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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Oncol.</journal-id>
<journal-title>Frontiers in Oncology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Oncol.</abbrev-journal-title>
<issn pub-type="epub">2234-943X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fonc.2021.735803</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Oncology</subject>
<subj-group>
<subject>Systematic Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Prognostic and Clinicopathological Significance of the Systemic Immune-Inflammation Index in Patients With Renal Cell Carcinoma: A Meta-Analysis</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Jin</surname>
<given-names>Mingyu</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1394853"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Yuan</surname>
<given-names>Shaoying</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Yuan</surname>
<given-names>Yiming</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Yi</surname>
<given-names>Luqi</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Department of Andrology, Guangdong Hospital of Traditional Chinese Medicine</institution>, <addr-line>Zhuhai</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Andrology Center, Peking University First Hospital</institution>, <addr-line>Beijing</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Department of Urology, Guangdong Hospital of Traditional Chinese Medicine</institution>, <addr-line>Zhuhai</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Walter J. Storkus, University of Pittsburgh, United States</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Ronald James Fecek, Lake Erie College of Osteopathic Medicine, United States; Antonella Argentiero, Istituto Nazionale dei Tumori (IRCCS), Italy</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Mingyu Jin, <email xlink:href="mailto:15919152830@163.com">15919152830@163.com</email>
</p>
</fn>
<fn fn-type="other" id="fn002">
<p>This article was submitted to Genitourinary Oncology, a section of the journal Frontiers in Oncology</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>07</day>
<month>12</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="collection">
<year>2021</year>
</pub-date>
<volume>11</volume>
<elocation-id>735803</elocation-id>
<history>
<date date-type="received">
<day>03</day>
<month>07</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>17</day>
<month>11</month>
<year>2021</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2021 Jin, Yuan, Yuan and Yi</copyright-statement>
<copyright-year>2021</copyright-year>
<copyright-holder>Jin, Yuan, Yuan and Yi</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 systemic immune-inflammation index (SII) is a hematological parameter based on neutrophil, platelet, and lymphocyte counts. Studies that have investigated the prognostic value of SII in patients with renal cell carcinoma (RCC) have reported controversial results. In this study, we systematically investigated the prognostic value of SII in patients with RCC.</p>
</sec>
<sec>
<title>Methods</title>
<p>We systematically searched English articles in the PubMed, Embase, Web of Science, and Cochrane Library databases up to October 2021. Hazard ratios (HRs) and odds ratios (ORs) with 95% confidence intervals (CIs) were used to obtain pooled results.</p>
</sec>
<sec>
<title>Results</title>
<p>The meta-analysis included 10 studies that enrolled 3,180 patients. A high SII was associated with poor overall survival (HR 1.75, 95% CI 1.33&#x2013;2.30, p&lt;0.001) in patients with RCC. However, a high SII was not shown to be a significant prognostic factor for progression-free survival/disease-free survival (HR 1.22, 95% CI 0.84&#x2013;1.76, p=0.293) or poor cancer-specific survival (HR 1.46, 95% CI 0.68&#x2013;3.12, p=0.332) in patients with RCC. A high SII was correlated with male sex (OR 1.51, 95% CI 1.11&#x2013;2.04, p=0.008), Fuhrman grade G3&#x2013;G4 (OR 1.80, 95% CI 1.08&#x2013;3.00, p=0.024), and poor risk based on the International Metastatic Renal Cell Carcinoma Database Consortium criteria (OR 19.12, 95% CI 9.13&#x2013;40.06, p&lt;0.001).</p>
</sec>
<sec>
<title>Conclusion</title>
<p>A high SII was independently associated with poor survival outcomes in patients with RCC. Additionally, an elevated SII indicated more aggressive disease. The SII may serve as a useful cost-effective prognostic indicator in patients with RCC.</p>
</sec>
</abstract>
<kwd-group>
<kwd>systemic immune-inflammation index</kwd>
<kwd>prognosis</kwd>
<kwd>meta-analysis</kwd>
<kwd>renal cell carcinoma</kwd>
<kwd>survival</kwd>
</kwd-group>
<counts>
<fig-count count="6"/>
<table-count count="3"/>
<equation-count count="0"/>
<ref-count count="50"/>
<page-count count="11"/>
<word-count count="3715"/>
</counts>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<title>Introduction</title>
<p>Renal cell carcinoma (RCC) is the third most common cancer of the urinary system and accounts for 2.2% of all human malignancies (<xref ref-type="bibr" rid="B1">1</xref>). Approximately 25%&#x2013;30% of patients with RCC present with metastases at the time of diagnosis (<xref ref-type="bibr" rid="B2">2</xref>). Among patients diagnosed with early-stage and localized disease, 25% develop recurrence or metastasis after radical surgical resection (<xref ref-type="bibr" rid="B3">3</xref>). Immune checkpoint inhibitors are widely accepted as an essential component of RCC treatment following rapid advances in immunotherapy for the management of RCC (<xref ref-type="bibr" rid="B4">4</xref>, <xref ref-type="bibr" rid="B5">5</xref>). The prognosis of patients with RCC remains poor; the 5-year survival rate is only 12% for stage IV metastatic disease (<xref ref-type="bibr" rid="B6">6</xref>). Prognostic markers are clinically useful for improved management of patients with RCC. Therefore, identification of novel and reliable prognostic indicators is urgently required to improve survival of patients with RCC (<xref ref-type="bibr" rid="B7">7</xref>).</p>
