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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Pharmacol.</journal-id>
<journal-title-group>
<journal-title>Frontiers in Pharmacology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Pharmacol.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1663-9812</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
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<article-id pub-id-type="publisher-id">1647888</article-id>
<article-id pub-id-type="doi">10.3389/fphar.2025.1647888</article-id>
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<article-categories>
<subj-group subj-group-type="heading">
<subject>Systematic Review</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Different nucleos(t)ide analogs in resected hepatitis B virus-associated hepatocellular carcinoma: a systematic review</article-title>
<alt-title alt-title-type="left-running-head">Qiu et al.</alt-title>
<alt-title alt-title-type="right-running-head">
<ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3389/fphar.2025.1647888">10.3389/fphar.2025.1647888</ext-link>
</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Qiu</surname>
<given-names>Hongquan</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/3101986"/>
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</contrib>
<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Zhang</surname>
<given-names>Yu</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1371171"/>
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</contrib>
<contrib contrib-type="author">
<name>
<surname>Xu</surname>
<given-names>Fengxia</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
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</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Xue</surname>
<given-names>Songhui</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
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<aff id="aff1">
<label>1</label>
<institution>Department of Nursing, Nantong Health College of Jiangsu Province</institution>, <city>Nantong</city>, <state>Jiangsu</state>, <country country="CN">China</country>
</aff>
<aff id="aff2">
<label>2</label>
<institution>Department of Laboratory Medicine, Haimen Hospital Affiliated to Xinglin College of Nantong University</institution>, <city>Nantong</city>, <state>Jiangsu</state>, <country country="CN">China</country>
</aff>
<aff id="aff3">
<label>3</label>
<institution>Department of General Surgery, The Sixth People&#x2019;s Hospital of Nantong</institution>, <city>Nantong</city>, <state>Jiangsu</state>, <country country="CN">China</country>
</aff>
<author-notes>
<corresp id="c001">
<label>&#x2a;</label>Correspondence: Songhui Xue, <email xlink:href="miaomiao20140319@163.com">miaomiao20140319@163.com</email>
</corresp>
<fn fn-type="equal" id="fn001">
<label>&#x2020;</label>
<p>These authors have contributed equally to this work and share first authorship</p>
</fn>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2025-11-14">
<day>14</day>
<month>11</month>
<year>2025</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2025</year>
</pub-date>
<volume>16</volume>
<elocation-id>1647888</elocation-id>
<history>
<date date-type="received">
<day>30</day>
<month>06</month>
<year>2025</year>
</date>
<date date-type="rev-recd">
<day>24</day>
<month>10</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>30</day>
<month>10</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2025 Qiu, Zhang, Xu and Xue.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Qiu, Zhang, Xu and Xue</copyright-holder>
<license>
<ali:license_ref start_date="2025-11-14">https://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License (CC BY)</ext-link>. 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.</license-p>
</license>
</permissions>
<abstract>
<sec>
<title>Background</title>
<p>To evaluate the effects of different types of nucleos(t)ide analogs on the survival rate of patients with hepatitis B virus-associated hepatocellular carcinoma (HBV-HCC) after radical resection through a network meta-analysis.</p>
</sec>
<sec>
<title>Methods</title>
<p>PubMed, Embase, the Cochrane Library, and CNKI databases were searched up to 6 March 2024. The NOS was used to assess the risk of bias in cohort studies, while the ROB tool in Review Manager was employed for randomized controlled trials. Data on overall survival (OS) and recurrence-free survival (RFS) were extracted from the literature to pool hazard ratios (HRs) and corresponding 95% CrIs. Meta-analysis was performed via R.</p>
</sec>
<sec>
<title>Results</title>
<p>24 studies involving 9,787 HBV-HCC patients were included. Compared with the control group, antiviral therapies using telbivudine (HR [95% CrI] &#x3d; 0.23 [0.12,0.44]), tenofovir disoproxil fumarate (HR [95% CrI] &#x3d; 0.40 [0.30,0.52]), lamivudine (HR [95% CrI] &#x3d; 0.50 [0.34, 0.75]), adefovir (HR [95% CrI] &#x3d; 0.55 [0.38,0.79]), and entecavir (HR [95% CrI] &#x3d; 0.55 [0.43,0.71]) significantly improved OS. Among these, telbivudine (98.22%) and tenofovir disoproxil fumarate (76.12%) demonstrated superior effects in improving OS. Compared with the control group, antiviral therapies using telbivudine (HR [95% CrI] &#x3d; 0.45 [0.28,0.70]), tenofovir disoproxil fumarate (HR [95% CrI] &#x3d; 0.52 [0.44,0.62]), entecavir (HR [95% CrI] &#x3d; 0.65 [0.55,0.77]),adefovir (HR [95% CrI] &#x3d; 0.79 [0.65,0.94]),and lamivudine (HR [95% CrI] &#x3d; 0.82 [0.71, 0.94]) significantly improved RFS. Telbivudine (SUCRA, 93.22%) and tenofovir disoproxil fumarate (SUCRA, 85.37%) exhibited superior effects in improving RFS.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>When compared to other nucleos(t)ide analogs, telbivudine and tenofovir disoproxil fumarate exhibited the most notable effects.</p>
</sec>
<sec>
<title>Systematic Review</title>
<p>Identifier CRD42024612794.</p>
</sec>
</abstract>
<kwd-group>
<kwd>hepatitis B virus</kwd>
<kwd>hepatocellular carcinoma</kwd>
<kwd>antiviral therapy</kwd>
<kwd>nucleos(t)ideanalogs</kwd>
<kwd>recurrence-free survival</kwd>
</kwd-group>
<funding-group>
<funding-statement>The author(s) declare that financial support was received for the research and/or publication of this article. This study was suppoeted by Scientific research project of Nantong Health Committee [grant number QA2020040] and Nantong Health and Wellness Committee Surface Program [grant number MB2020049].</funding-statement>
</funding-group>
<counts>
<fig-count count="2"/>
<table-count count="2"/>
<equation-count count="0"/>
<ref-count count="51"/>
<page-count count="11"/>
</counts>
<custom-meta-group>
<custom-meta>
<meta-name>section-in-acceptance</meta-name>
<meta-value>Gastrointestinal and Hepatic Pharmacology</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="s1">
<label>1</label>
<title>Introduction</title>
