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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Immunol.</journal-id>
<journal-title>Frontiers in Immunology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Immunol.</abbrev-journal-title>
<issn pub-type="epub">1664-3224</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fimmu.2024.1485303</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Immunology</subject>
<subj-group>
<subject>Systematic Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Efficacy and safety of PD-1/PD-L1 and CTLA-4 immune checkpoint inhibitors in the treatment of advanced colorectal cancer: a systematic review and meta-analysis</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Song</surname>
<given-names>Dandan</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2625759"/>
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<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
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<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Hou</surname>
<given-names>Shufu</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2622754"/>
<role content-type="https://credit.niso.org/contributor-roles/conceptualization/"/>
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</contrib>
<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Ma</surname>
<given-names>Ning</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
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</contrib>
<contrib contrib-type="author">
<name>
<surname>Yan</surname>
<given-names>Bing</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
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</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Gao</surname>
<given-names>Jing</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
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<aff id="aff1">
<sup>1</sup>
<institution>Department of Neurology, Shandong Provincial Third Hospital, Cheeloo College of Medicine, Shandong University</institution>, <addr-line>Jinan</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Shandong Provincial Third Hospital, Cheeloo College of Medicine, Shandong University</institution>, <addr-line>Jinan</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Department of Gastrointestinal Surgery, Central Hospital Affiliated to Shandong First Medical University</institution>, <addr-line>Jinan</addr-line>, <country>China</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Department of General Surgery, The First Affiliated Hospital of Shandong First Medical University</institution>, <addr-line>Jinan</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Guendalina Froechlich, University of Naples Federico II, Italy</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Yan Wu, Peking University, China</p>
<p>Zhiyuan Zheng, Wenzhou Medical University, China</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Jing Gao, <email xlink:href="mailto:15866727771@163.com">15866727771@163.com</email>
</p>
</fn>
<fn fn-type="equal" id="fn003">
<p>&#x2020;These authors have contributed equally to this work and share first authorship</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>01</day>
<month>11</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="collection">
<year>2024</year>
</pub-date>
<volume>15</volume>
<elocation-id>1485303</elocation-id>
<history>
<date date-type="received">
<day>23</day>
<month>08</month>
<year>2024</year>
</date>
<date date-type="accepted">
<day>15</day>
<month>10</month>
<year>2024</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2024 Song, Hou, Ma, Yan and Gao</copyright-statement>
<copyright-year>2024</copyright-year>
<copyright-holder>Song, Hou, Ma, Yan and Gao</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 terms.</p>
</license>
</permissions>
<abstract>
<sec>
<title>Background</title>
<p>The efficacy and safety of PD-1/PD-L1 inhibitors combined with CTLA-4 inhibitors in the treatment of advanced colorectal cancer is controversial. This meta-analysis aimed to evaluate the efficacy and safety of PD-1/PD-L1 inhibitors combined with CTLA-4 inhibitors for advanced colorectal cancer.</p>
</sec>
<sec>
<title>Methods</title>
<p>PubMed, Embase, the Cochrane Library, and Web of Science databases were systematically searched for relevant studies. Outcomes including median progression-free survival (mPFS), median overall survival (mOS), overall response rate (ORR), disease control rate (DCR), treatment-related adverse events (TRAEs) and &#x2265;grade 3 TRAEs were extracted for further analysis. The risk of bias was assessed by subgroup analysis.</p>
</sec>
<sec>
<title>Results</title>
<p>12 articles with 566 patients were identified and subjected to meta-analysis. With regard to survival analysis, the pooled mOS and mPFS were 6.66 months (95%CI 4.85-9.16) and 2.92 months (95%CI 2.23-3.83), respectively. In terms of tumor response, the pooled ORR and DCR were 21% (95%CI 6%-41%) and 49% (95%CI 27%-71%), respectively. The pooled AEs rate and &#x2265; grade 3 AEs rate were 94% (95%CI 86%-99%) and 44% (95%CI 30%-58%).</p>
</sec>
<sec>
<title>Conclusion</title>
<p>PD-1/PD-L1 inhibitors combined with CTLA-4 inhibitors have shown promising clinical responses in the treatment of colorectal cancer (CRC). Although the incidence of adverse reactions is high, they are generally tolerable.</p>
</sec>
<sec>
<title>Systematic review registration</title>
<p><uri xlink:href="https://inplasy.com/">https://inplasy.com/</uri>, identifier INPLASY202480030.</p>
</sec>
</abstract>
<kwd-group>
<kwd>immune checkpoint inhibitors</kwd>
<kwd>colorectal cancer</kwd>
<kwd>immunotherapy</kwd>
<kwd>PD-1</kwd>
<kwd>PD-L1</kwd>
<kwd>CTLA-4</kwd>
</kwd-group>
<counts>
<fig-count count="4"/>
<table-count count="7"/>
<equation-count count="0"/>
<ref-count count="79"/>
<page-count count="14"/>
<word-count count="5322"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-in-acceptance</meta-name>
<meta-value>Cancer Immunity and Immunotherapy</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>Colorectal cancer (CRC) is the third most commonly diagnosed malignancy worldwide and the fourth leading cause of cancer-related death (<xref ref-type="bibr" rid="B1">1</xref>, <xref ref-type="bibr" rid="B2">2</xref>). Its global incidence is expected to rise to 2.5 million new cases by 2035 (<xref ref-type="bibr" rid="B3">3</xref>, <xref ref-type="bibr" rid="B4">4</xref>). CRC development results from a complex interplay of genetic and environmental factors, including a sedentary lifestyle, age, obesity, and dietary habits (<xref ref-type="bibr" rid="B4">4</xref>&#x2013;<xref ref-type="bibr" rid="B8">8</xref>). Due to its insidious onset, approximately 20% of cases are diagnosed as metastatic colorectal cancer (mCRC) (<xref ref-type="bibr" rid="B9">9</xref>), and about 40% of patients with localized disease experience recurrence after prior treatment (<xref ref-type="bibr" rid="B10">10</xref>).The high mortality rate in advanced colorectal cancer (aCRC) is largely due to tumor progression and metastasis. Despite advances in treatment, the prognosis for aCRC patients remains poor, with a median overall survival (mOS) of 30 months (<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B12">12</xref>) and a 5-year survival rate of less than 14% (<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B14">14</xref>). Surgery, chemotherapy, and radiotherapy remain the primary therapeutic interventions for CRC, often used in combination depending on disease localization and progression (<xref ref-type="bibr" rid="B15">15</xref>&#x2013;<xref ref-type="bibr" rid="B18">18</xref>). Surgery is the cornerstone of curative treatment for localized CRC (stage I&#x2013;III) (<xref ref-type="bibr" rid="B19">19</xref>), and in mCRC with limited metastasis, surgery and chemotherapy may achieve curative outcomes in some cases (<xref ref-type="bibr" rid="B14">14</xref>, <xref ref-type="bibr" rid="B19">19</xref>, <xref ref-type="bibr" rid="B20">20</xref>). However, complete cancer cell removal is often unattainable, leading to disease recurrence in many patients (<xref ref-type="bibr" rid="B21">21</xref>). Although significant progress has been made in systemic and local therapies for aCRC, it remains rarely curable. Resistance to conventional treatments, systemic toxicity, and low selectivity highlight the need for more effective alternatives (<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B22">22</xref>).</p>
