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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Endocrinol.</journal-id>
<journal-title>Frontiers in Endocrinology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Endocrinol.</abbrev-journal-title>
<issn pub-type="epub">1664-2392</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fendo.2023.1256209</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Endocrinology</subject>
<subj-group>
<subject>Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Surgical outcomes of endoscopic thyroidectomy approaches for thyroid cancer: a systematic review and network meta-analysis</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Li</surname>
<given-names>Xiaosong</given-names>
</name>
<uri xlink:href="https://loop.frontiersin.org/people/2373103"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ding</surname>
<given-names>Wei</given-names>
</name>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Zhang</surname>
<given-names>Hong</given-names>
</name>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2200461"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
</contrib-group>
<aff id="aff1">
<institution>Department of Thyroid Surgery, The Second Hospital of Jilin University</institution>, <addr-line>Changchun, Jilin</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Takahisa Hiramitsu, Japanese Red Cross Nagoya Daini Hospital, Japan</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Mehmet Haciyanli, Izmir Katip Celebi University, T&#xfc;rkiye; Luiz Roberto Medina Dos Santos, Governador Celso Ramos Hospital, Brazil</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Hong Zhang, <email xlink:href="mailto:zhangh99@jlu.edu.cn">zhangh99@jlu.edu.cn</email>
</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>04</day>
<month>12</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="collection">
<year>2023</year>
</pub-date>
<volume>14</volume>
<elocation-id>1256209</elocation-id>
<history>
<date date-type="received">
<day>10</day>
<month>07</month>
<year>2023</year>
</date>
<date date-type="accepted">
<day>01</day>
<month>11</month>
<year>2023</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2023 Li, Ding and Zhang</copyright-statement>
<copyright-year>2023</copyright-year>
<copyright-holder>Li, Ding and Zhang</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>Objectives</title>
<p>This network meta-analysis assesses the outcomes of seven endoscopic approaches, offering valuable insights for researchers and practitioners in choosing the best method for thyroid cancer patients.</p>
</sec>
<sec>
<title>Methods</title>
<p>A systematic literature search was conducted in the PubMed, Embase and Web of Science databases up to March 2023. The analysis included seven endoscopic approaches, with a focus on their respective outcomes through network meta-analysis.</p>
</sec>
<sec>
<title>Results</title>
<p>This meta-analysis included 44 studies involving 8,672 patients. The axillo-bilateral breast approach (ABBA) and unilateral axillo-breast approach (UABA) showed advantages in terms of reduced operative time compared to other approaches (MD = 19.66 minutes, 95% CI = -31.66 to 70.98; MD = 30.32 minutes, 95% CI = -1.45 to 62.09, respectively). The UABA and anterior chest approach (ACA) exhibited superiority in controlling intraoperative bleeding (MD = -3.37 mL, 95% CI = -22.58 to 15.85; MD = -13.77 mL, 95% CI = -28.85 1.31, respectively). UABA and ACA also showed advantages in reducing hospital stays (MD = -0.39 days, 95% CI = -1.48 to 0.71; MD = -0.26 days, 95% CI = -1.33 to 0.81, respectively). The transoral approach (OA) yielded results comparable to those of conventional open thyroidectomy (COT) and outperformed other endoscopic surgeries with regards to lymph node retrieval and metastatic lymph node assessment. For the stimulated serum thyroglobulin (TG) levels, no significant difference was observed between bilateral axillo-breast approach (BABA) and OA compared to COT. However, chest-breast approach (CBA) showed significantly lower levels than COT (MD=-0.40 ng/ml, 95% CI =-0.72 to -0.09). Patients in the gasless unilateral transaxillary approach (GUA) group experienced a significant improvement in cosmetic satisfaction (MD=-2.08, 95% CI =-3.35 to -0.82). Importantly, no significant difference was observed in the incidence of surgical complications between endoscopic thyroidectomy and&#xa0;COT.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>Endoscopic thyroid surgery is a safe and effective choice for thyroid cancer patients. Different approaches have their advantages, allowing personalized selection based on the patient&#x2019;s needs. ABBA and UABA have shorter operative times, while UABA and ACA excel at controlling bleeding and shortening hospital stays. OA shows promise for lymph node assessment. These findings contribute to the growing evidence supporting endoscopic methods, expanding treatment options for thyroid cancer patients.</p>
</sec>
</abstract>
<kwd-group>
<kwd>network meta-analysis</kwd>
<kwd>endoscopic thyroidectomy</kwd>
<kwd>conventional open thyroidectomy</kwd>
<kwd>thyroid cancer</kwd>
<kwd>surgical approaches</kwd>
</kwd-group>
<counts>
<fig-count count="3"/>
<table-count count="3"/>
<equation-count count="0"/>
<ref-count count="58"/>
<page-count count="13"/>
<word-count count="5399"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-in-acceptance</meta-name>
<meta-value>Cancer Endocrinology</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>Thyroid cancer, the most common endocrine-related cancer, has been increasing rapidly in recent years and is particularly prevalent in young women (<xref ref-type="bibr" rid="B1">1</xref>). Conventional open thyroidectomy (COT) is the standard surgical treatment for thyroid cancer; however, the conspicuous scarring and the associated emotional burden pose significant challenges, especially for young female patients. Endoscopic thyroidectomies were first performed in 1997 (<xref ref-type="bibr" rid="B2">2</xref>). This minimally invasive surgery not only provides better cosmetic results, but also contribute to reduces surgical complications. The introduction of endoscopic thyroidectomy has attracted the interest of a wide range of surgeons. Over the past 20 years, lumpectomies have developed rapidly. The most common surgical approaches are the gasless unilateral transaxillary approach (GUA), bilateral axillo-breast approach (BABA), axillo-bilateral breast approach (ABBA), unilateral axillo-breast approach (UABA), chest-breast approach (CBA), anterior chest approach (ACA) and transoral approach (OA).</p>
<p>It is important to acknowledge that endoscopic surgeries are not uniformly &#x201c;minimally invasive&#x201d; and do not universally reduce invasiveness. While they offer advantages in terms of cosmesis and surgical complication reduction, these advantages may not be consistently realized in every case. Endoscopic surgeries, while typically associated with reduced scarring and fewer complications, can, in certain circumstances, present unique challenges. For example, the use of unconventional entry sites can increase the risk of injury to critical nerves, such as brachial plexus injury with the axillary approach (<xref ref-type="bibr" rid="B3">3</xref>), or central nerve palsy with the transoral approach can lead to central nerve palsy (<xref ref-type="bibr" rid="B4">4</xref>). In light of these nuances and the potential variability in outcomes, a comprehensive evaluation of the efficacy and safety of endoscopic thyroid surgery is imperative. Previous meta-analyses have often compared different surgical approaches solely with COT, leaving critical gaps in our understanding. To address these limitations and provide a more nuanced assessment, we employ network meta-analysis (NMA). This approach integrates a wealth of clinical experiences, allowing us to offer a more balanced perspective on the advantages and disadvantages of endoscopic thyroid surgery across various surgical techniques. Network meta-analysis can showcase direct and indirect comparison results (<xref ref-type="bibr" rid="B5">5</xref>). Through NMA, we aim to gain a more comprehensive understanding of when and how endoscopic procedures can truly be minimally invasive and when they might not offer significant advantages over conventional approaches.</p>
<p>In summary, this network meta-analysis seeks to provide a comprehensive evaluation of endoscopic thyroid surgery, considering the variable nature of &#x201c;minimally invasive&#x201d; outcomes. By doing so, we aim to offer a more detailed perspective on the true merits and limitations of endoscopic surgery in the treatment of thyroid cancer.</p>
</sec>
<sec id="s2">
<label>2</label>
<title>Methods</title>
<p>Our systematic review was designed based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PROSPERO) guidelines (<xref ref-type="bibr" rid="B6">6</xref>) and registered with PROSPERO (CRD42023430413). Ethical approval or registration was not required as this study involved an analysis of existing published data.</p>
<sec id="s2_1">
<label>2.1</label>
<title>Search strategy</title>