<p>In Asia, hepatocellular carcinoma (HCC) is most frequently caused by hepatitis B virus (HBV) infection. Treatments such as radical resection, transarterial chemoembolization (TACE), and radiofrequency ablation (RFA) can effectively improve the prognosis of patients with hepatitis B virus-associated hepatocellular carcinoma (HBV-HCC). Nevertheless, despite treatment, the 5-year survival rate remains at only 50%, with a recurrence rate surpassing 70% (<xref ref-type="bibr" rid="B34">Shen et al., 2018</xref>). Research has demonstrated that postoperative antiviral therapy using nucleos(t)ide analogs such as lamivudine (LAM), entecavir (ENT), adefovir (ADV), telbivudine (Ldt), and tenofovir disoproxil fumarate (TDF) can suppress the replication of hepatitis B virus deoxyribonucleic acid (HBV-DNA), reduce the HBV-DNA level in the body, improve overall survival (OS) and recurrence-free survival (RFS) in HBV-HCC patients (<xref ref-type="bibr" rid="B6">Choi et al., 2021</xref>; <xref ref-type="bibr" rid="B10">He et al., 2019</xref>; <xref ref-type="bibr" rid="B14">Huang et al., 2013</xref>; <xref ref-type="bibr" rid="B17">Kao et al., 2023</xref>; <xref ref-type="bibr" rid="B23">Li et al., 2023</xref>; <xref ref-type="bibr" rid="B26">Linye et al., 2023</xref>; <xref ref-type="bibr" rid="B30">Qi et al., 2021</xref>; <xref ref-type="bibr" rid="B29">Qi et al., 2020</xref>; <xref ref-type="bibr" rid="B31">Ren et al., 2018</xref>; <xref ref-type="bibr" rid="B33">Rui et al., 2017</xref>; <xref ref-type="bibr" rid="B35">Shen et al., 2022</xref>; <xref ref-type="bibr" rid="B41">Wang et al., 2022</xref>; <xref ref-type="bibr" rid="B43">Xiao et al., 2021</xref>; <xref ref-type="bibr" rid="B45">Xu et al., 2019</xref>; <xref ref-type="bibr" rid="B51">Zhong et al., 2016</xref>; <xref ref-type="bibr" rid="B2">Chen, 2015</xref>; <xref ref-type="bibr" rid="B4">Cheng et al., 2011</xref>; <xref ref-type="bibr" rid="B7">Ding et al., 2014</xref>; <xref ref-type="bibr" rid="B8">Fang et al., 2012</xref>; <xref ref-type="bibr" rid="B25">Lin et al., 2016</xref>; <xref ref-type="bibr" rid="B48">Zhang, 2015</xref>; <xref ref-type="bibr" rid="B15">Huang et al., 2015</xref>; <xref ref-type="bibr" rid="B18">Ke et al., 2013</xref>; <xref ref-type="bibr" rid="B49">Zhang et al., 2014</xref>; <xref ref-type="bibr" rid="B3">Chen et al., 2017</xref>), and thereby improve patient prognosis. However, no consensus has been reached on which specific antiviral drug offers the optimal effect for improving the prognosis. Some studies comparing tenofovir and ENT have suggested that TDF is superior to ENT in improving the survival rate and reducing the recurrence rate of HBV-HCC patients (<xref ref-type="bibr" rid="B12">Hu et al., 2022</xref>). However, research has reported no significant differences in OS or recurrence rate between the two drugs (<xref ref-type="bibr" rid="B23">Li et al., 2023</xref>). Similarly, studies comparing the efficacy of ENT and LAM have reported conflicting results. Research has found similar effects of ENT and LAM on OS in HBV-HCC patients (<xref ref-type="bibr" rid="B36">Shin et al., 2012</xref>), while ENT has been reported in other research to provide superior effects for improving OS compared to LAM (<xref ref-type="bibr" rid="B19">Kim et al., 2016</xref>). Therefore, we utilized a systematic review and network meta-analysis to integrate existing evidence, aiming to identify the optimal antiviral treatment for affected patients.</p>
</sec>
<sec sec-type="methods" id="s2">
<label>2</label>
<title>Methods</title>
<sec id="s2-1">
<label>2.1</label>
<title>Data and methods</title>
<p>The present study was carried out as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement (<xref ref-type="bibr" rid="B24">Liberati et al., 2009</xref>), and was pre-registered with the International Prospective Register of Systematic Reviews (PROSPERO) (CRD42024612794).</p>
</sec>
<sec id="s2-2">
<label>2.2</label>
<title>Literature retrieval</title>
<p>Literature searches were conducted across PubMed, Embase, the Cochrane Library, and CNKI databases, with the search cut-off date on 6 December 2024. The search strategy was based on MeSH and free-text terms, with no language restrictions. The primary search terms included but were not limited to: Hepatitis B virus, hepatocellular carcinoma, overall survival, recurrence-free survival, disease-free survival, progression-free survival, and their corresponding free-text terms.</p>
</sec>
<sec id="s2-3">
<label>2.3</label>
<title>Literature screening</title>
<p>The articles were first independently evaluated by two researchers, and a third researcher was responsible for consolidating the findings. Studies were included if they met the following criteria (<xref ref-type="bibr" rid="B34">Shen et al., 2018</xref>): they were randomized controlled trials (RCTs) or cohort studies (<xref ref-type="bibr" rid="B6">Choi et al., 2021</xref>); they involved patients with HBV-HCC who received radical resection as part of their treatment (<xref ref-type="bibr" rid="B10">He et al., 2019</xref>); they provided relatively complete follow-up data on OS or RFS (<xref ref-type="bibr" rid="B14">Huang et al., 2013</xref>); they used postoperative nucleos(t)ide analog antiviral therapy as the control. Exclusion criteria were as follows (<xref ref-type="bibr" rid="B34">Shen et al., 2018</xref>): Patients infected with other types of hepatitis viruses other than hepatitis B virus (<xref ref-type="bibr" rid="B6">Choi et al., 2021</xref>); Patients received preoperative antiviral therapy (<xref ref-type="bibr" rid="B10">He et al., 2019</xref>); Different patients were treated with different types of antiviral drugs after surgery and were not grouped according to the type; (<xref ref-type="bibr" rid="B14">Huang et al., 2013</xref>); Studies that failed to specify the type of antiviral drugs to be used (<xref ref-type="bibr" rid="B17">Kao et al., 2023</xref>); The patients received liver transplantation and interferon antiviral therapy (<xref ref-type="bibr" rid="B23">Li et al., 2023</xref>); The patients did not receive radical resection. Ultimately, 24 eligible articles were included.</p>
</sec>
<sec id="s2-4">
<label>2.4</label>
<title>Risk of bias assessment</title>
