Impact of Antibiotic Therapy and Metabolic Parameters in Non-Small Cell Lung Cancer Patients Receiving Checkpoint Inhibitors
Open accessAbstract
Introduction: In the current study, we aimed to assess the impact of antibiotics (ATB) and metabolic parameters on clinical outcome of non-small cell lung carcinoma (NSCLC) patients treated with immune checkpoint inhibitors (ICI). Methods: Data from fifty NSCLC patients referred for ICI between December 2015 and May 2019 were analyzed. All patients underwent 18F-fluorodeoxyglucose positron emission tomography computed tomography (18F-FDG PET/CT) and contrast-enhanced CT at baseline and for response assessment after 6–8 weeks. Patients who received ATB within 1 month before or after the first dose of ICI were compared with those who did not. Response assessment according to iRECIST and EORTC was evaluated, as well as progression-free survival (PFS) and overall survival (OS). For semi-quantitative parameters, we computed metabolic tumor volume (MTV), total lesion glycolysis (TLG) and their variations (∆). Results: Twenty NSCLC cases of 50 (40%) had received ATB. Patients receiving ATB had a higher number of metastases (p = 0.046), and were associated with an elevated tumor burden, expressed by TLG (687 vs. 235.3, p = 0.007) and MTV (125.6 vs. 40.6, p = 0.002), compared to no-ATB patients. According to iRECIST, progressive disease rate was significantly higher for ATB group (64.7% vs. 27.6%, p = 0.029). Likewise, PFS was shorter for ATB compared to no-ATB (median 4.1 vs. 12.4 months, p = 0.004), while no difference for OS was detected. On multivariate analysis, the effect of ATB remained significant for poor PFS along with performance status (ECOG ≥ 1), and ∆SUVmax. Conclusions: ATB therapy seems to be associated with a worse treatment response, PFS, and higher metabolic tumor burden in NSCLC patients treated with ICI.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Administration of high-risk antibiotics likely constitutes a surrogate for poor disease status and increased systemic inflammation before CAR-T, rather than causally driving altered CAR-T responsiveness.
“However, our results suggest that administration of these classes of antibiotics constitutes a likely surrogate for poor disease status and a state of increased systemic inflammation prior to initiation of CAR-T cell therapy, as was recently suggested in cancer patients treated with other ICBs28,35.”
From A non-antibiotic-disrupted gut microbiome is associated with clinical responses to CD19-CAR-T cell cancer immunotherapy (2023) · cites this paper as [35]
Administration of these antibiotics likely serves as a surrogate for poor disease status and increased systemic inflammation before CAR-T initiation.
“However, our results suggest that administration of these classes of antibiotics constitutes a likely surrogate for poor disease status and a state of increased systemic inflammation prior to initiation of CAR-T cell therapy, as was recently suggested in cancer patients treated with other ICBs28,35.”