<p>Immunotherapy has emerged as a promising approach, aiming to reverse tumor-induced immune suppression and activate antitumor responses (<xref ref-type="bibr" rid="B23">23</xref>). Immune checkpoints, such as programmed cell death 1 (PD-1), its ligand (PD-L1), and cytotoxic T lymphocyte antigen 4 (CTLA-4), have been extensively studied because of their overexpression in many solid tumors and hematological malignancies (<xref ref-type="bibr" rid="B24">24</xref>, <xref ref-type="bibr" rid="B25">25</xref>). Blocking the interaction between PD-1/PD-L1 or CTLA-4 and their ligands activates T cells, promoting tumor infiltration and cancer cell death (<xref ref-type="bibr" rid="B26">26</xref>, <xref ref-type="bibr" rid="B27">27</xref>). In response, the U.S. Food and Drug Administration (FDA) approved immune checkpoint inhibitors (ICIs) for patients with microsatellite instability-high (MSI-H) or mismatch repair-deficient (dMMR) CRC. These cancers exhibit high mutation rates and a strong neoantigen burden, triggering robust T cell-mediated tumor immune responses (<xref ref-type="bibr" rid="B28">28</xref>&#x2013;<xref ref-type="bibr" rid="B30">30</xref>). A recent study showed that 100% of 12 patients with advanced dMMR rectal cancer achieved a complete clinical and pathological response after six months of treatment with dostarlimab (<xref ref-type="bibr" rid="B31">31</xref>). However, ICIs have limited efficacy in proficient mismatch repair (pMMR), microsatellite-stable (MSS), or microsatellite instability-low (MSI-L) CRC, which account for 85% of cases (<xref ref-type="bibr" rid="B32">32</xref>, <xref ref-type="bibr" rid="B33">33</xref>). Given the biological complexity of the tumor microenvironment (TME) in most solid tumors, a multi-checkpoint inhibition strategy seems logical (<xref ref-type="bibr" rid="B34">34</xref>). Since CTLA-4 and PD-1 target non-redundant pathways, combining inhibitors for both may provide additive or synergistic effects. Some clinical trials have reported improved outcomes with combined PD-1/PD-L1 and CTLA-4 blockade compared to monotherapy (<xref ref-type="bibr" rid="B35">35</xref>). However, other studies suggest that combining these inhibitors has shown limited success in treating CRC (<xref ref-type="bibr" rid="B36">36</xref>). Moreover, combined ICI therapy is associated with a higher incidence of adverse events compared to single-agent treatment (<xref ref-type="bibr" rid="B37">37</xref>). To address these uncertainties, we conducted a systematic meta-analysis of the existing literature to evaluate the efficacy and safety of combining PD-1/PD-L1 and CTLA-4 inhibitors in CRC treatment.</p>
</sec>
<sec id="s2">
<label>2</label>
<title>Methods</title>
<sec id="s2_1">
<label>2.1</label>
<title>Article searching</title>
<p>This meta-analysis was conducted in strict accordance with the guidelines outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist (<xref ref-type="bibr" rid="B38">38</xref>), which ensures comprehensive, transparent, and methodologically sound reporting of systematic reviews and meta-analyses. The study protocol has been registered with the International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY) under Registration ID: INPLASY202480030.We performed a thorough search of online databases, including the Cochrane Library, Embase, and PubMed, for relevant clinical trials published up until April 13, 2024. The search terms included &#x201c;anti-PD-1,&#x201d; &#x201c;anti-PD-L1,&#x201d; &#x201c;anti-CTLA-4,&#x201d; &#x201c;immune checkpoint inhibitors,&#x201d; &#x201c;colorectal cancer,&#x201d; &#x201c;CRC,&#x201d; &#x201c;mCRC,&#x201d; and &#x201c;aCRC.&#x201d; Both free-text terms and Medical Subject Headings (MeSH) were used to search within titles and abstracts. Additionally, the reference lists of selected articles were screened to ensure comprehensive coverage. In cases of duplicate publications, the most comprehensive studies were selected for inclusion in the meta-analysis. Two authors independently extracted all relevant data, and any discrepancies were resolved through discussion and consensus.</p>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Study selection</title>
<p>Obtained records were exported to EndNote software (Clarivate Analytics, Philadelphia, PA, USA).After removing the duplicate publications, two review authors independently reviewed the title/abstract of the articles according to the inclusion and exclusion criteria. Afterward, the same two authors screened the full-texts of the selected records, independently. Discrepancies were resolved by consulting a third author.</p>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>Eligibility criteria</title>
<p>Trials were included if the following criteria were met (1):patients with aCRC aged 18 years or older were enrolled; (2):a PD-1/PD-L1 and CTLA-4 inhibitors with or without other standard treatments was given to one of the study arms; and (3):outcomes of interest in terms of efficacy (i.e. median overall survival [mOS], median progression-free survival [mPFS], objective response rate [ORR], disease control rate [DCR]),and safety (i.e.AEs and &#x2265; grade 3 AEs)were reported.</p>
<p>The exclusion criteria were as follows: (1) Non-advanced CRC included early, middle and locally advanced CRC; (2) animal experiments, cell research, reviews, meta-analyses,duplicates, case reports, or letters were not taken into consideration; and (3) studies with patient number less than 10 were excluded. Two investigators independently identified potential eligible articles through inclusion and exclusion criteria. Any disagreement regarding study inclusion was resolved between these two or with a third investigator.</p>
</sec>
<sec id="s2_4">
<label>2.4</label>
<title>Data extraction and quality assessment</title>
<p>Two researchers conducted independent literature searches, following predetermined criteria and specified strategies. This approach ensures a thorough and unbiased exploration of available literature, utilizing a systematic and structured methodology. Meticulous data extraction was performed, encompassing essential details such as authors, publication year, country, trial duration, Identifier, sample size, gender, age, median follow-up, name of ICIs, Other therapy besides ICIs,molecular phenotype and survival analyses, including mOS, mPFS, DCR, ORR, AEs&#x3001;&#x2265; grade 3 AEs. All included studies were treated as non-randomized trials. The quality of each study was meticulously evaluated using the methodological index for non-randomized studies (MINORS) (<xref ref-type="bibr" rid="B39">39</xref>). Studies scoring above 12 points were considered high-quality indicators. This stringent evaluation ensures that only studies meeting robust methodological standards contribute to the overall analysis.</p>
</sec>
<sec id="s2_5">
<label>2.5</label>
<title>Data synthesis</title>
<p>The primary efficacy endpoint was to estimate the mOS and mPFS after receiving PD-1/PD-L1 inhibitors combined with CTLA-4 inhibitors treatment regimens and the secondary efficacy endpoint was to estimate the pooled rate of ORR and DCR. The safety outcome was the pooled rate of AEs and &#x2265; grade 3 AEs, We used Cochrane&#x2019;s Q statistic to assess between-study heterogeneity and calculated the Isquare statistic. A random-effect model was applied if obvious heterogeneity was present (I2 &gt;50%), otherwise, a fixed-effect model was chosen (<xref ref-type="bibr" rid="B40">40</xref>). The subgroup analysis was conducted according to country(USA, Other), sample(&#x2265;40, &lt;40),other therapy(None,Yes), ICIs types (Nivolumab+Ipilimumab, Durvalumab+tremelimumab, QL1706 (PSB205)) and molecular phenotype (dMMR/MSI-H, pMMR/MSS, NR). Differences between groups were tested by the chi-square test. We used STATA version 18.0 (<xref ref-type="bibr" rid="B41">41</xref>) to calculate the pooled rates with metaprop command, which requires a nominator and a denominator (which is the total sample size) and some other options like random or fixed effects model. This command was built on the existing Stata command metan, which is routinely used to pool ratios and differences of means (<xref ref-type="bibr" rid="B42">42</xref>). A p-value less than 0.05 were treated as statistically significant.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<label>3</label>