<p>The PubMed, Embase and Web of Science Core Collection (WoSCC) were searched up to March 28, 2023. The following keywords and comprehensive combinations thereof were included: (&#x201c;endoscopic&#x201d; OR &#x201c;endoscopic surgery&#x201d; OR &#x201c;endoscopic-surgery&#x201d;) AND (&#x201c;thyroid cancer&#x201d; OR &#x201c;thyroid carcinoma&#x201d;) AND (&#x201c;thyroidectomy&#x201d; OR &#x201c; thyroid surgery&#x201d;).</p>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Inclusion and exclusion criteria</title>
<p>The inclusion criteria were as follows: (1) Original English articles; (2) studies comparing endoscopic surgery with COT or different endoscopic surgical approaches; (3) studies reporting indicators such as surgical results or complications; and (4) studies in which the patients were diagnosed with thyroid cancer. The exclusion criteria were as follows: (1) letters, reviews, meeting abstracts, case reports, and editorials; (2) studies without control groups; and (3) studies that did not report original data.</p>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>Data extraction and quality assessment</title>
<p>Two researchers independently extracted the data. We documented study characteristics (the first author, publication year, surgery approach, country, study design, number of patients, age, extent of surgery and follow-up); surgical outcomes [operative time, intraoperative bleeding volume, hospital days, volume of drainage, duration of drainage, retrieved LNs, metastatic LNs, stimulated serum thyroglobulin (TG) levels and TG levels after postoperative radioactive iodine (RAI)], and surgical complications (transient hypocalcemia, permanent hypocalcemia, transient vocal cord palsy, permanent vocal cord palsy, transient hypoparathyroidism, permanent hypoparathyroidism, postoperative bleeding, chyle leakage, hematoma, seroma, recurrence and infection).</p>
<p>Two researchers independently evaluated the quality of the articles using the Newcastle-Ottawa Scale (NOS), and disagreements were settled through joint discussion. An article with an NOS score &#x2265; 6 was considered a high-quality study (<xref ref-type="bibr" rid="B7">7</xref>); the NOS scores of the articles we included were all &gt; 6.</p>
</sec>
<sec id="s2_4">
<label>2.4</label>
<title>Statistical analysis</title>
<p>Data analysis was conducted using Stata14.1 software (Stata Corporation, College Station, TX, USA). Continuous variables (operative time, intraoperative bleeding volume, hospital days, volume of drainage, duration of drainage, retrieved LNs, metastatic LNs, stimulated TG levels, and TG levels after postoperative RAI) were recorded as mean differences (MD) with 95% confidence intervals (CI). Odds risks (OR) with 95% CI were calculated for dichotomous variables (transient hypocalcemia, permanent hypocalcemia, transient vocal cord palsy, permanent vocal cord palsy, transient hypoparathyroidism, permanent hypoparathyroidism, postoperative bleeding, chyle leakage, hematoma, seroma, recurrence, and infection). The consistency of the network was verified using local and global inconsistency tests. We used the node-splitting method to detect local inconsistencies between direct and indirect evaluations; If P&lt; 0.05, local inconsistency was considered to exist. The surfaces under the cumulative ranking (SUCRA) curves and mean ranks were used to rank the eight surgical methods. The higher the SUCRA value, the higher the efficiency. We assessed potential publication bias by &#x201c;comparison-adjusted&#x201d; funnel plots.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<label>3</label>
<title>Results</title>
<sec id="s3_1">
<label>3.1</label>
<title>Study characteristics</title>
<p>A total of 44 articles, involving a total of 8672 patients, were included in the NMA (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>). Of these, 38 were retrospective studies and six were prospective studies. Details of the articles&#x2019; characteristics are listed in <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>. Fifteen studies compared CBA with COT, five compared BABA with COT, eight compared OA with COT, two compared OA with CBA, nine compared GUA with COT, two compared ACA with COT, and two compared UABA with COT or CBA.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Flowchart of article screening. WoSCC, Web of Science Core Collection.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-14-1256209-g001.tif"/>
</fig>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Characteristics of meta-analysis included studies.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Author
</th>
<th valign="top" align="left">Year
</th>
<th valign="top" align="left">Country
</th>
<th valign="top" align="left">Study design
</th>
<th valign="top" align="left">No. of patients
</th>
<th valign="top" align="left">Arm1
</th>
<th valign="top" align="left">Arm2
</th>
<th valign="top" align="left">N1
</th>
<th valign="top" align="left">N2
</th>
<th valign="top" align="left">F1
</th>
<th valign="top" align="left">F2
</th>
<th valign="top" align="left">Age1
</th>
<th valign="top" align="left">Age2
</th>
<th valign="top" align="left">Arm1 Extent of surgery
</th>
<th valign="top" align="left">Arm2 Extent of surgery
</th>
<th valign="top" align="left">Follow up
</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">
<bold>Jong-hyuk Ahn (</bold>
<xref ref-type="bibr" rid="B8">8</xref>)</td>
<td valign="top" align="right">2020</td>
<td valign="top" align="left">South Korea</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">275</td>
<td valign="top" align="left">OA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">150</td>
<td valign="top" align="right">125</td>
<td valign="top" align="left">145/150</td>
<td valign="top" align="left">89/125</td>
<td valign="top" align="left">43.06 &#xb1; 10.90</td>
<td valign="top" align="left">51.02 &#xb1; 12.42</td>
<td valign="top" align="left">Lob:110;TT:40</td>
<td valign="top" align="left">Lob:40;TT:85</td>
<td valign="top" align="left">median105(6-926)</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Bian Cong (</bold>
<xref ref-type="bibr" rid="B9">9</xref>)</td>
<td valign="top" align="right">2018</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">60</td>
<td valign="top" align="left">OA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">30</td>
<td valign="top" align="right">30</td>
<td valign="top" align="left">29/30</td>
<td valign="top" align="left">30/30</td>
<td valign="top" align="left">26.50 &#xb1; 6.94</td>
<td valign="top" align="left">27.75 &#xb1; 6.94</td>
<td valign="top" align="left">N</td>
<td valign="top" align="left">N</td>
<td valign="top" align="left">N</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Min Ji Cho (</bold>
<xref ref-type="bibr" rid="B10">10</xref>)</td>
<td valign="top" align="right">2015</td>
<td valign="top" align="left">South Korea</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">94</td>
<td valign="top" align="left">BABA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">49</td>
<td valign="top" align="right">45</td>
<td valign="top" align="left">47/49</td>
<td valign="top" align="left">36/45</td>
<td valign="top" align="left">39.39 &#xb1; 8.9</td>
<td valign="top" align="left">49.44 &#xb1; 12.3</td>
<td valign="top" align="left">Lob &#xb1; CND:16/21(76.2%);TT &#xb1; CND:33/73(45.2%)</td>
<td valign="top" align="left">Lob &#xb1; CND:5/21(23.8%);TT &#xb1; CND:40/74(54.8%)</td>
<td valign="top" align="left">1,447.73 &#xb1; 42.58</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Yoo Seung Chung (</bold>
<xref ref-type="bibr" rid="B11">11</xref>)</td>
<td valign="top" align="right">2007</td>
<td valign="top" align="left">South Korea</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">301</td>
<td valign="top" align="left">BABA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">103</td>
<td valign="top" align="right">198</td>
<td valign="top" align="left">102/103</td>
<td valign="top" align="left">173/198</td>
<td valign="top" align="left">38.2 &#xb1; 8.2</td>
<td valign="top" align="left">47.2 &#xb1; 10.2</td>
<td valign="top" align="left">Lob:7;subTT:8;TT:88</td>
<td valign="top" align="left">Lob:12;subTT:14;TT:172</td>
<td valign="top" align="left">N</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Hengyuan Gao (</bold>
<xref ref-type="bibr" rid="B12">12</xref>)</td>
<td valign="top" align="right">2019</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">102</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">53</td>
<td valign="top" align="right">49</td>
<td valign="top" align="left">43/53</td>
<td valign="top" align="left">23/49</td>
<td valign="top" align="left">39.5 &#xb1; 11.6</td>
<td valign="top" align="left">46.5 &#xb1; 13.6</td>
<td valign="top" align="left">N</td>
<td valign="top" align="left">N</td>
<td valign="top" align="left">N</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Gong Yi (</bold>
<xref ref-type="bibr" rid="B13">13</xref>)</td>
<td valign="top" align="right">2019</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">117</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">72</td>
<td valign="top" align="right">45</td>
<td valign="top" align="left">50/72</td>
<td valign="top" align="left">21/45</td>
<td valign="top" align="left">36.4 &#xb1; 12.7</td>
<td valign="top" align="left">36.2 &#xb1; 11.6</td>
<td valign="top" align="left">N</td>
<td valign="top" align="left">N</td>
