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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>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">1739246</article-id>
<article-id pub-id-type="doi">10.3389/fphar.2026.1739246</article-id>
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<article-categories>
<subj-group subj-group-type="heading">
<subject>Original Research</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Edoxaban for stroke prevention in Chinese patients with atrial fibrillation: 1-year follow-up of the ETNA-AF-China study</article-title>
<alt-title alt-title-type="left-running-head">Guo 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.2026.1739246">10.3389/fphar.2026.1739246</ext-link>
</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Guo</surname>
<given-names>Xueyuan</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
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<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
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<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Formal analysis" vocab-term-identifier="https://credit.niso.org/contributor-roles/formal-analysis/">Formal Analysis</role>
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<contrib contrib-type="author">
<name>
<surname>Du</surname>
<given-names>Juan</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Formal analysis" vocab-term-identifier="https://credit.niso.org/contributor-roles/formal-analysis/">Formal Analysis</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Visualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/visualization/">Visualization</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Conceptualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/conceptualization/">Conceptualization</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Yin</surname>
<given-names>Yuehui</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/935995"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Validation" vocab-term-identifier="https://credit.niso.org/contributor-roles/validation/">Validation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Visualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/visualization/">Visualization</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Formal analysis" vocab-term-identifier="https://credit.niso.org/contributor-roles/formal-analysis/">Formal Analysis</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Qi</surname>
<given-names>Heng</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Validation" vocab-term-identifier="https://credit.niso.org/contributor-roles/validation/">Validation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Formal analysis" vocab-term-identifier="https://credit.niso.org/contributor-roles/formal-analysis/">Formal Analysis</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Visualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/visualization/">Visualization</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Jia</surname>
<given-names>Zhisheng</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Formal analysis" vocab-term-identifier="https://credit.niso.org/contributor-roles/formal-analysis/">Formal Analysis</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Validation" vocab-term-identifier="https://credit.niso.org/contributor-roles/validation/">Validation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Visualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/visualization/">Visualization</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ji</surname>
<given-names>Xiaojun</given-names>
</name>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Data curation" vocab-term-identifier="https://credit.niso.org/contributor-roles/data-curation/">Data curation</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhang</surname>
<given-names>Yuqing</given-names>
</name>
<xref ref-type="aff" rid="aff7">
<sup>7</sup>
</xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Data curation" vocab-term-identifier="https://credit.niso.org/contributor-roles/data-curation/">Data curation</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Liang</surname>
<given-names>Xue</given-names>
</name>
<xref ref-type="aff" rid="aff8">
<sup>8</sup>
</xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Data curation" vocab-term-identifier="https://credit.niso.org/contributor-roles/data-curation/">Data curation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Deng</surname>
<given-names>Bing</given-names>
</name>
<xref ref-type="aff" rid="aff9">
<sup>9</sup>
</xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Liu</surname>
<given-names>Jieyun</given-names>
</name>
<xref ref-type="aff" rid="aff10">
<sup>10</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2751564"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ma</surname>
<given-names>Juan</given-names>
</name>
<xref ref-type="aff" rid="aff11">
<sup>11</sup>
</xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Song</surname>
<given-names>Cangsang</given-names>
</name>
<xref ref-type="aff" rid="aff11">
<sup>11</sup>
</xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Feng</surname>
<given-names>Huifang</given-names>
</name>
<xref ref-type="aff" rid="aff12">
<sup>12</sup>
</xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Luo</surname>
<given-names>Suxin</given-names>
</name>
<xref ref-type="aff" rid="aff13">
<sup>13</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2757281"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Jingfeng</given-names>
</name>
<xref ref-type="aff" rid="aff14">
<sup>14</sup>
</xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Xiao</surname>
<given-names>Yongqi</given-names>
</name>
<xref ref-type="aff" rid="aff15">
<sup>15</sup>
</xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Li</surname>
<given-names>Lun</given-names>
</name>
<xref ref-type="aff" rid="aff16">
<sup>16</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1081607"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Cui</surname>
<given-names>Junyou</given-names>
</name>
<xref ref-type="aff" rid="aff17">
<sup>17</sup>
</xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Huang</surname>
<given-names>Zheng</given-names>
</name>
<xref ref-type="aff" rid="aff18">
<sup>18</sup>
</xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Cheng</surname>
<given-names>Xiang</given-names>
</name>
<xref ref-type="aff" rid="aff19">
<sup>19</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/354435"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Yi</surname>
<given-names>Yuan</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Validation" vocab-term-identifier="https://credit.niso.org/contributor-roles/validation/">Validation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Liu</surname>
