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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Pharmacol.</journal-id>
<journal-title>Frontiers in Pharmacology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Pharmacol.</abbrev-journal-title>
<issn pub-type="epub">1663-9812</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">720776</article-id>
<article-id pub-id-type="doi">10.3389/fphar.2021.720776</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Pharmacology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Common Immune-Related Adverse Events of Immune Checkpoint Inhibitors in the Gastrointestinal System: A Study Based on the US Food and Drug Administration Adverse Event Reporting System</article-title>
<alt-title alt-title-type="left-running-head">Bai et&#x20;al.</alt-title>
<alt-title alt-title-type="right-running-head">Common irAE Digestive Adverse Events</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Bai</surname>
<given-names>Xiaoyin</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="fn" rid="fn1">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1388906/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Jiang</surname>
<given-names>Shiyu</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="fn" rid="fn1">
<sup>&#x2020;</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhou</surname>
<given-names>Yangzhong</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="fn" rid="fn1">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1485178/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhen</surname>
<given-names>Hongnan</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1388285/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ji</surname>
<given-names>Junyi</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1395972/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Li</surname>
<given-names>Yi</given-names>
</name>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1521117/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ruan</surname>
<given-names>Gechong</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Yang</surname>
<given-names>Yang</given-names>
</name>
<xref ref-type="aff" rid="aff7">
<sup>7</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1387056/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Shen</surname>
<given-names>Kaini</given-names>
</name>
<xref ref-type="aff" rid="aff8">
<sup>8</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Luo</given-names>
</name>
<xref ref-type="aff" rid="aff9">
<sup>9</sup>
</xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Li</surname>
<given-names>Guanqiao</given-names>
</name>
<xref ref-type="aff" rid="aff10">
<sup>10</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Yang</surname>
<given-names>Hong</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/978695/overview"/>
</contrib>
</contrib-group>
<aff id="aff1">
<label>
<sup>1</sup>
</label>Department of Gastroenterology, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, <addr-line>Beijing</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<label>
<sup>2</sup>
</label>Department of Medical Oncology, Shanghai Medical College, Fudan University Shanghai Cancer Center, <addr-line>Shanghai</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<label>
<sup>3</sup>
</label>Department of Internal Medicine, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, <addr-line>Beijing</addr-line>, <country>China</country>
</aff>
<aff id="aff4">
<label>
<sup>4</sup>
</label>Department of Radiation Oncology, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, <addr-line>Beijing</addr-line>, <country>China</country>
</aff>
<aff id="aff5">
<label>
<sup>5</sup>
</label>School of Medicine, Tsinghua University, <addr-line>Beijing</addr-line>, <country>China</country>
</aff>
<aff id="aff6">
<label>
<sup>6</sup>
</label>Department of Oncology, Beijing Hospital, National Center of Gerontology, <addr-line>Beijing</addr-line>, <country>China</country>
</aff>
<aff id="aff7">
<label>
<sup>7</sup>
</label>Department of Pharmacy, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, <addr-line>Beijing</addr-line>, <country>China</country>
</aff>
<aff id="aff8">
<label>
<sup>8</sup>
</label>Department of Hematology, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, <addr-line>Beijing</addr-line>, <country>China</country>
</aff>
<aff id="aff9">
<label>
<sup>9</sup>
</label>Department of Respiratory and Critical Care Medicine, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Science, <addr-line>Beijing</addr-line>, <country>China</country>
</aff>
<aff id="aff10">
<label>
<sup>10</sup>
</label>Tsinghua Clinical Research Institute, School of Medicine, Tsinghua University, <addr-line>Beijing</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/907847/overview">Halina Was</ext-link>, Military Institute of Medicine, Poland</p>
</fn>
<fn fn-type="edited-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1321465/overview">Kevin Tyan</ext-link>, Harvard Medical School, United&#x20;States</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1457929/overview">Maria-Ioanna Christodoulou</ext-link>, European University Cyprus, Cyprus</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Hong Yang, <email>Yangh@pumch.cn</email>; Guanqiao Li, <email>guanqiaoli@mail.tsinghua.edu.cn</email>
</corresp>
<fn fn-type="equal" id="fn1">
<label>
<sup>&#x2020;</sup>
</label>
<p>These authors have contributed equally to this&#x20;work</p>
</fn>
<fn fn-type="other">
<p>This article was submitted to Pharmacology of Anti-Cancer Drugs, a section of the journal Frontiers in Pharmacology</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>29</day>