<p>The selected studies were independently assessed for risk of bias by two researchers, and the results were consolidated by a third researcher. All RCTs were evaluated using the Risk of Bias (ROB) tool in Review Manager, while cohort studies were assessed using the Newcastle-Ottawa Scale (NOS) (<xref ref-type="bibr" rid="B28">Lo et al., 2014</xref>). The ROB tool included the following evaluation criteria (<xref ref-type="bibr" rid="B34">Shen et al., 2018</xref>): method of random sequence generation (<xref ref-type="bibr" rid="B6">Choi et al., 2021</xref>); allocation concealment (<xref ref-type="bibr" rid="B10">He et al., 2019</xref>); blinding of participants (<xref ref-type="bibr" rid="B14">Huang et al., 2013</xref>); blinding of outcome assessors (<xref ref-type="bibr" rid="B17">Kao et al., 2023</xref>); completeness of outcome data (<xref ref-type="bibr" rid="B23">Li et al., 2023</xref>); selective outcome reporting (<xref ref-type="bibr" rid="B26">Linye et al., 2023</xref>); other potential sources of bias. The NOS included the following evaluation criteria (<xref ref-type="bibr" rid="B34">Shen et al., 2018</xref>): representativeness of the exposed group (<xref ref-type="bibr" rid="B6">Choi et al., 2021</xref>); representativeness of the non-exposed group (<xref ref-type="bibr" rid="B10">He et al., 2019</xref>); ascertainment of exposure (<xref ref-type="bibr" rid="B14">Huang et al., 2013</xref>); demonstration that the outcome of interest was not present at the start of the study (<xref ref-type="bibr" rid="B17">Kao et al., 2023</xref>); comparability of exposed and non-exposed groups in study design and statistical analysis (<xref ref-type="bibr" rid="B23">Li et al., 2023</xref>); assessment of outcome (<xref ref-type="bibr" rid="B26">Linye et al., 2023</xref>); adequacy of follow-up duration (<xref ref-type="bibr" rid="B30">Qi et al., 2021</xref>); completeness of follow-up in both exposed and non-exposed groups. The results of the risk of bias assessment are presented in <xref ref-type="table" rid="T1">Table 1</xref>.</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Basic characteristics of included studies.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="center">Author</th>
<th align="center">Year</th>
<th align="center">Region</th>
<th align="center">Intervention</th>
<th align="center">Age (mean &#xb1; SD)</th>
<th align="center">Gender (&#x2642;/&#x2640;)</th>
<th align="center">HBV DNA (log copies/mL)</th>
<th align="center">HBeAg (&#x2b;/&#x2212;)</th>
<th align="center">Tumor stage</th>
<th align="center">Tumor size (cm)</th>
<th align="center">Child&#x2013;pugh</th>
<th align="center">Study design</th>
<th align="center">QAT</th>
<th align="center">Outcomes</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td rowspan="2" align="center">Ke</td>
<td rowspan="2" align="center">2013</td>
<td rowspan="2" align="center">China</td>
<td align="center">Lamivudine</td>
<td align="center">48.94 &#xb1; 10.47</td>
<td align="center">129/12</td>
<td align="center">4.97</td>
<td align="center">15/126</td>
<td align="center">107/23/11 (BCLC [A/B/C])</td>
<td align="center">4.5</td>
<td align="center">141/0/0 (A/B/C)</td>
<td rowspan="2" align="center">Retro</td>
<td rowspan="2" align="center">8</td>
<td rowspan="2" align="center">OS, RFS</td>
</tr>
<tr>
<td align="center">Control</td>
<td align="center">49.70 &#xb1; 12.10</td>
<td align="center">127/14</td>
<td align="center">4.78</td>
<td align="center">16/125</td>
<td align="center">105/26/10 (BCLC [A/B/C])</td>
<td align="center">5</td>
<td align="center">28/14/1 (A/B/C)</td>
</tr>
<tr>
<td rowspan="2" align="center">Zhang</td>
<td rowspan="2" align="center">2014</td>
<td rowspan="2" align="center">China</td>
<td align="center">Entecavir</td>
<td rowspan="2" align="center">NA</td>
<td align="center">26/14</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td align="center">4.6</td>
<td align="center">33/6/1 (A/B/C)</td>
<td rowspan="2" align="center">Retro</td>
<td rowspan="2" align="center">9</td>
<td rowspan="2" align="center">OS, DFS</td>
</tr>
<tr>
<td align="center">Control</td>
<td align="center">31/16</td>
<td align="center">4.8</td>
<td align="center">37/10/0 (A/B/C)</td>
</tr>
<tr>
<td rowspan="2" align="center">Huang</td>
<td rowspan="2" align="center">2015</td>
<td rowspan="2" align="center">China</td>
<td align="center">Adefovir</td>
<td align="center">50.6 &#xb1; 7.8</td>
<td align="center">90/10</td>
<td rowspan="2" align="center">NA</td>
<td align="center">51/49</td>
<td align="center">8/60/32 (BCLC [0/A/B])</td>
<td align="center">4.9</td>
<td align="center">100/0/0 (A/B/C)</td>
<td rowspan="2" align="center">RCT</td>
<td rowspan="2" align="center">low risk: 2<break/>unclear risk: 2<break/>high risk: 3</td>
<td rowspan="2" align="center">OS, RFS</td>
</tr>
<tr>
<td align="center">Control</td>
<td align="center">50.5 &#xb1; 8.5</td>
<td align="center">89/11</td>
<td align="center">50/50</td>
<td align="center">8/59/33 (BCLC [0/A/B])</td>
<td align="center">5.1</td>
<td align="center">100/0/0 (A/B/C)</td>
</tr>
<tr>
<td rowspan="2" align="center">Ding</td>
<td rowspan="2" align="center">2014</td>
<td rowspan="2" align="center">China</td>
<td align="center">Entecavir</td>
<td align="center">47.22 &#xb1; 10.80</td>
<td align="center">56/18</td>
<td align="center">5.21</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td align="center">54/20/0 (A/B/C)</td>
<td rowspan="2" align="center">Retro</td>
<td rowspan="2" align="center">6</td>
<td rowspan="2" align="center">OS, RFS</td>
</tr>
<tr>
<td align="center">Control</td>
<td align="center">46.49 &#xb1; 11.02</td>
<td align="center">30/9</td>
<td align="center">5.02</td>
<td align="center">31/8/0 (A/B/C)</td>
</tr>
<tr>
<td rowspan="2" align="center">Lin</td>
<td rowspan="2" align="center">2016</td>
<td rowspan="2" align="center">China</td>
<td align="center">Entecavir</td>
<td align="center">54.2 &#xb1; 2.5</td>
<td align="center">26/9</td>
<td align="center">7.48</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td align="center">28/7/0 (A/B/C)</td>
<td rowspan="2" align="center">Retro</td>
<td rowspan="2" align="center">9</td>
<td rowspan="2" align="center">RFS</td>
</tr>
<tr>
<td align="center">Control</td>
<td align="center">53.1 &#xb1; 1.9</td>
<td align="center">20/5</td>
<td align="center">6.94</td>
<td align="center">20/5/0 (A/B/C)</td>
</tr>
<tr>
<td rowspan="2" align="center">Fang</td>
<td rowspan="2" align="center">2012</td>
<td rowspan="2" align="center">China</td>
<td align="center">Lamivudine</td>
<td align="center">48.9 &#xb1; 7.41</td>
<td align="center">20/6</td>
<td align="center">6.38</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">Retro</td>
<td rowspan="2" align="center">6</td>
<td rowspan="2" align="center">RFS</td>
</tr>
<tr>
<td align="center">Control</td>
<td align="center">50.0 &#xb1; 9.63</td>
<td align="center">23/7</td>
<td align="center">6.35</td>
</tr>
<tr>
<td rowspan="2" align="center">Cheng</td>
<td rowspan="2" align="center">2011</td>
<td rowspan="2" align="center">China</td>
<td align="center">Lamivudine</td>
<td align="center">45.32 &#xb1; 9.14</td>
<td align="center">38/12</td>
<td align="center">5.56 (5.53&#x2013;5.64)</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">Retro</td>
<td rowspan="2" align="center">7</td>
<td rowspan="2" align="center">RFS</td>
</tr>
<tr>
<td align="center">Control</td>
<td align="center">42.21 &#xb1; 8.76</td>
<td align="center">32/11</td>
<td align="center">5.68 (5.50&#x2013;5.83)</td>
</tr>
<tr>
<td rowspan="2" align="center">Chen</td>
<td rowspan="2" align="center">2015</td>
<td rowspan="2" align="center">China</td>
<td align="center">Lamivudine</td>
<td align="center">52.16 &#xb1; 5.14</td>
<td align="center">39/6</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td align="center">38/5/2/0 (AJCC)</td>