<title>Results</title>
<sec id="s3_1">
<label>3.1</label>
<title>Study selection and characteristics of the included studies</title>
<p>There were 1363 documents searched from the databases. Of these, 150 replicated studies were deleted. After reading the title and abstract of each article, 19 articles were screened out. The full texts of these articles were then assessed comprehensively. 12 articles (<xref ref-type="bibr" rid="B35">35</xref>, <xref ref-type="bibr" rid="B36">36</xref>, <xref ref-type="bibr" rid="B43">43</xref>&#x2013;<xref ref-type="bibr" rid="B52">52</xref>)that meet the criteria were selected with a total of 566 patients. <xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref> summarizes the detailed information about article selection. The 12 and 11 included studies were eligible for ORR and DCR, respectively. The 8 included studies were eligible for mPFS and adverse reaction data analysis, and of those, 6 were eligible for mOS data analysis. <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref> lists the characteristics of the 12 trials. The extracted characteristics were summarized as follows: authors, publication year, country, trial duration, Identifier, sample size, gender, age, median follow-up, name of ICIs, Other therapy besides ICIs and molecular phenotype.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Prisma flowchart illustrating the literature selection process.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-15-1485303-g001.tif"/>
</fig>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Baseline characteristics of included studies.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center">Study, year</th>
<th valign="middle" align="center">Country</th>
<th valign="middle" align="center">Duration</th>
<th valign="middle" align="center">Identifier</th>
<th valign="middle" align="center">Sample size</th>
<th valign="middle" align="center">Gender (M/F)</th>
<th valign="middle" align="center">Age (range)</th>
<th valign="middle" align="center">Median follow-up (months)</th>
<th valign="middle" align="center">Name of ICIs</th>
<th valign="middle" align="center">Other therapy besides ICIs</th>
<th valign="middle" align="center">Molecular<break/>phenotype</th>
<th valign="middle" align="center">MINORS<break/>score</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="center">Andr&#xe9; et&#xa0;al., 2022</td>
<td valign="middle" align="center">USA</td>
<td valign="middle" align="center">NR</td>
<td valign="middle" align="center">NCT02060188</td>
<td valign="middle" align="center">119</td>
<td valign="middle" align="center">70/49</td>
<td valign="middle" align="center">58 (21-88)</td>
<td valign="middle" align="center">50.9</td>
<td valign="middle" align="center">Nivolumab+Ipilimumab</td>
<td valign="middle" align="center">None</td>
<td valign="middle" align="center">dMMR/MSI-H</td>
<td valign="middle" align="center">14</td>
</tr>
<tr>
<td valign="middle" align="center">Chen et&#xa0;al., 2020</td>
<td valign="middle" align="center">Canada</td>
<td valign="middle" align="center">2016-2017</td>
<td valign="middle" align="center">NCT02870920</td>
<td valign="middle" align="center">119</td>
<td valign="middle" align="center">74/45</td>
<td valign="middle" align="center">65 (39-87)</td>
<td valign="middle" align="center">15.2</td>
<td valign="middle" align="center">Durvalumab+tremelimumab</td>
<td valign="middle" align="center">None</td>
<td valign="middle" align="center">pMMR/MSS</td>
<td valign="middle" align="center">15</td>
</tr>
<tr>
<td valign="middle" align="center">Cohen et&#xa0;al., 2020</td>
<td valign="middle" align="center">France</td>
<td valign="middle" align="center">2017-2018</td>
<td valign="middle" align="center">NCT03350126</td>
<td valign="middle" align="center">57</td>
<td valign="middle" align="center">30/27</td>
<td valign="middle" align="center">56.5(45.8-63.8)</td>
<td valign="middle" align="center">18.1</td>
<td valign="middle" align="center">Nivolumab+Ipilimumab</td>
<td valign="middle" align="center">None</td>
<td valign="middle" align="center">MSI/dMMR</td>
<td valign="middle" align="center">15</td>
</tr>
<tr>
<td valign="middle" align="center">Fakih et&#xa0;al., 2023</td>
<td valign="middle" align="center">USA</td>
<td valign="middle" align="center">2020-2022</td>
<td valign="middle" align="center">NCT04362839</td>
<td valign="middle" align="center">29</td>
<td valign="middle" align="center">12/17</td>
<td valign="middle" align="center">55 (36-75)</td>
<td valign="middle" align="center">NR</td>
<td valign="middle" align="center">Nivolumab+Ipilimumab</td>
<td valign="middle" align="center">Regorafenib</td>
<td valign="middle" align="center">MSS</td>
<td valign="middle" align="center">14</td>
</tr>
<tr>
<td valign="middle" align="center">Marie et&#xa0;al., 2021</td>
<td valign="middle" align="center">USA</td>
<td valign="middle" align="center">2016-2020</td>
<td valign="middle" align="center">NCT02754856</td>
<td valign="middle" align="center">23</td>
<td valign="middle" align="center">12/11</td>
<td valign="middle" align="center">56 (28&#x2013;69)</td>
<td valign="middle" align="center">27.6</td>
<td valign="middle" align="center">Durvalumab+tremelimumab</td>
<td valign="middle" align="center">None</td>
<td valign="middle" align="center">pMMR/dMMR</td>
<td valign="middle" align="center">15</td>
</tr>
<tr>
<td valign="middle" align="center">Monge et&#xa0;al., 2023</td>
<td valign="middle" align="center">USA</td>
<td valign="middle" align="center">NR</td>
<td valign="middle" align="center">NR</td>
<td valign="middle" align="center">18</td>
<td valign="middle" align="center">8/10</td>
<td valign="middle" align="center">56.5 (28-76)</td>
<td valign="middle" align="center">14</td>
<td valign="middle" align="center">Durvalumab+tremelimumab</td>
<td valign="middle" align="center">PexaVec</td>
<td valign="middle" align="center">pMMR/MSS</td>
<td valign="middle" align="center">13</td>
</tr>
<tr>
<td valign="middle" align="center">Monjazeb et&#xa0;al., 2021</td>
<td valign="middle" align="center">USA</td>
<td valign="middle" align="center">NR</td>
<td valign="middle" align="center">NCT02888743</td>
<td valign="middle" align="center">20</td>
<td valign="middle" align="center">9/11</td>
<td valign="middle" align="center">59 (29-79)</td>
<td valign="middle" align="center">3.9</td>
<td valign="middle" align="center">Durvalumab+tremelimumab</td>
<td valign="middle" align="center">Radiotherapy</td>
<td valign="middle" align="center">MSS</td>
<td valign="middle" align="center">12</td>
</tr>
<tr>
<td valign="middle" align="center">Morano et&#xa0;al., 2022</td>
<td valign="middle" align="center">Italy</td>
<td valign="middle" align="center">2019-2020</td>
<td valign="middle" align="center">NCT03832621</td>
<td valign="middle" align="center">33</td>
<td valign="middle" align="center">17/16</td>
<td valign="middle" align="center">58 (53-65)</td>
<td valign="middle" align="center">23.1</td>
<td valign="middle" align="center">Nivolumab+Ipilimumab</td>
<td valign="middle" align="center">Temozolomide</td>
<td valign="middle" align="center">pMMR/MSS</td>
<td valign="middle" align="center">14</td>
</tr>
<tr>
<td valign="middle" align="center">Parikh et&#xa0;al., 2021</td>
<td valign="middle" align="center">USA</td>
<td valign="middle" align="center">NR</td>
<td valign="middle" align="center">NCT03104439</td>
<td valign="middle" align="center">40</td>
<td valign="middle" align="center">22/18</td>
<td valign="middle" align="center">59 (26-83)</td>
<td valign="middle" align="center">16.6</td>
<td valign="middle" align="center">Nivolumab+Ipilimumab</td>
<td valign="middle" align="center">Radiotherapy</td>
<td valign="middle" align="center">MSS</td>
<td valign="middle" align="center">14</td>
</tr>
<tr>
<td valign="middle" align="center">Segal et&#xa0;al., 2021</td>
<td valign="middle" align="center">USA</td>
<td valign="middle" align="center">NR</td>
<td valign="middle" align="center">NCT03122509</td>
<td valign="middle" align="center">24</td>
<td valign="middle" align="center">13/11</td>
<td valign="middle" align="center">55 (26-78)</td>
<td valign="middle" align="center">21.8</td>
<td valign="middle" align="center">Durvalumab+tremelimumab</td>
<td valign="middle" align="center">Radiotherapy</td>
<td valign="middle" align="center">pMMR</td>
<td valign="middle" align="center">13</td>
</tr>
<tr>
<td valign="middle" align="center">Thibaudin et&#xa0;al., 2023</td>