<p>The role of the immune system in various stages of cancer progression has been extensively investigated over the last few years (<xref ref-type="bibr" rid="B8">8</xref>). Inflammation-based prognostic scores such as platelet-to-lymphocyte ratio (<xref ref-type="bibr" rid="B9">9</xref>), lymphocyte to monocyte ratio (<xref ref-type="bibr" rid="B10">10</xref>), and prognostic nutritional index (<xref ref-type="bibr" rid="B11">11</xref>) are cost-effective and reliable prognostic tools that are widely used in patients with cancer (<xref ref-type="bibr" rid="B10">10</xref>, <xref ref-type="bibr" rid="B12">12</xref>). Many studies have shown that the systemic immune-inflammation index (SII) is a useful prognostic marker for several malignant tumors, including pancreatic (<xref ref-type="bibr" rid="B13">13</xref>), gallbladder (<xref ref-type="bibr" rid="B14">14</xref>), non-small-cell lung (<xref ref-type="bibr" rid="B15">15</xref>), and laryngeal cancer (<xref ref-type="bibr" rid="B16">16</xref>), as well as for cholangiocarcinoma (<xref ref-type="bibr" rid="B17">17</xref>). Studies have investigated the prognostic value of SII in patients with RCC; however, the results are inconsistent (<xref ref-type="bibr" rid="B18">18</xref>&#x2013;<xref ref-type="bibr" rid="B25">25</xref>). Therefore, in this meta-analysis, we investigated the role of SII as a prognostic indicator of RCC and also the correlation between SII and clinicopathological features of RCC.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<title>Materials and Methods</title>
<sec id="s2_1">
<title>Study Guideline and Ethics Statement</title>
<p>This meta-analysis was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (<xref ref-type="bibr" rid="B26">26</xref>). All data used in this meta-analysis were based on previous studies; therefore, ethical approval and patient consent were not required for this study.</p>
</sec>
<sec id="s2_2">
<title>Search Strategy</title>
<p>The English databases of PubMed, Embase, Web of Science, and Cochrane Library were systematically searched up to October 2021. We used the following search terms: systemic immune-inflammation index OR SII AND renal cell carcinoma OR kidney cancer AND prognosis OR survival OR outcomes OR prognostic. The citation lists of the relevant studies were also manually checked for additional eligible articles. We selected only English publications.</p>
</sec>
<sec id="s2_3">
<title>Inclusion and Exclusion Criteria</title>
<p>The inclusion criteria were as follows: (1) studies that investigated the association between the SII and prognosis in patients diagnosed with RCC, (2) availability of hazard ratios (HRs) and 95% confidence intervals (CIs) for survival outcomes or data required to calculate these values, (3) an appropriately defined SII based on the following formula: platelet count &#xd7; neutrophil count/lymphocyte count, (4) availability of a cutoff value to divide the SII into high or low SII groups and, (5) articles published in English. The exclusion criteria were as follows: (1) case reports, reviews, meeting abstracts, letters, and comments, (2) duplicate articles with patient overlap, (3) insufficient data for detailed analysis and, (4) animal studies. The survival endpoints included overall survival (OS), progression-free survival (PFS), disease-free survival (DFS), and cancer-specific survival (CSS).</p>
</sec>
<sec id="s2_4">
<title>Data Extraction and Quality Assessment</title>
<p>Two investigators (M.J. and S.Y.) independently extracted information from all studies included in this meta-analysis, and any disagreements were resolved by discussion with a third investigator (Y.Y.). The following data were extracted: first author, publication year, country, sample size, sex, age, study period, survival outcomes, follow-up, cancer type, treatment methods used, cut-off value of the SII, number of patients with high and low SII scores, and HRs and 95% CIs for OS, PFS, DFS, and CSS. The Newcastle&#x2013;Ottawa quality assessment scale (NOS) (<xref ref-type="bibr" rid="B27">27</xref>) was used to assess the quality of the included studies. The NOS assesses the quality of studies with regard to the following aspects: subject selection, comparability of the subject, and clinical outcomes. The NOS score ranged from 0 to 9, and studies with NOS scores &#x2265;6 were considered high-quality studies.</p>
</sec>
<sec id="s2_5">
<title>Statistical Analysis</title>
<p>Pooled HRs and 95% CIs were calculated to determine the role of the SII as a prognostic marker in patients with RCC. Pooled HR &gt;1 (without 95% CI overlapping 1) indicated that a high SII correlated with poor prognosis. Heterogeneity among studies was assessed using the &#x3c7;2-based Q test and I<sup>2</sup> statistics. The I<sup>2</sup>&gt;50% and Ph&lt;0.10 indicated significant heterogeneity, and a random-effects model was used for analysis; a fixed-effects model was used in other cases. Subgroup analyses were performed to confirm the source of heterogeneity. The pooled odds ratios (ORs) and 95% CIs were used to determine the association between SII and clinicopathological factors. Pooled OR&gt;1 (without 95% CI overlapping 1) suggested that a high SII was associated with poor clinicopathological outcomes. Potential publication bias was evaluated using the Begg&#x2019;s test (<xref ref-type="bibr" rid="B28">28</xref>). All data analyses were performed using the Stata 12.0 software (Stata Corp LP, College Station, TX, USA). A P value &lt;0.05 (two-tailed) was considered statistically significant.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<title>Results</title>
<sec id="s3_1">
<title>Study Selection</title>
<p>
<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref> shows a detailed flow diagram of the study selection process. The initial literature search yielded 138 studies, of which 46 were included in the analysis after exclusion of duplicates. After screening of titles and abstracts, 32 studies were discarded and the full text was reviewed in 14. Four studies with insufficient survival data were eliminated. Finally, data of 10 studies that included 3,180 patients (<xref ref-type="bibr" rid="B18">18</xref>&#x2013;<xref ref-type="bibr" rid="B25">25</xref>, <xref ref-type="bibr" rid="B29">29</xref>, <xref ref-type="bibr" rid="B30">30</xref>) were analyzed in this meta-analysis.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Flow diagram of included studies for this meta-analysis.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-11-735803-g001.tif"/>