<td rowspan="2" align="center">NA</td>
<td align="center">41/4/0 (A/B/C)</td>
<td rowspan="2" align="center">Pro</td>
<td rowspan="2" align="center">7</td>
<td rowspan="2" align="center">RFS</td>
</tr>
<tr>
<td align="center">Control</td>
<td align="center">51.91 &#xb1; 4.82</td>
<td align="center">36/4</td>
<td align="center">34/5/1/0 (AJCC)</td>
<td align="center">38/2/0 (A/B/C)</td>
</tr>
<tr>
<td rowspan="2" align="center">Zhang</td>
<td rowspan="2" align="center">2015</td>
<td rowspan="2" align="center">China</td>
<td align="center">Lamivudine</td>
<td align="center">52.16 &#xb1; 5.14</td>
<td align="center">39/6</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td align="center">38/5/2/0 (TNM)</td>
<td rowspan="2" align="center">NA</td>
<td align="center">41/4/0 (A/B/C)</td>
<td rowspan="2" align="center">Pro</td>
<td rowspan="2" align="center">7</td>
<td rowspan="2" align="center">RFS</td>
</tr>
<tr>
<td align="center">Control</td>
<td align="center">51.91 &#xb1; 4.82</td>
<td align="center">36/4</td>
<td align="center">34/5/1/0 (TNM)</td>
<td align="center">38/3/0 (A/B/C)</td>
</tr>
<tr>
<td rowspan="2" align="center">Xu</td>
<td rowspan="2" align="center">2019</td>
<td rowspan="2" align="center">China</td>
<td align="center">Entecavir</td>
<td rowspan="2" align="center">NA</td>
<td align="center">32/5</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td align="center">24/13 (BCLC [0, A/B, C])</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">Retro</td>
<td rowspan="2" align="center">9</td>
<td rowspan="2" align="center">OS, RFS</td>
</tr>
<tr>
<td align="center">Control</td>
<td align="center">31/6</td>
<td align="center">28/9 (BCLC [0, A/B, C])</td>
</tr>
<tr>
<td rowspan="2" align="center">Xiao</td>
<td rowspan="2" align="center">2020</td>
<td rowspan="2" align="center">China</td>
<td align="center">Entecavir</td>
<td align="center">54.34 &#xb1; 9.71</td>
<td align="center">51/15</td>
<td rowspan="2" align="center">NA</td>
<td align="center">31/35</td>
<td rowspan="2" align="center">NA</td>
<td align="center">2.5 &#xb1; 0.6</td>
<td align="center">38/17/11 (A/B/C)</td>
<td rowspan="2" align="center">Retro</td>
<td rowspan="2" align="center">9</td>
<td rowspan="2" align="center">OS, PFS</td>
</tr>
<tr>
<td align="center">Control</td>
<td align="center">53.08 &#xb1; 9.22</td>
<td align="center">47/19</td>
<td align="center">27/39</td>
<td align="center">2.3 &#xb1; 0.7</td>
<td align="center">34/24/8 (A/B/C)</td>
</tr>
<tr>
<td rowspan="2" align="center">Ren</td>
<td rowspan="2" align="center">2018</td>
<td rowspan="2" align="center">China</td>
<td align="center">Entecavir</td>
<td rowspan="2" align="center">NA</td>
<td align="center">36/5</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td align="center">40/1 (BCLC [A/B])</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">Retro</td>
<td rowspan="2" align="center">5</td>
<td rowspan="2" align="center">OS</td>
</tr>
<tr>
<td align="center">Control</td>
<td align="center">67/8</td>
<td align="center">73/2 (BCLC [A/B])</td>
</tr>
<tr>
<td rowspan="4" align="center">Huang</td>
<td rowspan="4" align="center">2013</td>
<td rowspan="4" align="center">China</td>
<td align="center">Entecavir</td>
<td rowspan="3" align="center">50.87 &#xb1; 10.07</td>
<td rowspan="3" align="center">758/107</td>
<td rowspan="4" align="center">NA</td>
<td rowspan="3" align="center">512/353</td>
<td rowspan="4" align="center">NA</td>
<td rowspan="3" align="center">5.21 &#xb1; 2.16</td>
<td rowspan="4" align="center">NA</td>
<td rowspan="4" align="center">Retro</td>
<td rowspan="4" align="center">7</td>
<td rowspan="4" align="center">DFS</td>
</tr>
<tr>
<td align="center">Adefovir</td>
</tr>
<tr>
<td align="center">Lamivudine</td>
</tr>
<tr>
<td align="center">Control</td>
<td align="center">51.75 &#xb1; 10.71</td>
<td align="center">156/19</td>
<td align="center">92/83</td>
<td align="center">5.29 &#xb1; 1.88</td>
</tr>
<tr>
<td rowspan="2" align="center">Qi</td>
<td rowspan="2" align="center">2013</td>
<td rowspan="2" align="center">China</td>
<td align="center">Entecavir</td>
<td align="center">53.6 &#xb1; 5.1</td>
<td align="center">106/45</td>
<td align="center">4.8 &#xb1; 1.3</td>
<td align="center">106/45</td>
<td align="center">16/135 (BCLC [0/A])</td>
<td align="center">2.6 &#xb1; 0.4</td>
<td align="center">103/48 (A/B)</td>
<td rowspan="2" align="center">Pro</td>
<td rowspan="2" align="center">8</td>
<td rowspan="2" align="center">OS, RFS</td>
</tr>
<tr>
<td align="center">Control</td>
<td align="center">54.2 &#xb1; 6.7</td>
<td align="center">61/21</td>
<td align="center">5.0 &#xb1; 1.1</td>
<td align="center">61/21</td>
<td align="center">9/73 (BCLC [0/A])</td>
<td align="center">2.6 &#xb1; 0.4</td>
<td align="center">53/29 (A/B)</td>
</tr>
<tr>
<td rowspan="2" align="center">Rui</td>
<td rowspan="2" align="center">2017</td>
<td rowspan="2" align="center">China</td>
<td align="center">Lamivudine</td>
<td align="center">51.3 &#xb1; 12.0</td>
<td align="center">84/34</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td align="center">7.8 &#xb1; 2.3</td>
<td align="center">91/27 (A/B)</td>
<td rowspan="2" align="center">Retro</td>
<td rowspan="2" align="center">6</td>
<td rowspan="2" align="center">OS, TFS</td>
</tr>
<tr>
<td align="center">Control</td>
<td align="center">49.1 &#xb1; 12.4</td>
<td align="center">59/25</td>
<td align="center">7.8 &#xb1; 2.4</td>
<td align="center">69/15 (A/B)</td>
</tr>
<tr>
<td rowspan="2" align="center">Choi</td>
<td rowspan="2" align="center">2020</td>
<td rowspan="2" align="center">Korea</td>
<td align="center">Tenofovir</td>
<td align="center">54.6 &#xb1; 8.6</td>
<td align="center">433/134</td>
<td align="center">2.3 &#xb1; 2.4</td>
<td align="center">149/418</td>
<td align="center">142/425 (BCLC [0/A])</td>
<td align="center">2.8</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">Retro</td>
<td rowspan="2" align="center">9</td>
<td rowspan="2" align="center">OS, RFS</td>
</tr>
<tr>
<td align="center">Entecavir</td>
<td align="center">54.7 &#xb1; 9.3</td>
<td align="center">430/137</td>
<td align="center">2.2 &#xb1; 2.3</td>
<td align="center">137/430</td>
<td align="center">151/416 (BCLC [0/A])</td>
<td align="center">2.7</td>
</tr>
<tr>
<td rowspan="2" align="center">He</td>
<td rowspan="2" align="center">2019</td>
<td rowspan="2" align="center">China</td>
<td align="center">Telbivudine</td>
<td align="center">47.74 &#xb1; 1.393</td>
<td align="center">67/10</td>
<td rowspan="2" align="center">NA</td>
<td align="center">55/22</td>
<td align="center">14/63 (BCLC [0/A])</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">Retro</td>
<td rowspan="2" align="center">7</td>
<td rowspan="2" align="center">OS, DFS</td>
</tr>
<tr>
<td align="center">Adefovir</td>
<td align="center">50.87 &#xb1; 1.024</td>
<td align="center">90/21</td>
<td align="center">97/14</td>
<td align="center">18/93 (BCLC [0/A])</td>
</tr>
<tr>
<td rowspan="2" align="center">He</td>
