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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Pharmacol.</journal-id>
<journal-title>Frontiers in Pharmacology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Pharmacol.</abbrev-journal-title>
<issn pub-type="epub">1663-9812</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">1626681</article-id>
<article-id pub-id-type="doi">10.3389/fphar.2025.1626681</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Pharmacology</subject>
<subj-group>
<subject>Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Which is the optimal choice in lipid-lowering therapy for reducing major cardiovascular events? a network meta-analysis</article-title>
<alt-title alt-title-type="left-running-head">Niu 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.2025.1626681">10.3389/fphar.2025.1626681</ext-link>
</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Niu</surname>
<given-names>Qiang</given-names>
</name>
<uri xlink:href="https://loop.frontiersin.org/people/3063739/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/conceptualization/"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/>
<role content-type="https://credit.niso.org/contributor-roles/funding-acquisition/"/>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
<role content-type="https://credit.niso.org/contributor-roles/software/"/>
<role content-type="https://credit.niso.org/contributor-roles/visualization/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
<role content-type="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Qilei</given-names>
</name>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Chen</surname>
<given-names>Feng</given-names>
</name>
<role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
<role content-type="https://credit.niso.org/contributor-roles/validation/"/>
<role content-type="https://credit.niso.org/contributor-roles/visualization/"/>
<role content-type="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Li</surname>
<given-names>Bo</given-names>
</name>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1947152/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/conceptualization/"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/funding-acquisition/"/>
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<role content-type="https://credit.niso.org/contributor-roles/resources/"/>
<role content-type="https://credit.niso.org/contributor-roles/supervision/"/>
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<role content-type="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/"/>
</contrib>
</contrib-group>
<aff>
<institution>Department of Cardiology, Zibo Central Hospital</institution>, <addr-line>Zibo</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/691547/overview">Christina Maria Pabelick</ext-link>, Mayo Clinic, United States</p>
</fn>
<fn fn-type="edited-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1855616/overview">Evangelia Zvintzou</ext-link>, University of Patras, Greece</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2611376/overview">Liping Jiang</ext-link>, University of Illinois Chicago, United States</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Li Bo, <email>libosubmit@163.com</email>
</corresp>
</author-notes>
<pub-date pub-type="epub">
<day>03</day>
<month>09</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2025</year>
</pub-date>
<volume>16</volume>
<elocation-id>1626681</elocation-id>
<history>
<date date-type="received">
<day>11</day>
<month>05</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>12</day>
<month>08</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2025 Niu, Wang, Chen and Li.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Niu, Wang, Chen and Li</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec>
<title>Background</title>
<p>Currently, there are various lipid-lowering therapies in clinical practice, and the emergence of PCSK9 inhibitors has undoubtedly added a valuable tool to lipid-lowering strategies. However, existing studies lack comparisons between different PCSK9 inhibitors and between the outcomes of using PCSK9 inhibitors alone versus in combination with statins. Therefore, this study aims to explore the efficacy and safety of different lipid-lowering regimens, aiming to determine the optimal lipid-lowering regimen.</p>
</sec>
<sec>
<title>Methods</title>
<p>We searched PubMed/Medline and the Cochrane Library of Clinical Trials for related articles published up to October 2024. A network meta-analysis was applied including studies comparing PCSK9 inhibitors with statins or ezetimibe that have MACE outcomes. The efficacy endpoint was MACE, and the safety endpoints were new-onset diabetes and neurocognitive impairment.</p>
</sec>
<sec>
<title>Results</title>
<p>We included a total of 29 studies, comprising 68,686 patients. Compared to oral lipid-lowering drugs, PCSK9 inhibitors combined with statins significantly reduced the incidence of MACE. While, PCSK9 inhibitors alone did not significantly reduce the risk of MACE.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>For patients requiring intensive lipid lowering, the combination of PCSK9 inhibitors with statins provides the greatest clinical benefit. While, for patients with moderate to low risk who need only single-drug therapy, statins are generally preferred over PCSK9 inhibitors considering various factors.</p>