<td valign="middle" align="center">France</td>
<td valign="middle" align="center">2017-2019</td>
<td valign="middle" align="center">NCT03202758</td>
<td valign="middle" align="center">57</td>
<td valign="middle" align="center">24/33</td>
<td valign="middle" align="center">63.6 (28-80)</td>
<td valign="middle" align="center">36</td>
<td valign="middle" align="center">Durvalumab+tremelimumab</td>
<td valign="middle" align="center">mFOLFOX6</td>
<td valign="middle" align="center">MSS/MSI</td>
<td valign="middle" align="center">15</td>
</tr>
<tr>
<td valign="middle" align="center">Zhao et&#xa0;al., 2023</td>
<td valign="middle" align="center">China</td>
<td valign="middle" align="center">2020-2021</td>
<td valign="middle" align="center">NCT04296994 and NCT05171790</td>
<td valign="middle" align="center">27</td>
<td valign="middle" align="center">NR</td>
<td valign="middle" align="center">NR</td>
<td valign="middle" align="center">9.5</td>
<td valign="middle" align="center">QL1706 (PSB205)</td>
<td valign="middle" align="center">None</td>
<td valign="middle" align="center">NR</td>
<td valign="middle" align="center">14</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>M, male; F, female; NR, not report; Nivolumab; Ipilimumab; Durvalumab; Tremelimumab; Regorafenib; PexaVec; Radiotherapy; Temozolomide; mFOLFOX6; MSI,microsatellite instability; MSI-H,microsatellite instability -high; dMMR,deficient mismatch repair; pMMR,proficient mismatch repair; MSS,microsatellite stable group; MINORS,methodological index for non-randomized studies.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>Quality assessment</title>
<p>12 non-randomized studies were assessed using the methodological index for non-randomized studies (MINORS), which categorized studies into three dimensions based on eight items, including stated aim, population election, endpoints, and prospective calculation. The quality assessment details are shown in <xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>.</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Methodological index for non-randomized studies (MINORS) for quality.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center">Studies</th>
<th valign="middle" align="center">A clearly stated aim</th>
<th valign="middle" align="center">Inclusion of consecutive patients</th>
<th valign="middle" align="center">Prospective collection of data</th>
<th valign="middle" align="center">Endpoints appropriate to the aim of the study</th>
<th valign="middle" align="center">Unbiased assessment of the study endpoint</th>
<th valign="middle" align="center">Follow-up period appropriate to the aim of the study</th>
<th valign="middle" align="center">Loss to follow up less than 5%</th>
<th valign="middle" align="center">Prospective calculation of the study size</th>
<th valign="middle" align="center">Scores</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="center">Andr&#xe9; et&#xa0;al., 2022</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">14</td>
</tr>
<tr>
<td valign="middle" align="center">Chen et&#xa0;al., 2020</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">15</td>
</tr>
<tr>
<td valign="middle" align="center">Cohen et&#xa0;al., 2020</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">15</td>
</tr>
<tr>
<td valign="middle" align="center">Fakih et&#xa0;al., 2023</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">14</td>
</tr>
<tr>
<td valign="middle" align="center">Marie et&#xa0;al., 2021</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">15</td>
</tr>
<tr>
<td valign="middle" align="center">Monge et&#xa0;al., 2023</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">13</td>
</tr>
<tr>
<td valign="middle" align="center">Monjazeb et&#xa0;al., 2021</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">12</td>
</tr>
<tr>
<td valign="middle" align="center">Morano et&#xa0;al., 2022</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">14</td>
</tr>
<tr>
<td valign="middle" align="center">Parikh et&#xa0;al., 2021</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">14</td>
</tr>
<tr>
<td valign="middle" align="center">Segal et&#xa0;al., 2021</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">13</td>
</tr>
<tr>
<td valign="middle" align="center">Thibaudin et&#xa0;al., 2023</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">15</td>
</tr>
<tr>
<td valign="middle" align="center">Zhao et&#xa0;al., 2023</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">1</td>
<td valign="bottom" align="center">2</td>
<td valign="bottom" align="center">14</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s3_3">
<label>3.3</label>
<title>Efficacy</title>
<sec id="s3_3_1">
<label>3.3.1</label>
<title>Survival</title>
<p>5 studies with a total of 221 patients were included to determine the OS of patients treated with PD-1/PD-L1 inhibitor and CTLA-4 inhibitor. As shown in <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2A</bold>
</xref>, the random-effect model meta-analysis illuminated that the pooled mOS was 6.66 months (95%CI: 4.85-9.16, I2 = 79.9%, P=0.001), suggesting that PD-1/PD-L1 and CTLA-4 immune checkpoint inhibitors achieved good mOS in the treatment of aCRC. We also analyzed the mPFS of PD-1/PD-L1 inhibitor and CTLA-4 inhibitor in advanced CRC. As shown in <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2B</bold>
</xref>, the pooled mPFS of 340 patients in 8 studies was 2.92 months (95%CI: 2.23-3.83, I2 = 98.3%, P&lt;0.0001). The result suggests that PD-1/PD-L1 inhibitors and CTLA-4 inhibitors performed well in terms of mPFS in the treatment of aCRC. These results all indicate a PD-1/PD-L1 inhibitors and CTLA-4 inhibitors are to the benefit of aCRC patients&#x2019; survival, as supported by the meta-analysis outcomes.</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Forest plot for the <bold>(A)</bold> median overall survival (mOS) and <bold>(B)</bold> median progression-free survival (mPFS) in aCRC patients receiving PD-1/PD-L1 inhibitors combined with CTLA-4 inhibitors.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-15-1485303-g002.tif"/>
</fig>
</sec>
<sec id="s3_3_2">
<label>3.3.2</label>
<title>Response rates</title>
<p>We included 12 studies with a total of 566 patients to assess the objective response rate (ORR). The pooled ORR was 21% (95% CI: 6%&#x2013;41%, I&#xb2; = 95.92%, P &lt; 0.001, <xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3A</bold>
</xref>). For disease control rate (DCR), we pooled data from 11 studies involving 563 patients, resulting in a DCR of 49% (95% CI: 27%&#x2013;71%, I&#xb2; = 98.05%, P &lt; 0.001, <xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3B</bold>
</xref>). Subgroup analyses were conducted based on country (USA vs. Other), sample size (&#x2265;40 vs. &lt;40), additional therapy (None vs. Yes), type of immune checkpoint inhibitors (Nivolumab+Ipilimumab, Durvalumab+Tremelimumab, QL1706 [PSB205]), and molecular phenotype (dMMR/MSI-H vs. pMMR/MSS vs. NR) to further explore the efficacy of PD-1/PD-L1 and CTLA-4 inhibitors. As shown in <xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>, the ORR for patients treated in the USA was significantly lower compared to patients from other countries. Additionally, studies with sample sizes &#x2265;40 reported better ORR than those with &lt;40 samples. The subgroup of patients who did not receive additional therapies showed higher ORR compared to those who did. Furthermore, the combination of Nivolumab and Ipilimumab demonstrated a higher ORR than both Durvalumab+Tremelimumab and QL1706 (PSB205). The ORR for patients with dMMR/MSI-H was also higher than for those with pMMR/MSS. Similarly, the DCR followed the same pattern. More favorable outcomes were observed in patients from non-USA countries, in studies with sample sizes &#x2265;40, in those not receiving other therapies, in patients treated with Nivolumab+Ipilimumab, and in those with dMMR/MSI-H (<xref ref-type="table" rid="T4">
<bold>Table&#xa0;4</bold>
</xref>). These subgroup differences may be key sources of heterogeneity.</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Forest plot for the <bold>(A)</bold> Objective response rate (ORR) and <bold>(B)</bold> Disease control rate (DCR) in aCRC patients receiving PD-1/PD-L1 inhibitors combined with CTLA-4 inhibitors.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-15-1485303-g003.tif"/>
