Systematic review and meta‑analysis of factors predicting postoperative lung function after lung cancer resection

Abstract

INTRODUCTION:

Lung resection continues to be the most effective treatment for early‑stage lung cancer. Prediction of postoperative lung function is particularly important when evaluating patient eligibility for surgery, as it helps assess the likelihood of experiencing difficulty breathing after the operation.

AIM:

We aimed to identify the most common methods used to predict postoperative lung function in clinical practice and to compare their accuracy.

MATERIALS AND METHODS:

A systematic review and meta‑analysis were performed to synthesize research focused on the prediction of postoperative lung function. A total of 10 studies were included in the analysis. The Cochrane risk of bias tool was utilized to evaluate the risk of bias in the studies. Additionally, a meta‑analysis of the mean difference between the predicted and measured values of forced expiratory volume in 1 second (FEV ₁) was conducted. The I ² value was computed as a metric of coherence among studies, while funnel plots and the Begg test were used to evaluate the likelihood of publication bias.

RESULTS:

The analyzed studies had a low risk of bias. The meta‑analysis showed that computed tomography (CT) volume and density measurement had the highest level of accuracy for predicting postoperative FEV ₁ , with a mean difference between the predicted and actual value of 83 ml (95% CI, 41–116).

CONCLUSIONS:

The results indicate that using CT volume and density is the optimal method for predicting postoperative FEV ₁ . Additional research is necessary to establish the connection between the type of surgical procedure, adopted thresholds, and outcomes reported by patients.