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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Med.</journal-id>
<journal-title>Frontiers in Medicine</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Med.</abbrev-journal-title>
<issn pub-type="epub">2296-858X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fmed.2022.920732</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Medicine</subject>
<subj-group>
<subject>Systematic Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Diagnostic Utility of Non-invasive Tests for Inflammatory Bowel Disease: An Umbrella Review</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Shi</surname> <given-names>Jin-Tong</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="fn002"><sup>&#x2020;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1837607/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Zhang</surname> <given-names>Yuexin</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="fn002"><sup>&#x2020;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1858388/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>She</surname> <given-names>Yuehan</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="fn002"><sup>&#x2020;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1858900/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Goyal</surname> <given-names>Hemant</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/490613/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Wu</surname> <given-names>Zhi-Qi</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="corresp" rid="c001"><sup>&#x002A;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1525054/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Xu</surname> <given-names>Hua-Guo</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="corresp" rid="c002"><sup>&#x002A;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/478839/overview"/>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup><institution>Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University</institution>, <addr-line>Nanjing</addr-line>, <country>China</country></aff>
<aff id="aff2"><sup>2</sup><institution>Branch of National Clinical Research Center for Laboratory Medicine</institution>, <addr-line>Nanjing</addr-line>, <country>China</country></aff>
<aff id="aff3"><sup>3</sup><institution>Department of Medicine, The Wright Center for Graduate Medical Education</institution>, <addr-line>Scranton, PA</addr-line>, <country>United States</country></aff>
<author-notes>
<fn fn-type="edited-by"><p>Edited by: Xiang Xue, University of New Mexico, United States</p></fn>
<fn fn-type="edited-by"><p>Reviewed by: Jin-Xian Huang, The University of Hong Kong-Shenzhen Hospital, China; Salem Y. Mohamed, Zagazig University, Egypt; Ben Costello, University of the West of England, Bristol, United Kingdom</p></fn>
<corresp id="c001">&#x002A;Correspondence: Zhi-Qi Wu, <email>qiecho@126.com</email></corresp>
<corresp id="c002">Hua-Guo Xu, <email>huaguoxu@njmu.edu.cn</email></corresp>
<fn fn-type="equal" id="fn002"><p><sup>&#x2020;</sup>These authors have contributed equally to this work</p></fn>
<fn fn-type="other" id="fn004"><p>This article was submitted to Gastroenterology, a section of the journal Frontiers in Medicine</p></fn>
</author-notes>
<pub-date pub-type="epub">
<day>11</day>
<month>07</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="collection">
<year>2022</year>
</pub-date>
<volume>9</volume>
<elocation-id>920732</elocation-id>
<history>
<date date-type="received">
<day>15</day>
<month>04</month>
<year>2022</year>
</date>
<date date-type="accepted">
<day>30</day>
<month>05</month>
<year>2022</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2022 Shi, Zhang, She, Goyal, Wu and Xu.</copyright-statement>
<copyright-year>2022</copyright-year>
<copyright-holder>Shi, Zhang, She, Goyal, Wu and Xu</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>This study aims to consolidate evidence from published systematic reviews and meta-analyses evaluating the diagnostic performances of non-invasive tests for inflammatory bowel disease (IBD) in various clinical conditions and age groups.</p>
</sec>
<sec>
<title>Methods</title>
<p>Two independent reviewers systematically identified and appraised systematic reviews and meta-analyses assessing the diagnostic utility of non-invasive tests for IBD. Each association was categorized as adults, children, and mixed population, based on the age ranges of patients included in the primary studies. We classified clinical scenarios into diagnosis, activity assessment, and predicting recurrence.</p>
</sec>
<sec>
<title>Results</title>
<p>In total, 106 assessments from 43 reviews were included, with 17 non-invasive tests. Fecal calprotectin (FC) and fecal lactoferrin (FL) were the most sensitive for distinguishing IBD from non-IBD. However, anti-neutrophil cytoplasmic antibodies (ANCA) and FL were the most specific for it. FC and FL were the most sensitive and specific tests, respectively, to distinguish IBD from irritable bowel syndrome (IBS). Anti-<italic>Saccharomyces cerevisiae</italic> antibodies (ASCA), IgA, were the best test to distinguish Crohn&#x2019;s disease (CD) from ulcerative colitis (UC). Interferon-&#x03B3; release assay was the best test to distinguish CD from intestinal tuberculosis (ITB). Ultrasound (US) and magnetic resonance enterography (MRE) were both sensitive and specific for disease activity, along with the high sensitivity of FC. Small intestine contrast ultrasonography (SICUS) had the highest sensitivity, and FC had the highest specificity for operative CD recurrence.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>In this umbrella review, we summarized the diagnostic performance of non-invasive tests for IBD in various clinical conditions and age groups. Clinicians can use the suggested non-invasive test depending on the appropriate clinical situation in IBD patients.</p>
</sec>
</abstract>
<kwd-group>
<kwd>inflammatory bowel disease</kwd>
<kwd>non-invasive tests</kwd>
<kwd>diagnostic performance</kwd>
<kwd>Crohn&#x2019;s disease</kwd>
<kwd>ulcerative colitis</kwd>
</kwd-group>
<counts>
<fig-count count="3"/>
<table-count count="3"/>
<equation-count count="0"/>
<ref-count count="66"/>
<page-count count="12"/>
<word-count count="6850"/>
</counts>
</article-meta>
</front>
<body>
<sec id="S1" sec-type="intro">
<title>Introduction</title>
<p>Inflammatory bowel diseases (IBD) [Crohn&#x2019;s disease (CD) and ulcerative colitis (UC)] are idiopathic disorders causing inflammation of the gastrointestinal tract. IBD is emerging as a globally important disease with increasing incidence. Although incidence has started to relatively stabilize in western countries, the disease burden remains high as prevalence surpasses 0.3% (<xref ref-type="bibr" rid="B1">1</xref>).</p>
<p>Gastrointestinal endoscopy has remained a reference standard but invasive test for the diagnosis, management, prognostics, and surveillance of IBD. However, endoscopy can be associated with considerable cost, risk, and burden to patients and healthcare systems, and it is the lowest acceptable tool for patients (<xref ref-type="bibr" rid="B2">2</xref>).</p>
<p>Accurate non-invasive tests such as biomarkers and radiological examinations would be ideal (<xref ref-type="bibr" rid="B3">3</xref>, <xref ref-type="bibr" rid="B4">4</xref>). Several promising non-invasive tests that could fulfill this role, including fecal calprotectin (FC) (<xref ref-type="bibr" rid="B5">5</xref>) and ultrasound (US) (<xref ref-type="bibr" rid="B6">6</xref>), have been studied. Despite many studies assessing the diagnostic performance of non-invasive tests for IBD, to the best of our knowledge, there has been no systematic effort to summarize and critically appraise this body of evidence. Therefore, we performed an umbrella review of meta-analyses, based on different clinical conditions (including diagnosis, activity assessment, and recurrence) and age groups (children, adults, and mixed population), to provide a comprehensive synopsis of the diagnostic performance and validity of reported non-invasive tests for IBD.</p>
