Abstract
Objective
Guillain–Barré syndrome (GBS) induced by immune checkpoint inhibitors (ICIs) has been occasionally reported in randomized clinical trials (RCTs), but the post-marketing data are quite limited. This study aimed to comprehensively examine GBS events secondary to ICI treatments in the real-world patients based on the Food and Drug Administration Adverse Event Reporting System (FAERS).
Methods
Reports from January 2004 to March 2020 were extracted from the FAERS. GBS cases related to ICIs were identified to characterize their clinical features. The disproportionality and Bayesian analysis were performed for the detection of GBS signals associated with ICIs.
Results
In total, 149 GBS reports with ICIs as suspect drugs were screened out. These events were found to be more prevalent in adults ≥ 45 years (63.09%) and males (63.09%). The onsets of GBS were variable with a median time of 38 (range 0–628) days after ICI initiation. The outcomes tended to be severe with 61.74% hospitalization and 22.82% death. GBS events were most commonly reported in ipilimumab plus nivolumab treatment (24.83%), and this combination therapy also yielded stronger signal for GBS than other therapies based on the highest reporting odds ratio (ROR = 12.43, two-sided 95% CI = 8.62, 17.93), proportional reporting ratio (PRR = 12.39, χ2 = 300.90), information component (IC = 3.62, IC025 = 2.51) and empirical Bayes geometric mean (EBGM = 12.28, EBGM05 = 9.04).
Conclusion
As complements to the safety data from RCTs, the current pharmacovigilance research helps establish a more detailed overview of ICI-related GBS, which facilitates the understanding of this rare adverse drug effect.
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Data availability
All data have been presented in the manuscript. Other related information is available under request to the corresponding author.
References
Dizon DS, Krilov L, Cohen E, Gangadhar T, Ganz PA, Hensing TA, Hunger S, Krishnamurthi SS, Lassman AB, Markham MJ, Mayer E, Neuss M, Pal SK, Richardson LC, Schilsky R, Schwartz GK, Spriggs DR, Villalona-Calero MA, Villani G, Masters G (2016) Clinical cancer advances 2016: annual report on progress against cancer from the American Society of Clinical Oncology. J Clin Oncol 34(9):987–1011. https://doi.org/10.1200/JCO.2015.65.8427
Azoury SC, Straughan DM, Shukla V (2015) Immune checkpoint inhibitors for cancer therapy: clinical efficacy and safety. Curr Cancer Drug Targets 15(6):452–462. https://doi.org/10.2174/156800961506150805145120
Bahig H, Aubin F, Stagg J, Gologan O, Ballivy O, Bissada E, Nguyen-Tan FP, Soulieres D, Guertin L, Filion E, Christopoulos A, Lambert L, Tehfe M, Ayad T, Charpentier D, Jamal R, Wong P (2019) Phase I/II trial of Durvalumab plus Tremelimumab and stereotactic body radiotherapy for metastatic head and neck carcinoma. BMC Cancer 19(1):68. https://doi.org/10.1186/s12885-019-5266-4
Gubens MA, Sequist LV, Stevenson JP, Powell SF, Villaruz LC, Gadgeel SM, Langer CJ, Patnaik A, Borghaei H, Jalal SI, Fiore J, Saraf S, Raftopoulos H, Gandhi L (2019) Pembrolizumab in combination with ipilimumab as second-line or later therapy for advanced non-small-cell lung cancer: KEYNOTE-021 cohorts D and H. Lung Cancer 130:59–66. https://doi.org/10.1016/j.lungcan.2018.12.015
Zheng Q, Xu J, Gu X, Wu F, Deng J, Cai X, Wang G, Li G, Chen Z (2020) Immune checkpoint targeting TIGIT in hepatocellular carcinoma. Am J Transl Res 12(7):3212–3224
Kennedy LB, Salama AKS (2020) A review of cancer immunotherapy toxicity. CA Cancer J Clin 70(2):86–104. https://doi.org/10.3322/caac.21596
Astaras C, de Micheli R, Moura B, Hundsberger T, Hottinger AF (2018) Neurological adverse events associated with immune checkpoint inhibitors: diagnosis and management. Curr Neurol Neurosci Rep 18(1):3. https://doi.org/10.1007/s11910-018-0810-1