From A non-antibiotic-disrupted gut microbiome is associated with clinical responses to CD19-CAR-T cell cancer immunotherapy (2023) · cites this paper as [35]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1)
Eisenhauer, E. A., Therasse, P., Bogaerts, J., Schwartz, L. H., Sargent, D., Ford, R., Dancey, J., Arbuck, S., Gwyther, S., Mooney, M., et al. (2009) · European Journal of Cancer · doi:10.1016/j.ejca.2008.10.026 · Cited by 29,534 · see citing works
Pembrolizumab versus Chemotherapy for PD-L1-Positive Non-Small-Cell Lung Cancer
Reck, M., Rodríguez-Abreu, D., Robinson, A. G., Hui, R., Csőszi, T., Fülöp, A., Gottfried, M., Peled, N., Tafreshi, A., Cuffe, S., et al. (2016) · New England Journal of Medicine · doi:10.1056/nejmoa1606774 · Cited by 10,089 · see citing works
Nivolumab versus docetaxel in advanced nonsquamous non-small-cell lung cancer
Borghaei, H., Paz-Ares, L., Horn, L., Spigel, D. R., Steins, M., Ready, N. E., Chow, L. Q., Vokes, E. E., Felip, E., Holgado, E., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1507643 · Cited by 9,335 · see citing works
Pembrolizumab versus Ipilimumab in Advanced Melanoma
Robert, C., Schachter, J., Long, G. V., Arance, A., Grob, J. J., Mortier, L., Daud, A., Carlino, M. S., McNeil, C., Lotem, M., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1503093 · Cited by 5,887 · see citing works
Nivolumab versus Everolimus in Advanced Renal-Cell Carcinoma
Motzer, R. J., Escudier, B., McDermott, D. F., George, S., Hammers, H. J., Srinivas, S., Tykodi, S. S., Sosman, J. A., Procopio, G., Plimack, E. R., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1510665 · Cited by 5,807 · see citing works
Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors
Routy, B., Le Chatelier, E., Derosa, L., Duong, C. P. M., Alou, M. T., Daillère, R., Fluckiger, A., Messaoudene, M., Rauber, C., Roberti, M. P., et al. (2018) · Science · doi:10.1126/science.aan3706 · Cited by 5,671 · see citing works
Primary, Adaptive, and Acquired Resistance to Cancer Immunotherapy
Sharma, P., Hu-Lieskovan, S., Wargo, J. A., & Ribas, A. (2017) · Cell · doi:10.1016/j.cell.2017.01.017 · Cited by 5,588 · see citing works
Nivolumab for Recurrent Squamous-Cell Carcinoma of the Head and Neck
Ferris, R. L., Blumenschein, G., Fayette, J., Guigay, J., Colevas, A. D., Licitra, L., Harrington, K., Kasper, S., Vokes, E. E., Even, C., et al. (2016) · New England Journal of Medicine · doi:10.1056/nejmoa1602252 · Cited by 5,101 · see citing works
Anticancer immunotherapy by CTLA-4 blockade relies on the gut microbiota
Vétizou, M., Pitt, J. M., Daillère, R., Lepage, P., Waldschmitt, N., Flament, C., Rusakiewicz, S., Routy, B., Roberti, M. P., Duong, C. P. M., et al. (2015) · Science · doi:10.1126/science.aad1329 · Cited by 3,488 · see citing works
FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0
Boellaard, R., Delgado-Bolton, R., Oyen, W. J. G., Giammarile, F., Tatsch, K., Eschner, W., Verzijlbergen, F. J., Barrington, S. F., Pike, L. C., Weber, W. A., et al. (2015) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-014-2961-x · Cited by 3,303 · see citing works
The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients
Matson, V., Fessler, J., Bao, R., Chongsuwat, T., Zha, Y., Alegre, M.-L., Luke, J. J., & Gajewski, T. F. (2018) · Science · doi:10.1126/science.aao3290 · Cited by 3,107 · see citing works
iRECIST: guidelines for response criteria for use in trials testing immunotherapeutics
