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. 2022 Sep 6:12:951557.
doi: 10.3389/fonc.2022.951557. eCollection 2022.

Predictive value of baseline metabolic tumor volume for non-small-cell lung cancer patients treated with immune checkpoint inhibitors: A meta-analysis

Ke Zhu  1   2 , Danqian Su  1   2 , Jianing Wang  1   2 , Zhouen Cheng  1   2 , Yiqiao Chin  1   2 , Luyin Chen  1   2 , Chingtin Chan  1   2 , Rongcai Zhang  1   2 , Tianyu Gao  1 , Xiaosong Ben  3 , Chunxia Jing  1   4
Affiliations

Predictive value of baseline metabolic tumor volume for non-small-cell lung cancer patients treated with immune checkpoint inhibitors: A meta-analysis

Ke Zhu et al. Front Oncol. .

Abstract

Background: Immune checkpoint inhibitors (ICIs) have emerged as a promising treatment option for advanced non-small-cell lung cancer (NSCLC) patients, highlighting the need for biomarkers to identify responders and predict the outcome of ICIs. The purpose of this study was to evaluate the predictive value of baseline standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) derived from 18F-FDG-PET/CT in advanced NSCLC patients receiving ICIs.

Methods: PubMed and Web of Science databases were searched from January 1st, 2011 to July 18th, 2022, utilizing the search terms "non-small-cell lung cancer", "PET/CT", "standardized uptake value", "metabolic tumor volume", " total lesion glycolysis", and "immune checkpoint inhibitors". Studies that analyzed the association between PET/CT parameters and objective response, immune-related adverse events (irAEs) and prognosis of NSCLC patients treated with ICIs were included. We extracted the hazard ratio (HR) with a 95% confidence interval (CI) for progression-free survival (PFS) and overall survival (OS). We performed a meta-analysis of HR using Review Manager v.5.4.1.

Results: Sixteen studies were included for review and thirteen for meta-analysis covering 770 patients. As for objective response and irAEs after ICIs, more studies with consistent assessment methods are needed to determine their relationship with MTV. In the meta-analysis, low SUVmax corresponded to poor PFS with a pooled HR of 0.74 (95% CI, 0.57-0.96, P=0.02). And a high level of baseline MTV level was related to shorter PFS (HR=1.45, 95% CI, 1.11-1.89, P<0.01) and OS (HR, 2.72; 95% CI, 1.97-3.73, P<0.01) especially when the cut-off value was set between 50-100 cm3. SUVmean and TLG were not associated with the prognosis of NSCLC patients receiving ICIs.

Conclusions: High level of baseline MTV corresponded to shorter PFS and OS, especially when the cut-off value was set between 50-100 cm3. MTV is a potential predictive value for the outcome of ICIs in NSCLC patients.

Keywords: PET/CT (18)F-FDG; immune checkpoint inhibitor; metabolic tumor volume; non-small-cell lung cancer; standardized uptake value.

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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
Flowchart diagram for the literature search.
Figure 2
Figure 2
Results of quality assessment.
Figure 3
Figure 3
Forest plots of hazard ratios comparing progression free survival (A) or overall survival (B) of patients with high level versus low level max standardized uptake value treating with immune checkpoint inhibitors.
Figure 4
Figure 4
Forest plots of hazard ratios comparing progression free survival (A) or overall survival (B) of patients with high level versus low level mean standardized uptake value treating with immune checkpoint inhibitors.
Figure 5
Figure 5
Forest plots of hazard ratios comparing progression free survival (A) or overall survival (B) of patients with high level versus low level metabolic tumor volume treating with immune checkpoint inhibitors.
Figure 6
Figure 6
Forest plots of hazard ratios comparing progression free survival (A) or overall survival (B) of patients with high level versus low level total lesion glycolysis treating with immune checkpoint inhibitors.
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References

    1. World Health Organization . Cancer (2020). Available at: https://www.who.int/news-room/fact-sheets/detail/cancer (Accessed December 13, 2021).
    1. Salehi-Rad R, Li R, Paul MK, Dubinett SM, Liu B. The biology of lung cancer: Development of more effective methods for prevention, diagnosis, and treatment. Clin Chest (2020) 41(1):25–38. doi: 10.1016/j.ccm.2019.10.003 - DOI - PubMed
    1. Wang BY, Huang JY, Chen HC, Lin CH, Lin SH, Hung WH, et al. . The comparison between adenocarcinoma and squamous cell carcinoma in lung cancer patients. J Cancer Res Clin Oncol (2020) 146(1):43–52. doi: 10.1007/s00432-019-03079-8 - DOI - PMC - PubMed
    1. Cancer. lung cancer - non-small cell: Statistics (2021). Available at: https://www.cancer.net/cancer-types/lung-cancer-non-small-cell/statistics (Accessed December 13, 2021).
    1. Osmani L, Askin F, Gabrielson E, Li QK. Current WHO guidelines and the critical role of immunohistochemical markers in the subclassification of non-small cell lung carcinoma (NSCLC): Moving from targeted therapy to immunotherapy. Semin Cancer Biol (2018) 52:103–9. doi: 10.1016/j.semcancer.2017.11.019 - DOI - PMC - PubMed

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