</sec>
<sec id="S2">
<title>Methods</title>
<sec id="S2.SS1">
<title>Search Strategy</title>
<p>Two reviewers (J-TS and Z-QW) independently searched PubMed, Embase, Web of Science, and Cochrane Library databases from inception to 16 April 2020. The search was limited to systematic reviews and meta-analyses without language restrictions. <xref ref-type="supplementary-material" rid="SM1">Supplementary Appendix 1</xref> provides a detailed search strategy.</p>
</sec>
<sec id="S2.SS2">
<title>Study Selection and Data Extraction</title>
<p>Systematic reviews or meta-analyses meeting the following criteria were included: it described the conduct of the systematic review in adequate detail, and an attempt was made to identify all of the relevant primary studies in at least one database with provided search strategy and quality appraisal of the primary studies (<xref ref-type="bibr" rid="B7">7</xref>). Guidelines, narrative reviews, literature reviews, genetic studies, protocol, conference abstracts, and reviews assessing scoring indices were excluded.</p>
<p>Two reviewers (J-TS and Z-QW) independently carried out the study selection and data extraction from the eligible articles. Extracted data included author, year of publication, number of participants, number and type of studies included, appraisal instrument used, reference standard, outcomes assessed, heterogeneity, and study findings.</p>
</sec>
<sec id="S2.SS3">
<title>Quality Assessment</title>
<p>The methodological quality of included reviews was assessed independently by J-TS and Z-QW using the online AMSTAR 2 (A Measurement Tool to Assess Systematic Reviews) checklist (<xref ref-type="bibr" rid="B8">8</xref>). AMSTAR 2 is a validated and reliable quality measurement tool for systematic reviews, with 16 domains. Seven of these domains are considered critical. Shortcomings in any of the critical domains could affect the overall validity of a review. It results in an assessment of the methodologic quality as 1 of 2 grades: high, moderate, low, or critically low (<xref ref-type="bibr" rid="B9">9</xref>).</p>
</sec>
<sec id="S2.SS4">
<title>Identification of Age Groups</title>
<p>Based on the age ranges of primary studies included, associations can be categorized as adults, children, and mixed population. We defined children as under the age of 18 years (<xref ref-type="bibr" rid="B10">10</xref>). If a systematic review purporting to assess the accuracy in adults included people younger than 18 years, it would be classified as a mixed population. <xref ref-type="supplementary-material" rid="SM1">Supplementary Appendix 2</xref> presents the process of identifying age groups.</p>
</sec>
<sec id="S2.SS5">
<title>Overlapping and Outdated Associations</title>
<p>Associations in two or more reviews overlapped if they evaluated the same test in the same clinical condition and same age group. Incorporating results of overlapping reviews could lead to double inclusion resulting in biased findings and estimates (<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B12">12</xref>). In addition, up to 50% of published systematic reviews were considered out of date after 5.5 years. Therefore, we categorized overlapping systematic reviews as outdated (published before October 2015) and contemporary (published after October 2015).</p>
<p>For contemporary reviews found to have overlapping assessments, we generated a graphical cross-tabulation (citation matrix) of the overlapping reviews (in columns) and the included primary studies (in rows) (<xref ref-type="bibr" rid="B13">13</xref>). Corrected covered area (CCA) was a validated method to quantify the degree of overlap between two or more reviews. We used a citation matrix to calculate CCA. According to CCA, the overlap can be categorized as very high (CCA &#x003E; 15%), high (CCA 11&#x2013;15%), moderate (CCA 6&#x2013;10%), or slight (CCA 0&#x2013;5%) (<xref ref-type="bibr" rid="B14">14</xref>).</p>
<p>In all the systematic reviews that met the inclusion criteria, all non-overlapping reviews were included. A rigorous management tool was used for the overlapping reviews. <xref ref-type="supplementary-material" rid="SM1">Supplementary Appendix 3</xref> shows the citation matrices for all overlapping studies. <xref ref-type="supplementary-material" rid="SM1">Supplementary Appendix 4</xref> presents the management of overlapping reviews.</p>
</sec>
<sec id="S2.SS6">
<title>Data Synthesis</title>
<p>Systematic reviews that met the inclusion criteria formed the unit of analysis. Only data available from systematic reviews were presented. Results from systematic reviews were synthesized with a narrative synthesis, with a tabular presentation of findings and forest plots for studies that performed a meta-analysis. Summary tables describing review characteristics and findings were also presented.</p>
</sec>
<sec id="S2.SS7">
<title>Update of Eligible Reviews</title>
<p>We used the framework recommended by Garner et al. (<xref ref-type="bibr" rid="B15">15</xref>) to determine whether an update was necessary. An existing review qualified for an update if all of the following were met:</p>
<list list-type="simple">
<list-item>
<label>&#x2022;</label>
<p>The review achieved at least a moderate rating with the AMSTAR 2 quality assessment tool (<xref ref-type="bibr" rid="B9">9</xref>).</p>
</list-item>
<list-item>
<label>&#x2022;</label>
<p>A focused or abbreviated search of primary studies using the key search terms from the search strategy of an existing review to identify newly published studies that met the inclusion criteria of the review.</p>
</list-item>
<list-item>
<label>&#x2022;</label>
<p>The findings from newly published studies would change the conclusion or credibility of the review.</p>
</list-item>
</list>
<p><xref ref-type="supplementary-material" rid="SM1">Supplementary Appendix 5</xref> describes the search strategy used to identify newly published studies. YXZ and YHS initially screened the eligible newly published studies. Full-text screening and data extracting were accomplished by JTS and ZQW.</p>
<p>With findings from newly published studies, we relied on statistical methods using the bivariate model (<xref ref-type="bibr" rid="B16">16</xref>) to pool the data from newly published studies with the data from the original meta-analysis (<xref ref-type="bibr" rid="B17">17</xref>) (for meta-analyses) and discussion with senior authors (for reviews without meta-analyses) to determine whether a full update of the existing review was needed (<xref ref-type="bibr" rid="B18">18</xref>).</p>
<p>If an update was considered necessary, the original methods used in the conduct of the existing review were replicated. <xref ref-type="supplementary-material" rid="SM1">Supplementary Appendix 6</xref> summarizes the evaluation process for considering reviews for updates adapted from Ahmadzai et al. (<xref ref-type="bibr" rid="B19">19</xref>).</p>
</sec>
</sec>
<sec id="S3" sec-type="results">
<title>Results</title>
<sec id="S3.SS1">
<title>Literature Search</title>
<p>The search retrieved 1,897 articles. After removing duplicates and screening titles and abstracts, 113 articles qualified for full-text screening. Seven outdated reviews were further excluded. Finally, 46 reviews were included. <xref ref-type="supplementary-material" rid="SM1">Supplementary Appendix 7</xref> summarizes the study selection process with accurate numbers of studies. <xref ref-type="supplementary-material" rid="SM1">Supplementary Appendix 8</xref> provides the list of excluded studies with reasons for exclusion.</p>
</sec>
<sec id="S3.SS2">
<title>Methodological Quality</title>
<p>Twenty-two reviews (<xref ref-type="bibr" rid="B5">5</xref>, <xref ref-type="bibr" rid="B6">6</xref>, <xref ref-type="bibr" rid="B10">10</xref>, <xref ref-type="bibr" rid="B20">20</xref>&#x2013;<xref ref-type="bibr" rid="B38">38</xref>) were rated as moderate in quality, and twenty-three reviews (<xref ref-type="bibr" rid="B39">39</xref>&#x2013;<xref ref-type="bibr" rid="B60">60</xref>) were rated as low, while one review (<xref ref-type="bibr" rid="B61">61</xref>) was rated as critically low in quality (<xref ref-type="supplementary-material" rid="SM1">Supplementary Appendix 9</xref>). In the seven critical domains, most low-quality reviews had not stated that the methods were established before conducting the study.</p>