<td rowspan="2" align="center">2023</td>
<td rowspan="2" align="center">China</td>
<td align="center">Tenofovir</td>
<td align="center">50.97 &#xb1; 12.17</td>
<td align="center">63/11</td>
<td rowspan="2" align="center">NA</td>
<td align="center">16/58</td>
<td align="center">32/42 (BCLC [0/A])</td>
<td align="center">2.91 &#xb1; 0.82</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">RCT</td>
<td rowspan="2" align="center">Low risk: 2<break/>Unclear risk: 2<break/>High risk: 3</td>
<td rowspan="2" align="center">OS, RFS</td>
</tr>
<tr>
<td align="center">Entecavir</td>
<td align="center">49.78 &#xb1; 11.95</td>
<td align="center">66/8</td>
<td align="center">22/52</td>
<td align="center">21/53 (BCLC [0/A])</td>
<td align="center">3.05 &#xb1; 0.89</td>
</tr>
<tr>
<td rowspan="2" align="center">Kao</td>
<td rowspan="2" align="center">2022</td>
<td rowspan="2" align="center">China</td>
<td align="center">Tenofovir</td>
<td align="center">56.87 &#xb1; 8.89</td>
<td align="center">369/63</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td align="center">61/258/113 (BCLC [0/A/B])</td>
<td rowspan="2" align="center">NA</td>
<td align="center">423/9 (A/B &#x2b; C)</td>
<td rowspan="2" align="center">Retro</td>
<td rowspan="2" align="center">6</td>
<td rowspan="2" align="center">OS, RFS</td>
</tr>
<tr>
<td align="center">Entecavir</td>
<td align="center">56.87 &#xb1; 5.18</td>
<td align="center">1,162/203</td>
<td align="center">193/814/358 (BCLC [0/A/B])</td>
<td align="center">1,336/29 (A/B &#x2b; C)</td>
</tr>
<tr>
<td rowspan="2" align="center">Li</td>
<td rowspan="2" align="center">2023</td>
<td rowspan="2" align="center">China</td>
<td align="center">Tenofovir</td>
<td align="center">58.4 &#xb1; 10.5</td>
<td align="center">851/138</td>
<td align="center">3.3 &#xb1; 1.8</td>
<td align="center">261/728</td>
<td align="center">120/743/126 (BCLC [0/A/B])</td>
<td align="center">4.1 (0.5&#x2013;23.1)</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">Retro</td>
<td rowspan="2" align="center">8</td>
<td rowspan="2" align="center">OS, RFS</td>
</tr>
<tr>
<td align="center">Entecavir</td>
<td align="center">58.3 &#xb1; 9.8</td>
<td align="center">844/145</td>
<td align="center">3.3 &#xb1; 1.8</td>
<td align="center">270/719</td>
<td align="center">98/747/144 (BCLC [0/A/B])</td>
<td align="center">4.2 (0.3&#x2013;25.0)</td>
</tr>
<tr>
<td rowspan="2" align="center">Qi</td>
<td rowspan="2" align="center">2021</td>
<td rowspan="2" align="center">China</td>
<td align="center">Tenofovir</td>
<td align="center">49.9 &#xb1; 10.7</td>
<td align="center">122/22</td>
<td align="center">6 &#xb1; 6.67</td>
<td align="center">29/115</td>
<td align="center">10/107/8/19 (BCLC [0/A/B/C])</td>
<td align="center">5.6 &#xb1; 3.8</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">Retro</td>
<td rowspan="2" align="center">9</td>
<td rowspan="2" align="center">OS, RFS</td>
</tr>
<tr>
<td align="center">Entecavir</td>
<td align="center">49.3 &#xb1; 10.6</td>
<td align="center">247/41</td>
<td align="center">6 &#xb1; 6.57</td>
<td align="center">56/232</td>
<td align="center">18/212/19/39 (BCLC [0/A/B/C])</td>
<td align="center">5.4 &#xb1; 3.3</td>
</tr>
<tr>
<td rowspan="2" align="center">Shen</td>
<td rowspan="2" align="center">2022</td>
<td rowspan="2" align="center">China</td>
<td align="center">Tenofovir</td>
<td rowspan="2" align="center">NA</td>
<td align="center">52/10</td>
<td rowspan="2" align="center">NA</td>
<td align="center">15/47</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">Retro</td>
<td rowspan="2" align="center">7</td>
<td rowspan="2" align="center">RFS</td>
</tr>
<tr>
<td align="center">Entecavir</td>
<td align="center">450/83</td>
<td align="center">115/418</td>
</tr>
<tr>
<td rowspan="2" align="center">Wang</td>
<td rowspan="2" align="center">2022</td>
<td rowspan="2" align="center">China</td>
<td align="center">Tenofovir</td>
<td rowspan="2" align="center">NA</td>
<td align="center">231/34</td>
<td rowspan="2" align="center">NA</td>
<td align="center">77/188</td>
<td align="center">22/214/29 (BCLC [0/A/B])</td>
<td align="center">5.5 (0.9&#x2013;19.5)</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">Retro</td>
<td rowspan="2" align="center">8</td>
<td rowspan="2" align="center">OS, RFS</td>
</tr>
<tr>
<td align="center">Entecavir</td>
<td align="center">344/59</td>
<td align="center">117/286</td>
<td align="center">29/330/44 (BCLC [0/A/B])</td>
<td align="center">5.5 (0.8&#x2013;19.0)</td>
</tr>
<tr>
<td rowspan="2" align="center">Zhong</td>
<td rowspan="2" align="center">2016</td>
<td rowspan="2" align="center">China</td>
<td align="center">Adefovir</td>
<td align="center">49.8 &#xb1; 9.9</td>
<td align="center">36/2</td>
<td align="center">4.7 (2.7&#x2013;5.7)</td>
<td align="center">3/35</td>
<td rowspan="2" align="center">NA</td>
<td align="center">4.0 (2.0&#x2013;10.2)</td>
<td rowspan="2" align="center">NA</td>
<td rowspan="2" align="center">Retro</td>
<td rowspan="2" align="center">7</td>
<td rowspan="2" align="center">OS, RFS</td>
</tr>
<tr>
<td align="center">Lamivudine</td>
<td align="center">49 &#xb1; 9.7</td>
<td align="center">62/6</td>
<td align="center">5.2 (2.7&#x2013;6.0)</td>
<td align="center">7/61</td>
<td align="center">4.2 (0.8&#x2013;12.6)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Abbreviation: SD, standard deviation; HBV DNA, hepatitis-B virus deoxyribonucleic acid; HBeAg, Hepatitis B e Antigen; cm, centimeters; QAT, quality assessment tools score; OS, overall survival; DFS, disease-free survival; RFS, recurrence-free survival; NA, not available.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s2-5">
<label>2.5</label>
<title>Data extraction</title>
<p>Using a pre-designed data collection sheet, data extraction was completed independently by two researchers. Any discrepancies in the extracted data were resolved by consulting a third researcher to ensure consistency. The main extracted data included (<xref ref-type="bibr" rid="B34">Shen et al., 2018</xref>): General study information: first author, publication year, and study region (<xref ref-type="bibr" rid="B6">Choi et al., 2021</xref>); Basic participant information: sample size, gender composition, age, HBV DNA level, hepatitis B e antigen (HBeAg) status, Child-Pugh score (a clinical grading system used to assess liver function based on parameters such as bilirubin, albumin, prothrombin time, ascites, and hepatic encephalopathy), and antiviral therapies (<xref ref-type="bibr" rid="B10">He et al., 2019</xref>); Tumor characteristics: tumor size and stage (<xref ref-type="bibr" rid="B14">Huang et al., 2013</xref>); Outcome measures: OS, RFS, or progression-free survival (PFS).</p>
</sec>
<sec id="s2-6">
<label>2.6</label>
<title>Statistical analysis</title>