</fig>
</sec>
<sec id="s3_2">
<title>Characteristics of Included Studies</title>
<p>
<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref> summarizes the main characteristics of all studies included in our research. The total sample size was 3,180 and ranged from 31 to 646. Three studies were performed in Turkey (<xref ref-type="bibr" rid="B19">19</xref>, <xref ref-type="bibr" rid="B24">24</xref>, <xref ref-type="bibr" rid="B30">30</xref>), two in Italy (<xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B23">23</xref>), and one each in India (<xref ref-type="bibr" rid="B18">18</xref>), China (<xref ref-type="bibr" rid="B22">22</xref>), Japan (<xref ref-type="bibr" rid="B25">25</xref>), Austria (<xref ref-type="bibr" rid="B29">29</xref>), and Poland (<xref ref-type="bibr" rid="B20">20</xref>), respectively. The included studies were published between 2016 and 2021 and all were English publications. All 10 studies investigated the association between SII and OS (<xref ref-type="bibr" rid="B18">18</xref>&#x2013;<xref ref-type="bibr" rid="B25">25</xref>, <xref ref-type="bibr" rid="B29">29</xref>, <xref ref-type="bibr" rid="B30">30</xref>), three investigated the association between SII and PFS (<xref ref-type="bibr" rid="B18">18</xref>, <xref ref-type="bibr" rid="B23">23</xref>, <xref ref-type="bibr" rid="B30">30</xref>), one between SII and DFS (<xref ref-type="bibr" rid="B24">24</xref>), and two between SII and CSS (<xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B29">29</xref>). Eight studies recruited patients with metastatic RCC (<xref ref-type="bibr" rid="B18">18</xref>&#x2013;<xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B23">23</xref>, <xref ref-type="bibr" rid="B25">25</xref>, <xref ref-type="bibr" rid="B29">29</xref>, <xref ref-type="bibr" rid="B30">30</xref>), and two studies enrolled patients with localized disease (<xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B24">24</xref>). The cut-off values of SII ranged from 529 to 1,375 (median 730). All included studies were shown to be high-quality studies (NOS scores &#x2265;6).</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Main characteristics of all included studies.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Author</th>
<th valign="top" align="center">Year</th>
<th valign="top" align="center">Country</th>
<th valign="top" align="center">Sample size</th>
<th valign="top" align="center">Sex (M/F)</th>
<th valign="top" align="center">Age (year) Median(range)</th>
<th valign="top" align="center">Study period</th>
<th valign="top" align="center">Survival outcome</th>
<th valign="top" align="center">Follow-up (month)</th>
<th valign="top" align="center">Cancer type</th>
<th valign="top" align="center">Treatment methods</th>
<th valign="top" align="center">Cut-off value</th>
<th valign="top" align="center">No. of patients with high/low SII</th>
<th valign="top" align="center">NOS score</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Barua</td>
<td valign="top" align="center">2019</td>
<td valign="top" align="left">India</td>
<td valign="top" align="center">31</td>
<td valign="top" align="center">21/10</td>
<td valign="top" align="center">Mean: 55</td>
<td valign="top" align="center">2012-2017</td>
<td valign="top" align="left">OS, PFS</td>
<td valign="top" align="center">16.5</td>
<td valign="top" align="left">mRCC</td>
<td valign="top" align="left">Surgery</td>
<td valign="top" align="center">883</td>
<td valign="top" align="center">17/14</td>
<td valign="top" align="center">7</td>
</tr>
<tr>
<td valign="top" align="left">Bugdayci</td>
<td valign="top" align="center">2021</td>
<td valign="top" align="left">Turkey</td>
<td valign="top" align="center">187</td>
<td valign="top" align="center">149/38</td>
<td valign="top" align="center">61 (34-86)</td>
<td valign="top" align="center">2012-2019</td>
<td valign="top" align="left">OS</td>
<td valign="top" align="center">15</td>
<td valign="top" align="left">mRCC</td>
<td valign="top" align="left">Surgery+ TKIs</td>
<td valign="top" align="center">730</td>
<td valign="top" align="center">94/93</td>
<td valign="top" align="center">7</td>
</tr>
<tr>
<td valign="top" align="left">Chrom</td>
<td valign="top" align="center">2019</td>
<td valign="top" align="left">Poland</td>
<td valign="top" align="center">502</td>
<td valign="top" align="center">339/163</td>
<td valign="top" align="center">62 (22-88)</td>
<td valign="top" align="center">2008-2016</td>
<td valign="top" align="left">OS</td>
<td valign="top" align="center">52.5</td>
<td valign="top" align="left">mRCC</td>
<td valign="top" align="left">TKIs</td>
<td valign="top" align="center">730</td>
<td valign="top" align="center">208/294</td>
<td valign="top" align="center">8</td>
</tr>
<tr>
<td valign="top" align="left">De Giorgi</td>
<td valign="top" align="center">2019</td>
<td valign="top" align="left">Italy</td>
<td valign="top" align="center">313</td>
<td valign="top" align="center">235/78</td>
<td valign="top" align="center">65 (40-84)</td>
<td valign="top" align="center">2015-2016</td>
<td valign="top" align="left">OS</td>
<td valign="top" align="center">24</td>
<td valign="top" align="left">mRCC</td>
<td valign="top" align="left">ICIs</td>
<td valign="top" align="center">1375</td>
<td valign="top" align="center">96/217</td>
<td valign="top" align="center">7</td>
</tr>
<tr>
<td valign="top" align="left">Hu</td>
<td valign="top" align="center">2020</td>
<td valign="top" align="left">China</td>
<td valign="top" align="center">646</td>
<td valign="top" align="center">394/252</td>
<td valign="top" align="center">Mean: 54.77</td>
<td valign="top" align="center">2010-2013</td>
<td valign="top" align="left">OS, CSS</td>
<td valign="top" align="center">84</td>
<td valign="top" align="left">Localized RCC</td>