Wilgenhof S, Neyns B (2011) Anti-CTLA-4 antibody-induced Guillain-Barre syndrome in a melanoma patient. Ann Oncol 22(4):991–993. https://doi.org/10.1093/annonc/mdr028
Jacob A, Unnikrishnan DC, Mathew A, Thyagarajan B, Patel S (2016) A case of fatal Guillain-Barre syndrome from anti-PD1 monoclonal antibody use. J Cancer Res Clin Oncol 142(8):1869–1870. https://doi.org/10.1007/s00432-016-2191-7
Bristol-Myers Squibb Company, Princeton, NJ (2020) YERVOY® (ipilimumab) [package insert]. https://www.accessdata.fda.gov/drugsatfda_docs/label/2020/125377s115lbl.pdf. Accessed 25 November 2020
Bristol-Myers Squibb Company, Princeton, NJ (2020) OPDIVO® (nivolumab) [package insert]. https://www.accessdata.fda.gov/drugsatfda_docs/label/2020/125554s089lbl.pdf. Accessed 25 November 2020
Merck Sharp and Dohme Corp, Whitehouse Station, NJ (2020) KEYTRUDA® (pembrolizumab) [package insert]. https://www.accessdata.fda.gov/drugsatfda_docs/label/2020/125514s084lbl.pdf. Accessed 25 November 2020
Genentech Inc, South San Francisco, CA (2020) TECENTRIQ® (atezolizumab) [package insert]. https://www.accessdata.fda.gov/drugsatfda_docs/label/2020/761034s029lbl.pdf. Accessed 25 November 2020
EMD Serono Inc, Rockland, MA (2020) BAVENCIO® (avelumab) [package insert]. https://www.accessdata.fda.gov/drugsatfda_docs/label/2020/761049s009lbl.pdf. Accessed 25 November 2020
AstraZeneca Pharmaceuticals LP, Wilmington, DE (2020) IMFINZI® (durvalumab) [package insert]. https://www.accessdata.fda.gov/drugsatfda_docs/label/2020/761069s020lbl.pdf. Accessed 25 November 2020
Regeneron Pharmaceuticals Inc, Tarrytown, NY (2020) LIBTAYO® (cemiplimab-rwlc) [package insert]. https://www.accessdata.fda.gov/drugsatfda_docs/label/2020/761097s005lbl.pdf. Accessed 25 November 2020
Gaudy-Marqueste C, Monestier S, Franques J, Cantais E, Richard MA, Grob JJ (2013) A severe case of ipilimumab-induced guillain-barre syndrome revealed by an occlusive enteric neuropathy: a differential diagnosis for ipilimumab-induced colitis. J Immunother 36(1):77–78. https://doi.org/10.1097/CJI.0b013e31827807dd
de Maleissye MF, Nicolas G, Saiag P (2016) Pembrolizumab-induced demyelinating polyradiculoneuropathy. N Engl J Med 375(3):296–297. https://doi.org/10.1056/NEJMc1515584
Johnson DB, Manouchehri A, Haugh AM, Quach HT, Balko JM, Lebrun-Vignes B, Mammen A, Moslehi JJ, Salem JE (2019) Neurologic toxicity associated with immune checkpoint inhibitors: a pharmacovigilance study. J Immunother Cancer 7(1):134. https://doi.org/10.1186/s40425-019-0617-x
Sato K, Mano T, Iwata A, Toda T (2019) Neurological and related adverse events in immune checkpoint inhibitors: a pharmacovigilance study from the Japanese adverse drug event report database. J Neurooncol 145(1):1–9. https://doi.org/10.1007/s11060-019-03273-1
Fukazawa C, Hinomura Y, Kaneko M, Narukawa M (2018) Significance of data mining in routine signal detection: analysis based on the safety signals identified by the FDA. Pharmacoepidemiol Drug Saf 27(12):1402–1408. https://doi.org/10.1002/pds.4672
Harpaz R, DuMouchel W, LePendu P, Bauer-Mehren A, Ryan P, Shah NH (2013) Performance of pharmacovigilance signal-detection algorithms for the FDA adverse event reporting system. Clin Pharmacol Ther 93(6):539–546. https://doi.org/10.1038/clpt.2013.24
MedDRA MSSO (2020) Introductory guide for standardised MedDRA queries (SMQs) Version 23.0. https://admin.new.meddra.org/sites/default/files/guidance/file/SMQ_intguide_23_0_English.pdf. Accessed 25 November 2020
Poluzzi E, Raschi E, Piccinni C, Ponti FD (2012) Data mining techniques in pharmacovigilance: analysis of the publicly accessible FDA adverse event reporting system (AERS). Data mining applications in engineering and medicine. https://api.intechopen.com/chapter/pdf-preview/38579. Accessed 25 November 2020