<given-names>Mengqi</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Validation" vocab-term-identifier="https://credit.niso.org/contributor-roles/validation/">Validation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Chen</surname>
<given-names>Cathy</given-names>
</name>
<xref ref-type="aff" rid="aff20">
<sup>20</sup>
</xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Validation" vocab-term-identifier="https://credit.niso.org/contributor-roles/validation/">Validation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Unverdorben</surname>
<given-names>Martin</given-names>
</name>
<xref ref-type="aff" rid="aff20">
<sup>20</sup>
</xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Validation" vocab-term-identifier="https://credit.niso.org/contributor-roles/validation/">Validation</role>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Ma</surname>
<given-names>Changsheng</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1223886"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Conceptualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/conceptualization/">Conceptualization</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Supervision" vocab-term-identifier="https://credit.niso.org/contributor-roles/supervision/">Supervision</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
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<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x26; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/">Writing &#x2013; review and editing</role>
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<on-behalf-of>ETNA-AF-China investigators</on-behalf-of>
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<aff id="aff1">
<label>1</label>
<institution>Beijing Anzhen Hospital, Capital Medical University</institution>, <city>Beijing</city>, <country country="CN">China</country>
</aff>
<aff id="aff2">
<label>2</label>
<institution>Daiichi Sankyo (China) Holdings Co., Ltd</institution>, <city>Shanghai</city>, <country country="CN">China</country>
</aff>
<aff id="aff3">
<label>3</label>
<institution>The Second Affiliated Hospital of Chongqing Medical University</institution>, <city>Chongqing</city>, <country country="CN">China</country>
</aff>
<aff id="aff4">
<label>4</label>
<institution>The First Hospital of Changsha</institution>, <city>Changsha</city>, <country country="CN">China</country>
</aff>
<aff id="aff5">
<label>5</label>
<institution>The Fifth People&#x2019;s Hospital of Jinan</institution>, <city>Jinan</city>, <country country="CN">China</country>
</aff>
<aff id="aff6">
<label>6</label>
<institution>Wenzhou Central Hospital</institution>, <city>Wenzhou</city>, <country country="CN">China</country>
</aff>
<aff id="aff7">
<label>7</label>
<institution>Nanjing Jiangning Hospital</institution>, <city>Nanjing</city>, <country country="CN">China</country>
</aff>
<aff id="aff8">
<label>8</label>
<institution>The Fifth Affiliated Hospital of Zhengzhou University</institution>, <city>Zhengzhou</city>, <country country="CN">China</country>
</aff>
<aff id="aff9">
<label>9</label>
<institution>Longhua Hospital Shanghai University of Traditional Chinese Medicine</institution>, <city>Shanghai</city>, <country country="CN">China</country>
</aff>
<aff id="aff10">
<label>10</label>
<institution>Kaifeng Central Hospital</institution>, <city>Kaifeng</city>, <country country="CN">China</country>
</aff>
<aff id="aff11">
<label>11</label>
<institution>The First Hospital of Kunming</institution>, <city>Kunming</city>, <country country="CN">China</country>
</aff>
<aff id="aff12">
<label>12</label>
<institution>Taiyuan Central Hospital of Shanxi Medical University</institution>, <city>Taiyuan</city>, <country country="CN">China</country>
</aff>
<aff id="aff13">
<label>13</label>
<institution>The First Affiliated Hospital of Chongqing Medical University</institution>, <city>Chongqing</city>, <country country="CN">China</country>
</aff>
<aff id="aff14">
<label>14</label>
<institution>Sun Yat-sen Memorial hospital, Sun Yat-sen University</institution>, <city>Guangzhou</city>, <country country="CN">China</country>
</aff>
<aff id="aff15">
<label>15</label>
<institution>The Third People&#x2019;s Hospital of Nanning</institution>, <city>Nanning</city>, <country country="CN">China</country>
</aff>
<aff id="aff16">
<label>16</label>
<institution>Wuhan Puai Hospital</institution>, <city>Wuhan</city>, <country country="CN">China</country>
</aff>
<aff id="aff17">
<label>17</label>
<institution>Jiangyin People&#x2019;s Hospital</institution>, <city>Wuxi</city>, <country country="CN">China</country>
</aff>
<aff id="aff18">
<label>18</label>
<institution>The First Affiliated Hospital of Guangzhou Medical University</institution>, <city>Guangzhou</city>, <country country="CN">China</country>
</aff>
<aff id="aff19">
<label>19</label>
<institution>Union Hospital Affiliated with Tongji Medical College of Huazhong University of Science and Technology</institution>, <city>Wuhan</city>, <country country="CN">China</country>
</aff>
<aff id="aff20">
<label>20</label>
<institution>Daiichi Sankyo Inc.</institution>, <city>Basking Ridge</city>, <state>NJ</state>, <country country="US">United States</country>
</aff>
<author-notes>
<corresp id="c001">
<label>&#x2a;</label>Correspondence: Changsheng Ma, <email xlink:href="mailto:chshma@vip.sina.com">chshma@vip.sina.com</email>
</corresp>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2026-01-22">
<day>22</day>
<month>01</month>
<year>2026</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2026</year>
</pub-date>
<volume>17</volume>
<elocation-id>1739246</elocation-id>
<history>
<date date-type="received">
<day>04</day>
<month>11</month>
<year>2025</year>
</date>
<date date-type="rev-recd">
<day>24</day>
<month>12</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>02</day>
<month>01</month>
<year>2026</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2026 Guo, Du, Yin, Qi, Jia, Ji, Zhang, Liang, Deng, Liu, Ma, Song, Feng, Luo, Wang, Xiao, Li, Cui, Huang, Cheng, Yi, Liu, Chen, Unverdorben and Ma.</copyright-statement>
<copyright-year>2026</copyright-year>
<copyright-holder>Guo, Du, Yin, Qi, Jia, Ji, Zhang, Liang, Deng, Liu, Ma, Song, Feng, Luo, Wang, Xiao, Li, Cui, Huang, Cheng, Yi, Liu, Chen, Unverdorben and Ma</copyright-holder>
<license>
<ali:license_ref start_date="2026-01-22">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>Introduction</title>
<p>Non&#x2013;vitamin K antagonist oral anticoagulants (NOACs) are the first-line therapy to prevent ischaemic stroke in patients with atrial fibrillation (AF). However, studies on the effectiveness and safety of edoxaban for Chinese patients with AF, are limited.</p>
</sec>
<sec>
<title>Methods</title>