<td valign="top" align="left">Surgery</td>
<td valign="top" align="center">529</td>
<td valign="top" align="center">163/483</td>
<td valign="top" align="center">7</td>
</tr>
<tr>
<td valign="top" align="left">Lolli</td>
<td valign="top" align="center">2016</td>
<td valign="top" align="left">Italy</td>
<td valign="top" align="center">335</td>
<td valign="top" align="center">238/97</td>
<td valign="top" align="center">63 (27-88)</td>
<td valign="top" align="center">2006-2014</td>
<td valign="top" align="left">OS, PFS</td>
<td valign="top" align="center">49</td>
<td valign="top" align="left">mRCC</td>
<td valign="top" align="left">TKIs</td>
<td valign="top" align="center">730</td>
<td valign="top" align="center">126/209</td>
<td valign="top" align="center">9</td>
</tr>
<tr>
<td valign="top" align="left">Ozbek</td>
<td valign="top" align="center">2020</td>
<td valign="top" align="left">Turkey</td>
<td valign="top" align="center">176</td>
<td valign="top" align="center">111/65</td>
<td valign="top" align="center">Mean: 65.32</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="left">OS, DFS</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="left">Localized RCC</td>
<td valign="top" align="left">Surgery</td>
<td valign="top" align="center">830</td>
<td valign="top" align="center">52/124</td>
<td valign="top" align="center">6</td>
</tr>
<tr>
<td valign="top" align="left">Teishima</td>
<td valign="top" align="center">2020</td>
<td valign="top" align="left">Japan</td>
<td valign="top" align="center">179</td>
<td valign="top" align="center">145/34</td>
<td valign="top" align="center">65.5 (40-85)</td>
<td valign="top" align="center">2008-2018</td>
<td valign="top" align="left">OS</td>
<td valign="top" align="center">24</td>
<td valign="top" align="left">mRCC</td>
<td valign="top" align="left">TKIs</td>
<td valign="top" align="center">730</td>
<td valign="top" align="center">73/106</td>
<td valign="top" align="center">8</td>
</tr>
<tr>
<td valign="top" align="left">Laukhtina</td>
<td valign="top" align="center">2021</td>
<td valign="top" align="left">Austria</td>
<td valign="top" align="center">613</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">65</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="left">OS, CSS</td>
<td valign="top" align="center">31</td>
<td valign="top" align="left">mRCC</td>
<td valign="top" align="left">Surgery</td>
<td valign="top" align="center">710</td>
<td valign="top" align="center">298/315</td>
<td valign="top" align="center">7</td>
</tr>
<tr>
<td valign="top" align="left">Yilmaz</td>
<td valign="top" align="center">2021</td>
<td valign="top" align="left">Turkey</td>
<td valign="top" align="center">198</td>
<td valign="top" align="center">135/63</td>
<td valign="top" align="center">63 (29&#x2013;87)</td>
<td valign="top" align="center">2012-2019</td>
<td valign="top" align="left">OS, PFS</td>
<td valign="top" align="center">24(1-70)</td>
<td valign="top" align="left">mRCC</td>
<td valign="top" align="left">TKIs</td>
<td valign="top" align="center">1291</td>
<td valign="top" align="center">91/107</td>
<td valign="top" align="center">8</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>RCC, renal cell carcinoma; mRCC, metastatic renal cell carcinoma; TKIs, tyrosine kinase inhibitors; OS, overall survival; PFS, progression-free survival; DFS, disease-free survival; CSS, cancer-specific survival; ICIs, immune checkpoint inhibitors; NR, not reported; NOS, Newcastle-Ottawa Scale.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_3">
<title>Association Between the Systemic Immune-Inflammation Index and Survival Outcomes in Patients With Renal Cell Carcinoma</title>
<p>The prognostic value of SII for OS was determined based on data from 10 studies that included 3,180 patients (<xref ref-type="bibr" rid="B18">18</xref>&#x2013;<xref ref-type="bibr" rid="B25">25</xref>, <xref ref-type="bibr" rid="B29">29</xref>, <xref ref-type="bibr" rid="B30">30</xref>). The pooled HR and 95% CI are as follows: HR 1.75, 95% CI 1.33&#x2013;2.30, p&lt;0.001 (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref> and <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>). A random-effects model was used owing to significant heterogeneity (I<sup>2 =</sup> 92.4%, Ph&lt;0.001). Studies were stratified based on region, cancer type, cut-off value, treatment methods, and sample size for subgroup analyses. A high SII was associated with poor OS, regardless of geographical region, cancer type, and treatment methods (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>). A high SII was significantly correlated with poor OS at cut-off values &#x2264;730 (HR 1.81, 95% CI 1.41&#x2013;2.30, p&lt;0.001) (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>). Four studies that included 740 patients (<xref ref-type="bibr" rid="B18">18</xref>, <xref ref-type="bibr" rid="B23">23</xref>, <xref ref-type="bibr" rid="B24">24</xref>, <xref ref-type="bibr" rid="B30">30</xref>) reported an association between SII and PFS/DFS in patients with RCC. Results of pooled data were as follows: HR 1.22, 95% CI 0.84&#x2013;1.76, p=0.293, which indicate that SII was not a significant prognostic factor for PFS/DFS in patients with RCC (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref> and <xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>). Additionally, subgroup analysis indicated that a cut-off level &#x2264;730 was of prognostic value for poor PFS/DFS in patients with RCC (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>). Data obtained from two studies (<xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B29">29</xref>) showed that a high SII was not associated with poor CSS (pooled data HR 1.46, 95% CI 0.68&#x2013;3.12, p=0.332) (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref> and <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>). Subgroup analysis of CSS was not performed because of the limited sample size.</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Subgroup analyses of SII for prognosis in patients with RCC.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Subgroups</th>
<th valign="top" align="center">No. of studies</th>