<td valign="top" align="left">20.6 &#xb1; 5.3</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Fangdong Guo (</bold>
<xref ref-type="bibr" rid="B14">14</xref>)</td>
<td valign="top" align="right">2020</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">80</td>
<td valign="top" align="left">OA</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="right">40</td>
<td valign="top" align="right">40</td>
<td valign="top" align="left">40/40</td>
<td valign="top" align="left">40/40</td>
<td valign="top" align="left">29.8 &#xb1; 0.96</td>
<td valign="top" align="left">33.75 &#xb1; 1.19</td>
<td valign="top" align="left">N</td>
<td valign="top" align="left">N</td>
<td valign="top" align="left">N</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Youming Guo (</bold>
<xref ref-type="bibr" rid="B15">15</xref>)</td>
<td valign="top" align="right">2018</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">38</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">18</td>
<td valign="top" align="right">20</td>
<td valign="top" align="left">16/18</td>
<td valign="top" align="left">20/20</td>
<td valign="top" align="left">38.7 &#xb1; 11.8</td>
<td valign="top" align="left">43.0 &#xb1; 9.0</td>
<td valign="top" align="left">N</td>
<td valign="top" align="left">N</td>
<td valign="top" align="left">6 months</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Hyun Jun Hong (</bold>
<xref ref-type="bibr" rid="B16">16</xref>)</td>
<td valign="top" align="right">2011</td>
<td valign="top" align="left">South Korea</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">117</td>
<td valign="top" align="left">GUA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">57</td>
<td valign="top" align="right">60</td>
<td valign="top" align="left">51/57</td>
<td valign="top" align="left">49/60</td>
<td valign="top" align="left">39.6 &#xb1; 7.88</td>
<td valign="top" align="left">41.77 &#xb1; 9.61</td>
<td valign="top" align="left">HT</td>
<td valign="top" align="left">HT</td>
<td valign="top" align="left">N</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Nitish Gupta (</bold>
<xref ref-type="bibr" rid="B17">17</xref>)</td>
<td valign="top" align="right">2020</td>
<td valign="top" align="left">India</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">161</td>
<td valign="top" align="left">BABA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">40</td>
<td valign="top" align="right">121</td>
<td valign="top" align="left">37/40</td>
<td valign="top" align="left">108/60</td>
<td valign="top" align="left">38.69 &#xb1; 5.27</td>
<td valign="top" align="left">41.63 &#xb1; 6.20</td>
<td valign="top" align="left">TT;TT+CND</td>
<td valign="top" align="left">TT;TT+CND</td>
<td valign="top" align="left">&gt;6 months</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Jian kang Huang (</bold>
<xref ref-type="bibr" rid="B18">18</xref>)</td>
<td valign="top" align="right">2016</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">P</td>
<td valign="top" align="right">198</td>
<td valign="top" align="left">GUA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">75</td>
<td valign="top" align="right">123</td>
<td valign="top" align="left">59/75</td>
<td valign="top" align="left">92/123</td>
<td valign="top" align="left">37.8 &#xb1; 10.6</td>
<td valign="top" align="left">39.2 &#xb1; 11.3</td>
<td valign="top" align="left">N</td>
<td valign="top" align="left">N</td>
<td valign="top" align="left">52.4 &#xb1; 17.3</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Im Hyung-Jun (</bold>
<xref ref-type="bibr" rid="B19">19</xref>)</td>
<td valign="top" align="right">2012</td>
<td valign="top" align="left">South Korea</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">46</td>
<td valign="top" align="left">BABA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">25</td>
<td valign="top" align="right">21</td>
<td valign="top" align="left">25/25</td>
<td valign="top" align="left">17/21</td>
<td valign="top" align="left">40.8 &#xb1; 7.2</td>
<td valign="top" align="left">49.7 &#xb1; 6.9</td>
<td valign="top" align="left">N</td>
<td valign="top" align="left">N</td>
<td valign="top" align="left">N</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Jong Ju Jeong (</bold>
<xref ref-type="bibr" rid="B20">20</xref>)</td>
<td valign="top" align="right">2009</td>
<td valign="top" align="left">South Korea</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">449</td>
<td valign="top" align="left">GUA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">275</td>
<td valign="top" align="right">224</td>
<td valign="top" align="left">268/275</td>
<td valign="top" align="left">189/224</td>
<td valign="top" align="left">39.6 &#xb1; 8.8</td>
<td valign="top" align="left">49.5 &#xb1; 10.2</td>
<td valign="top" align="left">Lob:72;TT:203</td>
<td valign="top" align="left">Lob:9;TT:215</td>
<td valign="top" align="left">18.4(4-37)</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Eun Young Kim (</bold>
<xref ref-type="bibr" rid="B21">21</xref>)</td>
<td valign="top" align="right">2017</td>
<td valign="top" align="left">South Korea</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">738</td>
<td valign="top" align="left">GUA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">200</td>
<td valign="top" align="right">538</td>
<td valign="top" align="left">192/200</td>
<td valign="top" align="left">400/538</td>
<td valign="top" align="left">39.5 &#xb1; 0.8</td>
<td valign="top" align="left">48.9 &#xb1; 0.5</td>
<td valign="top" align="left">TT</td>
<td valign="top" align="left">TT</td>
<td valign="top" align="left">N</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Seon Kwang Kim (</bold>
<xref ref-type="bibr" rid="B22">22</xref>)</td>
<td valign="top" align="right">2015</td>
<td valign="top" align="left">South Korea</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">1003</td>
<td valign="top" align="left">ABBA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">173</td>
<td valign="top" align="right">830</td>
<td valign="top" align="left">160/173</td>
<td valign="top" align="left">734/173</td>
<td valign="top" align="left">37.95 &#xb1; 11.55</td>
<td valign="top" align="left">50.02 &#xb1; 19.34</td>
<td valign="top" align="left">Lob:116;subTT:1;TT:56</td>
<td valign="top" align="left">Lob:141;subTT:5;TT:684</td>
<td valign="top" align="left">69(52-77)</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Yoon Woo Koh (</bold>
<xref ref-type="bibr" rid="B23">23</xref>)</td>
<td valign="top" align="right">2009</td>
<td valign="top" align="left">South Korea</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">59</td>
<td valign="top" align="left">GUA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">29</td>
<td valign="top" align="right">30</td>
<td valign="top" align="left">26/29</td>
<td valign="top" align="left">24/30</td>
<td valign="top" align="left">36.5 &#xb1; 5.1</td>
<td valign="top" align="left">38.3 &#xb1; 4.5</td>
<td valign="top" align="left">HT+CND</td>
<td valign="top" align="left">HT+CND</td>
<td valign="top" align="left">minimun 18months</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Wan Wook Kim (</bold>
<xref ref-type="bibr" rid="B24">24</xref>)</td>
<td valign="top" align="right">2011</td>
<td valign="top" align="left">South Korea</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">228</td>
<td valign="top" align="left">BABA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">95</td>
<td valign="top" align="right">138</td>
<td valign="top" align="left">93/95</td>
<td valign="top" align="left">104/138</td>
<td valign="top" align="left">39.9 &#xb1; 9.1</td>
<td valign="top" align="left">51.8 &#xb1; 8.9</td>
<td valign="top" align="left">TT+CND</td>
<td valign="top" align="left">TT+CND</td>
<td valign="top" align="left">N</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Hayemin Lee (</bold>
<xref ref-type="bibr" rid="B25">25</xref>)</td>
<td valign="top" align="right">2012</td>
<td valign="top" align="left">South Korea</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">78</td>
<td valign="top" align="left">UABA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">37</td>
<td valign="top" align="right">41</td>
<td valign="top" align="left">37/37</td>
<td valign="top" align="left">38/41</td>
<td valign="top" align="left">42.3 &#xb1; 7.6</td>
<td valign="top" align="left">49.0 &#xb1; 10.8</td>
<td valign="top" align="left">Lob</td>
<td valign="top" align="left">Lob</td>
<td valign="top" align="right">54.3</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Hongqiang Li (</bold>
<xref ref-type="bibr" rid="B26">26</xref>)</td>
<td valign="top" align="right">2018</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">98</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">46</td>
<td valign="top" align="right">52</td>
<td valign="top" align="left">35/46</td>
<td valign="top" align="left">38/52</td>
<td valign="top" align="left">37.0 &#xb1; 10.0</td>
<td valign="top" align="left">37.5 &#xb1; 11.0</td>
<td valign="top" align="left">HT:16;TT:30</td>
<td valign="top" align="left">HT:21;TT:31</td>
<td valign="top" align="left">N</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Tingting Li (</bold>
<xref ref-type="bibr" rid="B27">27</xref>)</td>
<td valign="top" align="right">2022</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">P</td>
<td valign="top" align="right">172</td>