</sec>
</abstract>
<kwd-group>
<kwd>PCSK9 inhibitor</kwd>
<kwd>statin</kwd>
<kwd>MACE (major adverse cardiovascular events)</kwd>
<kwd>LDL-C</kwd>
<kwd>inclisiran</kwd>
</kwd-group>
<counts>
<page-count count="11"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Cardiovascular and Smooth Muscle Pharmacology</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1">
<title>Background</title>
<p>Atherosclerotic cardiovascular disease (ASCVD) remains a major threat to human life safety (<xref ref-type="bibr" rid="B25">Martin et al., 2024</xref>; <xref ref-type="bibr" rid="B33">Pirillo et al., 2023</xref>). Research on various risk factors of ASCVD remains a current hot topic. Blood lipid levels, particularly LDL-C, are widely recognized as independent risk factors closely associated with the occurrence and progression of atherosclerosis (<xref ref-type="bibr" rid="B33">Pirillo et al., 2023</xref>; <xref ref-type="bibr" rid="B8">Ference et al., 2024</xref>).</p>
<p>Currently, there are various lipid-lowering regimens, and statins have remained the cornerstone of lipid-lowering therapy due to robust evidence supporting their ability to reduce LDL-C and ASCVD risk (<xref ref-type="bibr" rid="B5">Collins et al., 2016</xref>). However, many patients, even when using the maximum tolerated dose of statins or adding other lipid-lowering drugs like ezetimibe, fail to achieve the ideal lipid levels recommended by guidelines (<xref ref-type="bibr" rid="B45">Serban et al., 2017</xref>).</p>
<p>While, the emergence of PCSK9 inhibitors may offer clinical promise to lipid-lowering therapy. By specifically binding to PCSK9, they prevent PCSK9 from binding to LDLR, inhibit PCSK9-mediated LDLR degradation, increase the number of LDLRs on the surface of hepatocytes, and thus significantly lower LDL-C levels and even further reduce the risk of major adverse cardiovascular events (MACE) (<xref ref-type="bibr" rid="B46">Shimada and Cannon, 2015</xref>). Numerous clinical trials have confirmed the potent LDL-C lowering effect of PCSK9 inhibitors (<xref ref-type="bibr" rid="B43">Sabatine et al., 2017</xref>; <xref ref-type="bibr" rid="B44">Schwartz et al., 2018</xref>; <xref ref-type="bibr" rid="B36">Raal et al., 2020</xref>). Consequently, more cardiovascular disease guidelines have recommended PCSK9 inhibitors; however, it is also noted that the recommended treatment regimens still involve the use of statins (<xref ref-type="bibr" rid="B24">Mach et al., 2020</xref>; <xref ref-type="bibr" rid="B50">Visseren et al., 2021</xref>; <xref ref-type="bibr" rid="B10">Grundy et al., 2019</xref>). That leads us to consider whether PCSK9 inhibitors can be used alone, without statins, to reduce the risk of MACE.</p>
<p>However, existing research lacks direct comparisons between different PCSK9 inhibitors and between monotherapy and combination therapy with statins. Therefore, this study is to explore the efficacy and safety of different lipid-lowering regimens in moderate to high-risk cardiovascular populations, including monotherapy with different PCSK9 inhibitors, combination therapy with different PCSK9 inhibitors and statins, and oral lipid-lowering drugs (statins or ezetimibe) alone, aiming to determine the optimal lipid-lowering regimen.</p>
</sec>
<sec sec-type="methods" id="s2">
<title>Methods</title>
<sec id="s2-1">
<title>Guidance and protocol</title>
<p>The methodology for the network meta-analysis follows the PRISMA-NMA guidelines (<xref ref-type="bibr" rid="B26">Moher et al., 2009</xref>). The protocol of the present study was registered in Open Science Framework database (ID:CRD42024558622).</p>
</sec>
<sec id="s2-2">
<title>Data sources and search strategy</title>
<p>We searched PubMed/Medline and the Cochrane Library of Clinical Trials for related articles published up to October 2024. The following keywords were used: PCSK9 inhibitor, alirocumab, evolocumab, inclisiran. Citations were screened at the title and abstract level and retrieved if considered relevant. Meanwhile, we checked the references of the retrieved studies for additional studies. The details of the search strategy conducted 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>Literature screening flow chart.</p>
</caption>
<table>
<tbody valign="top">
<tr>
<td align="left">
<inline-graphic xlink:href="fphar-16-1626681-fx1.tif"/>
</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s2-3">
<title>Selection criteria</title>
<p>We only included randomized controlled trials (RCT) that met the following inclusion criteria: 1. The study population consisted of adult patients with dyslipidemia or diagnosed ASCVD; 2. The trial compared alirocumab, evolocumab, or inclisiran with control strategies (placebo and/or other lipid-lowering drugs); 3. The study must include at least one of the following outcomes: MACE (cardiovascular death, non-fatal myocardial infarction, stroke, re-intervention, rehospitalization), new-onset diabetes, or neurocognitive impairment. There were no restrictions on follow-up duration and study size. Observational studies (including single-arm trials), case reports, case series studies, meta-analyses, and studies with duplicate data were excluded from this analysis.</p>
</sec>
<sec id="s2-4">
<title>Data extraction</title>