<th valign="top" align="center">No. of patients</th>
<th valign="top" align="center">Effects model</th>
<th valign="top" align="center">HR (95%CI)</th>
<th valign="top" align="center">p</th>
<th valign="top" colspan="2" align="center">Heterogeneity <italic>I</italic>
<sup>2</sup>(%) Ph</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">OS</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="left"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Total</td>
<td valign="top" align="center">10</td>
<td valign="top" align="center">3,180</td>
<td valign="top" align="left">Random</td>
<td valign="top" align="center">1.75 (1.33-2.30)</td>
<td valign="top" align="center">&lt;0.001</td>
<td valign="top" align="center">92.4</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Region</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="left"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Asia</td>
<td valign="top" align="center">6</td>
<td valign="top" align="center">1,417</td>
<td valign="top" align="left">Random</td>
<td valign="top" align="center">1.62 (1.12-2.34)</td>
<td valign="top" align="center">0.010</td>
<td valign="top" align="center">85.4</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Non-Asia</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">1,763</td>
<td valign="top" align="left">Random</td>
<td valign="top" align="center">1.92 (1.33-2.78)</td>
<td valign="top" align="center">0.001</td>
<td valign="top" align="center">88</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Cancer type</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="left"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Localized RCC</td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">822</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="center">1.96 (1.41-2.71)</td>
<td valign="top" align="center">&lt;0.001</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">0.363</td>
</tr>
<tr>
<td valign="top" align="left">mRCC</td>
<td valign="top" align="center">8</td>
<td valign="top" align="center">2,358</td>
<td valign="top" align="left">Random</td>
<td valign="top" align="center">1.70 (1.26-2.30)</td>
<td valign="top" align="center">0.001</td>
<td valign="top" align="center">93.2</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Cut-off value</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="left"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">&#x2264;730</td>
<td valign="top" align="center">6</td>
<td valign="top" align="center">2,462</td>
<td valign="top" align="left">Random</td>
<td valign="top" align="center">1.81 (1.41-2.30)</td>
<td valign="top" align="center">&lt;0.001</td>
<td valign="top" align="center">72.5</td>
<td valign="top" align="center">0.003</td>
</tr>
<tr>
<td valign="top" align="left">&gt;730</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">718</td>
<td valign="top" align="left">Random</td>
<td valign="top" align="center">1.64 (0.92-2.93)</td>
<td valign="top" align="center">0.096</td>
<td valign="top" align="center">92.2</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Treatments</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="left"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Surgery</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">1,466</td>
<td valign="top" align="left">Random</td>
<td valign="top" align="center">1.37 (1.03-1.81)</td>
<td valign="top" align="center">0.029</td>
<td valign="top" align="center">85.5</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">TKIs</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">1,214</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="center">1.87 (1.58-2.20)</td>
<td valign="top" align="center">&lt;0.001</td>
<td valign="top" align="center">27.8</td>
<td valign="top" align="center">0.245</td>
</tr>
<tr>
<td valign="top" align="left">Surgery + TKIs</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">187</td>
<td valign="top" align="left">&#x2013;</td>
<td valign="top" align="center">2.08 (1.40-3.09)</td>
<td valign="top" align="center">&lt;0.001</td>
<td valign="top" align="center">&#x2013;</td>
<td valign="top" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="left">ICIs</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">313</td>
<td valign="top" align="left">&#x2013;</td>
<td valign="top" align="center">2.99 (2.07-4.31)</td>
<td valign="top" align="center">&lt;0.001</td>
<td valign="top" align="center">&#x2013;</td>
<td valign="top" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="left">Sample size</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="left"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">&#x2264;200</td>
<td valign="top" align="center">5</td>
<td valign="top" align="center">771</td>
<td valign="top" align="left">Random</td>
<td valign="top" align="center">1.51 (1.04-2.18)</td>
<td valign="top" align="center">0.029</td>
<td valign="top" align="center">82.2</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">&gt;200</td>
<td valign="top" align="center">5</td>
<td valign="top" align="center">2,409</td>
<td valign="top" align="left">Random</td>
<td valign="top" align="center">1.97 (1.42-2.73)</td>
<td valign="top" align="center">&lt;0.001</td>
<td valign="top" align="center">85.0</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">PFS/DFS</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="left"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Total</td>
<td valign="top" align="center">4</td>
<td valign="top" align="center">740</td>
<td valign="top" align="left">Random</td>
<td valign="top" align="center">1.22 (0.84-1.76)</td>
<td valign="top" align="center">0.293</td>
<td valign="top" align="center">85.9</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Region</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="left"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Asia</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">405</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="center">1.02 (1.00-1.04)</td>
<td valign="top" align="center">0.048</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">0.943</td>
