Differential influence of antibiotic therapy and other medications on oncological outcomes of patients with non-small cell lung cancer treated with first-line pembrolizumab versus cytotoxic chemotherapy
- PMID: 33827906
- PMCID: PMC8031700
- DOI: 10.1136/jitc-2021-002421
Differential influence of antibiotic therapy and other medications on oncological outcomes of patients with non-small cell lung cancer treated with first-line pembrolizumab versus cytotoxic chemotherapy
Abstract
Background: Some concomitant medications including antibiotics (ATB) have been reproducibly associated with worse survival following immune checkpoint inhibitors (ICIs) in unselected patients with non-small cell lung cancer (NSCLC) (according to programmed death-ligand 1 (PD-L1) expression and treatment line). Whether such relationship is causative or associative is matter of debate.
Methods: We present the outcomes analysis according to concomitant baseline medications (prior to ICI initiation) with putative immune-modulatory effects in a large cohort of patients with metastatic NSCLC with a PD-L1 expression ≥50%, receiving first-line pembrolizumab monotherapy. We also evaluated a control cohort of patients with metastatic NSCLC treated with first-line chemotherapy. The interaction between key medications and therapeutic modality (pembrolizumab vs chemotherapy) was validated in pooled multivariable analyses.
Results: 950 and 595 patients were included in the pembrolizumab and chemotherapy cohorts, respectively. Corticosteroid and proton pump inhibitor (PPI) therapy but not ATB therapy was associated with poorer performance status at baseline in both the cohorts. No association with clinical outcomes was found according to baseline statin, aspirin, β-blocker and metformin within the pembrolizumab cohort. On the multivariable analysis, ATB emerged as a strong predictor of worse overall survival (OS) (HR=1.42 (95% CI 1.13 to 1.79); p=0.0024), and progression free survival (PFS) (HR=1.29 (95% CI 1.04 to 1.59); p=0.0192) in the pembrolizumab but not in the chemotherapy cohort. Corticosteroids were associated with shorter PFS (HR=1.69 (95% CI 1.42 to 2.03); p<0.0001), and OS (HR=1.93 (95% CI 1.59 to 2.35); p<0.0001) following pembrolizumab, and shorter PFS (HR=1.30 (95% CI 1.08 to 1.56), p=0.0046) and OS (HR=1.58 (95% CI 1.29 to 1.94), p<0.0001), following chemotherapy. PPIs were associated with worse OS (HR=1.49 (95% CI 1.26 to 1.77); p<0.0001) with pembrolizumab and shorter OS (HR=1.12 (95% CI 1.02 to 1.24), p=0.0139), with chemotherapy. At the pooled analysis, there was a statistically significant interaction with treatment (pembrolizumab vs chemotherapy) for corticosteroids (p=0.0020) and PPIs (p=0.0460) with respect to OS, for corticosteroids (p<0.0001), ATB (p=0.0290), and PPIs (p=0.0487) with respect to PFS, and only corticosteroids (p=0.0033) with respect to objective response rate.
Conclusion: In this study, we validate the significant negative impact of ATB on pembrolizumab monotherapy but not chemotherapy outcomes in NSCLC, producing further evidence about their underlying immune-modulatory effect. Even though the magnitude of the impact of corticosteroids and PPIs is significantly different across the cohorts, their effects might be driven by adverse disease features.
Keywords: immunotherapy; lung neoplasms.
© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
Conflict of interest statement
Competing interests: AC received speaker fees and grant consultancies by Astrazeneca, MSD, BMS, Roche, Novartis, Istituto Gentili and Astellas. RG received speaker fees and grant consultancies by Astrazeneca and Roche. JA reports receiving commercial research grants from Amphera and Roche, holds ownership interest (including patents) in Amphera BV, and is a consultant/advisory board member for Amphera, Boehringer Ingelheim, Bristol-Myers Squibb, Eli-Lilly, MSD and Roche. AF received grant consultancies by Roche, Pfizer, Astellas and BMS. FM received grant consultancies by MSD and Takeda. RC received speaker fees by BMS, MSD, Takeda, Pfizer, Roche and Astrazeneca. CG received speaker fees/grant consultancies by Astrazeneca, BMS, Boehringer-Ingelheim, Roche and MSD. MR received honoraria for scientific events by Roche, Astrazeneca, BMS, MSD and Boehringer Ingelheim. EB received speaker and travel fees from MSD, Astra-Zeneca, Pfizer, Helsinn, Eli-Lilly, BMS, Novartis and Roche; grant consultancies by Roche and Pfizer. MCG received grants from MSD, Astrazeneca, Novartis, Roche, Pfizer, Celgene, Tiziana Sciences, Clovis, Merck, Bayer, GSK, Spectrum, Blueprint, personal fees from Eli Lilly, Boheringer, Otsuka Pharma, Astrazeneca, Novartis, BMS, Roche, Pfizer, Celgene, Incyte, Inivata, Takeda, Bayer, MSD, Sanofi, Seattle Genetics, Daichii Sankyo, other financial supports from Eli Lilly, Astrazeneca, Novartis, BMS, Roche, Pfizer, Celgene, Tiziana Sciences, Clovis, Merck Serono, MSD, GSK, Spectrum and Blueprint. AA received grant consultancies by Takeda, MSD, BMJ, Astrazeneca, Roche and Pfizer. MDM received research funding from Tesaro-GlaxoSmithKline; acted in a consulting/advisory role for Novartis, Pfizer, Eisai, Takeda, Janssen, Astellas, Roche, AstraZeneca. FP received grant consultancies by MSD and Astrazeneca. PB received grant consultancies by Astrazeneca and Boehringer-Ingelheim. DJP received lecture fees from ViiV Healthcare, Bayer Healthcare and travel expenses from BMS and Bayer Healthcare; consulting fees for Mina Therapeutics, EISAI, Roche, Astra Zeneca; received research funding (to institution) from MSD, BMS. All other authors declare no competing interests. DJP is supported by grant funding from the Wellcome Trust Strategic Fund (PS3416) and has received direct project funding by the NIHR Imperial Biomedical Research Centre (BRC), ITMAT Push for Impact Grant Scheme 2019. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.
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