The Society of Thoracic Surgeons Lung Cancer Resection Risk Model: Higher Quality Data and Superior Outcomes

Area of Science:

• Thoracic Surgery
• Oncology
• Data Science

Background:

• The Society of Thoracic Surgeons (STS) develops risk-adjustment models for quality improvement in cardiothoracic surgery.
• An updated risk model for lung cancer resection was developed using a contemporary cohort from the STS General Thoracic Surgery Database (GTSD).

Purpose of the Study:

• To update the STS risk-adjustment model for lung cancer resections.
• To identify contemporary predictors of adverse events following lung cancer surgery.

Main Methods:

• Utilized data from 27,844 lung cancer resections performed between January 1, 2012, and December 31, 2014, from the STS GTSD.
• Employed logistic regression to develop risk models for operative mortality, major morbidity, and a composite outcome.

Main Results:

• Operative mortality was 1.4%, major morbidity was 9.1%, and the composite rate was 9.5%.
• Key predictors of mortality included age, male sex, pulmonary function, comorbidities (e.g., coronary artery disease, renal dysfunction), ASA rating, thoracotomy, induction therapy, reoperation, tumor stage, and extent of resection.
• For major morbidity, cigarette smoking emerged as a risk factor, while tumor stage and certain comorbidities became less significant.

Conclusions:

• Lung cancer resection demonstrates low operative mortality and complication rates within the GTSD.
• The updated STS risk models provide refined predictions, incorporating new factors like prior thoracic surgery.
• Continuous data auditing and reporting within the GTSD ensure the ongoing evolution and accuracy of risk models for quality assurance.