<p>In this study, R language was used as the primary data analysis tool, and the &#x201c;gemtc&#x201d; package was applied to perform Bayesian network meta-analysis to systematically synthesize and compare the effectiveness of multiple treatment regimens. Model convergence quality was first assessed by calculating the potential scale reduction factor (PSRF). A PSRF value close to 1 indicated that the simulation process had achieved good convergence, ensuring the stability and reliability of the statistical inference results. Then, the ranking of treatment regimens included in the studies was visualized using two methods: first, by calculating and reporting surface under the cumulative ranking curve (SUCRA) values to quantify the overall ranking of each antiviral drug; and second, by utilizing relative effect forest plots and league tables to compare the relative effectiveness of different types of antiviral drugs. Additionally, DFS, RFS, and TFS were combined for statistical analysis. Next, if a closed-loop structure was identified in the network diagram, the &#x201c;mtc.nodesplit&#x201d; function was used to perform inconsistency testing. This test was to examine significant differences between indirect and direct evidence to evaluate whether the consistency assumption of the network meta-analysis was valid. At last, the &#x201c;mtc.anohe&#x201d; function was applied to perform heterogeneity testing, assessing whether the variability among the included studies exceeded the range of random variation. Potential sources of heterogeneity were further explored to interpret the results more comprehensively.</p>
</sec>
</sec>
<sec sec-type="results" id="s3">
<label>3</label>
<title>Results</title>
<sec id="s3-1">
<label>3.1</label>
<title>Basic information of included studies</title>
<p>A total of 5,355 articles were retrieved from the above-mentioned databases. After removing 2,461 duplicates using Endnote 20, 2,894 articles remained. In the first round of screening, 2,857 articles that did not meet the study criteria were excluded after reviewing titles and abstracts, leaving 37 articles. In the second round of screening, after full-text reviews, we excluded 8 articles in which patients had received preoperative antiviral therapy and 5 articles where the types of antiviral drugs were not specified. Ultimately, 24 articles (<xref ref-type="bibr" rid="B6">Choi et al., 2021</xref>; <xref ref-type="bibr" rid="B10">He et al., 2019</xref>; <xref ref-type="bibr" rid="B14">Huang et al., 2013</xref>; <xref ref-type="bibr" rid="B17">Kao et al., 2023</xref>; <xref ref-type="bibr" rid="B23">Li et al., 2023</xref>; <xref ref-type="bibr" rid="B26">Linye et al., 2023</xref>; <xref ref-type="bibr" rid="B30">Qi et al., 2021</xref>; <xref ref-type="bibr" rid="B29">Qi et al., 2020</xref>; <xref ref-type="bibr" rid="B31">Ren et al., 2018</xref>; <xref ref-type="bibr" rid="B33">Rui et al., 2017</xref>; <xref ref-type="bibr" rid="B35">Shen et al., 2022</xref>; <xref ref-type="bibr" rid="B41">Wang et al., 2022</xref>; <xref ref-type="bibr" rid="B43">Xiao et al., 2021</xref>; <xref ref-type="bibr" rid="B45">Xu et al., 2019</xref>; <xref ref-type="bibr" rid="B51">Zhong et al., 2016</xref>; <xref ref-type="bibr" rid="B2">Chen, 2015</xref>; <xref ref-type="bibr" rid="B4">Cheng et al., 2011</xref>; <xref ref-type="bibr" rid="B7">Ding et al., 2014</xref>; <xref ref-type="bibr" rid="B8">Fang et al., 2012</xref>; <xref ref-type="bibr" rid="B25">Lin et al., 2016</xref>; <xref ref-type="bibr" rid="B48">Zhang, 2015</xref>; <xref ref-type="bibr" rid="B15">Huang et al., 2015</xref>; <xref ref-type="bibr" rid="B18">Ke et al., 2013</xref>; <xref ref-type="bibr" rid="B49">Zhang et al., 2014</xref>) meeting the criteria were included in the study. The 24 included studies were published between 2011 and 2023, involving a total of 9,787 patients. The literature retrieval and screening process are illustrated in <xref ref-type="fig" rid="F1">Figure 1</xref>. The included patients were predominantly from China, except for one study conducted in South Korea. The average age of the patients was approximately 50&#xa0;years, and most were classified as Child-Pugh grade A. The majority of the studies were retrospective. Detailed baseline characteristics are presented in <xref ref-type="table" rid="T1">Table 1</xref>.</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>PRISMA 2020 flow diagram.</p>
</caption>
<graphic xlink:href="fphar-16-1647888-g001.tif">
<alt-text content-type="machine-generated">Flowchart illustrating the process of identifying studies via databases and registers. Records identified: PubMed (1,355), Embase (1,217), Cochrane (385), CNKI (2,398). After removing duplicates (2,461), 2,894 records were screened. 2,857 records were excluded. 37 reports were sought for retrieval, with none unretrieved. 37 reports were assessed for eligibility, with 13 excluded due to unclear intervention and preoperative antivirus treatment. Finally, 24 studies were included in the review.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3-2">
<label>3.2</label>
<title>Risk of bias assessment</title>
<p>Of the 22 cohort studies included, 6 studies achieved a score of 9 on the NOS, 4 studies scored 8, 7 studies received a score of 7, 4 studies scored 6, and 1 study obtained a score of 5. Some studies had issues, including incomplete control of confounding factors, lack of descriptions regarding loss to follow-up, or short follow-up durations. The two included RCTs were rated as having a low risk of bias in 2 domains, unclear risk in 2 domains, and high risk in 3 domains. Both RCTs were open-label studies, with a high risk of bias in the domains of blinding and allocation concealment.</p>
</sec>
<sec id="s3-3">
<label>3.3</label>
<title>Effect of antiviral therapy on OS in HBV-HCC patients</title>
<p>For OS, a total of 17 studies, including 7,890 patients and five intervention measures, were included in the analysis (<xref ref-type="fig" rid="F2">Figure 2A</xref>). Heterogeneity analysis and inconsistency testing using the node-splitting method demonstrated that the network meta-analysis satisfied the assumptions of homogeneity and consistency. Compared with the control group, antiviral therapies using Ldt (HR [95% CrI] &#x3d; 0.23 [0.12, 0.44]), TDF (HR [95% CrI] &#x3d; 0.40 [0.30, 0.52]), LAM (HR [95% CrI] &#x3d; 0.50 [0.34, 0.75]), ADV (HR [95% CrI] &#x3d; 0.55 [0.38, 0.79]), and ENT (HR [95% CrI] &#x3d; 0.55 [0.43, 0.71]) significantly improved OS (<xref ref-type="fig" rid="F2">Figure 2B</xref>; <xref ref-type="table" rid="T2">Table 2</xref>). The SUCRA-based probability rankings were consistent with the trends observed in the forest plot and league table. Ldt showed the best effect in improving OS (SUCRA &#x3d; 98.22%).</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption>
<p>
<bold>(A)</bold> Network structure diagram of different antiviral therapies; <bold>(B)</bold> Forest plot of different antiviral therapies; <bold>(C)</bold> Network structure diagram of different antiviral therapies; <bold>(D)</bold> Forest plot of different antiviral therapie.</p>
</caption>
<graphic xlink:href="fphar-16-1647888-g002.tif">