<p>We report the 1-year interim follow-up data on edoxaban use in Chinese patients with AF from the ETNA-AF-China (NCT04747496), a multicentre, prospective, observational study conducted in 89 centres across the Chinese Mainland, enrolling 5,001 patients with a total of 2-year follow-up. No adjustment for multiple testing was made; therefore, all <italic>P</italic> values must be interpreted in an exploratory or descriptive manner.</p>
</sec>
<sec>
<title>Results</title>
<p>Overall, 4,877 patients (60&#xa0;mg edoxaban: 54.3%; 30&#xa0;mg edoxaban: 45.7%) completed 1-year follow-up (mean age &#xb1; standard deviation: 70.3 &#xb1; 9.5&#xa0;years; mean CHA<sub>2</sub>DS<sub>2</sub>-VASc score: 2.9 &#xb1; 1.4: mean HAS-BLED score: 1.8 &#xb1; 1.0). All-cause death occurred in 100 patients (annualised event rate: 2.30%/y), of whom 27 (0.62%/y) died from cardiovascular (CV) events. Annualised rates for major bleeding (45 patients [1.04%/y]), intracranial hemorrhage (ICH, nine patients [0.21%/y]), and major gastrointestinal bleeding (19 patients [0.44%/y]) were low. Patients receiving edoxaban 30&#xa0;mg had numerically higher rates of all-cause death, CV death, and major bleeding than edoxaban 60&#xa0;mg (<italic>P</italic> &#x3c; 0.05), potentially because of diverse baseline characteristics. Lower BMI, permanent AF type, history of major bleeding, and frailty identified as risk factors of all-cause death by multivariable Cox analysis. After 1&#xa0;year, 73.1% patients continued edoxaban use without suspension, discontinuation of edoxaban, or switching to other doses of edoxaban/other NOACs.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>In a large Chinese AF population, edoxaban showed low incidences of stroke and bleeding, notably major bleeding, ICH, major gastrointestinal bleeding, and CV mortalities, with the majority of patients still on edoxaban at the end of 1-year follow-up.</p>
</sec>
</abstract>
<kwd-group>
<kwd>atrial fibrillation</kwd>
<kwd>Chinese</kwd>
<kwd>edoxaban</kwd>
<kwd>non&#x2013;vitamin K antagonist oral anticoagulants</kwd>
<kwd>real-world</kwd>
</kwd-group>
<funding-group>
<funding-statement>The author(s) declared that financial support was received for this work and/or its publication. This study was funded by Daiichi Sankyo (China) Holdings Co., Ltd, Shanghai, China. The funder was not involved in the study design, collection, analysis, interpretation of data, the writing of this article, or the decision to submit it for publication. Editorial support was provided by Dr. Natasha Naval Aggarwal, Dr. Roopa Subbaiah, and Ashwini Patil, Indegene. Ltd., India, and was funded by Daiichi Sankyo (China) in accordance with the Good Publication Practice guidelines.</funding-statement>
</funding-group>
<counts>
<fig-count count="3"/>
<table-count count="3"/>
<equation-count count="0"/>
<ref-count count="42"/>
<page-count count="15"/>
</counts>
<custom-meta-group>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Cardiovascular and Smooth Muscle 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>Atrial fibrillation (AF) is the most common type of cardiac arrhythmia, affecting 2%&#x2013;4% of adults globally (<xref ref-type="bibr" rid="B3">Benjamin et al., 2019</xref>; <xref ref-type="bibr" rid="B38">Shi et al., 2022</xref>), with an estimated prevalence of 1.6% among Chinese adults (<xref ref-type="bibr" rid="B38">Shi et al., 2022</xref>). Globally, the prevalence of AF has increased over the past 2&#xa0;decades and is expected to continue growing for the next three&#xa0;decades, posing one of the largest public health challenges (<xref ref-type="bibr" rid="B30">Lippi et al., 2021</xref>). Recent studies have shown a rapid increase in the prevalence and the economic burden of AF in China, largely driven by an aging population, socio-economic growth, and a rising prevalence of its associated risk factors, including overweight or obesity (<xref ref-type="bibr" rid="B39">Sun et al., 2023</xref>). In 2021, the global prevalence of stroke was estimated at 93.8 million (<xref ref-type="bibr" rid="B16">Feigin et al., 2025</xref>), with &#x223c;17.8 million adults affected in China alone (<xref ref-type="bibr" rid="B40">Tu et al., 2023</xref>). Despite this, anticoagulation used among adults remains suboptimal. In Chinese community settings, AF management has seen limited progress, with oral anticoagulants being prescribed to only a small proportion (&#x223c;5%) of patients at high risk of stroke (<xref ref-type="bibr" rid="B24">Jiang et al., 2024</xref>). These gaps underscore the urgent need for regionally tailored analysis and a comprehensive strategy that integrates prevention and treatment of stroke (<xref ref-type="bibr" rid="B40">Tu et al., 2023</xref>).</p>
<p>Currently, non-vitamin K antagonist (VKA) oral anticoagulants (NOACs) are recommended as the first-choice treatment for preventing stroke and systemic embolism events (SEEs) in patients with AF (<xref ref-type="bibr" rid="B22">Hindricks et al., 2021</xref>; <xref ref-type="bibr" rid="B8">Chinese Society of Cardiology, Chinese Medical Association and Heart Rhythm Committee of Chinese Society of Biomedical Engineering, 2023</xref>; <xref ref-type="bibr" rid="B36">Schnabel et al., 2023</xref>; <xref ref-type="bibr" rid="B15">European Medicines Agency, 2024</xref>). Edoxaban, with the rapid onset mechanism of factor Xa direct inhibition, is administered orally at 60&#xa0;mg once daily (OD) and with a reduced dose of 30&#xa0;mg OD for patients with renal impairment (creatine clearance [CrCl] 15&#x2013;50&#xa0;mL/min, low body weight [&#x2264;60&#xa0;kg] or using specific P-glycoprotein [P-gp] inhibitors) by label recommendation (<xref ref-type="bibr" rid="B15">European Medicines Agency, 2024</xref>). Its antithrombotic efficacy was demonstrated in phase 3 of the ENGAGE AF-TIMI 48 trial reported, which showed reduced stroke or SEE events and lower rates of bleeding and cardiovascular (CV) death than warfarin in the non-valvular atrial fibrillation (NVAF) population (<xref ref-type="bibr" rid="B17">Giugliano et al., 2013</xref>). Based on this evidence, edoxaban was approved by the US Food and Drug Administration (FDA) (<xref ref-type="bibr" rid="B35">SAVAYSA, 2015</xref>), the European Medicines Agency (EMA), the Ministry of Health, Labour and Welfare (MHLW) in Japan, and the Korean Ministry of Food and Drug Safety (MFDS) in South Korea (<xref ref-type="bibr" rid="B9">Choi et al., 2021</xref>), for the prevention of ischemic stroke or SEE in AF. In China, edoxaban was approved in 2018 and added to the National Reimbursement Drug List in 2020 (<xref ref-type="bibr" rid="B42">Zhang et al., 2022</xref>). However, there is still limited real-world evidence on the clinical management of edoxaban use in the Chinese population with AF, and optimizing CV risk factors as part of an integrated approach to AF management (<xref ref-type="bibr" rid="B8">Chinese Society of Cardiology, Chinese Medical Association and Heart Rhythm Committee of Chinese Society of Biomedical Engineering, 2023</xref>; <xref ref-type="bibr" rid="B36">Schnabel et al., 2023</xref>; <xref ref-type="bibr" rid="B25">Joglar et al., 2024</xref>).</p>