<p>Study selection was independently conducted by two authors (Niu Qiang and Wang Qilei). Based on titles and abstracts retrieved from electronic searches, irrelevant studies were eliminated. Subsequently, these two authors examined the full texts of the remaining studies and the full-text reports of all potentially relevant trials and assessed them independently for eligibility on the basis of the defined inclusion criteria. The corresponding author (Li Bo) was responsible for contacting to obtain missing information when assessing inclusion criteria or lacking critical data. Any discrepancies were resolved by discussion. The risk of bias in included studies was assessed according to Cochrane Collaboration guidelines.</p>
</sec>
<sec id="s2-5">
<title>Quality assessment</title>
<p>We used the Cochrane risk of bias assessment tool (ROB 2) for assessing the risk of bias in eligible studies (<xref ref-type="bibr" rid="B47">Sterne et al., 2019</xref>). The grading of recommendations assessment, development, and evaluation (GRADE) were used to evaluate the certainty of evidence based on the risk of bias, inconsistency, indirectness, Imprecision, publication bias and incoherence (<xref ref-type="bibr" rid="B34">Puhan et al., 2014</xref>).</p>
</sec>
<sec id="s2-6">
<title>Statistical analysis</title>
<p>Statistical analysis was performed using the gemtc package in R software (version 4.1). Bayesian network meta-analysis was conducted using a consistency model, compare the efficacy and safety of any two therapies to determine the optimal treatment plan. Dichotomous variables were represented as risk ratios (RRs) and 95% confidence intervals (CI) were estimated. These models were based on 30,000 iterations after an initial 10,000 iterations. We considered there were statistically significant when the 95% confidence intervals did not cross 1. The surface under the cumulative ranking curve (SUCRA) was used to estimate the probability of treatment drugs ranking for each outcome. Statistical heterogeneity was interpreted by the I2 statistic (value exceeding 50% was considered substantial) (<xref ref-type="bibr" rid="B12">Higgins and Thompson, 2002</xref>). Publication bias was assessed using funnel plots with Egger regression test if more than 10 trials were included (<xref ref-type="bibr" rid="B6">Egger et al., 1997</xref>).</p>
</sec>
</sec>
<sec sec-type="results" id="s3">
<title>Results</title>
<sec id="s3-1">
<title>Search results and search results</title>
<p>We included a total of 29 studies involving 68,686 patients, comprising 14 studies on alirocumab, 12 studies on evolocumab, and 3 studies on inclisiran (<xref ref-type="bibr" rid="B43">Sabatine et al., 2017</xref>; <xref ref-type="bibr" rid="B44">Schwartz et al., 2018</xref>; <xref ref-type="bibr" rid="B36">Raal et al., 2020</xref>; <xref ref-type="bibr" rid="B27">Moriarty et al., 2015</xref>; <xref ref-type="bibr" rid="B48">Stroes et al., 2016</xref>; <xref ref-type="bibr" rid="B16">Kereiakes et al., 2015</xref>; <xref ref-type="bibr" rid="B4">Cannon et al., 2015</xref>; <xref ref-type="bibr" rid="B9">Ginsberg et al., 2016</xref>; <xref ref-type="bibr" rid="B49">Teramoto et al., 2016</xref>; <xref ref-type="bibr" rid="B19">Koh et al., 2018</xref>; <xref ref-type="bibr" rid="B41">Robinson et al., 2015</xref>; <xref ref-type="bibr" rid="B1">Bays et al., 2015</xref>; <xref ref-type="bibr" rid="B7">Farnier et al., 2016</xref>; <xref ref-type="bibr" rid="B11">Han et al., 2020</xref>; <xref ref-type="bibr" rid="B37">R&#xe4;ber et al., 2022</xref>; <xref ref-type="bibr" rid="B14">Janik et al., 2021</xref>; <xref ref-type="bibr" rid="B29">Nicholls et al., 2022</xref>; <xref ref-type="bibr" rid="B13">Hirayama et al., 2014</xref>; <xref ref-type="bibr" rid="B2">Blom et al., 2014</xref>; <xref ref-type="bibr" rid="B31">Nissen et al., 2016</xref>; <xref ref-type="bibr" rid="B28">Nicholls et al., 2016</xref>; <xref ref-type="bibr" rid="B40">Robinson et al., 2014</xref>; <xref ref-type="bibr" rid="B35">Raal et al., 2015</xref>; <xref ref-type="bibr" rid="B18">Kiyosue et al., 2016</xref>; <xref ref-type="bibr" rid="B21">Koskinas et al., 2019</xref>; <xref ref-type="bibr" rid="B20">Koren et al., 2012</xref>; <xref ref-type="bibr" rid="B38">Ray et al., 2020</xref>) (<xref ref-type="fig" rid="F1">Figure 1</xref>). Among these studies, there were also 4 studies comparing monotherapy with PCSK9 inhibitors against control groups. Study sizes ranged from 107 to 27,564 participants, with average ages ranging from 50.6 to 66.1 years, and male proportions varying from 47.7% to 81.5%. All the 29 studies was judged to be high by using the ROB 2.0. The characteristics of the participants and trials are reported in <xref ref-type="table" rid="T2">Table 2</xref>.</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>Network diagram of RCT.</p>
</caption>
<graphic xlink:href="fphar-16-1626681-g001.tif">
<alt-text content-type="machine-generated">Network diagram showing connections between various drug combinations, represented by labeled blue circles. Larger circles indicate greater sample sizes: &#x22;Statins/Ezetimibe&#x22; (n=32527), &#x22;Evolocumab + Statins&#x22; (n=19822), &#x22;Alirocumab + Statins&#x22; (n=14198), &#x22;Inclisiran + Statins&#x22; (n=1833), &#x22;Alirocumab&#x22; (n=299), and &#x22;Evolocumab&#x22; (n=416). Black lines connect the combinations.</alt-text>