</tr>
<tr>
<td valign="top" align="left">Non-Asia</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">335</td>
<td valign="top" align="left">&#x2013;</td>
<td valign="top" align="center">1.84 (1.43-2.36)</td>
<td valign="top" align="center">&lt;0.001</td>
<td valign="top" align="center">&#x2013;</td>
<td valign="top" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="left">Cancer type</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="left"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Localized RCC</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">176</td>
<td valign="top" align="left">&#x2013;</td>
<td valign="top" align="center">1.14 (0.53-2.43)</td>
<td valign="top" align="center">0.738</td>
<td valign="top" align="center">&#x2013;</td>
<td valign="top" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="left">mRCC</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">564</td>
<td valign="top" align="left">Random</td>
<td valign="top" align="center">1.23 (0.81-1.88)</td>
<td valign="top" align="center">0.330</td>
<td valign="top" align="center">90.6</td>
<td valign="top" align="center">&lt;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Cut-off value</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="left"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">&#x2264;730</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">335</td>
<td valign="top" align="left">&#x2013;</td>
<td valign="top" align="center">1.84 (1.43-2.36)</td>
<td valign="top" align="center">&lt;0.001</td>
<td valign="top" align="center">&#x2013;</td>
<td valign="top" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="left">&gt;730</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">405</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="center">1.02 (1.00-1.04)</td>
<td valign="top" align="center">0.048</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">0.943</td>
</tr>
<tr>
<td valign="top" align="left">Treatments</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="left"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Surgery</td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">207</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="center">1.02 (1.00-1.04)</td>
<td valign="top" align="center">0.047</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">0.777</td>
</tr>
<tr>
<td valign="top" align="left">TKIs</td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">533</td>
<td valign="top" align="left">Random</td>
<td valign="top" align="center">1.38 (0.74-2.55)</td>
<td valign="top" align="center">0.311</td>
<td valign="top" align="center">83.6</td>
<td valign="top" align="center">0.014</td>
</tr>
<tr>
<td valign="top" align="left">Sample size</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="left"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">&#x2264;200</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">405</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="center">1.02 (1.00-1.04)</td>
<td valign="top" align="center">0.048</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">0.943</td>
</tr>
<tr>
<td valign="top" align="left">&gt;200</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center">335</td>
<td valign="top" align="left">-0</td>
<td valign="top" align="center">1.84 (1.43-2.36)</td>
<td valign="top" align="center">&lt;0.001</td>
<td valign="top" align="center">&#x2013;</td>
<td valign="top" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="left">CSS</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="left"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Total</td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">1,259</td>
<td valign="top" align="left">Random</td>
<td valign="top" align="center">1.46 (0.68-3.12)</td>
<td valign="top" align="center">0.332</td>
<td valign="top" align="center">81.5</td>
<td valign="top" align="center">0.020</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>RCC, renal cell carcinoma; mRCC, metastatic renal cell carcinoma; TKIs, tyrosine kinase inhibitors; OS, overall survival; PFS, progression-free survival; DFS, disease-free survival; CSS, cancer-specific survival; ICIs, immune checkpoint inhibitors.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Forest plots showing the association between SII and overall survival (OS) in renal cell carcinoma (RCC).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-11-735803-g002.tif"/>
</fig>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Forest plots showing the association between SII and progression-free survival (PFS)/disease-free survival (DFS) in RCC.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-11-735803-g003.tif"/>
</fig>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Forest plots showing the association between SII and cancer-specific survival (CSS) in RCC.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-11-735803-g004.tif"/>
</fig>
</sec>
<sec id="s3_4">
<title>Correlation Between the Systemic Immune-Inflammation Index and Clinicopathological Factors in Patients With Renal Cell Carcinoma</title>
<p>Five studies (<xref ref-type="bibr" rid="B19">19</xref>, <xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B24">24</xref>, <xref ref-type="bibr" rid="B25">25</xref>) reported an association between SII and clinicopathological characteristics in RCC; sex (male vs. female), histopathological type (clear cell [ccRCC] vs. non-ccRCC), Fuhrman grade (G3&#x2013;G4 vs. G1&#x2013;G2), T stage (T3&#x2013;T4 vs. T1&#x2013;T2), sarcomatoid differentiation (present vs. absent), and the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) risk score (poor vs. favorable/intermediate) were associated with SII. The results showed that a high SII was correlated with male sex (OR 1.51, 95% CI 1.11&#x2013;2.04, p=0.008), Fuhrman grade G3&#x2013;G4 (OR 1.80, 95% CI 1.08&#x2013;3.00, p=0.024), and poor risk based on IMDC criteria (OR 19.12, 95% CI 9.13&#x2013;40.06, p&lt;0.001) (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5</bold>