</sec>
<sec id="S3.SS3">
<title>Overlapping and Non-overlapping Assessment</title>
<p>Seventeen reviews reported overlapping assessment (<xref ref-type="bibr" rid="B5">5</xref>, <xref ref-type="bibr" rid="B6">6</xref>, <xref ref-type="bibr" rid="B29">29</xref>, <xref ref-type="bibr" rid="B32">32</xref>, <xref ref-type="bibr" rid="B36">36</xref>, <xref ref-type="bibr" rid="B37">37</xref>, <xref ref-type="bibr" rid="B46">46</xref>, <xref ref-type="bibr" rid="B49">49</xref>&#x2013;<xref ref-type="bibr" rid="B52">52</xref>, <xref ref-type="bibr" rid="B54">54</xref>, <xref ref-type="bibr" rid="B58">58</xref>, <xref ref-type="bibr" rid="B59">59</xref>, <xref ref-type="bibr" rid="B61">61</xref>&#x2013;<xref ref-type="bibr" rid="B63">63</xref>). <xref ref-type="supplementary-material" rid="SM1">Supplementary Appendix 10</xref> describes the general characteristics of overlapping reviews, including the decision to retain or exclude an assessment. <xref ref-type="supplementary-material" rid="SM1">Supplementary Appendix 3</xref> provides the citation matrices for overlapping reviews to assess the degree of overlap. <xref ref-type="supplementary-material" rid="SM1">Supplementary Appendix 11</xref> lists forty-six reviews with non-overlapping assessments that were included and one contemporary review that was excluded because of overlap.</p>
</sec>
<sec id="S3.SS4">
<title>Study Characteristics of Reviews With Non-overlapping Assessments</title>
<p>Non-invasive tests for IBD assessed in the included reviews were FC, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), platelet count (PLT), hemoglobin (Hb), albumin (Alb), ASCA, anti-neutrophil cytoplasmic antibodies (ANCA), fecal lactoferrin (FL), US, computed tomography (CT), magnetic resonance imaging enterography (MRE), scintigraphy, autoantibodies-to-glycoprotein-2 (AntiGP2), interferon-&#x03B3; release assays (IGRA), fecal immunochemical (FIT), microRNA, and S100A12. Of the 46 reviews included, 43 conducted meta-analyses. <xref ref-type="supplementary-material" rid="SM1">Supplementary Table 1</xref> summarizes the general characteristics of the reviews and meta-analyses included in the umbrella review.</p>
</sec>
<sec id="S3.SS5">
<title>Summary Findings</title>
<p><xref ref-type="table" rid="T1">Table 1</xref> shows the diagnostic utility of non-invasive tests for IBD in different clinical scenarios and age groups. <xref ref-type="table" rid="T2">Tables 2</xref>, <xref ref-type="table" rid="T3">3</xref> show the diagnostic utility of non-invasive tests for CD and UC, respectively. The clinical scenarios include diagnosis (IBD vs. non-IBD), diagnosis (IBD vs. IBS), diagnosis (IBD vs. FGID, functional gastrointestinal disorders), diagnosis (CD vs. ITB, intestinal tuberculosis), diagnosis (CD vs. UC), activity assessment, and recurrence. <xref ref-type="fig" rid="F1">Figure 1</xref> presents the forest plots of sensitivity (Se) and specificity (Sp) of non-invasive tests for IBD. <xref ref-type="fig" rid="F2">Figures 2</xref>, <xref ref-type="fig" rid="F3">3</xref> present the forest plots for CD and UC, respectively. <xref ref-type="supplementary-material" rid="SM1">Supplementary Tables 2</xref>, <xref ref-type="supplementary-material" rid="SM1">3</xref> show the findings of meta-analyses and narrative synthesis from systematic reviews.</p>
<table-wrap position="float" id="T1">
<label>TABLE 1</label>
<caption><p>Summary findings for each non-invasive tests and diagnostic performance (IBD).</p></caption>
<table cellspacing="5" cellpadding="5" frame="hsides" rules="groups">
<thead>
<tr>
<td valign="top" align="left" colspan="2">Non-invasive tests</td>
<td valign="top" align="center" colspan="3">Diagnostic performance (95% CI)<hr/></td>
</tr>
<tr>
<td valign="top" colspan="2"/><td valign="top" align="center">Sensitivity</td>
<td valign="top" align="center">Specificity</td>
<td valign="top" align="center">AUC</td>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left" colspan="5"><bold>Mixed</bold></td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold><italic>Diagnosis- IBD vs. non-IBD</italic></bold></td>
</tr>
<tr>
<td valign="top" align="left">FC</td>
<td valign="top" align="center">FC</td>
<td valign="top" align="center">0.99 (0.92&#x2013;1.00) <xref ref-type="table-fn" rid="t1fns1">&#x002A;</xref> 0.882 (0.827&#x2013;0.921) &#x2020;</td>
<td valign="top" align="center">0.65 (0.54&#x2013;0.74) <xref ref-type="table-fn" rid="t1fns1">&#x002A;</xref> 0.799 (0.693&#x2013;0.875) &#x2020;</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Cut-off 50&#x03BC;g/g</td>
<td valign="top" align="center">0.850 (0.605&#x2013;0.955)</td>
<td valign="top" align="center">0.847 (0.647&#x2013;0.943)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Cut-off 100&#x03BC;g/g</td>
<td valign="top" align="center">0.72 (0.63&#x2013;0.80)</td>
<td valign="top" align="center">0.82 (0.78&#x2013;0.86)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">CRP</td>
<td valign="top" align="center">0.63 (0.51&#x2013;0.73)</td>
<td valign="top" align="center">0.88 (0.80&#x2013;0.93)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">ESR</td>
<td valign="top" align="center">0.66 (0.58&#x2013;0.73)</td>
<td valign="top" align="center">0.84 (0.80&#x2013;0.88)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">PLT</td>
<td valign="top" align="center">0.55 (0.36&#x2013;0.73)</td>
<td valign="top" align="center">0.88 (0.81&#x2013;0.93)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">Hb</td>
<td valign="top" align="center">0.37 (0.24&#x2013;0.52)</td>
<td valign="top" align="center">0.90 (0.83&#x2013;0.94)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">Alb</td>
<td valign="top" align="center">0.48 (0.31&#x2013;0.66)</td>
<td valign="top" align="center">0.94 (0.86&#x2013;0.98)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left">ASCA</td>
<td valign="top" align="center">ASCA</td>
<td valign="top" align="center">0.397 (0.376&#x2013;0.418)</td>
<td valign="top" align="center">0.925 (0.913&#x2013;0.937)</td>
<td valign="top" align="center">0.783</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">IgA</td>
<td valign="top" align="center">0.314 (0.285&#x2013;0.345)</td>
<td valign="top" align="center">0.96 (0.943&#x2013;0.973)</td>
<td valign="top" align="center">0.821</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">ANCA</td>
<td valign="top" align="center">0.328 (0.312&#x2013;0.344)</td>
<td valign="top" align="center">0.971 (0.964&#x2013;0.977)</td>
<td valign="top" align="center">0.872</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">FL</td>
<td valign="top" align="center">0.82 (0.72&#x2013;0.89)</td>
<td valign="top" align="center">0.95 (0.88&#x2013;0.98)</td>
<td valign="top" align="center">0.95 (0.93&#x2013;0.97)</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">US</td>
<td valign="top" align="center">0.73 (0.65&#x2013;0.80)</td>
<td valign="top" align="center">0.95 (0.91&#x2013;0.97)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">CT- per segment</td>
<td valign="top" align="center">0.85 (0.81&#x2013;0.88)</td>
<td valign="top" align="center">0.87 (0.84&#x2013;0.90)</td>
<td valign="top" align="center">0.933</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">microRNA</td>
<td valign="top" align="center">0.80 (0.79&#x2013;0.82)</td>
<td valign="top" align="center">0.84 (0.82&#x2013;0.86)</td>
<td valign="top" align="center">0.89</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold><italic>Diagnosis- IBD vs. IBS</italic></bold></td>
</tr>
<tr>
<td valign="top" align="left">FC</td>
<td valign="top" align="center">Cut-off 50&#x03BC;g/g</td>
<td valign="top" align="center">0.97 (0.91&#x2013;0.99)</td>
