Predicting complication risks after sleeve lobectomy for non-small cell lung cancer

Area of Science:

• Thoracic Surgery
• Surgical Oncology
• Pulmonary Medicine

Background:

• Sleeve lobectomy presents significant postoperative complication risks.
• Accurate risk assessment is crucial for surgical decision-making and perioperative care optimization.

Purpose of the Study:

• To develop and validate risk stratification models for predicting postoperative complications after sleeve lobectomy.
• To quantify the probability and severity of complications in non-small cell lung cancer (NSCLC) patients.

Main Methods:

• Retrospective analysis of 691 NSCLC patients undergoing sleeve lobectomy (July 2016 - December 2019).
• Development and validation of logistic regression models to predict overall, major, and minor complications.
• Kaplan-Meier method used to explore the prognostic impact of complications.

Main Results:

• 33.5% of patients experienced complications (5.1% major, 28.5% minor).
• Models demonstrated strong predictive performance: AUC 0.853 for overall complications, 0.751 for major complications.
• Models for minor complications showed AUCs ranging from 0.78 to 0.89.

Conclusions:

• Developed risk stratification models accurately predict complication probability and severity post-sleeve lobectomy.
• These models can inform clinical decision-making for NSCLC patients undergoing this procedure.
• Postoperative complications are significantly associated with a poorer prognosis.