<p>ETNA-AF-China is one of the Global Edoxaban Treatment in rouTine clinical prActice for patients with nonvalvular Atrial Fibrillation (ETNA-AF) programme, a large-scale noninterventional study that stands as the most extensive noninterventional study focusing on a single direct oral anticoagulant in clinical practice of AF with overall 2-year follow-up (<xref ref-type="bibr" rid="B12">De Caterina et al., 2019b</xref>; <xref ref-type="bibr" rid="B11">De Caterina et al., 2019a</xref>; <xref ref-type="bibr" rid="B13">De Caterina et al., 2021</xref>). The current analysis reports the 1-year interim cut-off data of the ongoing ETNA-AF-China study on the effectiveness and safety of edoxaban in Chinese patients with AF.</p>
</sec>
<sec sec-type="methods" id="s2">
<label>2</label>
<title>Methods</title>
<sec id="s2-1">
<label>2.1</label>
<title>Study design</title>
<p>ETNA-AF-China (Clinicaltrials.gov: NCT04747496) is a multicentre, prospective, observational study designed to evaluate the effectiveness and safety of edoxaban for stroke prevention in 89 sites across the Chinese Mainland, enrolling 5,001 patients with a total of 2-year follow-up. ETNA-AF-China included three predefined data cut-off points for analysis: baseline, 1-year outcomes, and final 2-year outcomes, based on scheduled follow-up data collection. Here, we present the first 1-year follow-up outcomes based on the interim data cut-off on 1 February 2024; data are subject to change as data collection was ongoing at the time of interim data cut-off. Final data cleaning for 2-year follow-up is ongoing. The detailed study design and rationale of the Global ETNA-AF programme, and baseline characteristics of ETNA-AF-China were previously published (<xref ref-type="bibr" rid="B12">De Caterina et al., 2019b</xref>; <xref ref-type="bibr" rid="B11">De Caterina et al., 2019a</xref>; <xref ref-type="bibr" rid="B21">Guo et al., 2024</xref>).</p>
</sec>
<sec id="s2-2">
<label>2.2</label>
<title>Patient population</title>
<p>Patients with a history of NVAF who were prescribed edoxaban at enrolment or baseline (&#x2264;1&#xa0;week after baseline) and did not simultaneously participate in an interventional trial were eligible upon providing written consent. No exclusion criteria were present to avoid any possible selection bias.</p>
</sec>
<sec id="s2-3">
<label>2.3</label>
<title>Objectives, definitions, and outcome measures</title>
<p>The primary objective of the study was to evaluate the real-world safety of edoxaban by evaluating bleeding events (including major, major or clinically relevant non-major [CRNM] bleeding according to the International Society on Thrombosis and Haemostasis&#x2019;s [ISTH] definition) (<xref ref-type="bibr" rid="B37">Schulman and Kearon, 2005</xref>) intracranial haemorrhage [ICH], all-cause and CV mortality in patients with AF. Stroke (ischaemic, haemorrhagic, and unknown), SEEs, transient ischaemic attack (TIA), and myocardial infarction (MI) were evaluated as secondary outcomes.</p>
<p>The CHA<sub>2</sub>DS<sub>2</sub>-VASc and HAS-BLED scores were both centrally calculated based on the investigator-reported baseline clinical characteristics of patients. The DOAC score was calculated based on the development and validation by R. Aggarwal (<xref ref-type="bibr" rid="B1">Aggarwal et al., 2023</xref>). The &#x2018;recommended dose&#x2019; for edoxaban treatment is 60&#xa0;mg OD as labelled and 30&#xa0;mg OD for those who met at least one of the following criteria: (1) moderate-severe renal impairment (CrCl &#x2264;50&#xa0;mL/min), (2) body weight &#x2264;60&#xa0;kg and (3), concomitant use of label-listed P-gp inhibitors. &#x201c;Non-recommended dose&#x201d; is referred to as not in line with label recommendation, that is, 60&#xa0;mg was considered non-recommended if the patient fulfilled at least one dose reduction criterion, or 30&#xa0;mg was non-recommended if the patient did not meet any dose reduction criterion.</p>
</sec>
<sec id="s2-4">
<label>2.4</label>
<title>Statistical analysis</title>
<p>Statistical analyses were performed on the full analysis set (FAS). FAS was defined as all patients with any documentation (such as post-baseline ADRs, AF-related clinical events, or hospitalisations) from at least one follow-up data collection or at final assessment (any information except &#x201c;lost to follow-up&#x201d;) from BAS.</p>
<p>Baseline analysis set (BAS) was defined as: (1) the patient with a confirmed history of NVAF by an electrical test (e.g., electrocardiogram, Holter monitoring, pacemaker, or implantable cardioverter-defibrillator). (2) The investigator confirmed that the patient was receiving treatment with edoxaban after providing informed consent. In addition, those patients who were judged by the investigator as not receiving edoxaban treatment after providing informed consent were additionally checked whether edoxaban initiation date was at least within 7&#xa0;days after baseline visit date. (3) The patient not concurrently participating in any other interventional studies was included (<xref ref-type="sec" rid="s13">Supplementary Figure S1</xref>).</p>
<p>The baseline characteristics were summarised descriptively as frequencies (&#x201c;n&#x201d; and percentage) and mean value &#xb1; standard deviation (SD) rounded to an integer. Patient characteristics between the 60&#xa0;mg and 30&#xa0;mg dose groups were compared using the chi-square test for the categorical data and the Mann&#x2013;Whitney <italic>U</italic> test for the continuous data. The normality of continuous data was checked using the Shapiro test. Adherence to label-recommendation (recommended dose/non-recommended dose) was calculated by dose prescription at baseline.</p>
<p>Based on the reported events of the investigators, annualised event rates of the safety and effectiveness outcomes were presented. No preplanned central adjudication of this real-world study was carried out; all events were reported by qualified investigators. Annualised event rates were estimated by censoring those lost to follow-up or premature termination. Annual rates were based on time exposure of whole population regardless of the discontinuation of edoxaban or edoxaban dose. The annualised event rates were calculated as 100&#x2a;[number of patients with at least one event within 2&#xa0;years after baseline] divided by [the sum of all individual patient observation time]. Individual patient observation time was defined as time in years from baseline data collection point (i.e., reference start date) until first event date (within 2&#xa0;years after baseline), or if patient completed/discontinued from the study without experiencing an event (within 2&#xa0;years after baseline), until the date of premature study discontinuation, or death, or last available follow-up date, or censoring after 24&#xa0;months from baseline data collection point whichever occurred first.</p>