<td valign="top" align="center">0.76 (0.66&#x2013;0.84)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Cut-off 100&#x03BC;g/g</td>
<td valign="top" align="center">0.92 (0.85&#x2013;0.96)</td>
<td valign="top" align="center">0.86 (0.82&#x2013;0.89)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">FL</td>
<td valign="top" align="center">0.78 (0.75&#x2013;0.82)</td>
<td valign="top" align="center">0.94 (0.91&#x2013;0.96)</td>
<td valign="top" align="center">0.94</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold><italic>Activity</italic></bold></td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">CT-Per segment</td>
<td valign="top" align="center">0.856 (0.76&#x2013;0.92)</td>
<td valign="top" align="center">0.855 (0.75&#x2013;0.92)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">US-Per segment</td>
<td valign="top" align="center">0.864 (0.761&#x2013;0.927) 0.82</td>
<td valign="top" align="center">0.883 (0.581&#x2013;0.976) 0.9</td>
<td valign="top" align="center">NA 0.90 (0.75&#x2013;1.00)</td>
</tr>
<tr>
<td valign="top" align="left">MRE</td>
<td valign="top" align="center">MRE</td>
<td valign="top" align="center">0.83 (0.75&#x2013;0.89)</td>
<td valign="top" align="center">0.93 (0.90&#x2013;0.95)</td>
<td valign="top" align="center">0.95 (0.93&#x2013;0.97)</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Per-patient</td>
<td valign="top" align="center">0.86 (0.78&#x2013;0.91)</td>
<td valign="top" align="center">0.91 (0.82&#x2013;0.96)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Per-lesion</td>
<td valign="top" align="center">0.72 (0.55&#x2013;0.84)</td>
<td valign="top" align="center">0.93 (0.90&#x2013;0.95)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Per-segment</td>
<td valign="top" align="center">0.75</td>
<td valign="top" align="center">0.91</td>
<td valign="top" align="center">0.88 (0.82&#x2013;0.93)</td>
</tr>
<tr>
<td valign="top" align="left">Scintigraphy</td>
<td valign="top" align="center">LS-per patient</td>
<td valign="top" align="center">0.91 (0.87&#x2013;0.95)</td>
<td valign="top" align="center">0.85 (0.76&#x2013;0.91)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">LS-per segment</td>
<td valign="top" align="center">0.79 (0.76&#x2013;0.82)</td>
<td valign="top" align="center">0.86 (0.82&#x2013;0.89)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left">FC</td>
<td valign="top" align="center">FC</td>
<td valign="top" align="center">0.85 (0.82&#x2013;0.87)</td>
<td valign="top" align="center">0.75 (0.71&#x2013;0.79)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Cut-off 50&#x03BC;g/g</td>
<td valign="top" align="center">0.92 (0.90&#x2013;0.94)</td>
<td valign="top" align="center">0.60 (0.52&#x2013;0.67)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Cut-off 100&#x03BC;g/g</td>
<td valign="top" align="center">0.84 (0.80&#x2013;0.88)</td>
<td valign="top" align="center">0.66 (0.59&#x2013;0.73)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Cut-off 250&#x03BC;g/g</td>
<td valign="top" align="center">0.80 (0.76&#x2013;0.84)</td>
<td valign="top" align="center">0.82 (0.77&#x2013;0.86)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">CRP</td>
<td valign="top" align="center">0.49 (0.34&#x2013;0.64)</td>
<td valign="top" align="center">0.92 (0.72&#x2013;0.98)</td>
<td valign="top" align="center">0.72 (0.68&#x2013;0.76)</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">FL</td>
<td valign="top" align="center">0.82 (0.73&#x2013;0.88)</td>
<td valign="top" align="center">0.79 (0.62&#x2013;0.89)</td>
<td valign="top" align="center">0.87 (0.84&#x2013;0.90)</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold><italic>Recurrence</italic></bold></td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">FC</td>
<td valign="top" align="center">0.78 (0.72&#x2013;0.83)</td>
<td valign="top" align="center">0.73 (0.68&#x2013;0.77)</td>
<td valign="top" align="center">0.83</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><hr/></td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold>Adults</bold></td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold><italic>Diagnosis- IBD vs. non-IBD</italic></bold></td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">FC</td>
<td valign="top" align="center">0.825 (0.661&#x2013;0.920)</td>
<td valign="top" align="center">0.900 (0.573&#x2013;0.984)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold><italic>Diagnosis- IBD vs. FGID</italic></bold></td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">FC</td>
<td valign="top" align="center">0.88 (0.80&#x2013;0.93)</td>
<td valign="top" align="center">0.72 (0.59&#x2013;0.82)</td>
<td valign="top" align="center">0.89</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><italic><bold>Activity</bold></italic></td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">CT-Per segment</td>
<td valign="top" align="center">0.84 (0.78&#x2013;0.90)</td>
<td valign="top" align="center">0.86 (0.81&#x2013;0.90)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">US-Per segment</td>
<td valign="top" align="center">0.860 (0.745&#x2013;0.928)</td>
<td valign="top" align="center">0.836 (0.533&#x2013;0.958)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><hr/></td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold>Children</bold></td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><italic><bold>Diagnosis-IBD vs. non-IBD</bold></italic></td>
</tr>
<tr>
<td valign="top" align="left">FC</td>
<td valign="top" align="center">FC</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">0.95 (0.93&#x2013;0.98)</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Cut-off 50&#x03BC;g/g</td>
<td valign="top" align="center">0.83 (0.73&#x2013;0.90)</td>
<td valign="top" align="center">0.85 (0.77&#x2013;0.91)</td>
<td valign="top" align="center">0.96</td>
</tr>
<tr>
<td valign="top" align="center" colspan="2">CRP</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">0.79 (0.73&#x2013;0.85)</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">ESR</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">0.84 (0.82&#x2013;0.87)</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">PLT</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">0.79 (0.75&#x2013;0.83)</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">Hb</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">0.76 (0.71&#x2013;0.80)</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">Alb</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">0.82 (0.73&#x2013;0.90)</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold><italic>Activity</italic></bold></td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">US</td>
<td valign="top" align="center">0.876 (0.542&#x2013;0.977)</td>
<td valign="top" align="center">1.0</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">Scintigraphy-MAAS-per segment</td>
<td valign="top" align="center">0.45 (0.37&#x2013;0.53)</td>
<td valign="top" align="center">0.94 (0.89&#x2013;0.97)</td>
<td valign="top" align="center">NA</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="t1fns1"><p><italic>NA, not available, &#x002A;age range: 0.8&#x2013;19.9, &#x2020;: age range: 14&#x2013;90. FC, fecal calprotectin; CRP, C-reactive protein; ESR, erythrocyte sedimentation rate; PLT, platelet count; Hb, hemoglobin; Alb, albumin; ASCA, Anti-Saccharomyces cerevisiae antibodies; ANCA, anti-neutrophil cytoplasmic antibodies; FL, fecal lactoferrin; US, Ultrasound; CT, computed tomography; MRE, magnetic resonance imaging enterography.</italic></p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap position="float" id="T2">
<label>TABLE 2</label>
<caption><p>Summary findings for each non-invasive tests and diagnostic performance (CD).</p></caption>
<table cellspacing="5" cellpadding="5" frame="hsides" rules="groups">
<thead>
<tr>
<td valign="top" align="left" colspan="2">Non-invasive tests</td>
<td valign="top" align="center" colspan="3">Diagnostic performance (95% CI)<hr/></td>
</tr>
<tr>
<td valign="top" colspan="2"/><td valign="top" align="center">Sensitivity</td>
<td valign="top" align="center">Specificity</td>
