Prediction of Long-Term Survival After Lung Cancer Surgery for Elderly Patients in The Society of Thoracic Surgeons General Thoracic Surgery Database.

Journal Article (Journal Article)

BACKGROUND: Prior risk models using the STS General Thoracic Surgery database (STS-GTSD) have been limited to 30-day outcomes. We have now linked STS data to Medicare data and sought to create a risk prediction model for long-term mortality after lung cancer resection in patients older than 65 years. METHODS: The STS-GTSD was linked to Medicare data for lung cancer resections from 2002 to 2013 as previously reported. Successful linkage was performed in 29,899 lung cancer resection patients. Cox proportional hazards modeling was used to create a long-term survival model. Variable selection was performed using statistically significant univariate factors and known clinical predictors of outcome. Calibration was assessed by dividing the cohort into deciles of predicted survival and discrimination assessed with a C-statistic corrected for optimism via 1,000 bootstrap replications. RESULTS: Median age was 73 years (interquartile range, 68 to 78 years), and 48% of the patients were male. Of the 29,094 patients with nonmissing pathologic stage, 69% were stage I, 18% stage II, 11% stage III, and 2% stage IV. Procedure performed was lobectomy in 69%, bilobectomy in 3%, pneumonectomy in 3%, segmentectomy in 7%, sleeve lobectomy in 1%, and wedge resection in 17%. Thoracoscopic approach was performed in 47% of resections. The final Cox model reveals that stage and age are the strongest predictors of long-term survival. Even after controlling for stage, wedge resection, segmentectomy, bilobectomy, and pneumonectomy are all associated with increased hazard of death in comparison with lobectomy. Thoracoscopic approach is associated with improved long-term survival in comparison with thoracotomy. Other modifiable predictive factors include smoking and low body mass index. Calibration of the model demonstrates excellent performance across all survival deciles and a C-statistic of 0.694. CONCLUSIONS: The STS-GTSD-Medicare long-term risk model includes several novel factors associated with mortality. Although medical factors predict long-term survival, age and stage are the strong predictors. Despite this, procedure choice and thoracoscopic/open approach are potentially modifiable predictors of long-term survival after lung cancer resection.

Full Text

Duke Authors

Cited Authors

  • Onaitis, MW; Furnary, AP; Kosinski, AS; Kim, S; Boffa, D; Tong, BC; Cowper, P; Jacobs, JP; Wright, CD; Putnam, JB; Fernandez, FG

Published Date

  • January 2018

Published In

Volume / Issue

  • 105 / 1

Start / End Page

  • 309 - 316

PubMed ID

  • 29174391

Electronic International Standard Serial Number (EISSN)

  • 1552-6259

Digital Object Identifier (DOI)

  • 10.1016/j.athoracsur.2017.06.071


  • eng

Conference Location

  • Netherlands