<p>Kaplan&#x2013;Meier curves were used to present the cumulative event rates of all stroke/SEE/TIA, major bleeding, and all-cause mortality. Two or more time-to-event data points of the curves were compared using the log-rank test. Univariable Cox regression analysis identified the hazard ratio (HR) and 95% confidence interval (CI) for recommended or non-recommended doses and 30&#xa0;mg versus 60&#xa0;mg related outcomes.</p>
<p>Multivariable Cox model was conducted using a stepwise regression method by the Akaike Information Criterion for all covariables while fixing edoxaban dosing (60&#xa0;mg and 30&#xa0;mg) and recommended/non-recommended doses. The prespecified variables included edoxaban dose, age category, gender, body mass index (BMI) category, creatinine clearance category, economic region, CHA<sub>2</sub>DS<sub>2</sub>-VASc score, modified HAS-BLED score, AF type, frailty, chronic obstructive pulmonary disease, prior TIA, hypertension, heart failure, diabetes, dyslipidaemia, valvular heart disease, prior stroke at baseline, and prior major bleeding.</p>
<p>Statistical analyses were performed using R Statistical Software (version 4.3.2, Boston, Massachusetts, United States). No adjustment for multiple testing was made; therefore, all P values must be interpreted in a purely exploratory or descriptive way.</p>
</sec>
<sec id="s2-5">
<label>2.5</label>
<title>Ethical standards</title>
<p>The study was approved by the institutional review boards and independent Ethics Committees from Beijing Anzhen Hospital (No. 2019-058D) and all participating centres in compliance with the Declaration of Helsinki and Guidelines for Good Pharmacoepidemiology Practice (GPP) (<xref ref-type="bibr" rid="B34">Public Policy Committee, International Society of Pharmacoepidemiology, 2016</xref>). All participants provided written informed consent.</p>
</sec>
</sec>
<sec sec-type="results" id="s3">
<label>3</label>
<title>Results</title>
<sec id="s3-1">
<label>3.1</label>
<title>Baseline characteristics</title>
<p>Of the overall 5,001 patients enrolled in the study, 124 patients were excluded because of either receiving unspecified doses, starting edoxaban more than 1&#xa0;week after baseline, participating simultaneously in other interventional studies, or being lost to follow-up without any post-baseline documentation (<xref ref-type="sec" rid="s13">Supplementary Figure S1</xref>). The baseline demographics and clinical characteristics of the FAS, consisting of 4,877 patients, with 2,650 patients (54.3%) initially received edoxaban 60&#xa0;mg and 2,227 (45.7%) received 30&#xa0;mg, are presented in <xref ref-type="table" rid="T1">Table 1</xref>. The overall mean (SD) patient age was 70.3 &#xb1; 9.5&#xa0;years, and 2,780 patients (57.0%) were male. The majority of the patient population belonged to the Eastern economic region (49.9%), followed by the Middle (33.5%), Northeastern (8.6%), and Western economic regions (8.1%) in China. The mean (SD) body weight was 67.9 &#xb1; 12.5&#xa0;kg, and the mean (SD) body mass index (BMI) was 25.0 &#xb1; 3.7&#xa0;kg/m<sup>2</sup>. The calculated mean (SD) CrCl by the Cockcroft&#x2013;Gault formula was 71.0 &#xb1; 27.2&#xa0;mL/min, and the mean (SD) estimated glomerular filtration rate (eGFR) by CrCl normalized to 1.73&#xa0;m<sup>2</sup> of body surface area using the Du Bois and Du Bois formula (<xref ref-type="bibr" rid="B32">Michels et al., 2010</xref>) was 58.7 &#xb1; 19.8&#xa0;mL/min/1.73&#xa0;m<sup>2</sup>. The calculated mean (SD) CHA<sub>2</sub>DS<sub>2</sub>-VASc and modified HAS-BLED scores were 2.9 &#xb1; 1.4 and 1.8 &#xb1; 1.0, respectively.</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Baseline demographics and clinical characteristics for the overall population.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Baseline characteristics</th>
<th align="left">Total [<italic>n</italic> &#x3d; 4,877]<xref ref-type="table-fn" rid="Tfn1">
<sup>a</sup>
</xref> (100%)</th>
<th align="left">60&#xa0;mg [<italic>n</italic> &#x3d; 2,650] (54.3%)</th>
<th align="left">30&#xa0;mg [<italic>n</italic> &#x3d; 2,227] (45.7%)</th>
<th align="left">
<italic>P</italic> value</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Male, <italic>n</italic> (%)</td>
<td align="left">2,780 (57.0)</td>
<td align="left">1812 (68.4)</td>
<td align="left">968 (43.5)</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">Age (years), mean (SD)</td>
<td align="left">70.3 (9.5)</td>
<td align="left">67.6 (9.1)</td>
<td align="left">73.4 (9.0)</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">By age sub-groups, <italic>n</italic> (%)</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">&#x3c;65&#xa0;years</td>
<td align="left">1,138 (23.3)</td>
<td align="left">820 (30.9)</td>
<td align="left">318 (14.3)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">&#x2265;65&#x2013;&#x3c;75&#xa0;years</td>
<td align="left">2039 (41.8)</td>
<td align="left">1,232 (46.5)</td>
<td align="left">807 (36.2)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">&#x2265;75&#x2013;&#x3c;85&#xa0;years</td>
<td align="left">1,468 (30.1)</td>
<td align="left">556 (21.0)</td>
<td align="left">912 (41.0)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">&#x2265;85&#xa0;years</td>
<td align="left">232 (4.8)</td>
<td align="left">42 (1.6)</td>
<td align="left">190 (8.5)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">Body weight<xref ref-type="table-fn" rid="Tfn2">
<sup>b</sup>
</xref> (kg), mean (SD)</td>
<td align="left">67.9 (12.5)</td>
<td align="left">73.3 (11.0)</td>
<td align="left">61.5 (11.1)</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">BMI<xref ref-type="table-fn" rid="Tfn3">
<sup>c</sup>
</xref> (kg/m<sup>2</sup>), mean (SD)</td>
<td align="left">25.0 (3.7)</td>
<td align="left">26.2 (3.4)</td>
<td align="left">23.5 (3.4)</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">By BMI subgroups, n (%)</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">&#x3c;18.5&#xa0;kg/m<sup>2</sup>
</td>
<td align="left">130 (2.7)</td>
<td align="left">6 (0.2)</td>
<td align="left">124 (5.6)</td>
<td align="left">&#x200b;</td>
</tr>
<tr>
<td align="left">&#x2265;18.5&#x2013;&#x3c; 25&#xa0;kg/m<sup>2</sup>
</td>
<td align="left">2,367 (48.5)</td>
<td align="left">991 (37.4)</td>
<td align="left">1,376 (61.8)</td>
<td align="left">&#x200b;</td>
</tr>
<tr>
<td align="left">&#x2265;25&#xa0;kg/m<sup>2</sup>
</td>
<td align="left">2,273 (46.6)</td>
<td align="left">1,623 (61.2)</td>
<td align="left">650 (29.2)</td>
<td align="left">&#x200b;</td>
</tr>
<tr>
<td align="left">(calc) creatinine clearance<xref ref-type="table-fn" rid="Tfn4">
<sup>d</sup>
</xref> (mL/min), mean (SD)</td>
<td align="left">71.0 (27.2)</td>
<td align="left">81.5 (26.2)</td>
