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Analyzing Risk Factors for Morbidity and Mortality After Lung Resection for Lung Cancer Using the NSQIP Database
*Raymond A Jean¹, *Matthew DeLuzio¹, *Alexander I Kraev², *Gongyi Wang³, Daniel J Boffa¹, Frank C Detterbeck¹, *Zuoheng Wang³, Anthony W Kim^1
1Yale School of Medicine, New Haven, CT;²Billings Clinic, Billings, MT;³Yale School of Public Health, New Haven, CT

Objective: To develop a predictive model that identifies pathways between the development of complications andmortality following pulmonary lobectomies.
Design: Retrospective cohort study.
Setting: Hospitalized Care
Patients: The American College of Surgeons (ACS) National Surgical Quality Improvement Project (NSQIP) database was examined for all patients undergoing elective lobectomies for cancer between 2005-2011.
Interventions: Fifty-four preoperative and intraoperative factors and 14 complications were considered for their impact on 30-day mortality. Multivariate logistic regression models and Least Absolute Shrinkage and Selection Operator (LASSO) were used to identify risk factors for mortality, both as direct predictors and as indirect predictors through the prediction of complications. Only factors which were significant under both the multivariate logistic regression and LASSO models were considered to be validated for the final model.
Main Outcome Measures: Postoperative 30 day mortality.
Results: There were 6435 thoracoscopic and open lobectomies identified. After modeling, 28 risk factors and 5 complications were found to be predictors for mortality. There were 7 clinical factors shared between the LASSO and multivariate logistic regressions that predicted mortality based on comorbidity: advanced age (OR 1.034, p=0.002), male sex (OR 1.828, p=0.005), preoperative dyspnea at rest (OR 4.24, p<0.001), preoperative dyspnea on exertion(OR 2.026, p=0.001), preoperative hyponatremia or hypernatremia (OR 1.882, p=0.017), preoperative anemia (OR 1.532, p=0.044), and open lobectomy (OR 2.198, p=0.002).
Conclusions: The clinical factors that predict postoperative complications and mortality are multiple and not necessarily aligned. Efforts to improve quality following anatomic pulmonary resections should focus on mechanisms to address both types of adverse outcomes.

Perioperative Risk Factors for Predicting Mortality
Variable	Odds Ratio	95% Confidence Interval	p-value
Age in years	1.034	1.013 - 1.056	0.002
Male Gender	1.828	1.199 - 2.789	0.005
Preop Hx Dyspnea at Rest	4.24	1.969 - 9.131	< 0.001
Preop Hx Dyspnea on Exertion	2.026	1.348 - 3.047	0.001
Preop Sodium 145	1.882	1.118 - 3.167	0.017
Preop HCT < 35 (female) or 40 (male)	1.532	1.011 - 2.322	0.044
Open Lobectomy	2.082	1.300 - 3.335	0.002

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