<month>11</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="collection">
<year>2021</year>
</pub-date>
<volume>12</volume>
<elocation-id>720776</elocation-id>
<history>
<date date-type="received">
<day>05</day>
<month>06</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>26</day>
<month>10</month>
<year>2021</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2021 Bai, Jiang, Zhou, Zhen, Ji, Li, Ruan, Yang, Shen, Wang, Li and Yang.</copyright-statement>
<copyright-year>2021</copyright-year>
<copyright-holder>Bai, Jiang, Zhou, Zhen, Ji, Li, Ruan, Yang, Shen, Wang, Li and Yang</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these&#x20;terms.</p>
</license>
</permissions>
<abstract>
<p>Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment; however, immune-related adverse events (irAEs) in the gastrointestinal (GI) system commonly occur. In this study, data were obtained from the US Food and Drug Administration adverse event reporting system between July 2014 and December 2020. Colitis, hepatobiliary disorders, and pancreatitis were identified as irAEs in our study. Reporting odds ratio (ROR) with information components (IC) was adopted for disproportionate analysis. A total of 70,330 adverse events were reported during the selected period, 4,075 records of which were associated with ICIs. GI toxicities have been reportedly increased with ICI, with ROR<sub>025</sub> of 17.2, 6.7, and 2.3 for colitis, hepatobiliary disorders, and pancreatitis, respectively. The risks of colitis, hepatobiliary disorders, and pancreatitis were higher with anti-CTLA-4 treatment than that with anti-PD-1 (ROR<sub>025</sub> 2.6, 1.3, and 1.1, respectively) or anti-PD-L1 treatment (ROR<sub>025</sub> 4.8, 1.3, and 1.3, respectively). Logistic analysis indicated that hepatobiliary disorders and pancreatitis more frequently occurred in female patients (adjusted odds ratio, 1.16 and 1.52; both <italic>p</italic>&#x20;&#x3c; 0.05). Consistently, polytherapy was a strong risk factor for colitis (adjusted odds ratio 2.52, <italic>p</italic>&#x20;&#x3c; 0.001), hepatobiliary disorders (adjusted odds ratio 2.50, <italic>p</italic>&#x20;&#x3c; 0.001), and pancreatitis (adjusted odds ratio 2.29, <italic>p</italic>&#x20;&#x3c; 0.001) according to multivariate logistic analysis. This pharmacovigilance analysis demonstrated an increased risk of all three GI irAEs associated with ICI therapies. The comparative analysis offered supportive insights on selecting GI irAEs for patients treated with&#x20;ICIs.</p>
</abstract>
<kwd-group>
<kwd>immune checkpoint inhibitors</kwd>
<kwd>digestive toxicities</kwd>
<kwd>fares</kwd>
<kwd>cancer</kwd>
<kwd>side effects</kwd>
</kwd-group>
<contract-num rid="cn001">2016-I2M-3-001 2019-I2M-2-007</contract-num>
<contract-sponsor id="cn001">Chinese Academy of Medical Sciences Initiative for Innovative Medicine<named-content content-type="fundref-id">10.13039/501100019018</named-content>
</contract-sponsor>
<contract-sponsor id="cn002">Foundation for Innovative Research Groups of the National Natural Science Foundation of China<named-content content-type="fundref-id">10.13039/501100012659</named-content>
</contract-sponsor>
</article-meta>
</front>
<body>
<sec id="s1">
<title>Introduction</title>
<p>The increasing clinical use of approved antibodies against programmed cell death protein 1 (PD-1) (pembrolizumab, nivolumab, and cemiplimab), programmed death-ligand 1 (PD-L1) (avelumab, atezolizumab, and durvalumab), and cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) (ipilimumab) has changed the paradigm of cancer treatment (<xref ref-type="bibr" rid="B1">Ackermann et&#x20;al., 2020</xref>). However, exaggerated immune responses and immune-related toxicities, known as immune-mediated adverse events (irAEs), decreased the patients&#x2019; survival. GI toxicities are the second most commonly reported irAEs, such as colitis, hepatotoxicity and biliary abnormality, and pancreatitis (<xref ref-type="bibr" rid="B21">Tan et&#x20;al., 2020</xref>). As the most common type, colitis more commonly occurs after the administration of anti-CTLA-4 antibodies (7&#x2013;12%) than that of anti-PD-1/PD-L1 antibodies (3%) (<xref ref-type="bibr" rid="B4">Davies and Duffield, 2017</xref>). This proportion increased to 12&#x2013;18% when combining CTLA-4 and PD-1/PD-L1 inhibitors (<xref ref-type="bibr" rid="B16">Motzer et&#x20;al., 2018</xref>). The incidence of immune-associated hepatotoxicity with either ipilimumab or nivolumab was approximately 5&#x2013;10%, which was lower than that of ipilimumab plus nivolumab treatment (25&#x2013;30%) (<xref ref-type="bibr" rid="B13">Larkin et&#x20;al., 2015</xref>). Immune-related acute pancreatitis only occurs in &#x3c;1% of patients (<xref ref-type="bibr" rid="B8">Friedman et&#x20;al., 2017</xref>). Despite the low incidence, it rapidly progresses and is associated with high mortality. Currently, the majority of GI irAEs were detected in clinical trials examining single drugs, making the comparison difficult. Therefore, irAEs related to ICIs should be investigated in the real-world setting. This study characterized the safety profiles of ICIs and performed a disproportionality analysis through data-mining using the US Food and Drug Administration adverse event reporting system (FAERS), a postmarketing safety surveillance database, aimed at providing the new insights into GI toxicities associated with different ICIs or their combination.</p>
</sec>
<sec sec-type="materials|methods" id="s2">
<title>Materials and Methods</title>
<sec id="s2-1">
<title>Data Collection</title>