<td align="left">59.2 (23.2)</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">By CrCl subgroups, <italic>n</italic> (%)</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">&#x2265;80&#xa0;mL/min</td>
<td align="left">1,262 (25.9)</td>
<td align="left">962 (36.3)</td>
<td align="left">300 (13.5)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">&#x2265;50&#x2013;&#x3c;80&#xa0;mL/min</td>
<td align="left">1865 (38.2)</td>
<td align="left">1,002 (37.8)</td>
<td align="left">863 (38.8)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">&#x2265;30&#x2013;&#x3c;50&#xa0;mL/min</td>
<td align="left">709 (14.5)</td>
<td align="left">123 (4.6)</td>
<td align="left">586 (26.3)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">&#x3c;30&#xa0;mL/min</td>
<td align="left">131 (2.7)</td>
<td align="left">10 (0.4)</td>
<td align="left">121 (5.4)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">(calc) eGFR<xref ref-type="table-fn" rid="Tfn5">
<sup>e</sup>
</xref> (mL/min/1.73&#xa0;m<sup>2</sup>), mean (SD)</td>
<td align="left">58.7 (19.8)</td>
<td align="left">64.7 (18.6)</td>
<td align="left">51.9 (18.8)</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">(calc) CHA<sub>2</sub>DS<sub>2</sub>-VASc score<xref ref-type="table-fn" rid="Tfn6">
<sup>f</sup>
</xref>, mean (SD)</td>
<td align="left">2.9 (1.4)</td>
<td align="left">2.6 (1.3)</td>
<td align="left">3.3 (1.4)</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">(calc) CHA<sub>2</sub>DS<sub>2</sub>-VA score<xref ref-type="table-fn" rid="Tfn7">
<sup>g</sup>
</xref>, mean (SD)</td>
<td align="left">2.9 (1.4)</td>
<td align="left">2.6 (1.4)</td>
<td align="left">3.1 (1.5)</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">(mod) HAS-BLED score<xref ref-type="table-fn" rid="Tfn8">
<sup>h</sup>
</xref>, mean (SD)</td>
<td align="left">1.8 (1.0)</td>
<td align="left">1.5 (1.0)</td>
<td align="left">2.0 (0.9)</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">DOAC score<xref ref-type="table-fn" rid="Tfn9">
<sup>i</sup>
</xref>, mean (SD)</td>
<td align="left">4.3 (2.3)</td>
<td align="left">3.6 (2.1)</td>
<td align="left">5.1 (2.3)</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">Type of AF<xref ref-type="table-fn" rid="Tfn10">
<sup>j</sup>
</xref>, <italic>n</italic> (%)</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">0.02</td>
</tr>
<tr>
<td align="left">Paroxysmal</td>
<td align="left">1780 (36.5)</td>
<td align="left">918 (34.6)</td>
<td align="left">862 (38.7)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">Persistent</td>
<td align="left">1,584 (32.5)</td>
<td align="left">862 (32.5)</td>
<td align="left">722 (32.4)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">Long-standing persistent</td>
<td align="left">828 (17.0)</td>
<td align="left">484 (18.3)</td>
<td align="left">344 (15.4)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">Permanent</td>
<td align="left">669 (13.7)</td>
<td align="left">377 (14.2)</td>
<td align="left">292 (13.1)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">LVEF categorised by 40%<xref ref-type="table-fn" rid="Tfn11">
<sup>k</sup>
</xref>
</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">0.09</td>
</tr>
<tr>
<td align="left">&#x3c;40%</td>
<td align="left">163 (6.4)</td>
<td align="left">78 (5.8)</td>
<td align="left">85 (7.1)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">&#x2265;40%</td>
<td align="left">2,379 (93.6)</td>
<td align="left">1,274 (94.2)</td>
<td align="left">1,105 (92.9)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">Perceived frailty<xref ref-type="table-fn" rid="Tfn12">
<sup>l</sup>
</xref>, <italic>n</italic> (%)</td>
<td align="left">309 (6.3)</td>
<td align="left">89 (3.4)</td>
<td align="left">220 (9.9)</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">COPD<xref ref-type="table-fn" rid="Tfn13">
<sup>m</sup>
</xref>, <italic>n</italic> (%)</td>
<td align="left">234 (4.8)</td>
<td align="left">109 (4.1)</td>
<td align="left">125 (5.6)</td>
<td align="left">0.02</td>
</tr>
<tr>
<td align="left">Hypertension<xref ref-type="table-fn" rid="Tfn14">
<sup>n</sup>
</xref>, <italic>n</italic> (%)</td>
<td align="left">3,581 (73.4)</td>
<td align="left">2010 (75.8)</td>
<td align="left">1,571 (70.5)</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">Heart failure (derived)<xref ref-type="table-fn" rid="Tfn15">
<sup>o</sup>
</xref>, <italic>n</italic> (%)</td>
<td align="left">716 (14.7)</td>
<td align="left">326 (12.3)</td>
<td align="left">390 (17.5)</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">Diabetes mellitus<xref ref-type="table-fn" rid="Tfn16">
<sup>p</sup>
</xref>, <italic>n</italic> (%)</td>
<td align="left">1,284 (26.3)</td>
<td align="left">737 (27.8)</td>
<td align="left">547 (24.6)</td>
<td align="left">0.01</td>
</tr>
<tr>
<td align="left">Dyslipidaemia<xref ref-type="table-fn" rid="Tfn15">
<sup>o</sup>
</xref>
<sup>,</sup>
<xref ref-type="table-fn" rid="Tfn17">
<sup>q</sup>
</xref>, <italic>n</italic> (%)</td>
<td align="left">1,225 (25.1)</td>
<td align="left">723 (27.3)</td>
<td align="left">502 (22.5)</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">Valvular disease<xref ref-type="table-fn" rid="Tfn18">
<sup>r</sup>
</xref>, <italic>n</italic> (%)</td>
<td align="left">265 (5.4)</td>
<td align="left">118 (4.5)</td>
<td align="left">147 (6.6)</td>
<td align="left">0.001</td>
</tr>
<tr>
<td align="left">History of ischaemic stroke, <italic>n</italic> (%)</td>
<td align="left">351 (7.2)</td>
<td align="left">169 (6.4)</td>
<td align="left">182 (8.2)</td>
<td align="left">0.02</td>
</tr>
<tr>
<td align="left">History of TIA, <italic>n</italic> (%)</td>
<td align="left">108 (2.2)</td>
<td align="left">57 (2.2)</td>
<td align="left">51 (2.3)</td>
<td align="left">0.82</td>
</tr>
<tr>
<td align="left">History of major or CRNM bleeding, <italic>n</italic> (%)</td>
<td align="left">62 (1.3)</td>
<td align="left">32 (1.2)</td>
<td align="left">30 (1.3)</td>
<td align="left">0.76</td>
</tr>
<tr>
<td align="left">History of major bleeding, <italic>n</italic> (%)</td>
<td align="left">54 (1.1)</td>
<td align="left">30 (1.1)</td>
<td align="left">24 (1.1)</td>
<td align="left">0.97</td>
</tr>
<tr>
<td align="left">Overall adherence to label<xref ref-type="table-fn" rid="Tfn19">
<sup>s</sup>
</xref>, <italic>n</italic> (%)</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">Recommended edoxaban dose</td>
<td align="left">3,269 (78.0)</td>
<td align="left">1790 (83.8)</td>
<td align="left">1,479 (71.9)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">Non-recommended edoxaban dose</td>
<td align="left">923 (22.0)</td>
<td align="left">345 (16.2)</td>
<td align="left">578 (28.1)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">Economic region, <italic>n</italic> (%)</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">East</td>
<td align="left">2,432 (49.9)</td>