</graphic>
</fig>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>Baseline characteristics of included studies.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Trial</th>
<th align="left">Register number</th>
<th align="left">Sample size</th>
<th align="left">Male (%)</th>
<th align="left">Age, years</th>
<th align="left">Diabetes (%)</th>
<th align="left">Follow-up/Treatment duration</th>
<th align="left">Investigational drug</th>
<th align="left">Statin (%)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">1.ODYSSEY ALTERNATIVE</td>
<td align="left">NCT01709513</td>
<td align="center">313</td>
<td align="center">54.8</td>
<td align="center">63.4</td>
<td align="center">23.9</td>
<td align="center">24W</td>
<td align="left">Alirocumab</td>
<td align="center">20.1</td>
</tr>
<tr>
<td align="left">2.ODYSSEY CHOICE II</td>
<td align="left">NCT02023879</td>
<td align="center">231</td>
<td align="center">56.3</td>
<td align="center">63.8</td>
<td align="center">16.5</td>
<td align="center">24W</td>
<td align="left">Alirocumab</td>
<td align="center">0</td>
</tr>
<tr>
<td align="left">3.ODYSSEY COMBO 1</td>
<td align="left">NCT01644175</td>
<td align="center">314</td>
<td align="center">66.2</td>
<td align="center">63</td>
<td align="center">43.3</td>
<td align="center">52W</td>
<td align="left">Alirocumab</td>
<td align="center">100</td>
</tr>
<tr>
<td align="left">4.ODYSSEY COMBO 2</td>
<td align="left">NCT01644188</td>
<td align="center">720</td>
<td align="center">73.6</td>
<td align="center">61.6</td>
<td align="center">31.0</td>
<td align="center">52W</td>
<td align="left">Alirocumab</td>
<td align="center">99.9</td>
</tr>
<tr>
<td align="left">5.ODYSSEY HIGH FH</td>
<td align="left">NCT01617655</td>
<td align="center">107</td>
<td align="center">53.3</td>
<td align="center">50.6</td>
<td align="center">14</td>
<td align="center">78W</td>
<td align="left">Alirocumab</td>
<td align="center">100</td>
</tr>
<tr>
<td align="left">6. ODYSSEY JAPAN</td>
<td align="left">NCT02017898</td>
<td align="center">215</td>
<td align="center">60.6</td>
<td align="center">60.8</td>
<td align="center">68.5</td>
<td align="center">52W</td>
<td align="left">Alirocumab</td>
<td align="center">100</td>
</tr>
<tr>
<td align="left">7.8. ODYSSEY KT</td>
<td align="left">NCT02289963</td>
<td align="center">199</td>
<td align="center">70.1</td>
<td align="center">60</td>
<td align="center">41</td>
<td align="center">24W</td>
<td align="left">Alirocumab</td>
<td align="center">100</td>
</tr>
<tr>
<td align="left">9.ODYSSEY LONG TERM</td>
<td align="left">NCT01507831</td>
<td align="center">2,338</td>
<td align="center">62.3</td>
<td align="center">60.5</td>
<td align="center">34.6</td>
<td align="center">78W</td>
<td align="left">Alirocumab</td>
<td align="center">100</td>
</tr>
<tr>
<td align="left">10.ODYSSEY OPTIONS I</td>
<td align="left">NCT01730040</td>
<td align="center">354</td>
<td align="center">65.3</td>
<td align="center">63.1</td>
<td align="center">50</td>
<td align="center">24W</td>
<td align="left">Alirocumab</td>
<td align="center">100</td>
</tr>
<tr>
<td align="left">11ODYSSEY OPTIONS II</td>
<td align="left">NCT01730053</td>
<td align="center">305</td>
<td align="center">61.3</td>
<td align="center">60.9</td>
<td align="center">41.3</td>
<td align="center">24W</td>
<td align="left">Alirocumab</td>
<td align="center">100</td>
</tr>
<tr>
<td align="left">12.ODYSSEY OUTCOMES</td>
<td align="left">NCT01663402</td>
<td align="center">18,924</td>
<td align="center">74.8</td>
<td align="center">58.6</td>
<td align="center">28.8</td>
<td align="center">208W</td>
<td align="left">Alirocumab</td>
<td align="center">100</td>
</tr>
<tr>
<td align="left">13.ODYSSEY EAST</td>
<td align="left">NCT02979015</td>
<td align="center">612</td>
<td align="center">75</td>
<td align="center">58.6</td>
<td align="center">27.5</td>
<td align="center">24W</td>
<td align="left">Alirocumab</td>
<td align="center">100</td>
</tr>
<tr>
<td align="left">14.PACMAN-AMI</td>
<td align="left">NCT03067844</td>
<td align="center">298</td>
<td align="center">81</td>
<td align="center">58.5</td>
<td align="center">10.3</td>
<td align="center">52W</td>
<td align="left">Alirocumab</td>
<td align="center">100</td>
</tr>
<tr>
<td align="left">15.CANTAB</td>
<td align="left">-</td>
<td align="center">2,171</td>
<td align="center">58.2</td>
<td align="center">63</td>
<td align="center">-</td>
<td align="center">96W</td>
<td align="left">Alirocumab</td>
<td align="center">90</td>
</tr>
<tr>
<td align="left">16.HUYGENS</td>
<td align="left">NCT03570697</td>
<td align="center">161</td>
<td align="center">71.4</td>
<td align="center">60.5</td>
<td align="center">16.8</td>
<td align="center">50W</td>
<td align="left">Evolocumab</td>
<td align="center">100</td>
</tr>
<tr>
<td align="left">17.YUKAWA I</td>
<td align="left">NCT01652703</td>
<td align="center">307</td>
<td align="center">62.9</td>
<td align="center">61.5</td>
<td align="center">38.1</td>
<td align="center">12W</td>
<td align="left">Evolocumab</td>
<td align="center">100</td>
</tr>
<tr>
<td align="left">18.DESCARTES</td>
<td align="left">NCT01516879</td>
<td align="center">901</td>
<td align="center">47.7</td>
<td align="center">56.2</td>
<td align="center">11.5</td>
<td align="center">52W</td>
<td align="left">Evolocumab</td>