<p>In this pharmacovigilance study, disproportional analysis was performed in FAERS, which retrospectively collects adverse event (AR) reports submitted by patients, medical professionals, pharmaceutical manufacturers, and others to the FDA to monitor safety risks associated with marketed drugs and biologics. Data of this study were retrieved from the publicly released FAERS (<ext-link ext-link-type="uri" xlink:href="https://www.open.fda.gov/">https://www.open.fda.gov/</ext-link>) between July 1, 2014, and December 31,&#x20;2020.</p>
</sec>
<sec id="s2-2">
<title>Data Processing</title>
<p>Medications used in this study included PD-1 (nivolumab, pembrolizumab, and cemiplimab), PD-L1 (atezolizumab, avelumab, and durvalumab), and CTLA-4 blockade (ipilimumab) alone or in combination. Polytherapy was defined as the combined administration of an anti-CTLA-4 antibody plus an anti-PD-1/PD-L1 antibody. To identify ICI-related records, both brand names and generic names were used. Furthermore, AE reports in FAERS are coded using the preferred term (PT) according to the Medical Dictionary for Regulatory Activities Terminology (MedDRA). Despite the rarity of immune-related pancreatitis (1.9%) (<xref ref-type="bibr" rid="B9">George et&#x20;al., 2019</xref>), immediate and appropriate management was vital to eliminate long-term toxicities. Thus, besides PTs of &#x201c;colitis&#x201d; and &#x201c;hepatobiliary disorders,&#x201d; PTs involving &#x201c;pancreatitis&#x201d; were also obtained from MedDRA version 20.0 (<ext-link ext-link-type="uri" xlink:href="https://www.meddra.org/;%20details%20in%20Supplemental%20materials">https://www.meddra.org/; details in Supplemental materials</ext-link>) in this study. Gender, age, year and country of reporting, and AE outcomes were also collected and analyzed.</p>
</sec>
<sec id="s2-3">
<title>Statistical Analysis</title>
<p>A disproportional analysis is a generally accepted mathematical algorithm used for calculating the association between a specific AE and a drug. We used either proportional reports reporting odds ratio (ROR) or Bayesian confidence propagation neural networks of information components (IC) to calculate disproportionality in this study. The relevant data-mining theory and calculation formulae have been described in detail in previous studies (<xref ref-type="bibr" rid="B18">Sakaeda et&#x20;al., 2013</xref>; <xref ref-type="bibr" rid="B23">Zhai et&#x20;al., 2019</xref>) when the entire database is used as a comparator. ROR was only used when comparing different treatment regimens. tROR<sub>025</sub> is defined as significant with a lower 95% confidence interval (CI) boundary of &#x3e;1 and with &#x2265;3 patients. Conversely, the lower boundary 95%CI of &#x3e;0 for IC (IC<sub>025</sub>) was deemed statistically significant. Demographic characteristics (age and gender) and treatment strategy (monotherapy or polytherapy) were used as covariates to predict risk factors for AEs by logistic regression analysis. All analyses were performed with SPSS version 23.0 (IBM Corporation, Armonk, NY, United&#x20;States).</p>
</sec>
</sec>
<sec sec-type="results" id="s3">
<title>Results</title>
<sec id="s3-1">
<title>Descriptive Analysis</title>
<p>A total of 70,330 reports of gastrointestinal, hepatobiliary, and pancreatic toxicities were identified from FAERS between July 1, 2014, and December 31, 2020. Collectively, 4,075 cases were reported with ICI treatment, including nivolumab (<italic>n</italic>&#x20;&#x3d; 2,267), pembrolizumab (<italic>n</italic>&#x20;&#x3d; 964), cemiplimab (<italic>n</italic>&#x20;&#x3d; 8), atezolizumab (<italic>n</italic>&#x20;&#x3d;&#x20;241), avelumab (<italic>n</italic>&#x20;&#x3d; 22), durvalumab (<italic>n</italic>&#x20;&#x3d; 76), and ipilimumab (<italic>n</italic>&#x20;&#x3d; 1,615). The clinical features of events are presented in <xref ref-type="table" rid="T1">Table&#x20;1</xref>. The number of male patients with ICI-related AEs nearly doubled that of female patients (2,093 vs. 1,320 events). AEs were mainly reported from Japan (43.0%), followed by the United&#x20;States (29.3%) and France (5.4%). Of all the outcomes reported, hospitalization (34.7%) and death (18.5%) were the most common, whereas life-threatening AEs occurred in 173 (4.2%) patients.</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Demographic and clinical characteristics of patients with ICIs-induced intestinal, hepatobiliary, and pancreatic toxicity.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">&#xa0;</th>
<th align="center">AEs&#x20;in ICIs (n&#x20;&#x3d;&#x20;4,075)</th>
<th align="center">AEs&#x20;in other drugs (n&#x20;&#x3d;&#x20;66,255)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Gender</td>
<td align="char" char="(">
</td>
<td align="char" char="(">
</td>
</tr>
<tr>
<td align="left">&#x2003;Male</td>
<td align="char" char="(">2,093 (51.4%)</td>
<td align="char" char="(">24,478 (36.9%)</td>
</tr>
<tr>
<td align="left">&#x2003;Female</td>
<td align="char" char="(">1,320 (32.4%)</td>
<td align="char" char="(">31,099 (46.9%)</td>
</tr>
<tr>
<td align="left">&#x2003;Missing</td>
<td align="char" char="(">662 (16.2%)</td>
<td align="char" char="(">10,678 (16.2%)</td>
</tr>
<tr>
<td colspan="3" align="left">Age</td>
</tr>
<tr>
<td align="left">&#x2003;&#x3c;65</td>
<td align="char" char="(">1,297 (31.8%)</td>
<td align="char" char="(">26,826 (40.5%)</td>
</tr>
<tr>
<td align="left">&#x2003;&#x2265;65</td>
<td align="char" char="(">1,523 (37.4%)</td>
<td align="char" char="(">14,268 (21.5%)</td>
</tr>
<tr>
<td align="left">&#x2003;Missing</td>
<td align="char" char="(">1,255 (30.8%)</td>
<td align="char" char="(">25,161 (38.0%)</td>
</tr>
<tr>