</xref> and <xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>). However, we observed no significant association between the SII and histopathological cancer type (OR 1.04, 95% CI 0.72&#x2013;1.51, p=0.840), T stage (OR 1.76, 95% CI 0.62&#x2013;5.01, p=0.292), or sarcomatoid differentiation (OR 1.74, 95% CI 0.50&#x2013;6.06, p=0.382) (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5</bold>
</xref> and <xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>).</p>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>Forest plots of the association between SII and clinicopathological features of RCC. <bold>(A)</bold> Sex; <bold>(B)</bold> Histological type; <bold>(C)</bold> Fuhrman grade; <bold>(D)</bold> T stage; <bold>(E)</bold> Sarcomatoid differentiation, and <bold>(F)</bold> IMDC risk.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-11-735803-g005.tif"/>
</fig>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>The meta-analysis of association between SII and clinicopathological factors in patients with RCC.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Variables</th>
<th valign="top" align="center">No. of studies</th>
<th valign="top" align="center">No. of patients</th>
<th valign="top" align="center">Effects model</th>
<th valign="top" align="center">OR (95%CI)</th>
<th valign="top" align="center">p</th>
<th valign="top" colspan="2" align="center">Heterogeneity <italic>I</italic>
<sup>2</sup>(%) Ph</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Sex (male vs female)</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">1,001</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="center">1.51(1.11-2.04)</td>
<td valign="top" align="center">0.008</td>
<td valign="top" align="center">42.8</td>
<td valign="top" align="center">0.174</td>
</tr>
<tr>
<td valign="top" align="left">Histological type (non-clear cell vs clear cell)</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">1,138</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="center">1.04(0.72-1.51)</td>
<td valign="top" align="center">0.840</td>
<td valign="top" align="center">4.7</td>
<td valign="top" align="center">0.350</td>
</tr>
<tr>
<td valign="top" align="left">Fuhrman grade (G3-G4 vs G1-G2)</td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">833</td>
<td valign="top" align="left">Random</td>
<td valign="top" align="center">1.80(1.08-3.00)</td>
<td valign="top" align="center">0.024</td>
<td valign="top" align="center">52.9</td>
<td valign="top" align="center">0.145</td>
</tr>
<tr>
<td valign="top" align="left">T stage (T3-T4 vs T1-T2)</td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">833</td>
<td valign="top" align="left">Random</td>
<td valign="top" align="center">1.76(0.62-5.01)</td>
<td valign="top" align="center">0.292</td>
<td valign="top" align="center">86.6</td>
<td valign="top" align="center">0.006</td>
</tr>
<tr>
<td valign="top" align="left">Sarcomatoid differentiation (present vs absent)</td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">833</td>
<td valign="top" align="left">Random</td>
<td valign="top" align="center">1.74(0.50-6.06)</td>
<td valign="top" align="center">0.382</td>
<td valign="top" align="center">58.9</td>
<td valign="top" align="center">0.119</td>
</tr>
<tr>
<td valign="top" align="left">IMDC risk (poor vs favorable/intermediate)</td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">492</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="center">19.12(9.13-40.06)</td>
<td valign="top" align="center">&lt;0.001</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">0.698</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>IMDC, International Metastatic Renal Cell Carcinoma Database Consortium.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_5">
<title>Publication Bias</title>
<p>As shown in <xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6</bold>
</xref>, we observed no significant publication bias in our meta-analysis based on funnel plots and Begg&#x2019;s test (p=0.592 for OS, p=0.734 for PFS/DFS, and p=1 for CSS).</p>
<fig id="f6" position="float">
<label>Figure&#xa0;6</label>
<caption>
<p>Publication bias assessment using Begg funnel plot. <bold>(A)</bold> Begg&#x2019;s test for OS; <bold>(B)</bold> Begg&#x2019;s test for PFS/DFS; <bold>(C)</bold> Begg&#x2019;s test for CSS.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-11-735803-g006.tif"/>
</fig>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<title>Discussion</title>
<p>The SII has been reported as a useful prognostic indicator in many solid tumors, including gallbladder (<xref ref-type="bibr" rid="B31">31</xref>), pancreatic (<xref ref-type="bibr" rid="B13">13</xref>), and colorectal cancer (<xref ref-type="bibr" rid="B32">32</xref>), as well as in intrahepatic cholangiocarcinoma (<xref ref-type="bibr" rid="B33">33</xref>). Studies have investigated the association between SII and survival outcomes in patients with RCC (<xref ref-type="bibr" rid="B18">18</xref>&#x2013;<xref ref-type="bibr" rid="B25">25</xref>, <xref ref-type="bibr" rid="B29">29</xref>, <xref ref-type="bibr" rid="B30">30</xref>); however, the results remain controversial. In the current meta-analysis, we analyzed data of 10 studies that included 3,180 patients and quantitatively investigated the role of SII as a prognostic indicator in RCC. Pooled data showed that a high SII was associated with poor OS but not with PFS/DFS or CSS in patients with RCC. Furthermore, a high SII was also correlated with a high Fuhrman grade and poor IMDC risk scores. In this meta-analysis, we observed that a high SII indicated poor survival outcomes and aggressive histopathological features in patients with RCC. To our knowledge, this is the first meta-analysis that investigated the prognostic value of the SII in patients with RCC. The immune system plays a critical role in tumor development <italic>via</italic> various mechanisms including tumor initiation, angiogenesis, and metastasis (<xref ref-type="bibr" rid="B34">34</xref>). The tumor microenvironment (TME) can trigger immune inflammatory responses and facilitate tumor progression (<xref ref-type="bibr" rid="B35">35</xref>). For example, natural killer and CD8+ T cells in the TME can recognize and eliminate more immunogenic cancer cells during the early stages of tumor development (<xref ref-type="bibr" rid="B36">36</xref>). Moreover, M2-type tumor-associated macrophages are protumorigenic and promote angiogenesis, lymphangiogenesis, and cancer cell proliferation and metastasis in the TME (<xref ref-type="bibr" rid="B37">37</xref>).</p>