<td valign="top" align="left">GUA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">73</td>
<td valign="top" align="right">99</td>
<td valign="top" align="left">54/73</td>
<td valign="top" align="left">61/99</td>
<td valign="top" align="left">36.63 &#xb1; 7.48</td>
<td valign="top" align="left">38.91 &#xb1; 8.36</td>
<td valign="top" align="left">Lob+CND</td>
<td valign="top" align="left">Lob+CND</td>
<td valign="top" align="left">12months</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Peiliang Lin (</bold>
<xref ref-type="bibr" rid="B28">28</xref>)</td>
<td valign="top" align="right">2020</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">91</td>
<td valign="top" align="left">ACA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">31</td>
<td valign="top" align="right">60</td>
<td valign="top" align="left">20/31</td>
<td valign="top" align="left">33/60</td>
<td valign="top" align="left">34.5 &#xb1; 10.98</td>
<td valign="top" align="left">44.75 &#xb1; 15.88</td>
<td valign="top" align="left">TT;subTT</td>
<td valign="top" align="left">TT;subTT</td>
<td valign="top" align="left">48 (19-76)</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Zhaodi Liu (</bold>
<xref ref-type="bibr" rid="B29">29</xref>)</td>
<td valign="top" align="right">2020</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">135</td>
<td valign="top" align="left">OA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">59</td>
<td valign="top" align="right">76</td>
<td valign="top" align="left">49/59</td>
<td valign="top" align="left">47/76</td>
<td valign="top" align="left">30.4 &#xb1; 7.4</td>
<td valign="top" align="left">42.3 &#xb1; 8.6</td>
<td valign="top" align="left">Lob+CND:50;TT+CND:9</td>
<td valign="top" align="left">Lob+CND:30;TT+CND:46</td>
<td valign="top" align="left">32(15-36)</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Zhaodi Liu (</bold>
<xref ref-type="bibr" rid="B29">29</xref>)</td>
<td valign="top" align="right">2020</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">102</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">43</td>
<td valign="top" align="right">76</td>
<td valign="top" align="left">38/43</td>
<td valign="top" align="left">47/76</td>
<td valign="top" align="left">32.0 &#xb1; 7.9</td>
<td valign="top" align="left">42.3 &#xb1; 8.6</td>
<td valign="top" align="left">Lob+CND:30;TT+CND:13</td>
<td valign="top" align="left">Lob+CND:30;TT+CND:46</td>
<td valign="top" align="left">32(15-36)</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Zhaodi Liu (</bold>
<xref ref-type="bibr" rid="B30">30</xref>)</td>
<td valign="top" align="right">2021</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">156</td>
<td valign="top" align="left">OA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">78</td>
<td valign="top" align="right">78</td>
<td valign="top" align="left">63/78</td>
<td valign="top" align="left">61/78</td>
<td valign="top" align="left">29.25 &#xb1; 2.04</td>
<td valign="top" align="left">31 &#xb1; 3.48</td>
<td valign="top" align="left">HT:57;TT:21</td>
<td valign="top" align="left">HT:54;TT:24</td>
<td valign="top" align="left">25 (19-34)</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>KangNan Mo (</bold>
<xref ref-type="bibr" rid="B31">31</xref>)</td>
<td valign="top" align="right">2018</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">55</td>
<td valign="top" align="left">UABA</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="right">22</td>
<td valign="top" align="right">33</td>
<td valign="top" align="left">21/22</td>
<td valign="top" align="left">32/33</td>
<td valign="top" align="left">31.7 &#xb1; 8.7</td>
<td valign="top" align="left">33.1 &#xb1; 7.8</td>
<td valign="top" align="left">HT:20;TT:2</td>
<td valign="top" align="left">HT:26;TT:7</td>
<td valign="top" align="left">N</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Ki Nam Park (</bold>
<xref ref-type="bibr" rid="B32">32</xref>)</td>
<td valign="top" align="right">2015</td>
<td valign="top" align="left">South Korea</td>
<td valign="top" align="left">P</td>
<td valign="top" align="right">152</td>
<td valign="top" align="left">GUA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">50</td>
<td valign="top" align="right">102</td>
<td valign="top" align="left">46/50</td>
<td valign="top" align="left">88/102</td>
<td valign="top" align="left">38.0 &#xb1; 9.4</td>
<td valign="top" align="left">50.8 &#xb1; 11.5</td>
<td valign="top" align="left">TT</td>
<td valign="top" align="left">TT</td>
<td valign="top" align="left">1year</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Rui Qu (</bold>
<xref ref-type="bibr" rid="B33">33</xref>)</td>
<td valign="top" align="right">2018</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">76</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">40</td>
<td valign="top" align="right">36</td>
<td valign="top" align="left">31/40</td>
<td valign="top" align="left">22/36</td>
<td valign="top" align="left">36.7 &#xb1; 10.0</td>
<td valign="top" align="left">43.2 &#xb1; 14.3</td>
<td valign="top" align="left">TT &#xb1; CND</td>
<td valign="top" align="left">TT &#xb1; CND</td>
<td valign="top" align="left">N</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Yanqing Qu (</bold>
<xref ref-type="bibr" rid="B34">34</xref>)</td>
<td valign="top" align="right">2021</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">134</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">68</td>
<td valign="top" align="right">68</td>
<td valign="top" align="left">46/68</td>
<td valign="top" align="left">51/68</td>
<td valign="top" align="left">44.34 &#xb1; 9.82</td>
<td valign="top" align="left">45.56 &#xb1; 8.91</td>
<td valign="top" align="left">HT:37;TT:30</td>
<td valign="top" align="left">HT:34;TT:33</td>
<td valign="top" align="left">36.4 &#xb1; 6.3</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Xiaoting Ren (</bold>
<xref ref-type="bibr" rid="B35">35</xref>)</td>
<td valign="top" align="right">2017</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">55</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">20</td>
<td valign="top" align="right">35</td>
<td valign="top" align="left">20/20</td>
<td valign="top" align="left">35/35</td>
<td valign="top" align="left">36.05 &#xb1; 7.54</td>
<td valign="top" align="left">36.06 &#xb1; 5.65</td>
<td valign="top" align="left">Lob+CND</td>
<td valign="top" align="left">Lob+CND</td>
<td valign="top" align="left">N</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Luyi Si (</bold>
<xref ref-type="bibr" rid="B36">36</xref>)</td>
<td valign="top" align="right">2022</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">62</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">UABA</td>
<td valign="top" align="right">26</td>
<td valign="top" align="right">36</td>
<td valign="top" align="left">18/26</td>
<td valign="top" align="left">33/36</td>
<td valign="top" align="left">34.00 &#xb1; 8.19</td>
<td valign="top" align="left">35.69 &#xb1; 7.66</td>
<td valign="top" align="left">HT+CND</td>
<td valign="top" align="left">HT+CND</td>
<td valign="top" align="left">N</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Haiqing Sun (</bold>
<xref ref-type="bibr" rid="B4">4</xref>)</td>
<td valign="top" align="right">2022</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">P</td>
<td valign="top" align="right">92</td>
<td valign="top" align="left">OA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">28</td>
<td valign="top" align="right">56</td>
<td valign="top" align="left">27/28</td>
<td valign="top" align="left">54/56</td>
<td valign="top" align="left">36.57 &#xb1; 8.03</td>
<td valign="top" align="left">39.66 &#xb1; 8.67</td>
<td valign="top" align="left">TT+CND</td>
<td valign="top" align="left">TT+CND</td>
<td valign="top" align="left">16(3-54)</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Haiqing Sun (</bold>
<xref ref-type="bibr" rid="B37">37</xref>)</td>
<td valign="top" align="right">2020</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">389</td>
<td valign="top" align="left">OA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">100</td>
<td valign="top" align="right">289</td>
<td valign="top" align="left">86/100</td>
<td valign="top" align="left">165/289</td>
<td valign="top" align="left">29.65 &#xb1; 6.57</td>
<td valign="top" align="left">45.18 &#xb1; 11.47</td>
<td valign="top" align="left">HT+CND</td>
<td valign="top" align="left">HT+CND</td>
<td valign="top" align="left">9(4-21)</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Haiqing Sun (</bold>
<xref ref-type="bibr" rid="B37">37</xref>)</td>
<td valign="top" align="right">2020</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">408</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">119</td>
<td valign="top" align="right">289</td>
<td valign="top" align="left">103/119</td>
<td valign="top" align="left">165/289</td>
<td valign="top" align="left">34.59 &#xb1; 7.69</td>
<td valign="top" align="left">45.18 &#xb1; 11.47</td>
<td valign="top" align="left">HT+CND</td>
<td valign="top" align="left">HT+CND</td>
<td valign="top" align="left">9(4-21)</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Peng Sun (</bold>
<xref ref-type="bibr" rid="B38">38</xref>)</td>
<td valign="top" align="right">2022</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">590</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">323</td>