<td align="center">87.7</td>
</tr>
<tr>
<td align="left">19.FOURIER</td>
<td align="left">NCT01764633</td>
<td align="center">27,564</td>
<td align="center">75.4</td>
<td align="center">62.5</td>
<td align="center">20</td>
<td align="center">113W</td>
<td align="left">Evolocumab</td>
<td align="center">100</td>
</tr>
<tr>
<td align="left">20.GAUSS III</td>
<td align="left">NCT01984424</td>
<td align="center">218</td>
<td align="center">51.4</td>
<td align="center">58.8</td>
<td align="center">11.9</td>
<td align="center">24W</td>
<td align="left">Evolocumab</td>
<td align="center">0</td>
</tr>
<tr>
<td align="left">21.GLAGOV</td>
<td align="left">NCT01813422</td>
<td align="center">968</td>
<td align="center">72.2</td>
<td align="center">59.8</td>
<td align="center">20.9</td>
<td align="center">76W</td>
<td align="left">Evolocumab</td>
<td align="center">98.6</td>
</tr>
<tr>
<td align="left">22.LAPLACE-2</td>
<td align="left">NCT01763866</td>
<td align="center">1896</td>
<td align="center">54.2</td>
<td align="center">59.8</td>
<td align="center">15.5</td>
<td align="center">78W</td>
<td align="left">Evolocumab</td>
<td align="center">100</td>
</tr>
<tr>
<td align="left">23.OSLER 1 &#x26; 2</td>
<td align="left">NCT01439880<break/>NCT01854918</td>
<td align="center">4,465</td>
<td align="center">50.5</td>
<td align="center">57.9</td>
<td align="center">13.4</td>
<td align="center">48W</td>
<td align="left">Evolocumab</td>
<td align="center">70.1</td>
</tr>
<tr>
<td align="left">24.RUTHERFORD-2</td>
<td align="left">NCT01763918</td>
<td align="center">329</td>
<td align="center">57.8</td>
<td align="center">51.2</td>
<td align="center">-</td>
<td align="center">12W</td>
<td align="left">Evolocumab</td>
<td align="center">100</td>
</tr>
<tr>
<td align="left">25.YUKAWA-2</td>
<td align="left">NCT01953328</td>
<td align="center">404</td>
<td align="center">60.4</td>
<td align="center">61.5</td>
<td align="center">48.8</td>
<td align="center">12W</td>
<td align="left">Evolocumab</td>
<td align="center">100</td>
</tr>
<tr>
<td align="left">26. EVOPACS</td>
<td align="left">NCT03287609</td>
<td align="center">307</td>
<td align="center">81.5</td>
<td align="center">60.7</td>
<td align="center">22.4</td>
<td align="center">8W</td>
<td align="left">Evolocumab</td>
<td align="center">100</td>
</tr>
<tr>
<td align="left">27.MENDEL</td>
<td align="left">NCT01375777</td>
<td align="center">406</td>
<td align="center">34</td>
<td align="center">50.8</td>
<td align="center">0.2</td>
<td align="center">12W</td>
<td align="left">Evolocumab</td>
<td align="center">0</td>
</tr>
<tr>
<td align="left">28.ORION-9</td>
<td align="left">NCT03397121</td>
<td align="center">481</td>
<td align="center">47.1</td>
<td align="center">56</td>
<td align="center">10</td>
<td align="center">540D</td>
<td align="left">Inclisiran</td>
<td align="center">100</td>
</tr>
<tr>
<td align="left">29.ORION-10</td>
<td align="left">NCT03399370</td>
<td align="center">1,561</td>
<td align="center">69.4</td>
<td align="center">66.1</td>
<td align="center">45</td>
<td align="center">540D</td>
<td align="left">Inclisiran</td>
<td align="center">90</td>
</tr>
<tr>
<td align="left">30.ORION-11</td>
<td align="left">NCT03400800</td>
<td align="center">1,617</td>
<td align="center">71.7</td>
<td align="center">64.8</td>
<td align="center">35.1</td>
<td align="center">540D</td>
<td align="left">Inclisiran</td>
<td align="center">94</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s3-2">
<title>Efficacy results</title>
<p>All included studies reported occurrences of major adverse cardiovascular events (MACE). In terms of MACE incidence, PCSK9 inhibitors combined with statins showed significant reductions compared to oral lipid-lowering drugs (statins, ezetimibe, or their combination) (<xref ref-type="fig" rid="F2">Figure 2</xref>), including alirocumab combined with statins (RR 0.85, 95% CI 0.7&#x2013;0.98, high certainty); evolocumab combined with statins (RR 0.82, 95% CI 0.64&#x2013;0.93, high certainty); and inclisiran combined with statins (RR 0.76, 95% CI 0.58&#x2013;1, high certainty). Compared to the use of alirocumab alone, the combination of PCSK9 inhibitors with statins significantly reduces the incidence of MACE events (moderate to low certainty): alirocumab combined with statins (RR 0.21, 95% CI 0.024&#x2013;0.8); evolocumab combined with statins (RR 0.2, 95% CI 0.024&#x2013;0.76); inclisiran combined with statins (RR 0.19, 95% CI 0.022&#x2013;0.74). However, monotherapy with PCSK9 inhibitors compared to oral lipid-lowering drugs not only didn&#x2019;t show significant reductions but even increased the risk of MACE events (high certainty): alirocumab (RR 4, 95% CI 1.1&#x2013;34, high certainty); evolocumab (RR 0.85, 95% CI 0.2&#x2013;4.9, high certainty). The SUCRA values indicate the overall ranking probability of each treatment regimen for this outcome, with inclisiran combined with statins considered the best treatment regimen for reducing MACE risk, with an SUCRA value of 0.79 (<xref ref-type="fig" rid="F3">Figure 3</xref>). The subsequent rankings were evolocumab combined with statins (0.69), alirocumab combined with statins (0.62), evolocumab monotherapy (0.59), oral lipid-lowering drugs (0.29), and alirocumab monotherapy (0.02).</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption>