<td valign="top" align="center">AUC</td>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left" colspan="5"><bold>Mixed</bold></td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold><italic>Diagnosis- IBD vs. non-IBD</italic></bold></td>
</tr>
<tr>
<td valign="top" align="left">FC</td>
<td valign="top" align="center">Cut-off 50&#x03BC;g/g</td>
<td valign="top" align="center">0.95 (0.92&#x2013;0.97)</td>
<td valign="top" align="center">0.84 (0.80&#x2013;0.87)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">SBCD</td>
<td valign="top" align="center">0.89 (0.68&#x2013;0.97)</td>
<td valign="top" align="center">0.55 (0.36&#x2013;0.73)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">FL</td>
<td valign="top" align="center">0.75 (0.65&#x2013;0.84)</td>
<td valign="top" align="center">1.00 (0.50&#x2013;1.00)</td>
<td valign="top" align="center">0.84 (0.81&#x2013;0.87)</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">MRI-SBCD</td>
<td valign="top" align="center">0.84 (0.77&#x2013;0.90)</td>
<td valign="top" align="center">0.97 (0.91&#x2013;0.99)</td>
<td valign="top" align="center">0.95</td>
</tr>
<tr>
<td valign="top" align="left">AntiGP2</td>
<td valign="top" align="center">AntiGP2</td>
<td valign="top" align="center">0.24 (0.18&#x2013;0.32)</td>
<td valign="top" align="center">0.96 (0.93&#x2013;0.97)</td>
<td valign="top" align="center">0.72 (0.68&#x2013;0.76)</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">IgA</td>
<td valign="top" align="center">0.15 (0.12&#x2013;0.18)</td>
<td valign="top" align="center">0.97 (median)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">IgG</td>
<td valign="top" align="center">0.19 (0.14&#x2013;0.25)</td>
<td valign="top" align="center">0.97 (0.94&#x2013;0.98)</td>
<td valign="top" align="center">0.71 (0.67&#x2013;0.75)</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold><italic>Diagnosis- CD vs. UC</italic></bold></td>
</tr>
<tr>
<td valign="top" align="left">AntiGP2</td>
<td valign="top" align="center">AntiGP2</td>
<td valign="top" align="center">0.20 (0.04&#x2013;0.35)</td>
<td valign="top" align="center">0.97 (median)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">IgA</td>
<td valign="top" align="center">0.11 (0.03&#x2013;0.20)</td>
<td valign="top" align="center">0.98 (median)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">IgG</td>
<td valign="top" align="center">0.30 (0.24&#x2013;0.36)</td>
<td valign="top" align="center">0.93 (median)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left">ASCA</td>
<td valign="top" align="center">ASCA</td>
<td valign="top" align="center">0.533 (0.508&#x2013;0.557)</td>
<td valign="top" align="center">0.892 (0.872&#x2013;0.910)</td>
<td valign="top" align="center">0.836</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">IgA</td>
<td valign="top" align="center">0.408 (0.381&#x2013;0.435)</td>
<td valign="top" align="center">0.955 (0.938&#x2013;0.967)</td>
<td valign="top" align="center">0.863</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">IgG</td>
<td valign="top" align="center">0.457 (0.432&#x2013;0.483)</td>
<td valign="top" align="center">0.935 (0.917&#x2013;0.949)</td>
<td valign="top" align="center">0.85</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold><italic>Diagnosis- CD vs. ITB</italic></bold></td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">ASCA</td>
<td valign="top" align="center">0.33 (0.27&#x2013;0.38)</td>
<td valign="top" align="center">0.83 (0.77&#x2013;0.88)</td>
<td valign="top" align="center">0.58</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">IGRA</td>
<td valign="top" align="center">0.828 (0.784&#x2013;0.855)</td>
<td valign="top" align="center">0.867 (0.832&#x2013;0.896)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2"><bold><italic>Activity</italic></bold></td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left" colspan="2">CT-SBCD-per patient</td>
<td valign="top" align="center">0.86 (0.79&#x2013;0.91)</td>
<td valign="top" align="center">0.84 (0.75&#x2013;0.90)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left">FC</td>
<td valign="top" align="center">FC</td>
<td valign="top" align="center">0.824 (0.802&#x2013;0.844)</td>
<td valign="top" align="center">0.721 (0.69&#x2013;0.75)</td>
<td valign="top" align="center">0.84</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Cut-off 50&#x03BC;g/g</td>
<td valign="top" align="center">0.831 (0.740&#x2013;0.895)</td>
<td valign="top" align="center">0.502 (0.359&#x2013;0.644)</td>
<td valign="top" align="center">0.774</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Cut-off 100&#x03BC;g/g</td>
<td valign="top" align="center">0.725 (0.657&#x2013;0.784)</td>
<td valign="top" align="center">0.728 (0.622&#x2013;0.814)</td>
<td valign="top" align="center">0.763</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Cut-off 200&#x03BC;g/g</td>
<td valign="top" align="center">0.495 (0.361&#x2013;0.629)</td>
<td valign="top" align="center">0.882 (0.738&#x2013;0.952)</td>
<td valign="top" align="center">0.67</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">FL</td>
<td valign="top" align="center">0.82 (0.73&#x2013;0.88)</td>
<td valign="top" align="center">0.71 (0.63&#x2013;0.78)</td>
<td valign="top" align="center">0.84 (0.80&#x2013;0.87)</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">MRI</td>
<td valign="top" align="center">0.9</td>
<td valign="top" align="center">0.89</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left">US</td>
<td valign="top" align="center">Per segment</td>
<td valign="top" align="center">0.725 (0.454&#x2013;0.894)</td>
<td valign="top" align="center">0.977 (0.700&#x2013;0.999)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">CEUS</td>
<td valign="top" align="center">0.94 (0.87&#x2013;0.97)</td>
<td valign="top" align="center">0.79 (0.67&#x2013;0.88)</td>
<td valign="top" align="center">0.94</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold><italic>Recurrence</italic></bold></td>
</tr>
<tr>
<td valign="top" align="left">FC</td>
<td valign="top" align="center">FC</td>
<td valign="top" align="center">0.75 (0.64&#x2013;0.84)</td>
<td valign="top" align="center">0.71 (0.64&#x2013;0.76)</td>
<td valign="top" align="center">0.79</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">POR-ER</td>
<td valign="top" align="center">0.82 (0.73&#x2013;0.89)</td>
<td valign="top" align="center">0.61 (0.51&#x2013;0.71)</td>
<td valign="top" align="center">0.77 (0.74&#x2013;0.81)</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">POR-CR</td>
<td valign="top" align="center">0.59 (0.47&#x2013;0.71)</td>
<td valign="top" align="center">0.88 (0.80&#x2013;0.93)</td>
<td valign="top" align="center">0.97</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">POR-Cut-off 50&#x03BC;g/g</td>
<td valign="top" align="center">0.90 (0.83&#x2013;0.96)</td>
<td valign="top" align="center">0.36 (0.25&#x2013;0.47)</td>
<td valign="top" align="center">0.72</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">POR-Cut-off 100&#x03BC;g/g</td>
<td valign="top" align="center">0.81 (0.71&#x2013;0.91)</td>
<td valign="top" align="center">0.57 (0.48&#x2013;0.64)</td>
<td valign="top" align="center">0.67</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">POR-Cut-off 150&#x03BC;g/g</td>
<td valign="top" align="center">0.70 (0.59&#x2013;0.81)</td>
<td valign="top" align="center">0.69 (0.61&#x2013;0.77)</td>
<td valign="top" align="center">0.73</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">POR-Cut-off 200&#x03BC;g/g</td>
<td valign="top" align="center">0.55 (0.43&#x2013;0.69)</td>
<td valign="top" align="center">0.71 (0.62&#x2013;0.79)</td>
<td valign="top" align="center">0.69</td>
</tr>
<tr>
<td valign="top" align="left">US</td>
<td valign="top" align="center">POR</td>
<td valign="top" align="center">0.94 (0.86&#x2013;0.97)</td>
<td valign="top" align="center">0.84 (0.62&#x2013;0.94)</td>
<td valign="top" align="center">0.9</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">POR-BS</td>
<td valign="top" align="center">0.82 (0.76&#x2013;0.88)</td>