<td align="left">1,447 (54.6)</td>
<td align="left">985 (44.2)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">Northeast</td>
<td align="left">417 (8.6)</td>
<td align="left">254 (9.6)</td>
<td align="left">163 (7.3)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">Middle</td>
<td align="left">1,632 (33.5)</td>
<td align="left">768 (29.0)</td>
<td align="left">864 (38.8)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">West</td>
<td align="left">396 (8.1)</td>
<td align="left">181 (6.8)</td>
<td align="left">215 (9.7)</td>
<td align="left">-</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="Tfn1">
<label>
<sup>a</sup>
</label>
<p>Based on full analysis set (FAS); all percentages are based on the total number of patients with all observations (including missing and unknown data).</p>
</fn>
<fn id="Tfn2">
<label>
<sup>b</sup>
</label>
<p>Body weight was missing for 55 patients.</p>
</fn>
<fn id="Tfn3">
<label>
<sup>c</sup>
</label>
<p>BMI, was missing for 107 patients.</p>
</fn>
<fn id="Tfn4">
<label>
<sup>d</sup>
</label>
<p>The CrCl calculation was based on the Cockcroft-Gault formula and was missing for 910 patients.</p>
</fn>
<fn id="Tfn5">
<label>
<sup>e</sup>
</label>
<p>eGFR, was calculated by the Du Bois and Du Boi method; it was missing for 973 patients.</p>
</fn>
<fn id="Tfn6">
<label>
<sup>f</sup>
</label>
<p>Derived variables of the CHA<sub>2</sub>DS<sub>2</sub>-VASc, score, CHA<sub>2</sub>DS<sub>2</sub>-VA, score and HAS-BLED, score. 138 patients had a missing CHA<sub>2</sub>DS<sub>2</sub>-VASc, score.</p>
</fn>
<fn id="Tfn7">
<label>
<sup>g</sup>
</label>
<p>165 patients had a missing CHA<sub>2</sub>DS<sub>2</sub>-VA, score.</p>
</fn>
<fn id="Tfn8">
<label>
<sup>h</sup>
</label>
<p>The HAS-BLED, score was calculated without &#x2018;labile INR&#x2019;; the renal impairment item was derived instead of investigator reported; alcohol abuse was defined as &#x3e;1 drink/d; missing for 565 patients.</p>
</fn>
<fn id="Tfn9">
<label>
<sup>i</sup>
</label>
<p>DOAC, score was missing for 539 patients.</p>
</fn>
<fn id="Tfn10">
<label>
<sup>j</sup>
</label>
<p>AF, type was missing for 16 patients.</p>
</fn>
<fn id="Tfn11">
<label>
<sup>k</sup>
</label>
<p>LVEF, data were missing for 2,335 patients (1,298 and 1,037 patients in the edoxaban 60&#xa0;mg and 30&#xa0;mg groups, respectively).</p>
</fn>
<fn id="Tfn12">
<label>
<sup>l</sup>
</label>
<p>Perceived frailty was missing for 867 patients.</p>
</fn>
<fn id="Tfn13">
<label>
<sup>m</sup>
</label>
<p>COPD, was missing for 87 patients.</p>
</fn>
<fn id="Tfn14">
<label>
<sup>n</sup>
</label>
<p>Hypertension was unknown in 22 patients.</p>
</fn>
<fn id="Tfn15">
<label>
<sup>o</sup>
</label>
<p>Patients were considered as heart failure with documented congestive HF, documented ischaemic cardiomyopathy, LVEF &#x3c;40%, or frequent dyspnoea (&#x2265;1/d) without COPD, and at least one of the following: documented severe valvular heart disease, documented CAD, post-myocardial infarction, valve replacement or documented hypertension treated with at least three drugs.</p>
</fn>
<fn id="Tfn16">
<label>
<sup>p</sup>
</label>
<p>Diabetes mellitus was unknown for 35 patients.</p>
</fn>
<fn id="Tfn17">
<label>
<sup>q</sup>
</label>
<p>Dyslipidaemia was unknown for 123 patients.</p>
</fn>
<fn id="Tfn18">
<label>
<sup>r</sup>
</label>
<p>Valvular disease was unknown for 114 patients.</p>
</fn>
<fn id="Tfn19">
<label>
<sup>s</sup>
</label>
<p>Recommended doses were calculated based on the percentage of judgeable patients (<italic>n</italic> &#x3d; 4,192); 685 patients were non-judgable dosing. <italic>P</italic> values were calculated by comparing 30&#xa0;mg and 60&#xa0;mg dose levels.</p>
</fn>
<fn>
<p>AF, atrial fibrillation; BMI, body mass index; COPD, chronic obstructive pulmonary disease; CrCl, creatinine clearance; CRNM, clinically relevant non-major; eGFR, estimated glomerular filtration rate; LVEF, left ventricular ejection fraction; TIA, transient ischaemic attack; SD, standard deviation.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>Most of the patients presented with paroxysmal (1780; 36.5%) and persistent AF (1,548; 32.5%), with only 17% and 13.7% of them having long-standing persistent and permanent AF, respectively. The majority of the patients (2,379; 93.6%) had a left ventricular ejection fraction of &#x2265;40%. The extent of perceived frailty was minimal (309; 6.3%).</p>
<p>Patients receiving 30&#xa0;mg edoxaban OD at baseline were older (mean 73.4&#xa0;years vs. 67.6&#xa0;years) had higher CHA<sub>2</sub>DS<sub>2</sub>-VASc score (3.3 vs. 2.6), CHA<sub>2</sub>DS<sub>2</sub>-VA score (3.1 vs. 2.6), modified HAS-BLED score (2.0 vs. 1.5), DOAC score (5.1 vs. 3.6), and more percentage of impaired renal function (CrCl &#x3c;80&#xa0;mL/min: 70.5% vs. 42.8%) than those receiving 60&#xa0;mg (all <italic>P</italic> &#x3c; 0.001). When compared with the 60&#xa0;mg group, the 30&#xa0;mg group had a higher proportion of patients with perceived frailty (9.9% vs. 3.4%; <italic>P</italic> &#x3c; 0.001), higher proportion of HF (17.5% vs. 12.3%; <italic>P</italic> &#x3c; 0.001), and valvular disease (6.6% vs. 4.5%, <italic>P</italic> &#x3d; 0.001), whereas a smaller percentage of hypertension (70.5% vs. 75.8%, <italic>P</italic> &#x3c; 0.001) and dyslipidaemia (22.5% vs. 27.3%, <italic>P</italic> &#x3c; 0.001) (<xref ref-type="sec" rid="s13">Supplementary Table S1</xref>; <xref ref-type="sec" rid="s13">Supplementary Figure S2</xref>).</p>
<p>The overall adherence of edoxaban to the label recommendation was high (3,269/4,192 [with evaluable data]; 78.0%; <italic>P</italic> &#x3c; 0.001), with a numerically higher adherence rate of recommended 60&#xa0;mg (1790; 83.8%) than recommended 30&#xa0;mg (1,479; 71.9%) (<xref ref-type="table" rid="T1">Table 1</xref>).</p>
<p>The baseline demographics and clinical characteristics of the patients based on the dosing recommendation in accordance with label, with 1790 patients (36.7%) initially received recommended 60&#xa0;mg edoxaban, 578 (11.9%) received non-recommended 30&#xa0;mg, 1,479 patients (30.3%) received recommended 30&#xa0;mg, and 345 patients (7.1%) received non-recommended 60&#xa0;mg, are presented in <xref ref-type="table" rid="T2">Table 2</xref>.</p>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>Baseline demographics and clinical characteristics by dosing recommendation in accordance with label&#x2a;.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Baseline characteristics</th>
<th align="left">Recommended 60&#xa0;mg [n &#x3d; 1790] (36.7%)</th>
<th align="left">Non-recommended 30&#xa0;mg [n &#x3d; 578] (11.9%)</th>
<th align="left">P value</th>
<th align="left">Recommended 30&#xa0;mg [n &#x3d; 1,479] (30.3%)</th>
<th align="left">Non-recommended 60&#xa0;mg [n &#x3d; 345] (7.1%)</th>
<th align="left">P value</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Male, n (%)</td>
