Comparison Between Wedge Resection and Lobectomy/Segmentectomy for Early-Stage Non-small Cell Lung Cancer: A Bayesian Meta-analysis and Systematic Review

Yucong Shi, Sizhi Wu, Shengsuo Ma, Yiwen Lyu, Huachong Xu, Li Deng, Xiaoyin Chen, Yucong Shi, Sizhi Wu, Shengsuo Ma, Yiwen Lyu, Huachong Xu, Li Deng, Xiaoyin Chen

Abstract

Background: Surgery has become an accepted method for the treatment of early-stage non-small cell lung cancer (NSCLC). The purpose of this Bayesian meta-analysis was to compare the overall survival (OS), disease-free survival (DFS), and relapse-free survival (RFS) between wedge resection and lobectomy/segmentectomy for treatment of early-stage NSCLC.

Methods: Eligible studies were retrieved from Web of Science, PubMed, MEDLINE, Cochrane Library, EMBASE, CNKI, and WanFang up to July 2021 and screened based on established selection criteria. The Bayesian meta-analysis was performed with the combination of the reported survival outcomes of the individual studies using a random-effect model. The OS, DFS, and RFS of the wedge resection group was compared with the lobectomy/segmentectomy group. The hazard ratio (HR) and standard error were extracted or calculated for each study using the Kaplan-Meier method.

Results: This study was registered with PROSPERO (INPLASY202080090).The pooled OS hazard ratio between segmentectomy and lobectomy was 1.1 [95% confidence interval (CI) 0.92-1.4], the pooled HR between lobectomy and wedge resection was 0.71 [95% CI 0.52-0.96], and the pooled HR between segmentectomy and wedge was 0.80 [95% CI 0.56-1.10]. The pooled HR of DFS or RFS was not statistically significant among the three surgical approaches.

Conclusions: Patients with early-stage NSCLC received lobectomy had the lowest hazard ratio of OS than patients received wedge resection, indicating that the overall survival of patients received lobectomy was higher than patients received wedge resection. However, regarding DFS and RFS, the three surgical approaches showed no significant difference.

Keywords: Meta analysis; Non-small cell lung cancer; Surgery method.

Conflict of interest statement

The author reports no conflicts of interest in this work.

© 2021. Society of Surgical Oncology.

Figures

Fig. 1
Fig. 1
Selection of studies for systematic review
Fig. 2
Fig. 2
Network meta-analysis of eligible comparisons for a OS, b DFS, and c RFS. Solid lines connect treatments that are directly compared in at least one study. Interrupted lines show the indirect comparisons for the treatments that have not been previously compared head-to-head and is formulated through the network model. Studies contributing with only one arm are not presented. Distances are for plot clarity alone. OS overall survival, DFS disease-free survival, RFS relapse-free survival
Fig. 3
Fig. 3
Bayesian meta-analysis of hazard ratio (HR) for OS. a Forest plot compared with segmentectomy. b Forest plot compared with lobectomy. c Forest plot compared with wedge resection. d Rankogram bar chart representing the ranking probability of each intervention. The X-axis is the intervention measure, and the Y-axis is the ranking probability. It represents the probability that the intervention is ranked in the NTH place. e Trajectories of different iterations and density map of different iterations. The pre-iteration times and the iteration times were set to 5000 and 20,000. Each Markov Chain Monte Carlo (MCMC) chain has reached stable fusion from the initial part. The overlapping area accounts for most of the fluctuation range of the chain in the subsequent calculation. The fluctuation of a single chain cannot be recognized by the naked eye. The convergence degree is satisfactory. Density graph showing the distribution of a posteriori value of a parameter. Its function is the same as that of a trajectory graph, which is used to diagnose the degree of a model. The value N represents the number of iterations. The value of Bandwidth represents the difference between the posterior distribution and the prior distribution. The smaller the value is, the smaller the difference between the distribution range of the parameter posterior value and the preset distribution range is. The curve distribution is normal distribution, and the convergence degree of the model is satisfactory. CI confidence interval, S segmentectomy, L lobectomy, W wedge resection, RFS relapse-free survival
Fig. 4
Fig. 4
Bayesian meta-analysis of hazard ratio (HR) for DFS. a Forest plot compared with segmentectomy. b Forest plot compared with lobectomy. c Forest plot compared with wedge resection. d Rankogram is a bar chart representing the ranking probability of each intervention. The X-axis is the intervention measure, and the Y-axis is the ranking probability. It represents the probability that the intervention is ranked in the NTH place. e Trajectories of different iterations and density map of different iterations. The convergence degree is satisfactory. The curve distribution is normal distribution. CI confidence interval, S segmentectomy, L lobectomy, W wedge resection, RFS relapse-free survival
Fig. 5
Fig. 5
Bayesian meta-analysis of hazard ratio (HR) for RFS. a Forest plot compared with segmentectomy. b Forest plot compared with lobectomy; c Forest plot compared with wedge resection. d Rankogram is a bar chart representing the ranking probability of each intervention. The X-axis is the intervention measure, and the Y-axis is the ranking probability. It represents the probability that the intervention is ranked in the NTH place. e Trajectories of different iterations and density map of different iterations. The convergence degree is satisfactory. The curve distribution is normal distribution. CI confidence interval; S segmentectomy; L lobectomy; W wedge resection; RFS relapse-free survival
Fig. 6
Fig. 6
Risk of bias in each included study. Review authors' judgements about each risk of bias item for each included study. Analyze from the following aspects: random sequence generation (selection bias), Allocation concealment (selection bias), Blinding of participants and personnel (performance bias), Blinding of outcome assessment (detection bias), Incomplete outcome data (attrition bias), Selective reporting (reporting bias), and other bias. +, low risk; −, high risk; ?, unclear risk)
Fig. 7
Fig. 7
Summary of risk of bias

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