</fig>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Subgroup analysis of pooled of the overall response rate.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" rowspan="2" align="center">Subgroup</th>
<th valign="middle" rowspan="2" align="center">NO. of studies</th>
<th valign="middle" rowspan="2" align="center">Ratio<break/>(95% CI)</th>
<th valign="middle" colspan="2" align="center">Heterogeneity</th>
</tr>
<tr>
<th valign="middle" align="center">I2 (%)</th>
<th valign="middle" align="center">Ph</th>
</tr>
</thead>
<tbody>
<tr>
<th valign="middle" colspan="5" align="left">Country</th>
</tr>
<tr>
<td valign="middle" align="left">USA</td>
<td valign="bottom" align="left">7</td>
<td valign="bottom" align="left">14% (0-39%)</td>
<td valign="bottom" align="left">94.52</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">Other</td>
<td valign="bottom" align="left">5</td>
<td valign="bottom" align="left">31% (4%-68%)</td>
<td valign="bottom" align="left">97.4</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Sample</th>
</tr>
<tr>
<td valign="bottom" align="left">&#x2265;40</td>
<td valign="bottom" align="left">5</td>
<td valign="bottom" align="left">35% (6%-73%)</td>
<td valign="bottom" align="left">98.71</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">&lt;40</td>
<td valign="bottom" align="left">7</td>
<td valign="bottom" align="left">12% (2%-26%)</td>
<td valign="bottom" align="left">81.42</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Other therapy</th>
</tr>
<tr>
<td valign="bottom" align="left">None</td>
<td valign="bottom" align="left">4</td>
<td valign="bottom" align="left">28% (0-73%)</td>
<td valign="bottom" align="left">98.46</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">Yes</td>
<td valign="bottom" align="left">8</td>
<td valign="bottom" align="left">18% (4%-37%)</td>
<td valign="bottom" align="left">90.51</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">ICIs</th>
</tr>
<tr>
<td valign="middle" align="left">Nivolumab+Ipilimumab</td>
<td valign="bottom" align="left">5</td>
<td valign="bottom" align="left">41%(20%-63%)</td>
<td valign="bottom" align="left">92.18</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">Durvalumab+tremelimumab</td>
<td valign="bottom" align="left">6</td>
<td valign="bottom" align="left">10% (0-35%)</td>
<td valign="bottom" align="left">95.01</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">QL1706 (PSB205)</td>
<td valign="bottom" align="left">1</td>
<td valign="bottom" align="left">7% (1%-24%)</td>
<td valign="bottom" align="left">&#x2013;</td>
<td valign="bottom" align="left">&#x2013;</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Molecular phenotype</th>
</tr>
<tr>
<td valign="middle" align="left">dMMR/MSI</td>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">63%(56%-70%)</td>
<td valign="middle" align="left">&#x2013;</td>
<td valign="middle" align="left">&#x2013;</td>
</tr>
<tr>
<td valign="middle" align="left">pMMR/MSS</td>
<td valign="middle" align="left">8</td>
<td valign="middle" align="left">15%(1%-36%)</td>
<td valign="middle" align="left">94.44</td>
<td valign="middle" align="left">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">NR</td>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">10%(3%-21%)</td>
<td valign="middle" align="left">&#x2013;</td>
<td valign="middle" align="left">&#x2013;</td>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap id="T4" position="float">
<label>Table&#xa0;4</label>
<caption>
<p>Subgroup analysis of pooled of the disease control rate.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" rowspan="2" align="center">Subgroup</th>
<th valign="middle" rowspan="2" align="center">NO. of studies</th>
<th valign="middle" rowspan="2" align="center">Ratio<break/>(95% CI)</th>
<th valign="middle" colspan="2" align="center">Heterogeneity</th>
</tr>
<tr>
<th valign="middle" align="center">I2 (%)</th>
<th valign="middle" align="center">Ph</th>
</tr>
</thead>
<tbody>
<tr>
<th valign="middle" colspan="5" align="left">Country</th>
</tr>
<tr>
<td valign="middle" align="left">USA</td>
<td valign="bottom" align="left">7</td>
<td valign="bottom" align="left">44%(14%-74%)</td>
<td valign="bottom" align="left">97.67</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">Other</td>
<td valign="bottom" align="left">4</td>
<td valign="bottom" align="left">58%(19%-97%)</td>
<td valign="bottom" align="left">98.78</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Sample</th>
</tr>
<tr>
<td valign="bottom" align="left">&#x2265;40</td>
<td valign="bottom" align="left">5</td>
<td valign="bottom" align="left">64% (34%-93%)</td>
<td valign="bottom" align="left">98.61</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">&lt;40</td>
<td valign="bottom" align="left">6</td>
<td valign="bottom" align="left">37% (8%-66%)</td>
<td valign="bottom" align="left">95.63</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Other therapy</th>
</tr>
<tr>
<td valign="bottom" align="left">None</td>
<td valign="bottom" align="left">4</td>
<td valign="bottom" align="left">56% (20%-92%)</td>
<td valign="bottom" align="left">98.64</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">Yes</td>
<td valign="bottom" align="left">7</td>
<td valign="bottom" align="left">45% (13%-77%)</td>
<td valign="bottom" align="left">97.91</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">ICIs</th>
</tr>
<tr>
<td valign="middle" align="left">Nivolumab+Ipilimumab</td>
<td valign="bottom" align="left">4</td>
<td valign="bottom" align="left">41%(20%-63%)</td>
<td valign="bottom" align="left">96.09</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">Durvalumab+tremelimumab</td>
<td valign="bottom" align="left">6</td>
<td valign="bottom" align="left">10% (0-35%)</td>
<td valign="bottom" align="left">98.52</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">QL1706 (PSB205)</td>
<td valign="bottom" align="left">1</td>
<td valign="bottom" align="left">26% (11%-46%)</td>
<td valign="bottom" align="left">&#x2013;</td>
<td valign="bottom" align="left">&#x2013;</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Molecular phenotype</th>
</tr>
<tr>
<td valign="middle" align="left">dMMR/MSI</td>
<td valign="bottom" align="left">2</td>
<td valign="bottom" align="left">87%(82%-92%)</td>
<td valign="bottom" align="left">&#x2013;</td>
<td valign="bottom" align="left">&#x2013;</td>
</tr>
<tr>
<td valign="middle" align="left">pMMR/MSS</td>
<td valign="bottom" align="left">7</td>
<td valign="bottom" align="left">35%(12%-62%)</td>
<td valign="bottom" align="left">94.95</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">NR</td>
<td valign="bottom" align="left">2</td>
<td valign="bottom" align="left">55%(40%-69%)</td>
<td valign="bottom" align="left">&#x2013;</td>
<td valign="bottom" align="left">&#x2013;</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
</sec>
<sec id="s3_4">
<label>3.4</label>
<title>Safety</title>
<p>The adverse events (AEs) associated with the combination of anti-PD-1/PD-L1 and anti-CTLA-4 in treating aCRC were analyzed, including both all-grade AEs and &#x2265; grade 3 AEs. Most patients experienced grade 1&#x2013;2 AEs, which were generally well tolerated. Data from 8 studies reported on the rates of any-grade AEs and &#x2265; grade 3 AEs. As shown in <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>, the pooled rate of all-grade AEs was 94% (95% CI: 86%&#x2013;99%, I&#xb2; = 84.02%, P &lt; 0.001, <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4A</bold>
</xref>), while the pooled rate of &#x2265; grade 3 AEs was 44% (95% CI: 30%&#x2013;59%, I&#xb2; = 90.47%, P &lt; 0.001, <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4B</bold>
</xref>). <xref ref-type="table" rid="T5">
<bold>Table&#xa0;5</bold>
</xref> and <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Figures S1, S2</bold>
</xref> indicate that the three most commonly reported AEs were fatigue (26%, 95% CI: 6%&#x2013;54%), diarrhea (19%, 95% CI: 9%&#x2013;31%), and anemia (18%, 95% CI: 0%&#x2013;55%). The most frequent &#x2265; grade 3 AEs were lymphopenia (5%, 95% CI: 3%&#x2013;7%), diarrhea (3%, 95% CI: 1%&#x2013;5%), and increased aspartate aminotransferase (3%, 95% CI: 2%&#x2013;5%).Subgroup analyses of AEs and &#x2265; grade 3 AEs were conducted, as shown in <xref ref-type="table" rid="T6">
<bold>Tables&#xa0;6</bold>
</xref> and <xref ref-type="table" rid="T7">
<bold>7</bold>