<p>The SII, calculated using blood test parameters, is a useful prognostic indicator based on the following underlying mechanisms: (a) neutrophils participate in different stages of tumor progression <italic>via</italic> production of a variety of cytokines (<xref ref-type="bibr" rid="B38">38</xref>). Neutrophils in the TME release various cytokines and chemokines such as reactive oxygen species and transforming growth factor (TGF)-&#x3b2; to educate themselves and other cell types to differentiate into a pro-cancer phenotype (<xref ref-type="bibr" rid="B39">39</xref>, <xref ref-type="bibr" rid="B40">40</xref>). (b) Platelets stimulate thrombopoiesis and tumor angiogenesis <italic>via</italic> production of TGF-&#x3b2;, promotion of adhesion, and prevention of cell death (<xref ref-type="bibr" rid="B41">41</xref>). (c) Cytotoxic lymphocytes play an important role in the cell-mediated immunological destruction of tumor cells (<xref ref-type="bibr" rid="B42">42</xref>). Lymphocytosis represents activation of the immune response and is associated with prolonged survival in patients with cancer (<xref ref-type="bibr" rid="B43">43</xref>). Therefore, a high SII, which could be secondary to elevated neutrophil or platelet counts, and/or low lymphocyte counts, is correlated with poor survival outcomes in patients with RCC. Notably, our results also indicate that a high SII was associated with a high Fuhrman grade and poor IMDC risk scores. The Fuhrman grade and IMDC risk scores reflect aggressiveness of the cancer; therefore, patients with a high SII tend to show tumor progression or recurrence after initial treatment.</p>
<p>Recent meta-analyses have investigated the prognostic role of SII in many cancer types, including hepatocellular (<xref ref-type="bibr" rid="B44">44</xref>), gastric (<xref ref-type="bibr" rid="B45">45</xref>), breast (<xref ref-type="bibr" rid="B46">46</xref>), and colorectal cancer (<xref ref-type="bibr" rid="B47">47</xref>). A meta-analysis that included 2,796 patients reported that a high SII was associated with poor prognosis in patients with hepatocellular carcinoma (<xref ref-type="bibr" rid="B44">44</xref>). Fu et&#xa0;al. observed that a high SII was significantly associated with poor OS and DFS in patients with gastric cancer (<xref ref-type="bibr" rid="B45">45</xref>). Huang et&#xa0;al. also reported that a high SII was associated with poor OS, PFS, and CSS in patients with urologic cancers (<xref ref-type="bibr" rid="B48">48</xref>). A recent meta-analysis observed that a high SII predicts poor survival outcomes in patients with gynecological cancers (<xref ref-type="bibr" rid="B49">49</xref>). The results of the aforementioned meta-analyses are consistent with our findings. Moreover, we observed an association between the SII and Fuhrman grade and IMDC risk scores in patients with RCC, which highlights the clinical usefulness of the SII to identify patients at high risk of tumor progression.</p>
<p>In a recent study, the authors performed transcriptome profiling of all three subgroups of RCC using machine learning and bioinformatics analysis (<xref ref-type="bibr" rid="B50">50</xref>); transcriptomic data of 891 patients were extracted from The Cancer Genome Atlas (TCGA) database; ccRCC samples obtained from mixed subgroups showed an inverse correlation between mitochondrial and angiogenesis-related genes in the TCGA database and external validation cohorts (<xref ref-type="bibr" rid="B50">50</xref>). Moreover, affiliation to the mixed subgroup was associated with a significantly shorter OS in patients with ccRCC and longer OS in patients with chromophobe RCC (<xref ref-type="bibr" rid="B50">50</xref>). These findings reported by Marquardt et&#xa0;al. (<xref ref-type="bibr" rid="B50">50</xref>) indicate heterogeneity among various histopathological subtypes of RCC, which can be attributed to the different gene clusters in each subgroup. These findings highlight the heterogeneity among recruited patients because the histopathological types were not the same.</p>
<p>Following are the limitations of this meta-analysis: (i) The relatively small sample size is a drawback of this research; this meta-analysis included only 10 studies that investigated 3,180 patients. Large-scale studies are warranted in future to provide deeper insight into this subject. (ii) The cut-off values of SII varied across the included studies, which may have contributed to a selection bias. (iii) Most studies were retrospectively designed; therefore, the inherent flaws associated with retrospective studies may have introduced heterogeneity in the meta-analysis, although we did not detect publication bias.</p>
</sec>
<sec id="s5" sec-type="conclusions">
<title>Conclusions</title>
<p>This meta-analysis highlights that a high SII was independently associated with poor survival outcomes in patients with RCC. Additionally, a high SII indicates greater aggressiveness of the malignancy. The SII may serve as a useful cost-effective prognostic indicator in patients with RCC.</p>
</sec>
<sec id="s6" sec-type="data-availability">
<title>Data Availability Statement</title>
<p>The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author.</p>
</sec>
<sec id="s7" sec-type="author-contributions">
<title>Author Contributions</title>
<p>MJ and SY provided the study conception and design. YY and LY contributed to the drafting of the article and final approval of the submitted version. All authors provided the analyses and interpretation of the data and completion of figures and tables. All authors contributed to the article and approved the submitted version.</p>
</sec>
<sec id="s8" 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="s9" 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>
</body>
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