<p>Ali: alirocumab; Evo: evolocumab; Inc: inclisiran; Sta:statins; OLLD: oral lipid-lowering drugs (statins, ezetimibe, or their combination).</p>
</caption>
<graphic xlink:href="fphar-16-1626681-g002.tif">
<alt-text content-type="machine-generated">Forest plot showing hazard ratios and 95% confidence intervals comparing various interventions. Vertical line at 1 indicates no effect. Red dots represent hazard ratios; horizontal lines indicate confidence intervals. Interventions are listed with respective hazard ratios and confidence intervals on the right.</alt-text>
</graphic>
</fig>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption>
<p>A: alirocumab; B: alirocumab combined with statins; C: evolocumab; D: evolocumab combined with statins; E: inclisiran combined with statins; F: oral lipid-lowering drugs.</p>
</caption>
<graphic xlink:href="fphar-16-1626681-g003.tif">
<alt-text content-type="machine-generated">Line graph showing cumulative probability against rank for six datasets, labeled A to F. A red solid line for A rises sharply after rank four. Other lines, including dashed and dotted styles in various colors, represent datasets B to F with differing slopes and intersections, indicating varied probability distributions.</alt-text>
</graphic>
</fig>
<p>In addition, subgroup analyses evaluating all-cause mortality showed that PCSK9 inhibitors added to statin treatment did not confer a significant mortality benefit. Comparisons among different PCSK9 inhibitor types also demonstrated no significant statistical differences in mortality rates (<xref ref-type="fig" rid="F4">Figure 4</xref>).</p>
<fig id="F4" position="float">
<label>FIGURE 4</label>
<caption>
<p>Ali: alirocumab; Evo: evolocumab; Inc: inclisiran; Sta:statins; OLLD: oral lipid-lowering drugs (statins, ezetimibe, or their combination).</p>
</caption>
<graphic xlink:href="fphar-16-1626681-g004.tif">
<alt-text content-type="machine-generated">Forest plot showing hazard ratios with confidence intervals for various interventions. Each red dot represents the point estimate. Interventions compared include Evo+Sta, Inc+Sta, OLLD, and Ali+Sta, with hazard ratios ranging from 1.0 to 1.4. The horizontal line represents the confidence interval for each estimate.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3-3">
<title>Safety results</title>
<p>Regarding safety, the most notable concerns included two aspects: new-onset diabetes and neurocognitive impairment. A total of 19 studies in the literature reported adverse events related to new-onset diabetes and neurocognitive impairment. Among them, 10 studies reported adverse events related to new-onset diabetes, and 16 studies reported adverse events related to neurocognitive impairment. Compared to the control groups, there were no statistically significant differences in the risk of new-onset diabetes among various PCSK9 inhibitors (high certainty) (<xref ref-type="fig" rid="F5">Figure 5A</xref>), ranked by SUCRA values as follows (<xref ref-type="fig" rid="F5">Figure 5B</xref>): alirocumab (0.70), oral lipid-lowering drugs (0.62), evolocumab (0.4), and inclisiran (0.28). Similarly, no significant differences were found among treatment regimens in the incidence of neurocognitive impairment (data unavailable for inclisiran) (high certainty) (<xref ref-type="fig" rid="F6">Figure 6A</xref>). Ranked by SUCRA values as follows (<xref ref-type="fig" rid="F6">Figure 6B</xref>): alirocumab (0.74), oral lipid-lowering drugs (0.61), and evolocumab (0.15).</p>
<fig id="F5" position="float">
<label>FIGURE 5</label>
<caption>
<p>
<bold>(A)</bold> Ali: alirocumab; Evo: evolocumab; Inc: inclisiran; OLLD: oral lipid-lowering drugs. <bold>(B)</bold> A: alirocumab; B: evolocumab; C: inclisiran; D oral lipid-lowering drugs.</p>
</caption>
<graphic xlink:href="fphar-16-1626681-g005.tif">
<alt-text content-type="machine-generated">Panel A shows a forest plot of hazard ratios with confidence intervals for six interventions compared: Ali vs. OLLD, Evo vs. OLLD, Inc vs. OLLD, Evo vs. Ali, Inc vs. Ali, and Inc vs. Evo. Panel B displays a cumulative probability plot with four curves labeled A, B, C, and D, representing different ranks.</alt-text>
</graphic>
</fig>
<fig id="F6" position="float">
<label>FIGURE 6</label>
<caption>
<p>
<bold>(A)</bold> Ali: alirocumab; Evo: evolocumab; OLLD: oral lipid-lowering drugs. <bold>(B)</bold> A: alirocumab; B: evolocumab; D: oral lipid-lowering drugs.</p>
</caption>
<graphic xlink:href="fphar-16-1626681-g006.tif">
<alt-text content-type="machine-generated">Panel A shows a forest plot comparing three interventions with hazard ratios and confidence intervals: Ali versus OLLD (0.92, 0.46-1.7), Evo versus OLLD (1.3, 0.62-3.2), and Evo versus Ali (1.5, 0.61-4.7). Panel B displays a line graph showing cumulative probability versus rank for three interventions, with red, blue, and green lines representing different treatments.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3-4">
<title>Publication bias</title>
<p>The funnel plot was approximately symmetrical (<xref ref-type="fig" rid="F7">Figure 7</xref>), and the p value after Egger&#x2019;s test was 0.3459, which indicated that there was no significant publication bias.</p>
<fig id="F7" position="float">
<label>FIGURE 7</label>
<caption>
<p>Funnel plot of network meta-analysis.</p>
</caption>