<td valign="top" align="right">267</td>
<td valign="top" align="left">248/323</td>
<td valign="top" align="left">207/267</td>
<td valign="top" align="left">36.5 &#xb1; 10.7</td>
<td valign="top" align="left">45.6 &#xb1; 11.7</td>
<td valign="top" align="left">Lob+CND:172;TT+CND:151</td>
<td valign="top" align="left">Lob+CND:147;TT+CND:120</td>
<td valign="top" align="left">48.5 &#xb1; 14.4</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Kyung Tae (</bold>
<xref ref-type="bibr" rid="B39">39</xref>)</td>
<td valign="top" align="right">2011</td>
<td valign="top" align="left">South Korea</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">67</td>
<td valign="top" align="left">GUA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">31</td>
<td valign="top" align="right">36</td>
<td valign="top" align="left">30/31</td>
<td valign="top" align="left">25/36</td>
<td valign="top" align="left">36.2 &#xb1; 9.9</td>
<td valign="top" align="left">44.6 &#xb1; 11.8</td>
<td valign="top" align="left">HT:28;TT:3</td>
<td valign="top" align="left">HT:36</td>
<td valign="top" align="left">36 &#xb1; 13</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Zhuo Tan (</bold>
<xref ref-type="bibr" rid="B40">40</xref>)</td>
<td valign="top" align="right">2015</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">64</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">34</td>
<td valign="top" align="right">30</td>
<td valign="top" align="left">32/34</td>
<td valign="top" align="left">26/30</td>
<td valign="top" align="left">30 &#xb1; 8.09</td>
<td valign="top" align="left">46.75 &#xb1; 14.73</td>
<td valign="top" align="left">HT+CND</td>
<td valign="top" align="left">HT+CND</td>
<td valign="top" align="left">N</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Denghuan Wang (</bold>
<xref ref-type="bibr" rid="B41">41</xref>)</td>
<td valign="top" align="right">2022</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">P</td>
<td valign="top" align="right">40</td>
<td valign="top" align="left">OA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">20</td>
<td valign="top" align="right">20</td>
<td valign="top" align="left">14/20</td>
<td valign="top" align="left">14/20</td>
<td valign="top" align="left">33.2 &#xb1; 18.9</td>
<td valign="top" align="left">32.8 &#xb1; 19.1</td>
<td valign="top" align="left">HT+CND</td>
<td valign="top" align="left">HT+CND</td>
<td valign="top" align="left">N</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Tiantian Wang (</bold>
<xref ref-type="bibr" rid="B42">42</xref>)</td>
<td valign="top" align="right">2020</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">P</td>
<td valign="top" align="right">160</td>
<td valign="top" align="left">OA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">80</td>
<td valign="top" align="right">80</td>
<td valign="top" align="left">80/80</td>
<td valign="top" align="left">80/80</td>
<td valign="top" align="left">31.48 &#xb1; 6.60</td>
<td valign="top" align="left">32.59 &#xb1; 5.18</td>
<td valign="top" align="left">N</td>
<td valign="top" align="left">N</td>
<td valign="top" align="left">22(12-33)</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Dapeng Xiang (</bold>
<xref ref-type="bibr" rid="B43">43</xref>)</td>
<td valign="top" align="right">2020</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">96</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">49</td>
<td valign="top" align="right">47</td>
<td valign="top" align="left">49/49</td>
<td valign="top" align="left">41/47</td>
<td valign="top" align="left">34.2 &#xb1; 7</td>
<td valign="top" align="left">46.9 &#xb1; 13.3</td>
<td valign="top" align="left">TT &#xb1; CNDTT+CND:43;TT+CND+CND:6</td>
<td valign="top" align="left">TT+CND:30;TT+CND:17</td>
<td valign="top" align="left">N</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Yang Yu (</bold>
<xref ref-type="bibr" rid="B44">44</xref>)</td>
<td valign="top" align="right">2020</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">197</td>
<td valign="top" align="left">ACA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">85</td>
<td valign="top" align="right">112</td>
<td valign="top" align="left">72/85</td>
<td valign="top" align="left">74/112</td>
<td valign="top" align="left">38.15 &#xb1; 11.72</td>
<td valign="top" align="left">47.79 &#xb1; 10.51</td>
<td valign="top" align="left">HT:47;TT:38</td>
<td valign="top" align="left">HT:63;TT:49</td>
<td valign="top" align="left">N</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Yuquan Yuan (</bold>
<xref ref-type="bibr" rid="B45">45</xref>)</td>
<td valign="top" align="right">2022</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">136</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">63</td>
<td valign="top" align="right">73</td>
<td valign="top" align="left">N</td>
<td valign="top" align="left">N</td>
<td valign="top" align="left">32.51 &#xb1; 6.03</td>
<td valign="top" align="left">36.00 &#xb1; 8.01</td>
<td valign="top" align="left">HT+CND</td>
<td valign="top" align="left">HT+CND</td>
<td valign="top" align="left">N</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Daqi Zhang (</bold>
<xref ref-type="bibr" rid="B46">46</xref>)</td>
<td valign="top" align="right">2019</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">400</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">200</td>
<td valign="top" align="right">200</td>
<td valign="top" align="left">183/200</td>
<td valign="top" align="left">170/200</td>
<td valign="top" align="left">31.46 &#xb1; 7.75</td>
<td valign="top" align="left">37.28 &#xb1; 6.22</td>
<td valign="top" align="left">HT+CND;TT+CND</td>
<td valign="top" align="left">HT+CND;TT+CND</td>
<td valign="top" align="left">54 &#xb1; 3.4</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Weidong Zhang (</bold>
<xref ref-type="bibr" rid="B47">47</xref>)</td>
<td valign="top" align="right">2021</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">95</td>
<td valign="top" align="left">OA</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="right">45</td>
<td valign="top" align="right">50</td>
<td valign="top" align="left">36/45</td>
<td valign="top" align="left">50/50</td>
<td valign="top" align="left">33.44 &#xb1; 6.87</td>
<td valign="top" align="left">34.44 &#xb1; 7.65</td>
<td valign="top" align="left">HT+CND</td>
<td valign="top" align="left">HT+CND</td>
<td valign="top" align="left">N</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Xing Zhang (</bold>
<xref ref-type="bibr" rid="B48">48</xref>)</td>
<td valign="top" align="right">2023</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">545</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">GUA</td>
<td valign="top" align="right">263</td>
<td valign="top" align="right">282</td>
<td valign="top" align="left">233/263</td>
<td valign="top" align="left">262/282</td>
<td valign="top" align="left">42.2 &#xb1; 9.1</td>
<td valign="top" align="left">40.9 &#xb1; 7.7</td>
<td valign="top" align="left">HT+CND</td>
<td valign="top" align="left">HT+CND</td>
<td valign="top" align="left">21.2 &#xb1; 19.0</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Chuanming Zheng (</bold>
<xref ref-type="bibr" rid="B49">49</xref>)</td>
<td valign="top" align="right">2018</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">22</td>
<td valign="top" align="left">GUA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">11</td>
<td valign="top" align="right">11</td>
<td valign="top" align="left">10/11</td>
<td valign="top" align="left">10/11</td>
<td valign="top" align="left">35.6 &#xb1; 2.6</td>
<td valign="top" align="left">48.5 &#xb1; 2.3</td>
<td valign="top" align="left">HT+CND</td>
<td valign="top" align="left">HT+CND</td>
<td valign="top" align="left">N</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Qunzai Zhao (</bold>
<xref ref-type="bibr" rid="B50">50</xref>)</td>
<td valign="top" align="right">2018</td>
<td valign="top" align="left">China</td>
<td valign="top" align="left">R</td>
<td valign="top" align="right">306</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">COT</td>
<td valign="top" align="right">48</td>
<td valign="top" align="right">258</td>
<td valign="top" align="left">46/48</td>
<td valign="top" align="left">182/258</td>
<td valign="top" align="left">36.5 &#xb1; 8.5</td>
<td valign="top" align="left">47.1 &#xb1; 12.6</td>
<td valign="top" align="left">TT+CND</td>
<td valign="top" align="left">TT+CND</td>
<td valign="top" align="left">40.8 &#xb1; 4.7</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>TT, Total thyroidectomy; HT, hemithyroidectomy; subTT, subtotal thyroidectomy; Lob, lobectomy; CND, central neck lymph node dissection; GUA, gasless unilateral transaxillary approach; BABA=bilateral axillo-breast approach; ABBA, axillo-bilateral breast approach; UABA, unilateral axillo-breast approach; CBA, chest-breast approach; ACA, anterior chest approach; OA, transoral approach; COT, conventional open thyroidectomy.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>Surgical outcomes</title>
<sec id="s3_2_1">
<label>3.2.1</label>
<title>Operative time (minute)</title>
<p>Operative time was reported in 41 studies. A total of 8301 patients and eight surgical methods were included. The network relationships for different surgical modalities are shown in <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2A</bold>