<td colspan="3" align="left">Year</td>
</tr>
<tr>
<td align="left">&#x2003;2014</td>
<td align="char" char="(">98 (2.4%)</td>
<td align="char" char="(">3,779 (5.7%)</td>
</tr>
<tr>
<td align="left">&#x2003;2015</td>
<td align="char" char="(">182 (4.5%)</td>
<td align="char" char="(">7,738 (11.7%)</td>
</tr>
<tr>
<td align="left">&#x2003;2016</td>
<td align="char" char="(">315 (7.7%)</td>
<td align="char" char="(">8,081 (12.2%)</td>
</tr>
<tr>
<td align="left">&#x2003;2017</td>
<td align="char" char="(">578 (14.2%)</td>
<td align="char" char="(">9,741 (14.7%)</td>
</tr>
<tr>
<td align="left">&#x2003;2018</td>
<td align="char" char="(">899 (22.1%)</td>
<td align="char" char="(">13,680 (20.6%)</td>
</tr>
<tr>
<td align="left">&#x2003;2019</td>
<td align="char" char="(">1,248 (30.6%)</td>
<td align="char" char="(">13,698 (20.7%)</td>
</tr>
<tr>
<td align="left">&#x2003;2020</td>
<td align="char" char="(">755 (18.5%)</td>
<td align="char" char="(">9,538 (14.4%)</td>
</tr>
<tr>
<td colspan="3" align="left">Outcomes</td>
</tr>
<tr>
<td align="left">&#x2003;Death</td>
<td align="char" char="(">754 (18.5%)</td>
<td align="char" char="(">7,862 (11.9%)</td>
</tr>
<tr>
<td align="left">&#x2003;Life-threatening</td>
<td align="char" char="(">173 (4.2%)</td>
<td align="char" char="(">2,957 (4.5%)</td>
</tr>
<tr>
<td align="left">&#x2003;Disability</td>
<td align="char" char="(">48 (1.2%)</td>
<td align="char" char="(">774 (1.2%)</td>
</tr>
<tr>
<td align="left">&#x2003;Hospitalization</td>
<td align="char" char="(">1,413 (34.7%)</td>
<td align="char" char="(">22,134 (33.4%)</td>
</tr>
<tr>
<td align="left">&#x2003;Congenital anomaly</td>
<td align="char" char="(">1 (0.0%)</td>
<td align="char" char="(">41 (0.0%)</td>
</tr>
<tr>
<td align="left">&#x2003;Other serious</td>
<td align="char" char="(">1,608 (39.5%)</td>
<td align="char" char="(">27,814 (42.0%)</td>
</tr>
<tr>
<td align="left">&#x2003;Required intervention</td>
<td align="char" char="(">1 (0.0%)</td>
<td align="char" char="(">34 (0.0%)</td>
</tr>
<tr>
<td align="left">&#x2003;Missing</td>
<td align="char" char="(">77 (1.9%)</td>
<td align="char" char="(">4,639 (7.0%)</td>
</tr>
<tr>
<td colspan="3" align="left">Report countries</td>
</tr>
<tr>
<td align="left">&#x2003;United&#x20;States</td>
<td align="char" char="(">1,197 (29.3%)</td>
<td align="char" char="(">25,044 (37.8%)</td>
</tr>
<tr>
<td align="left">&#x2003;Japan</td>
<td align="char" char="(">1,754 (42.8%)</td>
<td align="char" char="(">7,350 (11.1%)</td>
</tr>
<tr>
<td align="left">&#x2003;Great Britain</td>
<td align="char" char="(">89 (2.2%)</td>
<td align="char" char="(">3,841 (5.8%)</td>
</tr>
<tr>
<td align="left">&#x2003;France</td>
<td align="char" char="(">222 (5.4%)</td>
<td align="char" char="(">4,782 (7.2%)</td>
</tr>
<tr>
<td align="left">&#x2003;Canada</td>
<td align="char" char="(">42 (1.0%)</td>
<td align="char" char="(">3,836 (5.8%)</td>
</tr>
<tr>
<td align="left">&#x2003;Italy</td>
<td align="char" char="(">47 (1.2%)</td>
<td align="char" char="(">1,875 (2.8%)</td>
</tr>
<tr>
<td align="left">&#x2003;Other countries</td>
<td align="char" char="(">715 (17.5%)</td>
<td align="char" char="(">17,313 (26.1%)</td>
</tr>
<tr>
<td align="left">&#x2003;Missing</td>
<td align="char" char="(">9 (0.1%)</td>
<td align="char" char="(">2,214 (3.3%)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>ICIs, immune checkpoint inhibitors; AE, adverse&#x20;event.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3-2">
<title>Associations Between GI Disorders and ICIs</title>
<p>A disproportional analysis was performed to evaluate the associations of the occurrence of colitis, hepatobiliary disorders, or pancreatitis with ICI treatment. Overall, 1,737 colitis events were reported in the ICI group, including 1,229, 78, and 909 from anti-PD-1, anti-PD-L1, and anti-CTLA-4 drugs, respectively (<xref ref-type="table" rid="T2">Table&#x20;2</xref>). An increased risk of colitis was identified with ICI treatment (ROR<sub>025</sub> 17.2, IC<sub>025</sub> 3.9). The risk of colitis was higher in patients treated with anti-CTLA-4 antibodies than in those treated with anti-PD-1 (ROR<sub>025</sub> 2.6) or anti-PD-L1 antibodies (ROR<sub>025</sub> 4.8). As expected, colitis more frequently occurred in patients receiving anti-PD-1/PD-L1 plus anti-CTLA-4 antibodies (ROR<sub>025</sub> 1.7, IC<sub>025</sub> 0.5) than either single agent alone. Similarly, the risk of hepatobiliary disorders was also increased with ICI treatment (ROR<sub>025</sub> 6.7, IC<sub>025</sub> 2.6). Similar to colitis, the risk of hepatobiliary disorders in the anti-CTLA-4 antibodies group was speculated to be higher than PD-1/PD-L1 inhibitors (ROR<sub>025</sub> 1.3 and 1.3, respectively, <xref ref-type="table" rid="T2">Table&#x20;2</xref>). The risk was even higher in the combined anti-PD-1/PD-L1 and anti-CTLA-4 antibody treatment than that in monotherapy (ROR<sub>025</sub> 1.8). Regarding pancreatitis (<xref ref-type="table" rid="T2">Table&#x20;2</xref>), 202 reports were identified in the ICI group, indicating an increased risk (ROR<sub>025</sub> 2.3, IC<sub>025</sub> 1.1). Moreover, anti-PD-1/PD-L1 combined with anti-CTLA-4 inhibitors increased the number of patients treated with monotherapy (ROR<sub>025</sub>&#x20;1.2).</p>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>The associations of induced intestinal, hepatobiliary, and pancreatic toxicity with different ICI regimens.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th rowspan="2" align="left">Therapy</th>
<th colspan="3" align="center">Colitis</th>
<th colspan="3" align="center">Hepatobiliary</th>
<th colspan="3" align="center">Pancreatitis</th>
