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. 2022 Jan 1;13(2):364-372.
doi: 10.7150/jca.65374. eCollection 2022.

Association of Smoking Status with Efficacy of First-line Immune Checkpoint Inhibitors in Advanced Non-small Cell Lung Cancers: A Systematic Review and Meta-analysis

Jinchul Kim  1 , Hyerim Ha  1 , Jisun Park  1 , Jinhyun Cho  1 , Joo Han Lim  1 , Moon Hee Lee  1
Affiliations

Association of Smoking Status with Efficacy of First-line Immune Checkpoint Inhibitors in Advanced Non-small Cell Lung Cancers: A Systematic Review and Meta-analysis

Jinchul Kim et al. J Cancer. .

Abstract

Background: Although smoking status has potential as a biomarker for immune checkpoint blockade in advanced non-small cell lung cancer (NSCLC), its clinical significance remains obscure. This meta-analysis aims to assess the impact of the smoking status on the efficacy of first-line immunotherapy and to find better treatment in never-smoker and ever-smoker patients. Methods: We searched the MEDLINE, EMBASE, and Cochrane database for trials comparing immunotherapy with conventional chemotherapy as front-line treatment for advanced NSCLC. Random-effects models were used to pool estimates of hazard ratios (HRs) for overall survival with 95% confidence intervals (CIs). Predefined subgroup analysis was performed to investigate the difference in the efficacy between the single checkpoint blockade and checkpoint inhibitor plus chemotherapy combination in the never-smokers and current/former smokers. Results: Twelve trials involving 6,446 patients were included in the analysis. A statistically significant overall survival benefit over conventional chemotherapy was found for both checkpoint inhibitor monotherapy (HR, 0.71; 95% CI, 0.59-0.85) and checkpoint inhibitor plus chemotherapy (HR, 0.75; 95% CI, 0.63-0.90) in the current/former smoker group. There was no subgroup difference between monotherapy and combination treatment (p=0.67). However, there was an inconsistent survival outcome in the never-smoker group; checkpoint blockade monotherapy did not show significantly better efficacy than chemotherapy alone (HR, 1.05; 95% CI, 0.81-1.37), but combination treatment showed an overall survival benefit (HR, 0.64; 95% CI, 0.43-0.94). A significant subgroup difference existed between monotherapy and combination therapy (p=0.04). Similarly, there was a significant difference in efficacy of monotherapy between the current/former smoker and never-smoker group (p=0.01), but the efficacy of the combination treatment was comparable between the two groups (p=0.45). Conclusion: Smoking status, which is easily available information, could be used as a guide in clinical practice to choose better treatment in the front-line setting for advanced NSCLC patients.

Keywords: First-line treatment; Immune checkpoint inhibitor; Meta-analysis; Non-small cell lung cancer; Smoking.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interest exists.

Figures

Figure 1
Figure 1
Trial selection flow diagram.
Figure 2
Figure 2
Forest plot of meta-analysis comparing checkpoint inhibitor-based treatment versus chemotherapy for overall survival by smoking status. (A) never-smoker group; (B) current/former smoker group. The size of the squares corresponds to the weight of the study in the meta-analysis. The treatment effects were calculated using a random-effects model. ICI: immune checkpoint inhibitor; CI: confidence interval.
Figure 3
Figure 3
Forest plots of meta-analysis comparing checkpoint inhibitor-based treatment versus chemotherapy for overall survival according to treatment modality. (A) checkpoint inhibitor monotherapy; (B) checkpoint inhibitor plus chemotherapy combination. The size of the squares corresponds to the weight of the study in the meta-analysis. The treatment effects were calculated using a random-effects model. ICI: immune checkpoint inhibitor; CI: confidence interval.
Figure 4
Figure 4
Forest plots of meta-analysis comparing checkpoint inhibitor monotherapy versus chemotherapy for overall survival by smoking status in patients with PD-L1 expression ≥50%. The size of the squares corresponds to the weight of the study in the meta-analysis. The treatment effects were calculated using a random-effects model. ICI: immune checkpoint inhibitor; CI: confidence interval.
See this image and copyright information in PMC

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