</xref>. The results suggested that country, sample size, additional therapies, immune checkpoint inhibitors (ICIs), and molecular phenotype were potential sources of heterogeneity. Patients in the USA had a lower incidence of both all-grade AEs (90% vs. 96%) and &#x2265; grade 3 AEs (42% vs. 46%) compared to those from other countries, with lower heterogeneity. Studies with sample sizes &#x2265; 40 reported higher rates of all-grade AEs (94% vs. 92%) and &#x2265; grade 3 AEs (52% vs. 27%) than those with sample sizes &lt; 40. Additionally, patients receiving other therapies in combination with PD-1/PD-L1 and CTLA-4 inhibitors had slightly higher rates of both all-grade AEs (94% vs. 93%) and &#x2265; grade 3 AEs (45% vs. 42%). The type of ICIs used also influenced AE rates: Nivolumab+Ipilimumab had a lower rate of all-grade AEs (86% vs. 97%) compared to Durvalumab+Tremelimumab, with similar trends observed for &#x2265; grade 3 AEs (38% vs. 51%). Finally, the pMMR/MSS molecular phenotype was associated with a higher incidence of all-grade AEs (95% vs. 85%) and a greater occurrence of &#x2265; grade 3 AEs (45% vs. 31%).</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Forest plot for the <bold>(A)</bold> adverse events(AEs) rate and <bold>(B)</bold> and &#x2265;grade 3 AEs rate in aCRC patients receiving PD-1/PD-L1 inhibitors combined with CTLA-4 inhibitors.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-15-1485303-g004.tif"/>
</fig>
<table-wrap id="T5" position="float">
<label>Table&#xa0;5</label>
<caption>
<p>Adverse events of the studies included in the meta-analysis.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" rowspan="2" align="center">TRAEs</th>
<th valign="middle" colspan="2" align="center">All Grade</th>
</tr>
<tr>
<th valign="middle" align="center">ES,%(95%CI)</th>
<th valign="middle" align="center">I<sup>2%</sup>
</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="left">fatigue</td>
<td valign="middle" align="center">26 (6-54)</td>
<td valign="middle" align="center">96.84</td>
</tr>
<tr>
<td valign="middle" align="left">diarrhea</td>
<td valign="middle" align="center">19 (9-31)</td>
<td valign="middle" align="center">86.91</td>
</tr>
<tr>
<td valign="middle" align="left">anemia</td>
<td valign="middle" align="center">18 (0-55)</td>
<td valign="middle" align="center">98.37</td>
</tr>
<tr>
<td valign="middle" align="left">fever</td>
<td valign="middle" align="center">13 (1-35)</td>
<td valign="middle" align="center">96.17</td>
</tr>
<tr>
<td valign="middle" align="left">nausea</td>
<td valign="middle" align="center">12 (0-34)</td>
<td valign="middle" align="center">96.40</td>
</tr>
<tr>
<td valign="middle" align="left">pruritus</td>
<td valign="middle" align="center">10 (1-26)</td>
<td valign="middle" align="center">93.59</td>
</tr>
<tr>
<th valign="middle" rowspan="2" align="center">TRAEs</th>
<th valign="middle" colspan="2" align="center">&#x2265;3 Grade</th>
</tr>
<tr>
<th valign="middle" align="center">ES,%(95%CI)</th>
<th valign="middle" align="center">I<sup>2%</sup>
</th>
</tr>
<tr>
<td valign="middle" align="left">lymphopenia</td>
<td valign="middle" align="center">5 (3-7)</td>
<td valign="middle" align="center">0</td>
</tr>
<tr>
<td valign="middle" align="left">diarrhea</td>
<td valign="middle" align="center">3 (1-5)</td>
<td valign="middle" align="center">7.85</td>
</tr>
<tr>
<td valign="middle" align="left">Aspartate aminotransferase increase</td>
<td valign="middle" align="center">3 (2-5)</td>
<td valign="middle" align="center">0</td>
</tr>
<tr>
<td valign="middle" align="left">erythra</td>
<td valign="middle" align="center">3 (1-5)</td>
<td valign="middle" align="center">0</td>
</tr>
<tr>
<td valign="middle" align="left">anemia</td>
<td valign="middle" align="center">3 (1-5)</td>
<td valign="middle" align="center">0</td>
</tr>
<tr>
<td valign="middle" align="left">fatigue</td>
<td valign="middle" align="center">2 (1-4)</td>
<td valign="middle" align="center">0</td>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap id="T6" position="float">
<label>Table&#xa0;6</label>
<caption>
<p>Subgroup analysis of pooled of the adverse events.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" rowspan="2" align="center">Subgroup</th>
<th valign="middle" rowspan="2" align="center">NO. of studies</th>
<th valign="middle" rowspan="2" align="center">Ratio<break/>(95% CI)</th>
<th valign="middle" colspan="2" align="center">Heterogeneity</th>
</tr>
<tr>
<th valign="middle" align="center">I2 (%)</th>
<th valign="middle" align="center">Ph</th>
</tr>
</thead>
<tbody>
<tr>
<th valign="middle" colspan="5" align="left">Country</th>
</tr>
<tr>
<td valign="middle" align="left">USA</td>
<td valign="bottom" align="left">4</td>
<td valign="bottom" align="left">90% (81%-96%)</td>
<td valign="bottom" align="left">46.51</td>
<td valign="bottom" align="left">0.13</td>
</tr>
<tr>
<td valign="bottom" align="left">Other</td>
<td valign="bottom" align="left">4</td>
<td valign="bottom" align="left">96%(86%-100%)</td>
<td valign="bottom" align="left">86.29</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Sample</th>
</tr>
<tr>
<td valign="bottom" align="left">&#x2265;40</td>
<td valign="bottom" align="left">4</td>
<td valign="bottom" align="left">94% (82%-100%)</td>
<td valign="bottom" align="left">92</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">&lt;40</td>
<td valign="bottom" align="left">4</td>
<td valign="bottom" align="left">92% (83%-98%)</td>
<td valign="bottom" align="left">32.3</td>
<td valign="bottom" align="left">0.22</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Other therapy</th>
</tr>
<tr>
<td valign="bottom" align="left">None</td>
<td valign="bottom" align="left">3</td>
<td valign="bottom" align="left">93% (75%-100%)</td>
<td valign="bottom" align="left">&#x2013;</td>
<td valign="bottom" align="left">&#x2013;</td>
</tr>
<tr>
<td valign="middle" align="left">Yes</td>
<td valign="bottom" align="left">5</td>
<td valign="bottom" align="left">94% (87%-99%)</td>
<td valign="bottom" align="left">51.23</td>
<td valign="bottom" align="left">0.08</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">ICIs</th>
</tr>
<tr>
<td valign="middle" align="left">Nivolumab+Ipilimumab</td>
<td valign="bottom" align="left">3</td>
<td valign="bottom" align="left">86% (81%-91%)</td>
<td valign="bottom" align="left">&#x2013;</td>
<td valign="bottom" align="left">&#x2013;</td>
</tr>
<tr>
<td valign="middle" align="left">Durvalumab+tremelimumab</td>
<td valign="bottom" align="left">5</td>
<td valign="bottom" align="left">97% (89%-100%)</td>
<td valign="bottom" align="left">76</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Molecular phenotype</th>
</tr>
<tr>
<td valign="middle" align="left">dMMR/MSI</td>
<td valign="bottom" align="left">2</td>
<td valign="bottom" align="left">85%(80%-90%)</td>
<td valign="bottom" align="left">&#x2013;</td>
<td valign="bottom" align="left">&#x2013;</td>
</tr>
<tr>
<td valign="middle" align="left">pMMR/MSS</td>
<td valign="bottom" align="left">5</td>
<td valign="bottom" align="left">95%(84%-100%)</td>
<td valign="bottom" align="left">80.49</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">NR</td>
<td valign="bottom" align="left">1</td>
<td valign="bottom" align="left">98%(91%-100%)</td>
<td valign="bottom" align="left">&#x2013;</td>
<td valign="bottom" align="left">&#x2013;</td>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap id="T7" position="float">
<label>Table&#xa0;7</label>
<caption>
<p>Subgroup analysis of pooled of the &#x2265;grade 3 adverse events.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" rowspan="2" align="center">Subgroup</th>
<th valign="middle" rowspan="2" align="center">NO. of studies</th>
<th valign="middle" rowspan="2" align="center">Ratio<break/>(95% CI)</th>
<th valign="middle" colspan="2" align="center">Heterogeneity</th>
</tr>
<tr>
<th valign="middle" align="center">I2 (%)</th>
<th valign="middle" align="center">Ph</th>
</tr>
</thead>
<tbody>
<tr>
<th valign="middle" colspan="5" align="left">Country</th>
</tr>
<tr>
<td valign="middle" align="left">USA</td>
<td valign="bottom" align="left">4</td>
<td valign="bottom" align="left">42% (22%-63%)</td>
<td valign="bottom" align="left">87.29</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<td valign="bottom" align="left">Other</td>
<td valign="bottom" align="left">4</td>
<td valign="bottom" align="left">46% (24%-68%)</td>
<td valign="bottom" align="left">93.17</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Sample</th>
