Predicting Postoperative Lung Function Following Lung Cancer Resection: A Systematic Review and Meta-analysis

Area of Science:

• Pulmonary Medicine
• Thoracic Surgery
• Radiology

Background:

• Lung resection is the standard treatment for early-stage lung cancer.
• Accurate prediction of postoperative lung function is essential for surgical candidate selection and preventing dyspnea.
• Various techniques exist for predicting postoperative lung function, but their comparative accuracy is unclear.

Purpose of the Study:

• To identify and compare the accuracy of different techniques used for predicting postoperative lung function.
• To determine the optimal method for predicting forced expiratory volume in 1 second (FEV1) after lung surgery.

Main Methods:

• A systematic review and meta-analysis of 135 studies published up to February 18, 2018.
• Assessment of study risk of bias using PROBAST criteria.
• Identification of 17 studies with a low risk of bias for inclusion in the meta-analysis.

Main Results:

• Computed tomography (CT) volume and density measurements demonstrated the highest accuracy (mean difference 71 ml) and precision (standard deviation 207 ml) for predicting FEV1.
• Limited evidence was found for techniques predicting lung gas transfer capacity.

Conclusions:

• CT-based volume and density measurements are recommended as the preferred technique for predicting postoperative FEV1.
• Further research is needed to correlate proposed methods and thresholds with patient-reported outcomes.