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Meta-Analysis
. 2022 Jul 28:13:968729.
doi: 10.3389/fimmu.2022.968729. eCollection 2022.

The impact of antibiotic use on clinical features and survival outcomes of cancer patients treated with immune checkpoint inhibitors

Jiaxin Zhou  1   2 , Guowei Huang  3 , Wan-Ching Wong  4 , Da-Hai Hu  2 , Jie-Wen Zhu  5 , Ruiman Li  1 , Hong Zhou  1
Affiliations
Meta-Analysis

The impact of antibiotic use on clinical features and survival outcomes of cancer patients treated with immune checkpoint inhibitors

Jiaxin Zhou et al. Front Immunol. .

Abstract

Background: Nowadays, immune checkpoint inhibitors (ICIs) have become one of the essential immunotherapies for cancer patients. However, the impact of antibiotic (ATB) use on cancer patients treated with ICIs remains controversial.

Methods: Our research included retrospective studies and a randomized clinical trial (RCT) with cancer patients treated with ICIs and ATB, from the public database of PubMed, Web of Science, Embase, Cochrane, clinical trials, and JAMA. The survival outcomes included progression-free survival (PFS) and overall survival (OS). Meanwhile, hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated, and subgroup analyses were performed to determine the concrete association between ATB use and the prognosis of cancer patients treated in ICIs.

Results: Our results revealed that ATB use was associated with poor survival outcomes, including OS (HR: 1.94, 95% CI: 1.68-2.25, p <0.001) and PFS (HR: 1.83, 95% CI: 1.53-2.19, p <0.001). The subgroup analysis learned about the association between ATB use and the prognosis of cancer patients with ICI treatment, including 5 cancer types, 3 kinds of ICI, 5 different ATP windows, broad-spectrum ATB class, and ECOG score. ATB treatment was associated with poor OS of non-small-cell lung cancer (NSCLC), renal cell carcinoma (RCC), esophageal cancer (EC), and melanoma (MEL) in patients treated in ICIs, while non-small-cell lung cancer (NSCLC) and renal cell carcinoma (RCC) were associated with poor PFS. Meanwhile, it was strongly related to the ICI type and ATB window. Furthermore, it is firstly mentioned that the use of broad-spectrum ATB class was strongly associated with poor PFS.

Conclusion: In conclusion, our meta-analysis indicated that ATB use was significantly associated with poor OS and PFS of cancer patients treated with ICI immunotherapy, especially for patients with ATB use in the period of (-60 days; +30 days) near the initiation of ICI treatment. Also, different cancer types and the ICI type can also impact the survival outcome. This first reveals the strong relationship between the broad-spectrum ATB class and poor PFS. Still, more studies are needed for further study.

Keywords: PD-1; PD-L1; antibiotic; immune checkpoint inhibitor; survival outcomes.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flow diagram of the study search and selection in this meta-analysis.
Figure 2
Figure 2
The forest plot showing the relationship between ATB use and OS, PFS in cancer patients treated with ICIs. Overall survival (OS), progress-free survival (PFS); CI, confidential interval; Random, random-effects model; The random-effects model was adopted. (A) Overall survival (OS). (B) Progress-free survival (PFS). (A) Relationship between ATB use and OS in cancer patients treated with ICIs. (B) Relationship between ATB use and PFS in cancer patients treated with ICIs.
Figure 3
Figure 3
The forest plot showing the relationship between ATB use and OS, PFS in cancer patients treated with ICIs, based on randomized controlled trial (RCT). Overall survival (OS), progress-free survival (PFS); CI, confidential interval; Random, random-effects model. The random-effects model was adopted. (A) Overall survival (OS). (B) progress-free survival (PFS).
Figure 4
Figure 4
The subgroup analysis between ATB use and cancer prognosis (OS + PFS) of RCC and NSCLC cancer patients treated with ICIs. (A) The relationship between ATB use and OS of NSCLC patients treated with ICIs. (B) The relationship between ATB use and PFS of RCC patients treated with ICIs. (C) The relationship between ATB use and OS of esophagus cancer patients treated with ICIs. (D) The relationship between ATB use and OS of melanoma patients treated with ICIs. (E) The relationship between ATB use and PFS of NSCLC patients treated with ICIs. (F) The relationship between ATB use and PFS of RCC patients treated with ICIs.
Figure 5
Figure 5
The subgroup analysis between ATB use and different immune checkpoint inhibitors of cancer patients treated with ICIs. (A) The association between ATB use and OS in cancer patients treated with the combination of PD-1 inhibitor and PD-L1 inhibitor. (B) The association between ATB use and OS in cancer patients treated with PD-1 inhibitor. (C) The association between ATB use and OS in cancer patients treated with PD-L1 inhibitor. (D) The association between ATB use and PFS in cancer patients treated with the combination of PD-1 inhibitor and PD-L1 inhibitor. (E) The association between ATB use and PFS in cancer patients treated with PD-1 inhibitor.
Figure 6
Figure 6
In different ATB windows, the subgroup analysis between ATB use and OS of cancer patients treated with ICIs. (A) ATB window (−30 days, 0 day); (B) ATB window (−30 days, 30 days); (C) ATB window (−60 days, 0 days); (D) ATB window (−60 days, 30 days); and (E) ATB window (0 days, 30 day).
Figure 7
Figure 7
In different ATB window, the subgroup analysis between ATB use and PFS of cancer patients treated with ICIs. (A) ATB window (-30 days, 30 day); (B) ATB window (-60 days, 0 days); (C) ATB window (-60 days, 30 days); (D) ATB window (0 days, 30 days).
Figure 8
Figure 8
In broad- spectrum ATB class, the subgroup analysis between ATB use and PFS of cancer patients treated with ICIs.
See this image and copyright information in PMC

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