<graphic xlink:href="fphar-16-1626681-g007.tif">
<alt-text content-type="machine-generated">Funnel plot displaying the standard error on the vertical axis and the risk ratio centered at the comparison-specific effect on the horizontal axis. Dots represent individual studies, with a symmetrical distribution around the vertical line, suggesting no publication bias. P-value from Egger&#x27;s test is 0.3459.</alt-text>
</graphic>
</fig>
</sec>
</sec>
<sec sec-type="discussion" id="s4">
<title>Discussion</title>
<p>This study included a total of 29 RCTs aimed at evaluating various lipid-lowering regimens, including monotherapy with different PCSK9 inhibitors, combination therapy of different PCSK9 inhibitors with statins, and monotherapy with statins or ezetimibe, to assess their effectiveness in reducing MACE events and determining the optimal lipid-lowering regimen. According to our results, in terms of reducing MACE events, PCSK9 inhibitors combination with statins was significantly superior to other lipid-lowering regimens, among which Inclisiran combined with statins emerged with the highest probability of being the optimal choice based on SUCRA rankings. Additionally, as in the population included in the oral lipid-lowering drug group, more than 95% of the individuals used statins, our results indicate that the clinical benefits of statin monotherapy are not inferior to those of any PCSK9 inhibitor monotherapy.</p>
<p>Previous studies have consistently demonstrated the potent LDL-C lowering effects of statins and PCSK9 inhibitors (<xref ref-type="bibr" rid="B43">Sabatine et al., 2017</xref>; <xref ref-type="bibr" rid="B44">Schwartz et al., 2018</xref>; <xref ref-type="bibr" rid="B36">Raal et al., 2020</xref>; <xref ref-type="bibr" rid="B3">Cannon et al., 2004</xref>; <xref ref-type="bibr" rid="B22">LaRosa et al., 2005</xref>; <xref ref-type="bibr" rid="B30">Nissen et al., 2006</xref>). Statins inhibit cholesterol synthesis by limiting the action of HMG-CoA reductase, additionally, they upregulate LDL receptor (LDLR) expression and increase LDLR activity, enhancing the uptake and metabolism of LDL particles in the bloodstream. In contrast, PCSK9 inhibitors do not affect cholesterol synthesis directly. They primarily bind to free PCSK9, preventing it from attaching to LDL receptors (LDLRs), thereby reducing LDLR degradation and prolonging LDLR lifespan, which increases the clearance of LDL-C throughout its lifecycle (<xref ref-type="bibr" rid="B32">Norata et al., 2014</xref>; <xref ref-type="bibr" rid="B42">Roth and Davidson, 2018</xref>). Additionally, the efficacy of PCSK9 inhibitors in lowering LDL-C is limited by the concentration of free PCSK9. Once free PCSK9 levels reach zero, administering higher doses of PCSK9 inhibitors does not yield additional LDL-C reduction. Higher doses only prolong the duration of action without increasing the intensity of LDL-C lowering. It can be seen that statins and PCSK9 inhibitors have a synergistic effect in lowering LDL-C levels. Their combined use can further enhance lipid-lowering pathways, strengthen their respective mechanisms, and achieve a dual increase in the quantity and lifespan of LDLR. This leads to better LDL-C clearance capacity and significantly reduces LDL-C levels while providing additional clinical benefits by further lowering the risk of MACE. It&#x2019;s consistent with our conclusions and aligns with the recommendations of various cardiovascular-related guidelines. Moreover, our subgroup analyses demonstrated that adding PCSK9 inhibitors to background statin therapy did not significantly reduce all-cause mortality compared to statin monotherapy. Additionally, no statistically significant differences were observed among various PCSK9 inhibitor agents regarding mortality outcomes. These findings suggest a consistent mortality profile across different PCSK9 inhibitors when used as adjunctive lipid-lowering therapy. This aligns with prior large-scale randomized controlled trials, which have similarly reported limited evidence for mortality reduction despite significant improvements in lipid parameters and major adverse cardiovascular event rates.</p>
<p>Current clinical paradigms regard PCSK9 inhibitors as novel potent lipid-lowering agents, which demonstrate enhanced LDL-C reduction efficacy compared to statins, thereby enabling superior clinical outcomes. However, as shown in <xref ref-type="fig" rid="F2">Figure 2</xref>, the clinical benefits of statin monotherapy are not inferior to those of evolocumab and may even surpass those of alirocumab. This outcome surpassed our anticipated results. This may be due to the anti-inflammatory effects and improvement of endothelial function provided by statins beyond lipid-lowering (<xref ref-type="bibr" rid="B23">Liao and Laufs, 2005</xref>). Emerging evidence suggests that inflammation may play an even more pivotal role than dyslipidemia in the pathogenesis and progression of atherosclerosis (<xref ref-type="bibr" rid="B39">Ridker et al., 2023</xref>). The findings imply that the clinical benefits observed with certain interventions may not be solely attributable to their lipid-modifying effects. Rather, a more comprehensive mechanism&#x2014;encompassing anti-inflammatory actions and improvements in endothelial function&#x2014;may underlie the observed reduction in MACE risk. However, these effects are not yet well-documented for PCSK9 inhibitors, necessitating further research for confirmation. Furthermore, considering the factors of cost and administration route (<xref ref-type="bibr" rid="B15">Kazi et al., 2016</xref>; <xref ref-type="bibr" rid="B17">Khan et al., 2022</xref>), combined with treatment recommendations from both domestic and international guidelines, statins remain the most cost-effective and feasible monotherapy option for lipid lowering in most ASCVD patients requiring medication. Of course, the number of studies and participants in this subgroup was limited, and further research is warranted to validate these findings.</p>