</xref>. The global inconsistency test was not significant (p= 0.7353), and a comparison of the estimated operative time of different surgical methods using NMA is shown in the <xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>. There was no significant difference (p&gt;0.05) in operative time between the direct and indirect evaluations of the node-splitting models of local consistency. The shortest operative times were for the COT (95.6%), ABBA (71.5%), and UABA (61.4%), according to the SUCRA score.</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Network map of eligible comparisons for operative time <bold>(A)</bold>; intraoperative bleeding volume <bold>(B)</bold>; hospital days <bold>(C)</bold>; volume of drainage <bold>(D)</bold>; duration of drainage <bold>(E)</bold>; retrieved LNs <bold>(F)</bold>; metastatic LNs <bold>(G)</bold>.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-14-1256209-g002.tif"/>
</fig>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Network estimates of surgery comparisons for operative time and intraoperative bleeding volume.</p>
</caption>
<table frame="hsides">
<tbody>
<tr>
<td valign="middle" align="left">COT</td>
<td valign="middle" align="center">-</td>
<td valign="middle" align="left">-3.37 (-22.58,15.85)</td>
<td valign="middle" align="left">-13.77 (-28.85,1.31)</td>
<td valign="middle" align="center">-</td>
<td valign="middle" align="left">-0.07 (-5.13,4.99)</td>
<td valign="middle" align="left">0.74 (-8.56,10.04)</td>
<td valign="middle" align="left">3.14 (-4.08,10.35)</td>
</tr>
<tr>
<td valign="middle" align="left" style="background-color:#e7e6e6">-19.66 (-70.98,31.66)</td>
<td valign="middle" align="left">ABBA</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="middle" align="left" style="background-color:#e7e6e6">-30.32 (-62.09,1.45)</td>
<td valign="middle" align="left" style="background-color:#e7e6e6">-10.66 (-71.02,49.70)</td>
<td valign="middle" align="left">UABA</td>
<td valign="middle" align="left">-10.40 (-34.92,14.11)</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" align="left">3.30 (-15.24,21.84)</td>
<td valign="middle" align="left">4.11 (-16.91,25.13)</td>
<td valign="middle" align="left">6.50 (-13.63,26.64)</td>
</tr>
<tr>
<td valign="middle" align="left" style="background-color:#e7e6e6">-33.25 (-69.87,3.38)</td>
<td valign="middle" align="left" style="background-color:#e7e6e6">-13.59 (-76.63,49.46)</td>
<td valign="middle" align="left" style="background-color:#e7e6e6">-2.92 (-51.41,45.56)</td>
<td valign="middle" align="left">ACA</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" align="left">13.70 (-2.34,29.74)</td>
<td valign="middle" align="left">14.51 (-3.29,32.31)</td>
<td valign="middle" align="left">16.91 (0.05,33.77)</td>
</tr>
<tr>
<td valign="middle" align="left" style="background-color:#e7e6e6">-38.02 (-68.29,-7.75)</td>
<td valign="middle" align="left" style="background-color:#e7e6e6">-18.36 (-77.94,41.23)</td>
<td valign="middle" align="left" style="background-color:#e7e6e6">-7.70 (-51.58,36.18)</td>
<td valign="middle" align="left" style="background-color:#e7e6e6">-4.77 (-52.29,42.74)</td>
<td valign="middle" align="left">BABA</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="middle" align="left" style="background-color:#e7e6e6">-49.61 (-62.30,-36.92)</td>
<td valign="middle" align="left" style="background-color:#e7e6e6">-29.95 (-82.82,22.92)</td>
<td valign="middle" align="left" style="background-color:#e7e6e6">-19.29 (-50.24,11.66)</td>
<td valign="middle" align="left" style="background-color:#e7e6e6">-16.36 (-55.13,22.40)</td>
<td valign="middle" align="left" style="background-color:#e7e6e6">-11.59 (-44.42,21.24)</td>
<td valign="middle" align="left">CBA</td>
<td valign="middle" align="left">0.81 (-9.11,10.72)</td>
<td valign="middle" align="left">3.20 (-4.66,11.07)</td>
</tr>
<tr>
<td valign="middle" align="left" style="background-color:#e7e6e6">-50.60 (-67.21,-33.99)</td>
<td valign="middle" align="left" style="background-color:#e7e6e6">-30.94 (-84.88,23.00)</td>
<td valign="middle" align="left" style="background-color:#e7e6e6">-20.28 (-55.81,15.26)</td>
<td valign="middle" align="left" style="background-color:#e7e6e6">-17.35 (-57.57,22.86)</td>
<td valign="middle" align="left" style="background-color:#e7e6e6">-12.58 (-47.11,21.95)</td>
<td valign="middle" align="left" style="background-color:#e7e6e6">-0.99 (-21.07,19.09)</td>
<td valign="middle" align="left">GUA</td>
<td valign="middle" align="left">2.40 (-9.18,13.97)</td>
</tr>
<tr>
<td valign="middle" align="left" style="background-color:#e7e6e6">-77.18 (-93.81,-60.54)</td>
<td valign="middle" align="left" style="background-color:#e7e6e6">-57.52 (-111.46,-3.57)</td>
<td valign="middle" align="left" style="background-color:#e7e6e6">-46.85 (-82.10,-11.61)</td>
<td valign="middle" align="left" style="background-color:#e7e6e6">-43.93 (-84.15,-3.71)</td>
<td valign="middle" align="left" style="background-color:#e7e6e6">-39.16 (-73.70,-4.62)</td>
<td valign="middle" align="left" style="background-color:#e7e6e6">-27.57 (-46.84,-8.29)</td>
<td valign="middle" align="left" style="background-color:#e7e6e6">-26.58 (-49.93,-3.23)</td>
<td valign="middle" align="left">OA</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>
<inline-graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-14-1256209-i001.tif"/> operative time <inline-graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-14-1256209-i002.tif"/> intraoperative bleeding volume.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_2_2">
<label>3.2.2</label>
<title>Intraoperative bleeding (mL)</title>
<p>Twenty-five studies, involving a total of 4440 patients and six surgical methods, reported intraoperative bleeding volume. The network relationships between the different surgical methods are shown in <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2B</bold>
</xref>. The global inconsistency test was not significant (p=0.6823), and the comparison of the NMA estimation of intraoperative bleeding volume between the different surgical methods is shown in <xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>. There was no significant difference (p&gt;0.05) between the direct and indirect evaluations of the node-splitting models of local consistency for intraoperative bleeding volume. The surgical methods with the least amount of intraoperative bleeding were ACA (92.4%), UABA (57.1%), and COT (45.5%) according to the SUCRA score.</p>
</sec>
<sec id="s3_2_3">
<label>3.2.3</label>
<title>Hospital days (days)</title>
<p>Hospital days were reported in 34 studies, involving a total of 7682 patients and a comparison of eight surgical methods. The network relationships between the different surgical methods are shown in <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2C</bold>
</xref>. The global inconsistency test was not significant (p=0.6894), and the comparison of hospital days estimated by the NMA for the different surgical methods is shown in <xref ref-type="supplementary-material" rid="SM1">
<bold>Table S1</bold>
</xref>(Supplementary). No significant difference (p&gt;0.05) was observed between the direct and indirect evaluations of the node-splitting models of local consistency for hospital days. The surgical procedures with the shortest hospital days were UABA (72.8%), ACA (66%), and COT (52.5%), according to the SUCRA score.</p>
</sec>
<sec id="s3_2_4">
<label>3.2.4</label>
<title>Drainage situation</title>
<p>Twenty studies, involving a total of 3281 patients and the comparison of six surgical methods, recorded the volume of drainage. The network relationships between the different surgical methods are shown in <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2D</bold>
</xref>. The global inconsistency test was not significant (p=0.2120). A comparison of the NMA estimation for different surgical methods is shown in <xref ref-type="supplementary-material" rid="SM1">
<bold>Table S2</bold>
</xref> (Supplementary). There was no significant difference (p&gt;0.05) between the direct and indirect evaluations of the node-splitting models of local consistency for volume of drainage. The surgical methods with the lowest volume of drainage were COT (92.1%), UABA (65.7%), and BABA (61.1%), according to the SUCRA score. Fourteen studies, involving a total of 2238 patients and the comparison of six surgical methods, recorded the duration of drainage. The network relationships between the different surgical methods are shown in <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2E</bold>
</xref>. The global inconsistency test was not significant (p=0.8308). A comparison of the duration of drainage estimated by NMA for different surgical methods is shown in <xref ref-type="supplementary-material" rid="SM1">
<bold>Table S3</bold>
</xref>. There was no significant difference (p&gt;0.05) between the direct and indirect evaluations of the node-splitting models of local consistency for duration of drainage. The shortest surgical procedures for the duration of drainage were COT (76.9%), UABA (68.2%), and OA (50.2%), according to the SUCRA score.</p>
</sec>
<sec id="s3_2_5">
<label>3.2.5</label>
<title>Lymph node situation</title>