<alt-text content-type="machine-generated">Network diagrams labeled A and C show connections between treatments: LAM, ENT, ADV, Ldt, TDF, and CTRL, with varying line thickness. Forest plots labeled B and D compare these treatments to CTRL, listing hazard ratios and 95% credible intervals for each, demonstrating treatment effectiveness.</alt-text>
</graphic>
</fig>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>League table of OS following different antiviral therapies.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left"/>
<th align="left">Control</th>
<th align="left">LAM</th>
<th align="left">ENT</th>
<th align="left">ADV</th>
<th align="left">Ldt</th>
<th align="left">TDF</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Control</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">LAM</td>
<td align="left">1.99 (1.34, 2.97)</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">ENT</td>
<td align="left">1.81 (1.41, 2.31)</td>
<td align="left">0.91 (0.57, 1.44)</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">ADV</td>
<td align="left">1.82 (1.26, 2.62)</td>
<td align="left">0.91 (0.57, 1.45)</td>
<td align="left">1.01 (0.65, 1.57)</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Ldt</td>
<td align="left">4.34 (2.26, 8.38)</td>
<td align="left">
<bold>2.18 (1.07, 4.45)</bold>
</td>
<td align="left">
<bold>2.4 (1.2, 4.85)</bold>
</td>
<td align="left">
<bold>2.38 (1.39, 4.12)</bold>
</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">TDF</td>
<td align="left">2.51 (1.91, 3.3)</td>
<td align="left">1.26 (0.78, 2.03)</td>
<td align="left">
<bold>1.39 (1.24, 1.56)</bold>
</td>
<td align="left">1.38 (0.87, 2.18)</td>
<td align="left">0.58 (0.28, 1.17)</td>
<td align="left"/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Bold indicates that the row intervention is significantly different from the column intervention.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3-4">
<label>3.4</label>
<title>Effect of antiviral therapy on RFS in HBV-HCC patients</title>
<p>For RFS, a total of 23 studies, including 9,671 patients and five intervention measures, were included in the analysis (<xref ref-type="fig" rid="F2">Figure 2C</xref>). Heterogeneity analysis and inconsistency testing using the node-splitting method demonstrated that the network meta-analysis satisfied the assumptions of homogeneity and consistency. Given that most studies reported RFS, we treated DFS and TFS as RFS for analysis. Compared with the control group, antiviral therapies using Ldt (HR [95% CrI] &#x3d; 0.45 [0.28, 0.70]), TDF (HR [95% CrI] &#x3d; 0.52 [0.44, 0.62]), ENT (HR [95% CrI] &#x3d; 0.65 [0.55, 0.77]), ADV (HR [95% CrI] &#x3d; 0.79 [0.65, 0.94]), and LAM (HR [95% CrI] &#x3d; 0.82 [0.71, 0.94]) significantly improved RFS (<xref ref-type="fig" rid="F2">Figure 2D</xref> and <xref ref-type="sec" rid="s12">Supplementary Table S1</xref>). The SUCRA-based probability rankings were consistent with the trends observed in the forest plot and league table. Ldt showed the best effect in improving RFS (SUCRA &#x3d; 93.22%).</p>
</sec>
</sec>
<sec sec-type="discussion" id="s4">
<label>4</label>
<title>Discussion</title>
<p>The results of this study indicated that nucleos(t)ide analogs, such as LAM, ENT, ADV, Ldt, and TDF, significantly improved OS and RFS in HBV-HCC patients after radical resection, compared to those who did not receive nucleos(t)ide analog antiviral therapy. A key mechanism of HBV-induced carcinogenesis is the extensive replication of HBV in the body following infection. This process leads to the integration of HBV DNA into the host hepatocyte genome, triggering the activation of proto-oncogenes and impairing the function of tumor suppressor genes, thereby driving the development and progression of liver cancer (<xref ref-type="bibr" rid="B16">Jiang et al., 2021</xref>). In HBV-HCC patients, after taking nucleos(t)ide analog antiviral drugs, these analogs are converted into triphosphate compounds through catalysis by cellular kinases. Due to the absence of a 3&#x2032;-hydroxyl group in their ribose molecules, the triphosphate compounds, once integrated into viral DNA, cause the termination of DNA chain elongation. This process inhibits HBV-DNA replication and effectively reduces the HBV viral load (<xref ref-type="bibr" rid="B20">Levrero and Zucman-Rossi, 2016</xref>). Studies have found that high HBV viral load in the serum can promote the growth and metastasis of HCC (<xref ref-type="bibr" rid="B38">Su et al., 2013</xref>; <xref ref-type="bibr" rid="B13">Huang et al., 2011</xref>). Radical resection alters the immune status of HBV-HCC patients, making them prone to HBV reactivation and high HBV viral load replication postoperatively (<xref ref-type="bibr" rid="B21">Li et al., 2020</xref>; <xref ref-type="bibr" rid="B42">Wang et al., 2023</xref>). Nucleos(t)ide analogs, which can inhibit HBV-DNA replication, effectively reduce the HBV-DNA level, thereby improving OS and RFS in these patients. Additionally, treatment with nucleos(t)ide analogs has been shown to reduce the levels of regulatory T cells (Tregs) in the peripheral blood of patients with chronic hepatitis B (<xref ref-type="bibr" rid="B9">He and Zhao, 2019</xref>; <xref ref-type="bibr" rid="B44">Xu, 2021</xref>). Research has indicated that CD4<sup>&#x2b;</sup>CD25<sup>high</sup> regulatory T cells suppress Th cell responses and HBV-specific cytotoxic T lymphocyte-mediated immune responses, which are considered key contributors to HBV immune tolerance (<xref ref-type="bibr" rid="B5">Cheng et al., 2023</xref>; <xref ref-type="bibr" rid="B47">Yu, 2018</xref>). Nucleos(t)ide analogs can decrease the levels of peripheral Tregs, thereby reducing immune tolerance, modulating the patient&#x2019;s immune status (<xref ref-type="bibr" rid="B9">He and Zhao, 2019</xref>), and facilitating viral clearance in HBV-HCC patients. This mechanism contributes to the improvement of OS and RFS in these patients.</p>
