emory University School of Medicine, Atlanta, GA; Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA. Electronic address: Felix.fernandez@emoryhealthcare.org.
Abstract
BACKGROUND: Clinical variables associated with 30-day mortality after lung cancer surgery are well known. However, the effects of nonclinical factors, including insurance coverage, household income, education, type of treatment center, and area of residence, on short-term survival are less appreciated. We studied the National Cancer Data Base, a joint endeavor of the Commission on Cancer of the American College of Surgeons and the American Cancer Society, to identify disparities in 30-day mortality after lung cancer resection based on these nonclinical factors. STUDY DESIGN: We performed a retrospective cohort analysis of patients undergoing lung cancer resection from 2003 to 2011 using the National Cancer Data Base. Data were analyzed using a multivariable logistic regression model to identify risk factors for 30-day mortality. RESULTS: During our study period, 215,645 patients underwent lung cancer resection. We found that clinical variables, such as age, sex, comorbidity, cancer stage, preoperative radiation, extent of resection, positive surgical margins, and tumor size were associated with 30-day mortality after resection. Nonclinical factors, including living in lower-income neighborhoods with a lesser proportion of high school graduates, and receiving cancer care at a nonacademic medical center were also independently associated with increased 30-day postoperative mortality. CONCLUSIONS: This study represents the largest analysis of 30-day mortality for lung cancer resection to date from a generalizable national cohort. Our results demonstrate that, in addition to known clinical risk factors, several nonclinical factors are associated with increased 30-day mortality after lung cancer resection. These disparities require additional investigation to improve lung cancer patient outcomes. Published by Elsevier Inc.
BACKGROUND: Clinical variables associated with 30-day mortality after lung cancer surgery are well known. However, the effects of nonclinical factors, including insurance coverage, household income, education, type of treatment center, and area of residence, on short-term survival are less appreciated. We studied the National Cancer Data Base, a joint endeavor of the Commission on Cancer of the American College of Surgeons and the American Cancer Society, to identify disparities in 30-day mortality after lung cancer resection based on these nonclinical factors. STUDY DESIGN: We performed a retrospective cohort analysis of patients undergoing lung cancer resection from 2003 to 2011 using the National Cancer Data Base. Data were analyzed using a multivariable logistic regression model to identify risk factors for 30-day mortality. RESULTS: During our study period, 215,645 patients underwent lung cancer resection. We found that clinical variables, such as age, sex, comorbidity, cancer stage, preoperative radiation, extent of resection, positive surgical margins, and tumor size were associated with 30-day mortality after resection. Nonclinical factors, including living in lower-income neighborhoods with a lesser proportion of high school graduates, and receiving cancer care at a nonacademic medical center were also independently associated with increased 30-day postoperative mortality. CONCLUSIONS: This study represents the largest analysis of 30-day mortality for lung cancer resection to date from a generalizable national cohort. Our results demonstrate that, in addition to known clinical risk factors, several nonclinical factors are associated with increased 30-day mortality after lung cancer resection. These disparities require additional investigation to improve lung cancerpatient outcomes. Published by Elsevier Inc.
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