<td valign="top" align="center">0.88 (0.74&#x2013;0.95)</td>
<td valign="top" align="center">0.875</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">POR-SICUS</td>
<td valign="top" align="center">0.99 (0.99&#x2013;1.00)</td>
<td valign="top" align="center">0.74 (0.73&#x2013;0.74)</td>
<td valign="top" align="center">0.92</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">POR-SBCD&#x2013;SICUS</td>
<td valign="top" align="center">0.899 (0.817&#x2013;0.953)</td>
<td valign="top" align="center">0.808 (0.606&#x2013;0.934)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">MRI-POR</td>
<td valign="top" align="center">0.973 (0.891&#x2013;0.998)</td>
<td valign="top" align="center">0.837 (0.616&#x2013;0.959)</td>
<td valign="top" align="center">0.9767</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><hr/></td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold>Children</bold></td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold><italic>Diagnosis- IBD vs. non-IBD</italic></bold></td>
</tr>
<tr>
<td valign="top" align="left">FC</td>
<td valign="top" align="center">Cut-off 50&#x03BC;g/g</td>
<td valign="top" align="center">0.97 (0.86&#x2013;1.00)</td>
<td valign="top" align="center">0.79 (0.69&#x2013;0.87)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">Cut-off 100&#x03BC;g/g</td>
<td valign="top" align="center">1.00 (0.93&#x2013;1.00)</td>
<td valign="top" align="center">0.98 (0.93&#x2013;1.00)</td>
<td valign="top" align="center">NA</td>
</tr>
</tbody>
</table></table-wrap>
<table-wrap position="float" id="T3">
<label>TABLE 3</label>
<caption><p>Summary findings for each non-invasive tests and diagnostic performance (UC).</p></caption>
<table cellspacing="5" cellpadding="5" frame="hsides" rules="groups">
<thead>
<tr>
<td valign="top" align="left" colspan="2">Non-invasive tests</td>
<td valign="top" align="center" colspan="3">Diagnostic performance (95% CI)&#x002A;<hr/></td>
</tr>
<tr>
<td valign="top" colspan="2"/><td valign="top" align="center">Sensitivity</td>
<td valign="top" align="center">Specificity</td>
<td valign="top" align="center">AUC</td>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left" colspan="5"><bold>Mixed</bold></td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold><italic>Diagnosis- IBD vs. non-IBD</italic></bold></td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">FC</td>
<td valign="top" align="center">0.78 (0.69&#x2013;0.86)</td>
<td valign="top" align="center">0.78 (0.70&#x2013;0.84)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">ANCA</td>
<td valign="top" align="center">0.522</td>
<td valign="top" align="center">0.99</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">FL</td>
<td valign="top" align="center">0.82 (0.67&#x2013;0.91)</td>
<td valign="top" align="center">1.00 (0.67&#x2013;1.00)</td>
<td valign="top" align="center">0.94 (0.91&#x2013;0.96)</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold><italic>Diagnosis- UC vs. CD</italic></bold></td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">ANCA</td>
<td valign="top" align="center">0.553 (0.530&#x2013;0.576)</td>
<td valign="top" align="center">0.885 (0.871&#x2013;0.898)</td>
<td valign="top" align="center">0.818</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold><italic>Activity</italic></bold></td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">US-per segment</td>
<td valign="top" align="center">0.886 (0.800&#x2013;0.939)</td>
<td valign="top" align="center">0.819 (0.456&#x2013;0.961)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left">MRE</td>
<td valign="top" align="center">MRE</td>
<td valign="top" align="center">0.88 (0.86&#x2013;0.91)</td>
<td valign="top" align="center">0.88 (0.84&#x2013;0.91)</td>
<td valign="top" align="center">0.93</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">DWI-per segment</td>
<td valign="top" align="center">0.929 (0.858&#x2013;0.966)</td>
<td valign="top" align="center">0.910 (0.797&#x2013;0.963)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">LP</td>
<td valign="top" align="center">0.493 (0.410&#x2013;0.578)</td>
<td valign="top" align="center">0.891 (0.813&#x2013;0.944)</td>
<td valign="top" align="center">0.82</td>
</tr>
<tr>
<td/>
<td valign="top" align="center">SBCD-per patient</td>
<td valign="top" align="center">0.88 (0.82&#x2013;0.92)</td>
<td valign="top" align="center">0.81 (0.72&#x2013;0.88)</td>
<td valign="top" align="center">0.91</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">FC</td>
<td valign="top" align="center">0.873 (0.854&#x2013;0.891) <xref ref-type="table-fn" rid="t3fns1">&#x002A;</xref> 0.76 (0.71&#x2013;0.81) &#x2020;</td>
<td valign="top" align="center">0.771 (0.737&#x2013;0.803) <xref ref-type="table-fn" rid="t3fns1">&#x002A;</xref> 0.71 (0.62&#x2013;0.78) &#x2020;</td>
<td valign="top" align="center">0.91<xref ref-type="table-fn" rid="t3fns1">&#x002A;</xref> 0.79 (0.75&#x2013;0.82) &#x2020;</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">FIT</td>
<td valign="top" align="center">0.72 (0.57&#x2013;0.84)</td>
<td valign="top" align="center">0.80 (0.67&#x2013;0.89)</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">FL</td>
<td valign="top" align="center">0.81 (0.64&#x2013;0.92)</td>
<td valign="top" align="center">0.82 (0.61&#x2013;0.93)</td>
<td valign="top" align="center">0.88 (0.85&#x2013;0.91)</td>
</tr>
<tr>
<td valign="top" align="left" colspan="5"><bold><italic>Recurrence</italic></bold></td>
</tr>
<tr>
<td valign="top" align="left" colspan="2">FC</td>
<td valign="top" align="center">0.75 (0.70&#x2013;0.79)</td>
<td valign="top" align="center">0.77 (0.74&#x2013;0.80)</td>
<td valign="top" align="center">0.82</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="t3fns1"><p><italic>NA, not available; &#x002A;: endoscopic activity as reference; &#x2020;: histological activity as reference.</italic></p></fn>
</table-wrap-foot>
</table-wrap>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption><p>Forest plots of sensitivity and specificity of non-invasive tests for inflammatory bowel disease from meta-analyses. CI, confidence interval. &#x002A;Age range: 0.8&#x2013;19.9, <sup>&#x2020;</sup>age range: 14&#x2013;90.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmed-09-920732-g001.tif"/>
</fig>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption><p>Forest plots of sensitivity and specificity of non-invasive tests for Crohn&#x2019;s disease from meta-analyses. CI, confidence interval.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmed-09-920732-g002.tif"/>
</fig>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption><p>Forest plots of sensitivity and specificity of non-invasive tests for ulcerative colitis from meta-analyses. CI, confidence interval.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmed-09-920732-g003.tif"/>
</fig>
</sec>
<sec id="S3.SS6">
<title>Diagnosis: Inflammatory Bowel Disease vs. Non-inflammatory Bowel Disease</title>
<sec id="S3.SS6.SSS1">
<title>Mixed Population</title>
<p>For IBD, FC was the most sensitive test with a sensitivity of 0.99 (0.92&#x2013;1.00) (<xref ref-type="bibr" rid="B46">46</xref>). ANCA showed the highest specificity 0.971 (0.964&#x2013;0.977) (<xref ref-type="bibr" rid="B20">20</xref>). The sensitivity and specificity of CT, FL, and microRNA were both balanced (<xref ref-type="bibr" rid="B41">41</xref>, <xref ref-type="bibr" rid="B44">44</xref>). The other tests performed well in specificity but poorly in sensitivity, including US, ESR, CRP, PLT, Alb, Hb, and ASCA (<xref ref-type="bibr" rid="B20">20</xref>, <xref ref-type="bibr" rid="B46">46</xref>).</p>
<p>For UC, FL had both the best sensitivity (0.82; 0.67&#x2013;0.91) and the best specificity (1.00; 0.67&#x2013;1.00) (<xref ref-type="bibr" rid="B44">44</xref>). The other biomarkers were FC (Se, 0.78; 0.69&#x2013;0.86/Sp, 0.78; 0.70&#x2013;0.84) (<xref ref-type="bibr" rid="B21">21</xref>), and ANCA (Se, 0.522/Sp, 0.99) (<xref ref-type="bibr" rid="B64">64</xref>).</p>