Seymour, L., Bogaerts, J., Perrone, A., Ford, R., Schwartz, L. H., Mandrekar, S., Lin, N. U., Litière, S., Dancey, J., Chen, A., et al. (2017) · The Lancet Oncology · doi:10.1016/s1470-2045(17)30074-8 · Cited by 2,472 · see citing works
Young, H. E., Baum, R. P., Cremerius, U., Herholz, K., Hoekstra, O. S., Lammertsma, A. A., Pruim, J., & Price, P. (1999) · European Journal of Cancer · doi:10.1016/s0959-8049(99)00229-4 · Cited by 1,716 · see citing works
Schwabe, R. F., & Jobin, C. (2013) · Nature Reviews Cancer · doi:10.1038/nrc3610 · Cited by 1,689 · see citing works
T-cell invigoration to tumour burden ratio associated with anti-PD-1 response
Huang, A. C., Postow, M. A., Orlowski, R. J., Mick, R., Bengsch, B., Manne, S., Xu, W., Harmon, S., Giles, J. R., Wenz, B., et al. (2017) · Nature · doi:10.1038/nature22079 · Cited by 1,664 · see citing works
Chaput, N., Lepage, P., Coutzac, C., Soularue, E., Le Roux, K., Monot, C., Boselli, L., Routier, E., Cassard, L., Collins, M., et al. (2017) · Annals of Oncology · doi:10.1093/annonc/mdx108 · Cited by 1,310 · see citing works
Diem, S., Schmid, S., Krapf, M., Flatz, L., Born, D., Jochum, W., Templeton, A. J., & Früh, M. (2017) · Lung Cancer · doi:10.1016/j.lungcan.2017.07.024 · Cited by 992 · see citing works
Derosa, L., Hellmann, M. D., Spaziano, M., Halpenny, D., Fidelle, M., Rizvi, H., Long, N., Plodkowski, A. J., Arbour, K. C., Chaft, J. E., et al. (2018) · Annals of Oncology · doi:10.1093/annonc/mdy103 · Cited by 908 · see citing works
Pinato, D. J., Howlett, S., Ottaviani, D., Urus, H., Patel, A., Mineo, T., Brock, C., Power, D., Hatcher, O., Falconer, A., et al. (2019) · JAMA Oncology · doi:10.1001/jamaoncol.2019.2785 · Cited by 626 · see citing works
Metagenomic approaches for defining the pathogenesis of inflammatory bowel diseases
Peterson, D. A., Frank, D. N., Pace, N. R., & Gordon, J. I. (2008) · Cell Host & Microbe · doi:10.1016/j.chom.2008.05.001 · Cited by 503 · see citing works
Cancer and the gut microbiota: An unexpected link
Zitvogel, L., Galluzzi, L., Viaud, S., Vétizou, M., Daillère, R., Merad, M., & Kroemer, G. (2015) · Science Translational Medicine · doi:10.1126/scitranslmed.3010473 · Cited by 465 · see citing works
Tinsley, N., Zhou, C., Tan, G., Rack, S., Lorigan, P., Blackhall, F., Krebs, M., Carter, L., Thistlethwaite, F., Graham, D., et al. (2020) · The Oncologist · doi:10.1634/theoncologist.2019-0160 · Cited by 201 · see citing works
Ahmed, J., Kumar, A., Parikh, K., Anwar, A., Knoll, B. M., Puccio, C. A., Chun, H. G., Fanucchi, M. P., & Lim, S. H. (2018) · OncoImmunology · doi:10.1080/2162402x.2018.1507670 · Cited by 173 · see citing works
Zhao, S., Gao, G., Li, W., Li, X., Zhao, C., Jiang, T., Jia, Y., He, Y., Li, A., Su, C., et al. (2019) · Lung Cancer · doi:10.1016/j.lungcan.2019.01.017 · Cited by 164 · see citing works
Antibiotic therapy and outcome from immune-checkpoint inhibitors
Pinato, D. J., Gramenitskaya, D., Altmann, D. M., Boyton, R. J., Mullish, B. H., Marchesi, J. R., & Bower, M. (2019) · Journal for ImmunoTherapy of Cancer · doi:10.1186/s40425-019-0775-x · Cited by 116 · see citing works
The human microbiome, asthma, and allergy
Riiser, A. (2015) · Allergy Asthma and Clinical Immunology · doi:10.1186/s13223-015-0102-0 · Cited by 110 · see citing works
Type 2 diabetes and gut microbiome: at the intersection of known and unknown
Upadhyaya, S., & Banerjee, G. (2015) · Gut Microbes · doi:10.1080/19490976.2015.1024918 · Cited by 109 · see citing works
Antibiotic Use Does Not Appear to Influence Response to Nivolumab