</tr>
<tr>
<td valign="bottom" align="left">&#x2265;40</td>
<td valign="bottom" align="left">5</td>
<td valign="bottom" align="left">52% (35%-70%)</td>
<td valign="bottom" align="left">92.46</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">&lt;40</td>
<td valign="bottom" align="left">3</td>
<td valign="bottom" align="left">27% (16%-38%)</td>
<td valign="bottom" align="left">&#x2013;</td>
<td valign="bottom" align="left">&#x2013;</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Other therapy</th>
</tr>
<tr>
<td valign="bottom" align="left">None</td>
<td valign="bottom" align="left">3</td>
<td valign="bottom" align="left">42% (20%-64%)</td>
<td valign="bottom" align="left">&#x2013;</td>
<td valign="bottom" align="left">&#x2013;</td>
</tr>
<tr>
<td valign="middle" align="left">Yes</td>
<td valign="bottom" align="left">5</td>
<td valign="bottom" align="left">45% (24%-67%)</td>
<td valign="bottom" align="left">89.84</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">ICIs</th>
</tr>
<tr>
<td valign="middle" align="left">Nivolumab+Ipilimumab</td>
<td valign="bottom" align="left">4</td>
<td valign="bottom" align="left">38% (20%-56%)</td>
<td valign="bottom" align="left">89.39</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">Durvalumab+tremelimumab</td>
<td valign="bottom" align="left">4</td>
<td valign="bottom" align="left">51% (33%-69%)</td>
<td valign="bottom" align="left">84.53</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Molecular phenotype</th>
</tr>
<tr>
<td valign="middle" align="left">dMMR/MSI</td>
<td valign="bottom" align="left">2</td>
<td valign="bottom" align="left">31%(25%-38%)</td>
<td valign="bottom" align="left">&#x2013;</td>
<td valign="bottom" align="left">&#x2013;</td>
</tr>
<tr>
<td valign="middle" align="left">pMMR/MSS</td>
<td valign="bottom" align="left">5</td>
<td valign="bottom" align="left">45%(25%-65%)</td>
<td valign="bottom" align="left">87.85</td>
<td valign="bottom" align="left">&lt;0.001</td>
</tr>
<tr>
<td valign="middle" align="left">NR</td>
<td valign="bottom" align="left">1</td>
<td valign="bottom" align="left">67%(53%-79%)</td>
<td valign="bottom" align="left">&#x2013;</td>
<td valign="bottom" align="left">&#x2013;</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<label>4</label>
<title>Discussion</title>
<p>Chemotherapy, cytotoxic drugs, and molecular targeted therapies have commonly been used in the treatment of advanced colorectal cancer (aCRC), but their efficacy has plateaued (<xref ref-type="bibr" rid="B14">14</xref>, <xref ref-type="bibr" rid="B53">53</xref>). Recently, numerous clinical trials related to immunotherapy have confirmed that it is an encouraging new treatment strategy for colorectal cancer (<xref ref-type="bibr" rid="B54">54</xref>&#x2013;<xref ref-type="bibr" rid="B57">57</xref>). The two most widely studied immune checkpoints are PD-1 and CTLA-4. PD-1 is a cell surface receptor commonly found on T cells, B cells, and NK cells. When the PD-1 receptor binds to its ligand, it inhibits cell proliferation, cytokine secretion, and the cytotoxic capabilities of immune cells, thus weakening the immune response (<xref ref-type="bibr" rid="B58">58</xref>). CTLA-4 receptors, expressed on activated or regulatory T cells, bind to B7 ligands on antigen-presenting cells with a higher affinity and lower surface density. This binding prevents CD28 receptors from interacting with B7 ligands, leading to a net downregulation of T cell activation (<xref ref-type="bibr" rid="B59">59</xref>). A previous meta-analysis indicated that PD-1 inhibitors and combination immunotherapy demonstrate promising clinical responses and overall survival (OS) rates, alongside manageable adverse events (AEs) in the treatment of dMMR colorectal cancer (<xref ref-type="bibr" rid="B60">60</xref>). Although single-agent immune checkpoint inhibitors (ICIs) perform well, one study noted that ICI therapy resistance has been observed in up to 50% of patients with microsatellite instability-high (MSI-H) CRC. Furthermore, single-agent ICIs show minimal efficacy in patients with proficient mismatch repair (pMMR) or microsatellite stable (MSS) metastatic CRC (<xref ref-type="bibr" rid="B61">61</xref>, <xref ref-type="bibr" rid="B62">62</xref>). To address tumor escape mechanisms, substantial efforts have been made to enhance the clinical efficacy of ICIs in colorectal cancer through combination therapies. Specifically, the combination of CTLA-4 and PD-1/PD-L1 blockade increases T cell activation and treatment efficacy, resulting in better antitumor outcomes (<xref ref-type="bibr" rid="B56">56</xref>, <xref ref-type="bibr" rid="B63">63</xref>). Preclinical studies have shown that combined immunotherapy is superior to monotherapy. The dual blockade of PD-1/PD-L1 and CTLA-4 can increase the number of T cells regulated by multiple mechanisms and enhance their effector function (<xref ref-type="bibr" rid="B64">64</xref>). Currently, extensive research is being conducted to extend the indications for dual immune checkpoint blockade with PD-1 and CTLA-4 to various solid tumors (<xref ref-type="bibr" rid="B64">64</xref>, <xref ref-type="bibr" rid="B65">65</xref>). However, the efficacy and safety of PD-1/PD-L1 and CTLA-4 immune checkpoint inhibitors in the treatment of aCRC remain largely unconfirmed. Twelve clinical trials involving 566 patients with metastatic colorectal cancer (mCRC) have reported results for these agents. Therefore, we conducted a meta-analysis to provide valid and reliable conclusions. We compared the effectiveness and AEs of several therapy regimens involving PD-1/PD-L1 and CTLA-4 immune checkpoint inhibitors for potential clinical application. The pooled objective response rate (ORR), disease control rate (DCR), and overall AE rate were 50%, 33%, 94%, and 44%, respectively. The pooled median overall survival (mOS) and median progression-free survival (mPFS) were 8.81 months and 2.57 months.</p>
<p>In order to further analyze the efficacy and safety of PD-1/PD-L1 and CTLA-4 immune checkpoint inhibitors, we performed subgroup analyses based on country (USA, Other), sample size (&#x2265;40, &lt;40), other therapies (None, Yes), types of ICIs (Nivolumab+Ipilimumab, Durvalumab+tremelimumab, QL1706 (PSB205)), and molecular phenotypes (dMMR/MSI-H, pMMR/MSS, NR). In terms of country, the USA exhibited lower ORR and DCR, as well as fewer AEs and grade &#x2265;3 AEs compared to other countries. Regarding sample size, when the sample size is &#x2265;40, this may indicate higher ORR, DCR, and an increased incidence of AEs and grade &#x2265;3 AEs. Concerning ICIs types, Nivolumab+Ipilimumab is considered to have higher efficacy and safety than Durvalumab+tremelimumab and QL1706 (PSB205). From the molecular phenotype perspective, the efficacy of dual ICIs in pMMR/MSS aCRC patients is lower than that in dMMR/MSI-H aCRC patients, while the incidence of adverse events may be higher. This discrepancy arises because MSI-H tumors typically have a high tumor mutation burden (TMB) and a high tumor neoantigen burden (TNB), which can activate the immune system more effectively. In contrast, MSS tumors have a lower mutation burden and generate relatively fewer neoantigens, reducing the likelihood of T cells recognizing and attacking tumor cells (<xref ref-type="bibr" rid="B4">4</xref>, <xref ref-type="bibr" rid="B61">61</xref>). Notably, the combination of different treatment modalities is often believed to enhance therapeutic effects. However, our analysis yielded opposite results. When PD-1/PD-L1 and CTLA-4 immune checkpoint inhibitors are combined with other treatments (such as chemotherapy, radiotherapy, etc.), the ORR and DCR are significantly lower, and the risk of adverse effects is higher. This may be due to the limited number of studies that we did not categorize by different treatment regimens. However, a careful review of the literature reveals that the efficacy of PD-1/PD-L1 and CTLA-4 immune checkpoint inhibitors combined with chemotherapy is better than the pooled results. Past studies have demonstrated that cytotoxic chemotherapy could reduce immunosuppressive T-regulatory cells, induce cell surface death receptor density to promote immune killing, and enhance the release of neoantigens in the microenvironment (<xref ref-type="bibr" rid="B66">66</xref>&#x2013;<xref ref-type="bibr" rid="B68">68</xref>). In the