<p>For CD, FC showed the highest sensitivity: 0.95 (0.92&#x2013;0.97) (<xref ref-type="bibr" rid="B21">21</xref>). FL showed the highest specificity: 1.00 (0.50&#x2013;1.00) (<xref ref-type="bibr" rid="B44">44</xref>). Also, the specificity of anti-GP2 was good (<xref ref-type="bibr" rid="B49">49</xref>).</p>
</sec>
<sec id="S3.SS6.SSS2">
<title>Adults</title>
<p>For IBD, only FC was performed with Se of 0.825 (0.661&#x2013;0.920) and Sp of 0.900 (0.573&#x2013;0.984) (<xref ref-type="bibr" rid="B5">5</xref>). For UC, there was a review showing that the Se and Sp for ANCA IgG were 0.67 (0.54&#x2013;0.79) and 0.85 (0.70&#x2013;0.94), respectively (<xref ref-type="bibr" rid="B39">39</xref>).</p>
</sec>
<sec id="S3.SS6.SSS3">
<title>Children</title>
<p>For IBD, FC with a cutoff of 50 &#x03BC;g/g showed the highest AUC of 0.96 (<xref ref-type="bibr" rid="B21">21</xref>). The AUCs of other biomarkers [FC, CRP, ESR, PLT, Hb, and Alb (<xref ref-type="bibr" rid="B30">30</xref>)] ranged from 0.76 to 0.95. One review presented results of US from three primary studies: sensitivity range from 0.39 to 0.55 and specificity range from 0.90 to 1.00 (<xref ref-type="bibr" rid="B35">35</xref>).</p>
<p>For CD, FC with a cutoff of 100 &#x03BC;g/g performed best with a sensitivity of 1.00 (0.93&#x2013;1.00) and specificity of 0.98 (0.93&#x2013;1.00) (<xref ref-type="bibr" rid="B21">21</xref>). MRE (Se, 0.84; 0.77&#x2013;0.90/Sp, 0.97; 0.91&#x2013;0.99) (<xref ref-type="bibr" rid="B22">22</xref>) also performed well in SBCD.</p>
</sec>
</sec>
<sec id="S3.SS7">
<title>Diagnosis: Inflammatory Bowel Disease vs. Irritable Bowel Syndrome</title>
<sec id="S3.SS7.SSS1">
<title>Mixed Population</title>
<p>For IBD, FC with a cutoff of 50 &#x03BC;g/g was the most sensitive test with a sensitivity of 0.97 (0.91&#x2013;0.99) (<xref ref-type="bibr" rid="B52">52</xref>). As for specificity, FL was the best: 0.94 (0.91&#x2013;0.96) (<xref ref-type="bibr" rid="B24">24</xref>). One review presented the diagnostic performance of fecal S100A12 (Se, 0.86; 0.73&#x2013;0.94/Sp, 0.96; 0.79&#x2013;0.99) (<xref ref-type="bibr" rid="B39">39</xref>) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table 3</xref>).</p>
</sec>
</sec>
<sec id="S3.SS8">
<title>Diagnosis: Inflammatory Bowel Disease vs. Functional Gastrointestinal Disorders</title>
<sec id="S3.SS8.SSS1">
<title>Adults</title>
<p>For IBD, there was only one test: FC (Se, 0.88; 0.80&#x2013;0.93/Sp, 0.71; 0.59&#x2013;0.82) (<xref ref-type="bibr" rid="B53">53</xref>).</p>
</sec>
</sec>
<sec id="S3.SS9">
<title>Diagnosis: Crohn&#x2019;s Disease vs. Ulcerative Colitis</title>
<sec id="S3.SS9.SSS1">
<title>Mixed Population</title>
<p>To differentiate CD from UC, the sensitivity of tests is generally low, including anti-GP2, ASCA (<xref ref-type="bibr" rid="B20">20</xref>, <xref ref-type="bibr" rid="B54">54</xref>). ASCA IgA showed the highest specificity of 0.955 (0.938&#x2013;0.967) (<xref ref-type="bibr" rid="B20">20</xref>). To differentiate UC from CD, the only test included in our analysis was ANCA (Se, 0.553; 0.530&#x2013;0.576/Sp, 0.885; 0.871&#x2013;0.898) (<xref ref-type="bibr" rid="B20">20</xref>).</p>
</sec>
</sec>
<sec id="S3.SS10">
<title>Diagnosis: Crohn&#x2019;s Disease vs. Intestinal Tuberculosis</title>
<sec id="S3.SS10.SSS1">
<title>Mixed Population</title>
<p>IGRA (Se, 0.828; 0.784&#x2013;0.855/Sp, 1.00; 0.867&#x2013;0.896) (<xref ref-type="bibr" rid="B48">48</xref>) had better diagnostic performance than ASCA (Se, 0.828; 0.784&#x2013;0.855/Sp, 0.867; 0.832&#x2013;0.896) (<xref ref-type="bibr" rid="B25">25</xref>).</p>
</sec>
</sec>
<sec id="S3.SS11">
<title>Activity</title>
<sec id="S3.SS11.SSS1">
<title>Mixed Population</title>
<p>For IBD, FC with a cutoff of 50 &#x03BC;g/g presented the highest sensitivity of 0.92 (0.90&#x2013;0.94) (<xref ref-type="bibr" rid="B42">42</xref>), and MRE showed the highest specificity of 0.93 (0.90&#x2013;0.95) (<xref ref-type="bibr" rid="B30">30</xref>). Besides, other radiological examinations [US, leukocyte scintigraphy (LS), and CT] all performed well with balanced sensitivity and specificity (<xref ref-type="bibr" rid="B6">6</xref>, <xref ref-type="bibr" rid="B30">30</xref>, <xref ref-type="bibr" rid="B43">43</xref>, <xref ref-type="bibr" rid="B56">56</xref>, <xref ref-type="bibr" rid="B59">59</xref>). However, other biomarkers (CRP and FL) were not as good as radiological examinations (<xref ref-type="bibr" rid="B27">27</xref>). One review suggested a sensitivity range of 0.64 to 0.93 and a specificity range of 0.71 to 1, showing that the diagnostic accuracy of TAUS (transabdominal US) remains inconclusive (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table 3</xref>) (<xref ref-type="bibr" rid="B35">35</xref>).</p>
<p>For CD, US showed the best specificity of 0.977 (0.700&#x2013;0.999) (<xref ref-type="bibr" rid="B6">6</xref>). Contrast-enhanced ultrasound (CEUS) was the most sensitive test with a sensitivity of 0.94 (0.87&#x2013;0.97) (<xref ref-type="bibr" rid="B45">45</xref>). CT and MRE also performed well; however, the sensitivity of DWI-MRE was poor (<xref ref-type="bibr" rid="B23">23</xref>, <xref ref-type="bibr" rid="B28">28</xref>, <xref ref-type="bibr" rid="B34">34</xref>, <xref ref-type="bibr" rid="B47">47</xref>). FC and FL performed slightly worse than CT and MRE (<xref ref-type="bibr" rid="B32">32</xref>, <xref ref-type="bibr" rid="B55">55</xref>). For UC, US had both best sensitivity (0.886, 0.800&#x2013;0.939) and specificity (0.819, 0.456&#x2013;0.961) (<xref ref-type="bibr" rid="B6">6</xref>). Among other tests, the specificity of FIT and FL and the sensitivity of FC and FL were fair (<xref ref-type="bibr" rid="B32">32</xref>, <xref ref-type="bibr" rid="B36">36</xref>).</p>
</sec>
<sec id="S3.SS11.SSS2">
<title>Adults</title>
<p>For IBD, US and CT have similar diagnostic performance. The sensitivity of ultrasound was slightly higher (0.860; 0.745&#x2013;0.928) (<xref ref-type="bibr" rid="B6">6</xref>), while the specificity of CT was slightly higher (0.86; 0.81&#x2013;0.90) (<xref ref-type="bibr" rid="B43">43</xref>). Monoclonal anti-granulocyte antibody scintigraphy (MAAS) was sensitive (Se, 0.94; 0.89&#x2013;0.97), but its specificity was not good (Sp, 0.45; 0.37&#x2013;0.53) (<xref ref-type="bibr" rid="B43">43</xref>).</p>
</sec>
<sec id="S3.SS11.SSS3">
<title>Children</title>
<p>For IBD, US had great performance: Se, 0.876 (0.542&#x2013;0.977); Sp, 1.00 (<xref ref-type="bibr" rid="B6">6</xref>). One review reported the diagnostic accuracy of TAUS, but showed that it remained inconclusive (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table 3</xref>) (<xref ref-type="bibr" rid="B35">35</xref>). The other review showed that the sensitivity of positron emission tomography/CT (PET/CT): 0.59 (0.36&#x2013;0.79) (SBFT, small-bowel follow through, used as the reference standard); 0.86 (0.70&#x2013;0.95) (colonoscopy used as the reference standard) and the specificity: 1.00 (0.77&#x2013;1.00) and 0.50 (0.01&#x2013;0.99), respectively (<xref ref-type="bibr" rid="B43">43</xref>).</p>
</sec>
</sec>
<sec id="S3.SS12">
<title>Recurrence</title>
<sec id="S3.SS12.SSS1">
<title>Mixed Population</title>
<p>For IBD, the only test was FC (Se, 0.78; 0.72&#x2013;0.83/Sp, 0.73; 0.68&#x2013;0.77/AUC, 0.83) (<xref ref-type="bibr" rid="B40">40</xref>). For UC, the sensitivity and specificity of FC were 0.75 (0.70&#x2013;0.79) and 0.77 (0.74&#x2013;0.80), respectively (<xref ref-type="bibr" rid="B33">33</xref>). For CD, FC showed the sensitivity of 0.75 (0.64&#x2013;0.84) and specificity of 0.71 (0.64&#x2013;0.76) (<xref ref-type="bibr" rid="B40">40</xref>).</p>
<p>For postoperative CD, SICUS showed the highest sensitivity of 0.99 (0.99&#x2013;1.00) (<xref ref-type="bibr" rid="B62">62</xref>). FC for clinical recurrence presented the highest specificity of 0.88 (0.80&#x2013;0.93), while FC for endoscopic recurrence presented with better sensitivity (<xref ref-type="bibr" rid="B26">26</xref>). Besides, MRE and other subtypes of US performed well in both sensitivity and specificity (<xref ref-type="bibr" rid="B50">50</xref>, <xref ref-type="bibr" rid="B51">51</xref>, <xref ref-type="bibr" rid="B57">57</xref>).</p>