<p>The number of retrieved LNs was reported in 33 studies, involving a total of 6569 patients and eight surgical methods. The network relationship between the number of retrieved LNs and the different surgical methods is shown in <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2F</bold>
</xref>. The global inconsistency test was not significant (p=0.2835), and a comparison of the number of lymph node recoveries estimated by the NMA for different surgical methods is shown in <xref ref-type="supplementary-material" rid="SM1">
<bold>Table S4</bold>
</xref>(Supplementary). There was no significant difference (p&gt;0.05) between the direct and indirect evaluations of the node-splitting models of local consistency for the number of retrieved LNs. The surgical methods with the highest number of retrieved LNs were ACA (81.4%), COT (72.7%), and OA (71.6%) according to the SUCRA grade. Seventeen studies discussed the number of metastatic LNs, involving a total of 3453 patients and comparing five surgical methods. The network relationship between the number of metastatic LNs and different surgical methods is shown in <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2G</bold>
</xref>. The global inconsistency test was not significant (p=0.3129), and a comparison of the number of metastatic LNs estimated by NMA for different surgical methods is shown in <xref ref-type="supplementary-material" rid="SM1">
<bold>Table S5</bold>
</xref> (Supplementary). There was no significant difference (p&gt;0.05) between the direct and indirect evaluations of the node-splitting models of local consistency for the number of metastatic LNs. The surgical methods with the highest number of metastatic LNs were OA (63.3%), BABA (61.4%), and COT (54.9%), according to the SUCRA grade.</p>
</sec>
</sec>
<sec id="s3_3">
<label>3.3</label>
<title>Stimulated TG levels and TG levels after RAI</title>
<p>In our meta-analysis, we found that stimulated TG levels were not significantly different between BABA (MD=0.04 ng/ml,[-0.41,0.49], <italic>p</italic> =0.86), OA (MD=-0.46 ng/ml,[-1.39,0.48],<italic>p</italic> =0.34), and COT groups. However, it was significantly lower in the CBA group (MD=-0.40 ng/ml,[-0.72,-0.09];<italic>p</italic> =0.01) than in the COT group (<xref ref-type="supplementary-material" rid="SM1">
<bold>Figure S1</bold>
</xref> in Supplementary). There was no significant difference in TG levels after RAI treatment between the CBA (MD=-0.13[-0.31,0.06],<italic>p</italic> =0.18)and COT groups (<xref ref-type="supplementary-material" rid="SM1">
<bold>Figure S2</bold>
</xref> in Supplementary).</p>
</sec>
<sec id="s3_4">
<label>3.4</label>
<title>Postoperative pain</title>
<p>Five studies reported postoperative pain using the visual analog scale (VAS); detailed information is shown in the <xref ref-type="supplementary-material" rid="SM1">
<bold>Figure S3</bold>
</xref> (Supplementary). Our meta-analysis showed that CBA was not significantly lower than COT in terms of postoperative pain (MD=-0.66[-1.39,0.07], <italic>p</italic> =0.08).</p>
</sec>
<sec id="s3_5">
<label>3.5</label>
<title>Cosmetic satisfaction</title>
<p>There have been reports of postoperative cosmetic satisfaction with the common measurement method, detailed information was shown in <xref ref-type="supplementary-material" rid="SM1">
<bold>Figure S4</bold>
</xref> (Supplementary). Our meta-analysis showed that GUA was significantly better than COT in terms of cosmetic satisfaction (MD=-2.08[-3.35,-0.82], <italic>p</italic> =0.001).</p>
</sec>
<sec id="s3_6">
<label>3.6</label>
<title>Surgical complications</title>
<p>We compared the incidence of bleeding, transient or permanent hypoparathyroidism, transient or permanent vocal cord palsy, transient or permanent hypocalcemia, chyle leak, infection, seroma, hematoma, and recurrence between the endoscopic and COT groups. Our results suggested no significant difference in the incidence of surgical complications between the two groups (<xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>).</p>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Comparison of endoscopic thyroidectomy and COT for surgical complications.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Complication
</th>
<th valign="top" align="left">Surgery
</th>
<th valign="top" align="left">Model Selected
</th>
<th valign="top" align="left">OR (95% CI)
</th>
<th valign="top" align="left"><italic>P</italic>
</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>Bleeding</bold>
</td>
<td valign="top" align="left">BABA</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="left">1.76(0.45,6.85)</td>
<td valign="top" align="right">0.42</td>
</tr>
<tr>
<td valign="top" align="left">GUA</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="left">1.91(0.51,7.20)</td>
<td valign="top" align="right">0.34</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>transient hypoparathyroidism</bold>
</td>
<td valign="top" align="left">OA</td>
<td valign="top" align="left">Random</td>
<td valign="top" align="left">0.55(0.25,1.25)</td>
<td valign="top" align="right">0.16</td>
</tr>
<tr>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">Random</td>
<td valign="top" align="left">2.34(0.74,7.37)</td>
<td valign="top" align="right">0.15</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>permanent hypoparathyroidism</bold>
</td>
<td valign="top" align="left">OA</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="left">0.35 (0.07,1.91)</td>
<td valign="top" align="right">0.23</td>
</tr>
<tr>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="left">1.45(0.55,3.78)</td>
<td valign="top" align="right">0.45</td>
</tr>
<tr>
<td valign="top" rowspan="4" align="left">
<bold>transient vocal cord palsy</bold>
</td>
<td valign="top" align="left">OA</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="left">0.55(0.29,1.04)</td>
<td valign="top" align="right">0.07</td>
</tr>
<tr>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="left">0.90(0.53,1.53)</td>
<td valign="top" align="right">0.69</td>
</tr>
<tr>
<td valign="top" align="left">GUA</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="left">1.50(0.97,2.32)</td>
<td valign="top" align="right">0.07</td>
</tr>
<tr>
<td valign="top" align="left">BABA</td>
<td valign="top" align="left">Random</td>
<td valign="top" align="left">2.99(0.97,9.19)</td>
<td valign="top" align="right">0.06</td>
</tr>
<tr>
<td valign="top" rowspan="3" align="left">
<bold>permanent vocal cord palsy</bold>
</td>
<td valign="top" align="left">OA</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="left">1.76(0.16,18.95)</td>
<td valign="top" align="right">0.64</td>
</tr>
<tr>
<td valign="top" align="left">GUA</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="left">1.30(0.39,4.32)</td>
<td valign="top" align="right">0.67</td>
</tr>
<tr>
<td valign="top" align="left">BABA</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="left">5.33(0.53,56.79)</td>
<td valign="top" align="right">0.16</td>
</tr>
<tr>
<td valign="top" rowspan="3" align="left">
<bold>transient hypocalcemia</bold>
</td>
<td valign="top" align="left">BABA</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="left">1.13(0.79,1.62)</td>
<td valign="top" align="right">0.51</td>
</tr>
<tr>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="left">0.52(0.27,1.01)</td>
<td valign="top" align="right">0.05</td>
</tr>
<tr>
<td valign="top" align="left">GUA</td>
<td valign="top" align="left">Random</td>
<td valign="top" align="left">1.20(0.42,3.47)</td>
<td valign="top" align="right">0.74</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>permanent hypocalcemia</bold>
</td>
<td valign="top" align="left">BABA</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="left">0.41(0.14,1.26)</td>
<td valign="top" align="right">0.12</td>
</tr>
<tr>
<td valign="top" align="left">GUA</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="left">0.51(0.15,1.76)</td>
<td valign="top" align="right">0.29</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>chyle leak</bold>
</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="left">0.26(0.06,1.14)</td>
<td valign="top" align="right">0.07</td>
</tr>
<tr>
<td valign="top" align="left">OA</td>
<td valign="top" align="left">Random</td>
<td valign="top" align="left">1.12(0.07,19.39)</td>
<td valign="top" align="right">0.94</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>Infection</bold>
</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="left">0.43(0.08,2.38)</td>
<td valign="top" align="right">0.34</td>
</tr>
<tr>
<td valign="top" align="left">OA</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="left">1.55(0.22,10.88)</td>
<td valign="top" align="right">0.66</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>Seroma</bold>
</td>
<td valign="top" align="left">GUA</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="left">1.98(0.99,3.96)</td>
<td valign="top" align="right">0.05</td>
</tr>
<tr>
<td valign="top" align="left">BABA</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="left">1.08(0.21,5.56)</td>
<td valign="top" align="right">0.93</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>Hematoma</bold>
</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="left">1.13(0.24,5.29)</td>
<td valign="top" align="right">0.88</td>
</tr>
<tr>
<td valign="top" align="left">GUA</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="left">0.65(0.11,3.93)</td>