<th colspan="3" align="center">All GI</th>
</tr>
<tr>
<th align="center">No. of AEs</th>
<th align="center">ROR (ROR<sub>025</sub>; ROR<sub>975</sub>)</th>
<th align="center">IC (IC<sub>025</sub>; IC<sub>975</sub>)</th>
<th align="center">No. of AEs</th>
<th align="center">ROR (ROR<sub>025</sub>; ROR<sub>975</sub>)</th>
<th align="center">IC (IC<sub>025</sub>; IC<sub>975</sub>)</th>
<th align="center">No. of AEs</th>
<th align="center">ROR (ROR<sub>025</sub>; ROR<sub>975</sub>)</th>
<th align="center">IC (IC<sub>025</sub>; IC<sub>975</sub>)</th>
<th align="center">No. of AEs</th>
<th align="center">ROR (ROR<sub>025</sub>; ROR<sub>975</sub>)</th>
<th align="center">IC (IC<sub>025</sub>; IC<sub>975</sub>)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">All ICIs</td>
<td align="center">1737</td>
<td align="char" char="(">18.1 (17.2; 19.1)</td>
<td align="char" char="(">3.9 (3.8; 4.0)</td>
<td align="center">2,295</td>
<td align="char" char="(">7.0 (6.7; 7.3)</td>
<td align="char" char="(">2.7 (2.6; 2.7)</td>
<td align="center">202</td>
<td align="char" char="(">2.6 (2.3; 3.0)</td>
<td align="char" char="(">1.4 (1.1; 1.5)</td>
<td align="center">4,075</td>
<td align="char" char="(">8.6 (8.4; 8.9)</td>
<td align="char" char="(">2.9 (2.8; 2.9)</td>
</tr>
<tr>
<td align="left">Anti-PD-1 antibody</td>
<td align="center">1,229</td>
<td align="char" char="(">15.4 (14.5; 16.3)</td>
<td align="char" char="(">3.8 (3.7; 3.8)</td>
<td align="center">1936</td>
<td align="char" char="(">7.3 (7.0; 7.7)</td>
<td align="char" char="(">2.7 (2.7; 2.8)</td>
<td align="center">168</td>
<td align="char" char="(">2.7 (2.3; 3.2)</td>
<td align="char" char="(">1.4 (1.2; 1.6)</td>
<td align="center">3,190</td>
<td align="char" char="(">8.3 (8.0; 8.6)</td>
<td align="char" char="(">2.9 (2.8; 2.9)</td>
</tr>
<tr>
<td align="left">Nivolumab</td>
<td align="center">910</td>
<td align="char" char="(">16.7 (15.6; 17.9)</td>
<td align="char" char="(">3.9 (3.8; 4.0)</td>
<td align="center">1,374</td>
<td align="char" char="(">7.7 (7.3; 8.2)</td>
<td align="char" char="(">2.8 (2.7; 2.9)</td>
<td align="center">115</td>
<td align="char" char="(">2.8 (2.3; 3.3)</td>
<td align="char" char="(">1.4 (1.1; 1.7)</td>
<td align="center">2,267</td>
<td align="char" char="(">8.8 (8.4; 9.2)</td>
<td align="char" char="(">3.0 (2.9; 3.0)</td>
</tr>
<tr>
<td align="left">Pembrolizumab</td>
<td align="center">339</td>
<td align="char" char="(">11.9 (10.6; 13.2)</td>
<td align="char" char="(">3.5 (3.3; 3.6)</td>
<td align="center">587</td>
<td align="char" char="(">6.4 (5.9; 7.0)</td>
<td align="char" char="(">2.6 (2.5; 2.7)</td>
<td align="center">55</td>
<td align="char" char="(">2.6 (2.0; 3.5)</td>
<td align="char" char="(">1.4 (0.9; 1.7)</td>
<td align="center">964</td>
<td align="char" char="(">7.3 (6.8; 7.8)</td>
<td align="char" char="(">2.7 (2.6; 2.8)</td>
</tr>
<tr>
<td align="left">Cemiplimab</td>
<td align="center">2</td>
<td align="char" char="(">5.6 (1.4; 22.4)</td>
<td align="char" char="(">1.5 (-1.1; 2.9)</td>
<td align="center">6</td>
<td align="char" char="(">5.3 (2.4; 12.1)</td>
<td align="char" char="(">2.0 (0.6; 2.9)</td>
<td align="center">0</td>
<td align="left"/>
<td align="char" char="(">-0.6 (-10.9; 1.4)</td>
<td align="center">8</td>
<td align="char" char="(">4.8 (2.3; 9.7)</td>
<td align="char" char="(">1.9 (0.7; 2.7)</td>
</tr>
<tr>
<td align="left">Anti-PD-L1 antibody</td>
<td align="center">78</td>
<td align="char" char="(">6.6 (5.3; 8.3)</td>
<td align="char" char="(">2.6 (2.3; 2.9)</td>
<td align="center">248</td>
<td align="char" char="(">6.8 (6.0; 7.8)</td>
<td align="char" char="(">2.7 (2.5; 2.8)</td>
<td align="center">18</td>
<td align="char" char="(">2.2 (1.4; 3.4)</td>
<td align="char" char="(">1.1 (0.3; 1.6)</td>
<td align="center">337</td>
<td align="char" char="(">6.2 (5.6; 7.0)</td>
<td align="char" char="(">2.5 (2.4; 2.7)</td>
</tr>
<tr>
<td align="left">Atezolizumab</td>
<td align="center">54</td>
<td align="char" char="(">6.8 (5.2; 8.9)</td>
<td align="char" char="(">2.7 (2.2; 3.0)</td>
<td align="center">181</td>
<td align="char" char="(">7.4 (6.4; 8.6)</td>
<td align="char" char="(">2.8 (2.5; 3.0)</td>
<td align="center">13</td>
<td align="char" char="(">2.3 (1.4; 4.0)</td>
<td align="char" char="(">1.1 (0.2; 1.8)</td>
<td align="center">241</td>
<td align="char" char="(">6.6 (5.8; 7.6)</td>
<td align="char" char="(">2.6 (2.4; 2.8)</td>
</tr>
<tr>
<td align="left">Avelumab</td>
<td align="center">10</td>
<td align="char" char="(">9.5 (5.1; 17.8)</td>
<td align="char" char="(">2.7 (1.7; 3.5)</td>
<td align="center">12</td>
<td align="char" char="(">3.6 (2.0; 6.3)</td>
<td align="char" char="(">1.7 (0.7; 2.3)</td>
<td align="center">1</td>
<td align="char" char="(">1.3 (0.2; 9.5)</td>
<td align="char" char="(">0.3 (&#x2212;3.5; 2.0)</td>
<td align="center">22</td>
<td align="char" char="(">4.4 (2.9; 6.8)</td>
<td align="char" char="(">2.0 (1.3; 2.5)</td>
</tr>
<tr>
<td align="left">Durvalumab</td>
<td align="center">16</td>
<td align="char" char="(">5.7 (3.5; 9.3)</td>
<td align="char" char="(">2.3 (1.5; 2.9)</td>
<td align="center">56</td>
<td align="char" char="(">6.4 (4.9; 8.4)</td>
<td align="char" char="(">2.6 (2.1; 2.9)</td>
<td align="center">4</td>
<td align="char" char="(">2.0 (0.8; 5.4)</td>
<td align="char" char="(">0.9 (&#x2212;0.9; 1.9)</td>
<td align="center">76</td>
<td align="char" char="(">5.9 (4.6; 7.4)</td>
<td align="char" char="(">2.4 (2.0; 2.7)</td>
</tr>
<tr>
<td colspan="13" align="left">Anti-CTLA-4 antibody</td>
</tr>
<tr>
<td align="left">&#x2003;Ipilimumab</td>
<td align="center">909</td>
<td align="char" char="(">43.1 (40.1; 46.2)</td>