<p>Furthermore, our study findings suggested that different types of nucleos(t)ide analogs exhibited varying effects on improving OS and RFS in HBV-HCC patients. LAM, ENT, and ADV were less effective than Ldt in improving OS, while ENT was less effective than TDF. In terms of improving RFS, LAM was less effective than ENT, and both LAM and ADV were less effective than Ldt. Moreover, LAM, ENT, and ADV were all less effective than TDF. These differences may be attributed to variations in the specific mechanisms by which different nucleos(t)ide analogs inhibit HBV-DNA replication. LAM is a cytosine analog that inhibits DNA replication by competitively binding to the active site of HBV reverse transcriptase, thereby blocking its activity. ADV is an adenosine monophosphate analog that competes with natural nucleoside triphosphates (NTPs) to inhibit HBV DNA polymerase. ENT is a guanosine analog that competes with dGTP for HBV DNA polymerase. Ldt is a thymidine deoxynucleotide analog that competes with HBV&#x2019;s natural substrate, thymidine 5&#x2032;-adenosine. TDF is a diphosphate of fovir, which competes for incorporation into the viral DNA chain. Due to the absence of a 3&#x2032;-OH group, tenofovir blocks DNA chain elongation and inhibits viral replication (<xref ref-type="bibr" rid="B11">Hruba et al., 2023</xref>; <xref ref-type="bibr" rid="B50">Zhang et al., 2019</xref>). Since HBV is a retrovirus, its reverse transcriptase lacks proofreading capability and cannot correct mismatched nucleotides (<xref ref-type="bibr" rid="B46">Yasutake et al., 2020</xref>). This characteristic leads to the presence of viral strains with diverse genetic sequences in HBV-HCC patients. During long-term postoperative use of nucleos(t)ide analogs, drug-resistant strains with greater survival ability and replication potential are gradually selected. Consequently, drug resistance frequently develops, leading to reduced sensitivity of the virus to antiviral therapy (<xref ref-type="bibr" rid="B37">Song et al., 2012</xref>; <xref ref-type="bibr" rid="B27">Liu et al., 2021</xref>). Clinical trial evidence has indicated that the rates of drug resistance vary depending on the type of nucleos(t)ide analog used in treatment. During LAM treatment, the drug resistance rate was approximately 20% after 1&#xa0;year and increased to as high as 70% after 5&#xa0;years. Furthermore, about 50% of patients who develop LAM resistance would also develop resistance to ENT within 5&#xa0;years of treatment (<xref ref-type="bibr" rid="B1">Amini-Bavil-Olyaee et al., 2010</xref>). For ADV, the resistance rate was around 2% after 2&#xa0;years and approximately 29% after 5&#xa0;years (<xref ref-type="bibr" rid="B32">Roediger et al., 2022</xref>). During Ldt, the resistance rate was 11% after 2&#xa0;years (<xref ref-type="bibr" rid="B39">Tacke and Kroy, 2016</xref>). For ENT, the resistance rate was 1.2% after 5&#xa0;years of treatment (<xref ref-type="bibr" rid="B40">Takayama et al., 2021</xref>), while TDF showed a similarly low resistance rate during treatment (<xref ref-type="bibr" rid="B22">Li et al., 2021</xref>). This may be related to the poorer effectiveness of LAM in improving OS and RFS, compared to the better outcomes observed with Ldt, TDF, and ENT. The differences in resistance rates among various nucleos(t)ide analogs may be attributed to their specific resistance mechanisms and mutation sites. For LAM, resistance is primarily associated with mutations at rtM204I/V in the POL/RT region. ADV resistance is linked to mutations at rtN236T in the D domain. ENT resistance develops after the emergence of the rtM204V &#x2b; rtL180M mutations. Ldt resistance is associated with mutations at rtL80I and rtL80V, while TDF resistance is related to mutations at rtP177G and rtF249A (<xref ref-type="bibr" rid="B22">Li et al., 2021</xref>).</p>
<p>This study has certain limitations. First, most of the included studies are cohort studies, with relatively few RCTs addressing the topic. Second, some of the included studies had small sample sizes. The study did not ascertain the effects of other non-nucleoside antiviral drugs, such as interferons, or combination therapy regimens due to the limited number of studies. All participants were from East Asian populations, limiting the generalizability of the conclusions. Caution is needed when applying these findings to populations in other regions. Future research should consider including multinational data to enhance global applicability. Third, many of the included RCTs were open-label designed, with no mention of allocation concealment or blinding methods, raising the possibility of implementation and measurement biases, which could affect the reliability of the results. Fourth, the outcome measures did not account for the incidence of adverse events, as only a few studies provided relevant data. Fifth, owing to the small number of included studies, publication bias was not examined. Sixth, excluding preoperative antiviral therapy may affect the external validity of the findings, as preoperative treatment is clinically significant in preventing viral reactivation and improving prognosis. Future research could consider evaluating the impact of preoperative treatment.</p>
</sec>
<sec sec-type="conclusion" id="s5">
<label>5</label>
<title>Conclusion</title>
<p>Different types of nucleos(t)ide analogs can improve both OS and RFS in HBV-HCC patients after radical resection. Although the findings of this study suggest that Ldt and TDF exhibit the most notable effects on OS and RFS in HBV-HCC patients, it may cause drug resistance. As the Ldt therapy is used continuously, drug resistance may occur, which may limit its long-term effectiveness. Due to the limitations of this study, the results of this study should be interpreted with caution. Clinicians should be cautious when applying these findings to long-term treatment plans. Further research is needed to explore strategies to prevent and manage drug resistance in these patients.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="s6">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="sec" rid="s12">Supplementary Material</xref>, further inquiries can be directed to the corresponding author.</p>
</sec>
<sec sec-type="author-contributions" id="s7">
<title>Author contributions</title>
<p>HQ: Supervision, Writing &#x2013; original draft, Writing &#x2013; review and editing. YZ: Formal Analysis, Investigation, Writing &#x2013; review and editing. FX: Methodology, Writing &#x2013; review and editing. SX: Conceptualization, Funding acquisition, Resources, Writing &#x2013; review and editing.</p>
</sec>
<sec sec-type="COI-statement" id="s9">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="ai-statement" id="s10">
<title>Generative AI statement</title>
<p>The author(s) declare that no Generative AI was used in the creation of this manuscript.</p>
<p>Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.</p>
</sec>
<sec sec-type="disclaimer" id="s11">
<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 sec-type="supplementary-material" id="s12">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fphar.2025.1647888/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fphar.2025.1647888/full&#x23;supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="Table1.docx" id="SM1" mimetype="application/docx" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
<fn-group>
<fn fn-type="custom" custom-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/489768/overview">Piyameth Dilokthornsakul</ext-link>, Chiang Mai University, Thailand</p>
</fn>
<fn fn-type="custom" custom-type="reviewed-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/849940/overview">H. Syed Iqbal</ext-link>, YR Gaitonde Centre for AIDS Research and Education, India</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2704075/overview">Yutang Li</ext-link>, Fudan University, China</p>
</fn>
</fn-group>
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