<td valign="top" align="right">0.64</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>Recurrence</bold>
</td>
<td valign="top" align="left">CBA</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="left">1.74(0.40,7.48)</td>
<td valign="top" align="right">0.46</td>
</tr>
<tr>
<td valign="top" align="left">GUA</td>
<td valign="top" align="left">Fixed</td>
<td valign="top" align="left">0.25(0.03,2.08)</td>
<td valign="top" align="right">0.2</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s3_7">
<label>3.7</label>
<title>Ranking</title>
<p>Our NMA ranked various surgical methods for operative time, intraoperative bleeding volume, hospital days, volume of drainage, duration of drainage, retrieved LNs and metastatic LNs (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>).</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Surgery ranking curves for operative time <bold>(A)</bold>; intraoperative bleeding volume <bold>(B)</bold>; hospital days <bold>(C)</bold>; volume of drainage <bold>(D)</bold>; duration of drainage <bold>(E)</bold>; retrieved LNs <bold>(F)</bold>; metastatic LNs <bold>(G)</bold>.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-14-1256209-g003.tif"/>
</fig>
</sec>
<sec id="s3_8">
<label>3.8</label>
<title>Publication bias</title>
<p>The comparison-adjusted funnel plots of this meta-analysis clearly showed that the included studies were symmetrical, indicating a relatively low publication bias in terms of operative time, intraoperative bleeding volume, hospital days, volume of drainage, duration of drainage, retrieved LNs, metastatic LNs. Detailed information is provided in the <xref ref-type="supplementary-material" rid="SM1">
<bold>Figure S5</bold>
</xref> (Supplementary).</p>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<label>4</label>
<title>Discussion</title>
<p>This meta-analysis found that endoscopic surgery not only has a lower incidence of complications than COT but may even be superior to COT in terms of operative bleeding volume, hospital days, and retrieved LNs. Previous meta-analyses have explored the efficacy of endoscopic thyroidectomy for thyroid neoplasms, but only compared different endoscopic surgeries or conventional surgeries (<xref ref-type="bibr" rid="B51">51</xref>, <xref ref-type="bibr" rid="B52">52</xref>). Our study adopted an NMA approach to comprehensively and meticulously discuss the advantages of seven surgical approaches. Among the various surgical approaches, ABBA stands out for its notably shorter operative time and proximity to COT. ACA excels in effectively controlling intraoperative bleeding. UABA demonstrates superior outcomes in terms of hospital stay and drainage, while OA prove to be more conducive to straightforward lymph node acquisition. The patients included in the study were all patients with thyroid cancer, and studies only focused on different endoscopic surgeries, which greatly reduced research heterogeneity and made our results more reliable.</p>
<p>COT required the least operative time, which is consistent with previous research results (<xref ref-type="bibr" rid="B15">15</xref>, <xref ref-type="bibr" rid="B16">16</xref>, <xref ref-type="bibr" rid="B22">22</xref>). This may be because of the need for additional surgical channels and workspaces for endoscopic surgery. For endoscopic surgery, the ABBA and UABA require shorter operative times. It needs to be emphasized that OA serves as the &#x201c;shortest surgical pathway&#x201d; for endoscopic surgery, but the results show that it has the longest operative time. The main reason for this phenomenon may be: 1) To improve safety and feasibility, OA usually involves three oral vestibular incisions (<xref ref-type="bibr" rid="B53">53</xref>), and during the surgical process, the three trocars often encounter unavoidable collisions in the limited workspace, subsequently increasing the difficulty of the surgery; 2) OA is a top-down operation. Owing to the presence of the thyroid cartilage, treatment of the superior thyroid requires more time than other methods. Many of the operation time data included in this study did not specify whether it was a total thyroidectomy or lobectomy, and roughly categorizing them into the same category would, to some extent, have affected our conclusion. ACA and UABA show obvious advantages in terms of intraoperative bleeding volume and hospital stay, while OA and GUA often have poor control of intraoperative bleeding volume due to the need for more extensive free platysma muscle to create surgical space. In the transaxillary approach, the UABA is relatively better than the GUA in bleeding control; however, because it does not require CO<sub>2</sub> insufflation, it avoids the occurrence of mediastinal emphysema, subcutaneous emphysema, and other related gas complications.</p>
<p>Thyroid cancer has a high rate of central lymph node metastasis (<xref ref-type="bibr" rid="B54">54</xref>), which is associated with high patient mortality (<xref ref-type="bibr" rid="B55">55</xref>). This study reveals that ACA outperforms COT in terms of retrieving LNs; however, it&#x2019;s important to note that the limited inclusion of only two articles involving ACA may introduce potential bias into the interpretation of this result. OA exhibits superior results in the retrieval of both total LNs and metastatic LNs compared to other endoscopic procedures. This can be attributed to the fact that, from top to bottom, the field of view in OA can seamlessly encompass the central region, thereby circumventing sternum and clavicle limitations, which uniquely facilitates the removal of central LNs.</p>
<p>TG is an important indicator for the postoperative follow-up of thyroid cancer, and lower stimulated TG levels are considered to be associated with total thyroidectomy and low recurrence rate (<xref ref-type="bibr" rid="B56">56</xref>). We found no difference between the endoscopic surgery and COT groups for TG, with CBA being significantly lower than COT. Regarding postoperative pain, CBA was not significantly better than COT. The reasons for this may be as follows: (1) fewer articles were included and (2) inconsistent measurement time points after surgery. We found that many studies used different methods to measure postoperative pain, which made it difficult to merge the results of the studies. However, this meta-analysis included studies that used VAS scores. It is well known that endoscopic thyroid surgery avoids scarring on the neck, and our results fully demonstrate this advantage. However, we also encountered a difficulty, there is no common scoring criterion for objective evaluation, and it is necessary for us to find a more objective standard in future research. The incidence of postoperative complications was not lower in the endoscopic surgery group than that in the COT group. Each surgical approach has its own drawbacks; for example, OA is prone to incision infection (<xref ref-type="bibr" rid="B8">8</xref>), CBA causes subcutaneous effusion (<xref ref-type="bibr" rid="B57">57</xref>), and GUA causes brachial plexus nerve injury (<xref ref-type="bibr" rid="B58">58</xref>).</p>
<p>Our NMA had some limitations. First, most of the included articles were retrospective studies, and further large-scale randomized controlled trials are needed. Second, the articles we included were all from Asia, which may limit the generalisability of our results. Third, the scope of surgery included in the article was not specified, and there was a certain degree of heterogeneity.</p>
</sec>
<sec id="s5" sec-type="conclusion">
<label>5</label>
<title>Conclusion</title>
<p>Based on comprehensive NMA, endoscopic thyroidectomy is safe and feasible. Endoscopic surgical approaches have unique advantages. ABBA and UABA are the closest to COT in terms of operative time and are superior to other endoscopic surgeries. The UABA and ACA are superior to other surgical approaches in controlling intraoperative bleeding and hospital stay. UABA and BABA showed significant advantages in terms of postoperative drainage volume. The OA is more adept at retrieving lymph nodes. Endoscopic thyroidectomy did not increase the incidence of postoperative complications. However, it is clear that careful selection and consideration of the surgical approach are essential. In light of these findings, it is apparent that prospective, randomized studies are needed to validate and further refine the findings of our NMA, providing a more robust foundation for surgeons to make informed decisions when selecting appropriate endoscopic surgical approaches.</p>
</sec>
<sec id="s6" sec-type="author-contributions">
<title>Author contributions</title>
<p>XL: Data curation, Writing &#x2013; original draft. HZ: Writing &#x2013; review &amp; editing. WD: Data curation, Writing &#x2013; original draft.</p>
</sec>
</body>
<back>
<sec id="s7" sec-type="funding-information">
<title>Funding</title>
<p>The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.</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>
<sec id="s10" 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/fendo.2023.1256209/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fendo.2023.1256209/full#supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="DataSheet_1.pdf" id="SM1" mimetype="application/pdf"/>
</sec>
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