<td align="char" char="(">5.2 (5.1; 5.2)</td>
<td align="center">750</td>
<td align="char" char="(">10.3 (9.6; 11.1)</td>
<td align="char" char="(">3.2 (3.1; 3.3)</td>
<td align="center">66</td>
<td align="char" char="(">3.9 (3.0; 4.9)</td>
<td align="char" char="(">1.9 (1.5; 2.2)</td>
<td align="center">1,615</td>
<td align="char" char="(">16.4 (15.6; 17.4)</td>
<td align="char" char="(">3.7 (3.6; 3.8)</td>
</tr>
<tr>
<td align="left">&#x2003;Polytherapy</td>
<td align="center">487</td>
<td align="char" char="(">38.0 (34.6; 41.8)</td>
<td align="char" char="(">5.0 (4.9; 5.1)</td>
<td align="center">649</td>
<td align="char" char="(">15.9 (14.7; 17.3)</td>
<td align="char" char="(">3.8 (3.6; 3.9)</td>
<td align="center">52</td>
<td align="char" char="(">5.2 (4.0; 6.8)</td>
<td align="char" char="(">2.3 (1.8; 2.6)</td>
<td align="center">1,087</td>
<td align="char" char="(">19.4 (18.2; 20.8)</td>
<td align="char" char="(">3.9 (3.8; 4.0)</td>
</tr>
<tr>
<td align="left">&#x2003;Nivolumab &#x2b; ipilimumab</td>
<td align="center">446</td>
<td align="char" char="(">36.7 (33.2; 40.5)</td>
<td align="char" char="(">5.0 (4.8; 5.1)</td>
<td align="center">620</td>
<td align="char" char="(">16.2 (14.8; 17.6)</td>
<td align="char" char="(">3.8 (3.7; 3.9)</td>
<td align="center">45</td>
<td align="char" char="(">4.8 (3.6; 6.4)</td>
<td align="char" char="(">2.2 (1.7; 2.5)</td>
<td align="center">1,015</td>
<td align="char" char="(">19.2 (17.9; 20.6)</td>
<td align="char" char="(">3.9 (3.8; 4.0)</td>
</tr>
<tr>
<td align="left">&#x2003;Pembrolizumab &#x2b; ipilimumab</td>
<td align="center">41</td>
<td align="char" char="(">56.8 (40.9; 79.0)</td>
<td align="char" char="(">5.0 (4.4; 5.3)</td>
<td align="center">29</td>
<td align="char" char="(">11.9 (8.1; 17.4)</td>
<td align="char" char="(">3.2 (2.6; 3.6)</td>
<td align="center">7</td>
<td align="char" char="(">12.4 (5.8; 26.2)</td>
<td align="char" char="(">2.8 (1.5; 3.6)</td>
<td align="center">72</td>
<td align="char" char="(">23.1 (17.8; 30.1)</td>
<td align="char" char="(">4.0 (3.6; 4.3)</td>
</tr>
<tr>
<td colspan="13" align="left">Comparison</td>
</tr>
<tr>
<td align="left">&#x2003;Anti-CTLA-4 vs. anti-PD-1</td>
<td align="center">&#x2014;</td>
<td align="char" char="(">2.9 (2.6; 3.1)</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="char" char="(">1.4 (1.3; 1.6)</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="char" char="(">1.4 (1.1; 1.9)</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="char" char="(">2.0 (1.9; 2.1)</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">&#x2003;Anti-CTLA-4 vs. anti-PD-L1</td>
<td align="center">&#x2014;</td>
<td align="char" char="(">6.1 (4.8; 7.7)</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="char" char="(">1.5 (1.3; 1.7)</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="char" char="(">1.8 (1.0; 3.0)</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="char" char="(">2.6 (2.3; 2.9)</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">&#x2003;Anti-PD-1 vs. anti-PD-L1</td>
<td align="center">&#x2014;</td>
<td align="char" char="(">1.9 (1.7; 2.1)</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="char" char="(">1.0 (0.9; 1.2)</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="char" char="(">1.2 (0.8; 2.0)</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="char" char="(">1.9 (1.7; 2.0)</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">&#x2003;Polytherapy vs. monotherapy</td>
<td align="center">&#x2014;</td>
<td align="char" char="(">1.9 (1.7; 2.1)</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="char" char="(">1.9 (1.8; 2.1)</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="char" char="(">1.6 (1.2; 2.2)</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="char" char="(">1.9 (1.7; 2.0)</td>
<td align="center">&#x2014;</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>ICIs, immune checkpoint inhibitors.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3-3">
<title>Risk Factors for GI irAEs</title>
<p>Logistic regression analysis was performed according to GI AE subtypes indicating polytherapy as a strong risk factor for colitis [adjusted odds ratio, 2.89 (95%CI: 2.52, 3.31), <italic>p</italic>&#x20;&#x3c; 0.001], hepatobiliary disorders [adjusted odds ratio, 2.80 (95%CI: 2.50, 3.12), <italic>p</italic>&#x20;&#x3c; 0.001], and pancreatitis [adjusted odds ratio, 2.29 (95%CI: 1.59, 3.31), <italic>p</italic>&#x20;&#x3c; 0.001] (<xref ref-type="table" rid="T3">Table&#x20;3</xref>). Hepatobiliary disorders more frequently occurred in female patients [adjusted odds ratio, 1.16 (95%CI: 1.05, 1.29); <italic>p</italic>&#x20;&#x3d; 0.004]. Meanwhile, patients aged &#x2265;65&#xa0;years were less likely to develop colitis [adjusted odds ratio, 0.87 (95%CI: 0.76, 0.98); <italic>p</italic>&#x20;&#x3d; 0.025] and pancreatitis [adjusted odds ratio, 0.67 (95%CI: 0.48, 0.93); <italic>p</italic>&#x20;&#x3d; 0.018]. The details of data are shown in <xref ref-type="table" rid="T3">Table&#x20;3</xref>.</p>
<table-wrap id="T3" position="float">
<label>TABLE 3</label>
<caption>
<p>Multivariate logistic analysis of patients with common GI irAEs.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Characteristics</th>
<th align="center">AEs&#x20;of interest</th>
<th align="center">All other AEs</th>
<th align="center">OR crude</th>
<th align="center">OR-adjusted</th>
<th align="center">
<italic>p</italic> value</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">GI irAEs</td>
<td align="center">4,075</td>
<td align="center">36,637</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">Female sex</td>
<td align="center">1,607</td>
<td align="center">11,826</td>