van Puijenbroek EP, Bate A, Leufkens HG, Lindquist M, Orre R, Egberts AC (2002) A comparison of measures of disproportionality for signal detection in spontaneous reporting systems for adverse drug reactions. Pharmacoepidemiol Drug Saf 11(1):3–10. https://doi.org/10.1002/pds.668
Evans SJ, Waller PC, Davis S (2001) Use of proportional reporting ratios (PRRs) for signal generation from spontaneous adverse drug reaction reports. Pharmacoepidemiol Drug Saf 10(6):483–486. https://doi.org/10.1002/pds.677
Bate A, Lindquist M, Edwards IR, Olsson S, Orre R, Lansner A, De Freitas RM (1998) A Bayesian neural network method for adverse drug reaction signal generation. Eur J Clin Pharmacol 54(4):315–321. https://doi.org/10.1007/s002280050466
Szarfman A, Machado SG, O’Neill RT (2002) Use of screening algorithms and computer systems to efficiently signal higher-than-expected combinations of drugs and events in the US FDA’s spontaneous reports database. Drug Saf 25(6):381–392. https://doi.org/10.2165/00002018-200225060-00001
Sakaeda T, Tamon A, Kadoyama K, Okuno Y (2013) Data mining of the public version of the FDA Adverse Event Reporting System. Int J Med Sci 10(7):796–803. https://doi.org/10.7150/ijms.6048
Liu R, Zhang P (2019) Towards early detection of adverse drug reactions: combining pre-clinical drug structures and post-market safety reports. BMC Med Inform Decis Mak 19(1):279. https://doi.org/10.1186/s12911-019-0999-1
Touat M, Talmasov D, Ricard D, Psimaras D (2017) Neurological toxicities associated with immune-checkpoint inhibitors. Curr Opin Neurol 30(6):659–668. https://doi.org/10.1097/WCO.0000000000000503
World Health Organization (2016) Guillain–Barré syndrome. http://www.who.int/mediacentre/factsheets/guillain-barre-syndrome/en. Accessed 25 November 2020
Yuki N, Hartung HP (2012) Guillain-Barre syndrome. N Engl J Med 366(24):2294–2304. https://doi.org/10.1056/NEJMra1114525
O’Connor JM, Seidl-Rathkopf K, Torres AZ, You P, Carson KR, Ross JS, Gross CP (2018) Disparities in the use of programmed death 1 immune checkpoint inhibitors. Oncologist 23(11):1388–1390. https://doi.org/10.1634/theoncologist.2017-0673
Irelli A, Sirufo MM, D’Ugo C, Ginaldi L, De Martinis M (2020) Sex and gender influences on cancer immunotherapy response. Biomedicines. https://doi.org/10.3390/biomedicines8070232
DePinho RA (2000) The age of cancer. Nature 408(6809):248–254. https://doi.org/10.1038/35041694
Sejvar JJ, Baughman AL, Wise M, Morgan OW (2011) Population incidence of Guillain-Barre syndrome: a systematic review and meta-analysis. Neuroepidemiology 36(2):123–133. https://doi.org/10.1159/000324710
Supakornnumporn S, Katirji B (2017) Guillain-Barre syndrome triggered by immune checkpoint inhibitors: a case report and literature review. J Clin Neuromuscul Dis 19(2):80–83. https://doi.org/10.1097/CND.0000000000000193
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QF designed the research, collected and analyzed the data, and wrote the manuscript draft; YH participated in the data collection and analysis; XW contributed to the quality assessment; BZ designed and directed the research, and corrected the manuscript.
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Ethical approval was waived by the Institutional Review Board of Peking Union Medical College Hospital because this was an observational study based on the FAERS, which is a public anonymized database.
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Fan, Q., Hu, Y., Wang, X. et al. Guillain–Barré syndrome in patients treated with immune checkpoint inhibitors. J Neurol 268, 2169–2174 (2021). https://doi.org/10.1007/s00415-021-10404-0
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DOI: https://doi.org/10.1007/s00415-021-10404-0