Thibaudin study, a median PFS of 8.2 months and an objective response rate of 63% were reported for the treatment plan involving durvalumab and tremelimumab combined with mFOLFOX6, which compares favorably with FOLFOX monotherapy (<xref ref-type="bibr" rid="B44">44</xref>). This study supports the notion that chemo-immunotherapy could promote immune responses against shared tumor antigens and neoantigens in MSS metastatic CRC, with this immune response associated with therapeutic efficacy. In another study, temozolomide in combination with ipilimumab and nivolumab in patients with microsatellite stabilization achieved encouraging results, with median PFS and mOS of 7.0 and 18.4 months, respectively, and an overall response rate of 45% (<xref ref-type="bibr" rid="B47">47</xref>). This provides evidence of the role of temozolomide as an immune-sensitizing agent for MSS and immune-cold aCRCs. However, the combination of radiotherapy with CTLA-4 and PD-1 blockers for the treatment of aCRC was less than satisfactory. Although preclinical data suggest that radiation can induce tumor-specific immune responses (<xref ref-type="bibr" rid="B69">69</xref>), increase T-cell infiltration (<xref ref-type="bibr" rid="B70">70</xref>), and promote immune-mediated tumor cell death (<xref ref-type="bibr" rid="B71">71</xref>), clinical trials to date have not met their intended goals. In a study involving 40 aCRC patients receiving nivolumab and ipilimumab in combination with radiation therapy, Parikh observed a DCR of 25% and an ORR of 10% (<xref ref-type="bibr" rid="B48">48</xref>), significantly lower than those reported in previous studies that did not involve radiation therapy. Two other similar clinical trials combining PD-L1 and CTLA-4 inhibitors with radiation therapy in aCRC patients also failed to meet their predefined endpoints, although they noted that this treatment can enhance the immunogenicity of the local and systemic immune microenvironment (<xref ref-type="bibr" rid="B36">36</xref>, <xref ref-type="bibr" rid="B49">49</xref>). In the future, more clinical trials are warranted to investigate the timing factors associated with radiation in immunotherapy and to identify appropriate radiation dosages (<xref ref-type="bibr" rid="B72">72</xref>, <xref ref-type="bibr" rid="B73">73</xref>).</p>
<p>The results of this meta-analysis demonstrate that the combination of PD-1 inhibitors and CTLA-4 inhibitors has shown promising and profound clinical responses in clinical studies. The synergistic effect of combining PD-1/PD-L1 and CTLA-4 inhibitors surpasses the sum of their individual contributions as monotherapies (<xref ref-type="bibr" rid="B74">74</xref>, <xref ref-type="bibr" rid="B75">75</xref>). Thibaudin reported that the median progression-free survival (mPFS) for metastatic colorectal cancer treated with durvalumab and tremelimumab in combination with FOLFOX was 8.2 months, significantly higher than the mPFS of 5-6 months for FOLFOX alone and comparable to the mPFS of 8 months for the bevacizumab-combined chemotherapy regimen (<xref ref-type="bibr" rid="B44">44</xref>, <xref ref-type="bibr" rid="B76">76</xref>). A previous meta-analysis of PD-1/PD-L1 inhibitors in the treatment of aCRC suggested that the objective response rate (ORR) for dMMR/MSI-H aCRC was 37%, while that for pMMR/MSS aCRC was 11% (<xref ref-type="bibr" rid="B77">77</xref>). In our molecular phenotype subgroup analysis, the ORR for PD-1/PD-L1 inhibitors combined with CTLA-4 inhibitors in dMMR/MSI-H aCRC was 63%, whereas in pMMR/MSS aCRC it was 18%, both significantly higher than the 37% and 11% observed for PD-1/PD-L1 inhibitors alone, respectively. Treatment-related adverse events (TRAEs) are associated with overactivation of the immune system, leading to damage to one or more organs. As expected, we observed that the incidence of TRAEs in patients receiving the combination of anti-PD-1/PD-L1 and anti-CTLA-4 therapy was higher compared to those receiving anti-PD-1/PD-L1 monotherapy (94% vs. 85%) (<xref ref-type="bibr" rid="B36">36</xref>, <xref ref-type="bibr" rid="B77">77</xref>). Among the included studies, the highest incidence of grade &#x2265;3 TRAEs was reported by Parikh (<xref ref-type="bibr" rid="B48">48</xref>). Notably, despite a high incidence of grade &#x2265;3 TRAEs in this study, only a few patients discontinued treatment due to clinically relevant toxicity. Similar results were observed in other studies. Moreover, we found that grade &#x2265;3 TRAEs often occurred in the early stages of treatment, and most TRAEs could be controlled and resolved with a short interruption of treatment and a brief course of oral steroid therapy (<xref ref-type="bibr" rid="B61">61</xref>, <xref ref-type="bibr" rid="B78">78</xref>). Currently, the incidence of TRAEs is common in anti-PD-1/PD-L1 + anti-CTLA-4 combination therapy, although the pathogenesis is poorly understood (<xref ref-type="bibr" rid="B79">79</xref>). We believe that the occurrence of grade &#x2265;3 TRAEs may be associated with drug dosage, treatment cycles, and the patients&#x2019; physical conditions. In anti-PD-1/PD-L1 + anti-CTLA-4 combination therapy, it is crucial to enhance monitoring of immunotherapy during treatment, pay attention to severe TRAEs, and manage them according to relevant guidelines.</p>
</sec>
<sec id="s5">
<label>5</label>
<title>Limitations</title>
<p>There are several limitations in the current meta-analysis. First, most studies had small sample sizes. Additionally, there is currently limited data on the combination therapy of PD-1 inhibitors and CTLA-4 inhibitors, and few studies are randomized or blinded. Second, we relied on published trial data but did not have access to raw patient data, which may introduce biases in our analysis. Therefore, more large-scale clinical trials are needed to further validate the efficacy and safety of the combination therapy of PD-1 inhibitors and CTLA-4 inhibitors. Third, it is crucial to identify the predominant factors influencing immunosuppressive therapy. Due to the limited experimental data, this study did not analyze the associations between gender, age, tumor mutation burden (TMB), tumor neoantigen burden (TNB), and the site of metastasis with treatment efficacy and safety.</p>
</sec>
<sec id="s6" sec-type="conclusions">
<label>6</label>
<title>Conclusion</title>
<p>In summary, our meta-analysis demonstrates the efficacy and safety of combination therapy with PD-1 inhibitors and CTLA-4 inhibitors in patients with aCRC, supporting its potential for future clinical application. However, due to the limited clinical data available, further large-scale, multicenter randomized controlled trials (RCTs) are necessary to confirm these findings.</p>
</sec>
</body>
<back>
<sec id="s7" sec-type="data-availability">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Material</bold>
</xref>. Further inquiries can be directed to the corresponding author.</p>
</sec>
<sec id="s8" sec-type="author-contributions">
<title>Author contributions</title>
<p>DS: Data curation, Methodology, Supervision, Validation, Writing &#x2013; original draft. SH: Conceptualization, Data curation, Methodology, Software, Visualization, Writing &#x2013; review &amp; editing. NM: Data curation, Funding acquisition, Methodology, Resources, Software, Supervision, Writing &#x2013; original draft. BY: Formal analysis, Funding acquisition, Investigation, Methodology, Software, Supervision, Validation, Writing &#x2013; review &amp; editing. JG: Data curation, Formal analysis, Investigation, Software, Supervision, Validation, Visualization, Writing &#x2013; review &amp; editing.</p>
</sec>
<sec id="s9" sec-type="funding-information">
<title>Funding</title>
<p>The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was funded by Servier. The funders had no role or input in the study itself.</p>
</sec>
<sec id="s10" sec-type="COI-statement">
<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 id="s12" sec-type="disclaimer">
<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="s13" sec-type="supplementary-material">
<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/fimmu.2024.1485303/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fimmu.2024.1485303/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="DataSheet1.docx" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document"/>
</sec>
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