<td align="center">1.01 (0.94,1.09)</td>
<td align="center">1.08 (0.99,1.17)</td>
<td align="char" char=".">0.077</td>
</tr>
<tr>
<td align="left">Age &#x2265;65</td>
<td align="center">1,932</td>
<td align="center">12,792</td>
<td align="center">0.90 (0.83,0.97)</td>
<td align="center">0.96 (0.88,1.04)</td>
<td align="char" char=".">0.295</td>
</tr>
<tr>
<td align="left">Polytherapy</td>
<td align="center">2,186</td>
<td align="center">8,577</td>
<td align="center">2.75 (2.55,2.97)</td>
<td align="center">2.87 (2.62,3.15)</td>
<td align="char" char=".">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">Colitis</td>
<td align="center">1,737</td>
<td align="center">38,975</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">Female sex</td>
<td align="center">618</td>
<td align="center">12,815</td>
<td align="center">0.93 (0.83,1.04)</td>
<td align="center">0.94 (0.82,1.07)</td>
<td align="char" char=".">0.340</td>
</tr>
<tr>
<td align="left">Age &#x2265;65</td>
<td align="center">714</td>
<td align="center">14,010</td>
<td align="center">0.82 (0.73,0.93)</td>
<td align="center">0.87 (0.76,0.98)</td>
<td align="char" char=".">0.025</td>
</tr>
<tr>
<td align="left">Polytherapy</td>
<td align="center">981</td>
<td align="center">9,782</td>
<td align="center">2.68 (2.40,2.90)</td>
<td align="center">2.89 (2.52,3.31)</td>
<td align="char" char=".">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">Pancreatitis</td>
<td align="center">202</td>
<td align="center">40,510</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">Female sex</td>
<td align="center">105</td>
<td align="center">13,328</td>
<td align="center">1.50 (1.11,2.01)</td>
<td align="center">1.52 (1.09,2.12)</td>
<td align="char" char=".">0.014</td>
</tr>
<tr>
<td align="left">Age &#x2265;65</td>
<td align="center">82</td>
<td align="center">14,642</td>
<td align="center">0.63 (0.45,0.87)</td>
<td align="center">0.67 (0.48,0.93)</td>
<td align="char" char=".">0.018</td>
</tr>
<tr>
<td align="left">Polytherapy</td>
<td align="center">102</td>
<td align="center">10,661</td>
<td align="center">2.22 (1.61,3.06)</td>
<td align="center">2.29 (1.59,3.31)</td>
<td align="char" char=".">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">Hepatobiliary</td>
<td align="center">2,295</td>
<td align="center">38,417</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
<td align="center">&#x2014;</td>
</tr>
<tr>
<td align="left">Female sex</td>
<td align="center">1,002</td>
<td align="center">12,431</td>
<td align="center">1.06 (0.97,1.17)</td>
<td align="center">1.16 (1.05,1.29)</td>
<td align="char" char=".">0.004</td>
</tr>
<tr>
<td align="left">Age &#x2265;65</td>
<td align="center">1,224</td>
<td align="center">13,500</td>
<td align="center">0.95 (0.86,1.05)</td>
<td align="center">1.03 (0.93,1.14)</td>
<td align="char" char=".">0.584</td>
</tr>
<tr>
<td align="left">Polytherapy</td>
<td align="center">1,317</td>
<td align="center">9,446</td>
<td align="center">2.83 (2.57,3.12)</td>
<td align="center">2.80 (2.50,3.12)</td>
<td align="char" char=".">&#x3c;0.001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>GI, gastrointestinal.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
</sec>
<sec sec-type="discussion" id="s4">
<title>Discussion</title>
<p>As an extensive pharmacovigilance analysis on GI irAEs after ICI treatments obtained from the FAERS database, this study demonstrated that increased risk of colitis, hepatobiliary abnormalities, and pancreatitis was associated with ICI monotherapy or combination therapies. Among those administered ICIs, PD-1 plus CTLA-4 polytherapy correlated with increased risk of these three GI irAEs. This comparative analysis provided abundant data on GI profiles of individual ICIs alone or combined, providing supportive safety insights in selecting specific ICI therapies for patients with preexisting GI disorders and identifying posttherapeutic GI irAEs.</p>
<p>Based on a previous meta-analysis, ipilimumab was reportedly correlated with a higher risk of high-grade colitis as compared with anti-PD-1/PD-L1 inhibitors (<italic>p</italic>&#x20;&#x3d; 0.021) (<xref ref-type="bibr" rid="B5">De Velasco et&#x20;al., 2017</xref>). In line with this, the present study also showed that patients receiving ipilimumab were more likely to experience colitis. Moreover, the risk of colitis was also demonstrated to be higher with PD-1 than with PD-L1 inhibitors. As irAE onset has been indicated as a predictor for ICI treatment efficacy (<xref ref-type="bibr" rid="B17">Rogado et&#x20;al., 2019</xref>; <xref ref-type="bibr" rid="B24">Zhou et&#x20;al., 2020</xref>), rechallenging ICI treatment is an option for selected patients after discontinuation due to toxicity or clinical decision (<xref ref-type="bibr" rid="B10">Gobbini et&#x20;al., 2020</xref>). The risk of colitis with different ICI agents may inform tailoring of ICI treatment for patients previously diagnosed with immune-related colitis.</p>
<p>Hepatobiliary disorders commonly occur in patients with cancer. A higher risk of immune-mediated hepatitis secondary to ICIs has been observed (<xref ref-type="bibr" rid="B14">Lin et&#x20;al., 2020</xref>). The risk of increased aspartate aminotransferase level (relative risk 1.80, <italic>p</italic>&#x20;&#x3d; 0.020) has been reportedly associated with ICIs compared with non-ICI treatment (<xref ref-type="bibr" rid="B5">De Velasco et&#x20;al., 2017</xref>). This study confirmed that liver injury may occur with ICI treatment and indicated no difference in hepatic transaminase elevation between CTLA-4 and PD-1/PD-L1 inhibitors.</p>