<p>Additionally, among the three PCSK9 inhibitors currently widely used in clinical practice, the SCURA values indicate that the most beneficial treatment regimen may be the combination of inclisiran and statins. Of course, this result only comes from SUCRA rankings, without direct or statistical comparison supports. Based on the current evidence base, the optimal PCSK9 inhibitor cannot be definitively ascertained at present. Based on the SCURA ranking framework, we believe that this result may be due to inclisiran&#x2019;s exceptionally long half-life, allowing it to maintain a stable low level of LDL-C in patients over a longer period, thereby reducing LDL-C fluctuations and minimizing the incidence and progression of ASCVD and MACE events. We keenly anticipates further evidence generation regarding inclisiran&#x2019;s long-term clinical profile. However, due to cost considerations, its widespread use among ASCVD patients is currently limited, and we look forward to its promising performance once included in medical insurance coverage.</p>
<p>In terms of safety, we limited our discussion to newly diagnosed diabetes and neurocognitive impairment, as these outcomes were both clinically significant and sufficiently represented in our dataset. There is no statistically significant difference in the occurrence of new-onset diabetes or neurocognitive impairment. Several factors may explain this finding. First, most included trials investigated PCSK9 inhibitors as add-on therapy to established statin treatment, and the incremental risk for these adverse events may not substantially exceed that already associated with statins. Second, some trials reported a relatively low number of events and had limited follow-up durations, which could reduce the statistical power to detect rare adverse outcomes. Third, heterogeneity in diagnostic definitions and event reporting may have influenced the pooled estimates. Furthermore, these findings are consistent with the results of major outcome trials such as FOURIER and ODYSSEY OUTCOMES, which reported no significant increase in diabetes or neurocognitive adverse events with PCSK9 inhibitor therapy, even at very low LDL-C levels. Collectively, these observations suggest that while safety concerns warrant ongoing surveillance, current evidence does not indicate a substantial additional risk of diabetes or neurocognitive impairment when PCSK9 inhibitors are used on top of statins.</p>
</sec>
<sec id="s5">
<title>Limitations</title>
<p>Our study has several limitations. Firstly, there is a lack of relevant studies directly comparing different types of PCSK9 inhibitors, and further large-scale studies are needed. Secondly, studies on monotherapy with PCSK9 inhibitors are limited, including the number of studies, number of participants, and follow-up duration. Thirdly, some studies may employ slightly different definitions of MACE, which may create bias.</p>
</sec>
<sec sec-type="conclusion" id="s6">
<title>Conclusion</title>
<p>The emergence of PCSK9 inhibitors has provided us with more tools for lowering cholesterol, when combined with statins, it can provide the greatest clinical benefit for ASCVD patients. However, it is important to emphasize that statins remain the cornerstone of lipid-lowering therapy, with well-established clinical benefits. The long-term benefits of PCSK9 inhibitor monotherapy still require further clinical observation and validation. Therefore, when choosing monotherapy for lipid-lowering treatment, it is still recommended to first use statins in accordance with guideline recommendations.</p>
</sec>
</body>
<back>
<sec sec-type="author-contributions" id="s7">
<title>Author contributions</title>
<p>QN: Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation, Methodology, Software, Visualization, Writing &#x2013; original draft, Writing &#x2013; review and editing. QW: Data curation, Investigation, Writing &#x2013; review and editing. FC: Formal Analysis, Methodology, Validation, Visualization, Writing &#x2013; review and editing. BL: Conceptualization, Data curation, Funding acquisition, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing &#x2013; review and editing.</p>
</sec>
<sec sec-type="funding-information" id="s8">
<title>Funding</title>
<p>The author(s) declare that financial support was received for the research and/or publication of this article. This study was supported by the Zibo Health and Medical Research Project (grant numbers: 20230301007) and Taishan Scholars Program of Shandong Province tsqn, China (NO.tsqn202306402).</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>
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