</sec>
</sec>
<sec id="S3.SS13">
<title>Reviews Eligible for Update</title>
<p>We searched for newly published studies for each moderate quality review (<xref ref-type="supplementary-material" rid="SM1">Supplementary Appendix 6</xref>). After screening, 8 reviews (<xref ref-type="bibr" rid="B20">20</xref>, <xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B26">26</xref>, <xref ref-type="bibr" rid="B28">28</xref>&#x2013;<xref ref-type="bibr" rid="B30">30</xref>, <xref ref-type="bibr" rid="B32">32</xref>, <xref ref-type="bibr" rid="B35">35</xref>) have eligible new published studies. However, after calculation, no reviews need to be updated. The overview of updating was presented in <xref ref-type="supplementary-material" rid="SM1">Supplementary Appendix 12</xref>.</p>
</sec>
</sec>
<sec id="S4" sec-type="discussion">
<title>Discussion</title>
<p>Our detailed umbrella review synthesized existing systematic reviews and meta-analyses into one user-friendly document. A total of 106 associations, including 17 non-invasive tests, have been studied.</p>
<sec id="S4.SS1">
<title>Main Findings</title>
<p>Evidence from the umbrella review suggests that FC (0.99) and FL (0.82) were the most sensitive markers for distinguishing IBD from non-IBD. Similarly, ANCA (0.971) and FL (0.95) were the most specific marker for this purpose. To distinguish IBD from IBS, the most sensitive one was FC (cutoff 50 &#x03BC;g/g, 0.97; cutoff 100 &#x03BC;g/g, 0.92) and the most specific marker was FL (0.94). To distinguish CD from UC, all tests had low sensitivity, with ASCA IgA (0.955) having the highest specificity. IGRA (Se, 0.828; Sp, 0.867) was the best test to distinguish CD from ITB. There is only one test to diagnose IBD from FGID and only one test to distinguish UC from CD, FC, and ANCA. As for assessing activity, US (Se, 0.864; Sp, 0.883) and MRE (Se, 0.83; Sp, 0.93) perform well. The sensitivity of FC (0.85) was also good. As for postoperative recurrence of CD, SICUS (0.99) had the highest sensitivity and FC (CR: 0.88) had the highest specificity. We concluded that biomarkers played a good role in diagnosis, while radiological examinations, especially MRE and US, were more prominent in assessing activity and predicting recurrence. <xref ref-type="supplementary-material" rid="SM1">Supplementary Table 4</xref> presents the characteristic of diagnostic performance and clinical use of each test.</p>
</sec>
<sec id="S4.SS2">
<title>Strengths and Limitations</title>
<p>Compared with other studies summarizing non-invasive tests for IBD (<xref ref-type="bibr" rid="B65">65</xref>, <xref ref-type="bibr" rid="B66">66</xref>), our umbrella review provides the first systematic appraisal of the evidence using robust criteria. We used the AMSTAR 2 tool to assess the quality of reviews and used CCA to evaluate the degree of overlapping and report the highest quality and most current review. Besides, our umbrella review included both blood, stool biomarkers and radiological examinations. Furthermore, we rigorously classified the assessments into age groups based on the exact age range of the primary studies included and into several groups to discuss the diagnostic performance in a different clinical condition more rigorously and reasonably.</p>
<p>Several limitations are present in this review. Lack of data, including missing meta-data, hindered the reporting of some elements of the umbrella review and lack of reviews of children or adults alone. In addition, one review (<xref ref-type="bibr" rid="B20">20</xref>) could not undergo the normal updating process because it did not report the included studies of each assessment. Besides, some reviews were rated as low quality for the most common reason: lack of protocol. However, registering protocol has been rare, especially in the IBD field. What&#x2019;s more, since most articles do not report the value of AUC, we can&#x2019;t do a good comparison and analysis of AUC.</p>
</sec>
<sec id="S4.SS3">
<title>Implications for Practice and Future Research</title>
<p>This comprehensive umbrella review could help clinicians make better decisions about the appropriate tests prior to endoscopy. In terms of diagnosis, we suggested that in patients with symptoms suggestive of IBD in whom the clinician considers endoscopy, FC could be a sensitive test for safely excluding IBD. For patients with a negative result, we recommend that they continue to be monitored rather than do endoscopic examination immediately, unless it is very urgent. In patients with a positive result, FL is a good choice because of their low false-positive rate and consequent reduction of unnecessary endoscopies if patients are willing to have a stool test; if not, ANCA is an alternative. Clinicians can use our results to select a specific marker based on the practical situation. If both tests are positive, the patient is highly likely to have IBD. Endoscopic examination can be followed to confirm the diagnosis and disease classification. Radiation examinations, especially US and MRE, performed well in the activity assessment and predicting relapse. For patients with CD, we recommend having FC or US tests regularly to monitor the disease activity. Specifically, US or MRE is recommended for patients requiring postoperative recurrence monitoring. For patients with UC, MRE is the best choice to assess activity and predict relapse.</p>
<p>Our results show that there are not many reviews for children, especially in activity assessment and predicting recurrence. However, the use of endoscopy, invasive and requiring general anesthesia, can lead to child disobedience and disapproval of parents. An attitude of &#x201C;wait and see&#x201D; may cause unnecessary concerns and loss of wellbeing in children with IBD. Therefore, high-quality prospective studies on non-invasive testing in children should be complemented.</p>
</sec>
</sec>
<sec id="S5" sec-type="conclusion">
<title>Conclusion</title>
<p>In summary, this umbrella review summarized the diagnostic performance of non-invasive tests for IBD in different clinical conditions and age groups and offered our suggestions on how to use the non-invasive tests appropriately. Researchers and clinicians could choose a suitable test based on our results. Further studies on non-invasive tests in children are needed.</p>
</sec>
<sec id="S6" sec-type="data-availability">
<title>Data Availability Statement</title>
<p>The original contributions presented in this study are included in the article/<xref ref-type="supplementary-material" rid="SM1">Supplementary Material</xref>, further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec id="S7">
<title>Author Contributions</title>
<p>All authors listed have made a substantial, direct, and intellectual contribution to the work, and approved it for publication.</p>
</sec>
<sec id="audiscl1">
<title>Author Disclaimer</title>
<p>The corresponding authors had full access to all the data in the study and has final responsibility for the decision to submit for publication.</p>
</sec>
<sec id="conf1" 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="pudiscl1" 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>
<back>
<sec id="S8" sec-type="funding-information">
<title>Funding</title>
<p>This study was supported by the Natural Science Foundation of Jiangsu Province of China (BK20181492), the National Key Clinical Department of Laboratory Medicine of China in Nanjing, the Key Laboratory for Laboratory Medicine of Jiangsu Province (ZDXKB2016005), and the Priority Academic Program Development of Jiangsu Higher Education Institutions. The funder of the study had no role in the study design, data collection, data analysis, data interpretation, or writing of the manuscript.</p>
</sec>
<sec id="S9" 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/fmed.2022.920732/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fmed.2022.920732/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Data_Sheet_1.docx" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
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