<p>Gender difference has been observed in the irAE incidence (<xref ref-type="bibr" rid="B22">Valpione et&#x20;al., 2018</xref>; <xref ref-type="bibr" rid="B7">Duma et&#x20;al., 2019</xref>). Recently, a large pharmacovigilance study indicated gender-related differences in endocrine irAEs, with a significantly lower occurrence of thyroid dysfunction in male patients (<xref ref-type="bibr" rid="B15">Morganstein et&#x20;al., 2017</xref>; <xref ref-type="bibr" rid="B23">Zhai et&#x20;al., 2019</xref>). The evidence of GI irAEs is increased further, showing that the occurrence of hepatobiliary disorders more frequently occurs in female patients. This gender difference may be associated with greater antigen-presenting activity, more frequent antibody expression, and higher sex hormone levels in female patients (<xref ref-type="bibr" rid="B20">Shen et&#x20;al., 2016</xref>). Thus, enhanced immunoactivity after the ICI administration may result in increased toxicity in their male counterparts, which could be incorporated into safety evaluation, especially when rechallenging the ICI treatment.</p>
<p>Results in the relationship between age and irAE incidence have been reportedly inconsistent. A previous report demonstrated an increased likelihood (odds ratio, 5.4) of irAE-related hospitalization in patients aged &#x3e;65&#xa0;years (<xref ref-type="bibr" rid="B2">Balaji et&#x20;al., 2019</xref>), whereas other reports suggested no increased risk of irAEs or irAE-related hospitalization in older patients administered with PD-1 antibody (<xref ref-type="bibr" rid="B19">Sattar et&#x20;al., 2019</xref>; <xref ref-type="bibr" rid="B12">Ksienski et&#x20;al., 2020</xref>). These inconsistencies could be due to the sample size of the study and the bias of different drugs. Based on the current population-based study, patients aged &#x2265;65&#xa0;years seem to be less likely to experience colitis and pancreatitis.</p>
<p>An increasing number of published studies have revealed that irAEs due to polytherapy occurred more frequently than those due to monotherapy. Consistent with previous observations, this study presents real-world evidence that combination treatment could result in a considerably higher rate of GI AEs secondary to ICI treatment (<xref ref-type="bibr" rid="B3">Boutros et&#x20;al., 2016</xref>; <xref ref-type="bibr" rid="B11">Khoja et&#x20;al., 2017</xref>). When treating patients with cancer currently treated with or previously exposed to ICIs with GI disorders, general practitioners and GI physicians should consider that this could be some irAE presentation. Medication history and patient demographics and characteristics should be carefully evaluated. Once irAEs are suspected, consultation with medical oncologists is necessary to manage these immune-related GI disorders.</p>
<p>The AE signal mining methods in this study consisted of three main categories: proportional disequilibrium, logistic regression modeling, and association rule mining. Furthermore, ROR and IC in the proportional imbalance algorithm were used for signals in reports obtained from the FAERS database (<xref ref-type="bibr" rid="B6">Dias et&#x20;al., 2015</xref>). The limitations of this study are specific to the use of the FAERS database. Reports are spontaneous; therefore, exposure data may be lacking and cause under- and overreporting. Furthermore, due to the retrospective nature of pharmacovigilance databases, the causality should be cautiously interpreted.</p>
<p>Our real-world pharmacovigilance analysis demonstrated an increased risk of GI AEs due to ICIs. AE patterns greatly vary with different ICI regimens and patient characteristics. With the increasing use of ICIs, studies regarding irAEs and rechallenging ICIs are warranted in the following years to standardize management strategies, minimize irAE-related mortality, and thereby promote survival benefit to patients with cancer.</p>
</sec>
</body>
<back>
<sec id="s5">
<title>Data Availability Statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="sec" rid="s10">Supplementary Material</xref>, further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec id="s6">
<title>Author Contributions</title>
<p>XB, SJ, YZ and HZ contributed equally to this work. XB and YZ collected and analyzed the data. XB and SJ designed the research study and wrote the paper. HZ updated and re-analyzed the revised data, JJ contributed to the design of the study. YL, GR, YY, KS, and LW revised the draft. All authors have approved the final version of the manuscript.</p>
</sec>
<sec id="s7">
<title>Funding</title>
<p>The work was supported by the CAMS Innovation Fund for Medical Sciences (2016-I2M-3-001, 2019-I2M-2-007, 2021-1-I2M-001), the National Natural Science Foundation of China (81801632, 81970495), Natural Science Foundation of Beijing Municipality (No. 7202161), and the Fundamental Research Funds for the Center Universities (3332021007).</p>
</sec>
<sec sec-type="COI-statement" id="s8">
<title>Conflict of Interest</title>
<p>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.</p>
</sec>
<sec sec-type="disclaimer" id="s9">
<title>Publisher&#x2019;s Note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations or those of the publisher, the editors, and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec id="s10">
<title>Supplementary Material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fphar.2021.720776/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fphar.2021.720776/full&#x23;supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="Table1.docx" id="SM1" mimetype="application/docx" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
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