Kaderbhaï, C., Richard, C., Fumet, J.-D., Aarnink, A., FOUCHER, P., Coudert, B. P., Favier, L., Lagrange, A., Limagne, E., Boidot, R., et al. (2017) · Anticancer Research · doi:10.21873/anticanres.11680 · Cited by 107 · see citing works
Ouaknine, J., de Tauriers, P. H., Duménil, C., Neveux, N., Dumoulin, J., Giraud, V., Labrune, S., Tisserand, J. C., Julié, C., Emile, J., et al. (2019) · Journal for ImmunoTherapy of Cancer · doi:10.1186/s40425-019-0658-1 · Cited by 100 · see citing works
Castello, A., Rossi, S., Mazziotti, E., Toschi, L., & Lopci, E. (2019) · Journal of Nuclear Medicine · doi:10.2967/jnumed.119.237768 · Cited by 91 · see citing works
Self-citationHuemer, F., Rinnerthaler, G., Westphal, T., Hackl, H., Hutarew, G., Gampenrieder, S. P., Weiß, L., & Greil, R. (2018) · Oncotarget · doi:10.18632/oncotarget.24751 · Cited by 88 · see citing works
Duménil, C., Massiani, M.-A., Dumoulin, J., Giraud, V., Labrune, S., Chinet, T., & Leprieur, E. G. (2018) · PLoS ONE · doi:10.1371/journal.pone.0195945 · Cited by 60 · see citing works
Guo, J., Lin, C., Lin, C.-Y., Hsieh, M., Kuo, H., Lien, M.-Y., Shao, Y., Huang, T., & Hsu, C. (2019) · Anticancer Research · doi:10.21873/anticanres.13765 · Cited by 53 · see citing works
Castello, A., Toschi, L., Rossi, S., Mazziotti, E., & Lopci, E. (2020) · Journal of Cancer Research and Clinical Oncology · doi:10.1007/s00432-020-03150-9 · Cited by 53 · see citing works
Self-citationPrognostic Value of 18 F-Fluorodeoxyglucose PET/Computed Tomography in Non–Small-Cell Lung Cancer
Cheng, G., & Huang, H. (2017) · PET Clinics · doi:10.1016/j.cpet.2017.08.006 · Cited by 34 · see citing works
Ferris, R. L., Blumenschein, G. R., Harrington, K. J., Fayette, J., Guigay, J., Colevas, A. D., Licitra, L. F., Vokes, E. E., Gillison, M. L., Even, C., et al. (2017) · Cancer Research · doi:10.1158/1538-7445.am2017-ct022 · Cited by 26 · see citing works
Impact of antibiotic use on response to treatment with immune checkpoint inhibitors.
Khan, U., Peña, C., Brouwer, J., Hoffman, K., Choudhury, A. R., Zhang, C., Thakkar, P. V., Betel, D., Sarkar, S., Sonnenberg, G. F., et al. (2019) · Journal of Clinical Oncology · doi:10.1200/jco.2019.37.4_suppl.143 · Cited by 11 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Stein-Thoeringer, C. K., Saini, N. Y., Zamir, E., Blumenberg, V., Schubert, M.-L., Mor, U., Fante, M. A., Schmidt, S., Hayase, E., Hayase, T., et al. (2023) · Nature Medicine · doi:10.1038/s41591-023-02234-6 · Cited by 255 · see citing works
- Authors
- Castello, A., Rossi, S., Toschi, L., & Lopci, E.
- Affiliations
- IRCCS Humanitas Research Hospital (IT)
- Corresponding author
- Lopci, Egesta
- Venue
- Journal of Clinical Medicine
- Publisher
- MDPI AG
- Published
- 2021-03-17
- Volume
- 10
- Issue
- 6
- Pages
- 1251
- ISSN
- 2077-0383 (ISSN-L)
- PMC
- PMC8002619
- OpenAlex
- W3138943871
- Cited by
- 36
- References
- 37
- Citations by year
- 2026: 5 · 2025: 3 · 2024: 6 · 2023: 10 · 2022: 10 · 2021: 2
- FWCI
- 2.55
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Journal of Clinical Medicine (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Associazione Italiana per la Ricerca sul Cancro (18923)
- Topics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Diagnosis and Treatment
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Treatments and Mutations
- Keywords
- non-small cell lung cancer, immune checkpoint inhibitors, antibiotic therapy, metabolic tumor volume, total lesion glycolysis, FDG PET/CT, progression-free survival, treatment response, immune-related adverse events
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review