<td align="left">1,278 (71.4%)</td>
<td align="left">371 (64.2%)</td>
<td align="left">0.001</td>
<td align="left">506 (34.2%)</td>
<td align="left">161 (46.7%)</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">Age (years), mean (SD)</td>
<td align="left">67.0 (8.9)</td>
<td align="left">71.4 (9.1)</td>
<td align="left">&#x3c;0.001</td>
<td align="left">74.2 (8.8)</td>
<td align="left">71.5 (8.6)</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">By age sub-groups, n (%)</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">&#x3c;0.001</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">&#x3c;65&#xa0;years</td>
<td align="left">585 (32.7%)</td>
<td align="left">109 (18.9%)</td>
<td align="left">-</td>
<td align="left">184 (12.4%)</td>
<td align="left">64 (18.6%)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">65&#x2013;74&#xa0;years</td>
<td align="left">854 (47.7%)</td>
<td align="left">243 (42.0%)</td>
<td align="left">-</td>
<td align="left">512 (34.6%)</td>
<td align="left">150 (43.5%)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">75&#x2013;84&#xa0;years</td>
<td align="left">333 (18.6%)</td>
<td align="left">194 (33.6%)</td>
<td align="left">-</td>
<td align="left">643 (43.5%)</td>
<td align="left">112 (32.5%)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">&#x2265;85&#xa0;years</td>
<td align="left">18 (1.0%)</td>
<td align="left">32 (5.5%)</td>
<td align="left">-</td>
<td align="left">140 (9.5%)</td>
<td align="left">19 (5.5%)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">Body weight<xref ref-type="table-fn" rid="Tfn21">
<sup>b</sup>
</xref> (kg), mean (SD)</td>
<td align="left">75.3 (10.1)</td>
<td align="left">72.8 (8.4)</td>
<td align="left">&#x3c;0.001</td>
<td align="left">56.1 (7.9)</td>
<td align="left">60.5 (6.8)</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">BMI<xref ref-type="table-fn" rid="Tfn22">
<sup>c</sup>
</xref> (kg/m<sup>2</sup>), mean (SD)</td>
<td align="left">26.7 (3.2)</td>
<td align="left">26.3 (3.1)</td>
<td align="left">0.004</td>
<td align="left">22.1 (2.8)</td>
<td align="left">23.2 (2.6)</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">By BMI subgroups, n (%)</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">0.03</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">&#x3c;18.5&#xa0;kg/m<sup>2</sup>
</td>
<td align="left">0 (0.0%)</td>
<td align="left">0 (0.0%)</td>
<td align="left">-</td>
<td align="left">124 (8.4%)</td>
<td align="left">6 (1.7%)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">(18.5&#x2013;25) kg/m<sup>2</sup>
</td>
<td align="left">553 (30.9%)</td>
<td align="left">205 (35.5%)</td>
<td align="left">-</td>
<td align="left">1,122 (75.9%)</td>
<td align="left">265 (76.8%)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">&#x2265;25&#xa0;kg/m<sup>2</sup>
</td>
<td align="left">1,229 (68.7%)</td>
<td align="left">363 (62.8%)</td>
<td align="left">-</td>
<td align="left">202 (13.7%)</td>
<td align="left">70 (20.3%)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">(calc) creatinine clearance<xref ref-type="table-fn" rid="Tfn23">
<sup>d</sup>
</xref> (mL/min), mean (SD)</td>
<td align="left">85.4 (25.2)</td>
<td align="left">76.4 (21.5)</td>
<td align="left">&#x3c;0.001</td>
<td align="left">51.3 (19.5)</td>
<td align="left">57.5 (19.1)</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">By CrCL (mL/min), n (%)</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">&#x3c;0.001</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">0.002</td>
</tr>
<tr>
<td align="left">&#x2265;80&#xa0;mL/min</td>
<td align="left">920 (51.4%)</td>
<td align="left">201 (34.8%)</td>
<td align="left">-</td>
<td align="left">96 (6.5%)</td>
<td align="left">34 (9.9%)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">&#x2265;50&#x2013;&#x3c;80&#xa0;mL/min</td>
<td align="left">870 (48.6%)</td>
<td align="left">377 (65.2%)</td>
<td align="left">-</td>
<td align="left">477 (32.3%)</td>
<td align="left">126 (36.5%)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">&#x2265;30&#x2013;&#x3c;50&#xa0;mL/min</td>
<td align="left">0 (0.0%)</td>
<td align="left">0 (0.0%)</td>
<td align="left">-</td>
<td align="left">586 (39.6%)</td>
<td align="left">123 (35.7%)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">&#x3c;30&#xa0;mL/min</td>
<td align="left">0 (0.0%)</td>
<td align="left">0 (0.0%)</td>
<td align="left">-</td>
<td align="left">121 (8.2%)</td>
<td align="left">10 (2.9%)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">(calc) eGFR<xref ref-type="table-fn" rid="Tfn24">
<sup>e</sup>
</xref> (mL/min/1.73&#xa0;m<sup>2</sup>), mean (SD)</td>
<td align="left">66.9 (17.8)</td>
<td align="left">61.2 (16.2)</td>
<td align="left">&#x3c;0.001</td>
<td align="left">47.6 (18.3)</td>
<td align="left">51.3 (17.9)</td>
<td align="left">0.001</td>
</tr>
<tr>
<td align="left">(calc) CHA<sub>2</sub>DS<sub>2</sub>-VASc score<xref ref-type="table-fn" rid="Tfn25">
<sup>f</sup>
</xref>, mean (SD)</td>
<td align="left">2.5 (1.3)</td>
<td align="left">3.0 (1.4)</td>
<td align="left">&#x3c;0.001</td>
<td align="left">3.4 (1.4)</td>
<td align="left">3.1 (1.3)</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">(calc) CHA<sub>2</sub>DS<sub>2</sub>-VA score<xref ref-type="table-fn" rid="Tfn26">
<sup>g</sup>
</xref>, mean (SD)</td>
<td align="left">2.7 (1.4)</td>
<td align="left">3.1 (1.5)</td>
<td align="left">&#x3c;0.001</td>
<td align="left">3.2 (1.5)</td>
<td align="left">2.9 (1.4)</td>
<td align="left">0.01</td>
</tr>
<tr>
<td align="left">(mod) HAS-BLED score<xref ref-type="table-fn" rid="Tfn27">
<sup>h</sup>
</xref>, mean (SD)</td>
<td align="left">1.5 (1.0)</td>
<td align="left">1.9 (1.0)</td>
<td align="left">&#x3c;0.001</td>
<td align="left">2.1 (0.9)</td>
<td align="left">2.0 (0.9)</td>
<td align="left">0.04</td>
</tr>
<tr>
<td align="left">DOAC score<xref ref-type="table-fn" rid="Tfn28">
<sup>i</sup>
</xref>, mean (SD)</td>
<td align="left">3.5 (2.1)</td>
<td align="left">4.4 (2.2)</td>
<td align="left">&#x3c;0.001</td>
<td align="left">5.4 (2.3)</td>
<td align="left">4.7 (2.3)</td>
<td align="left">&#x3c;0.001</td>
</tr>
<tr>
<td align="left">Type of AF<xref ref-type="table-fn" rid="Tfn29">
<sup>j</sup>
</xref>, <italic>n</italic> (%)</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">0.51</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">0.11</td>
</tr>
<tr>
<td align="left">Paroxysmal</td>
<td align="left">660 (36.9%)</td>
<td align="left">217 (37.5%)</td>
<td align="left">-</td>
<td align="left">575 (38.9%)</td>
<td align="left">117 (33.9%)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">Persistent</td>
<td align="left">585 (32.7%)</td>
<td align="left">200 (34.6%)</td>
<td align="left">-</td>
<td align="left">478 (32.3%)</td>
<td align="left">107 (31.0%)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">Permanent</td>
<td align="left">241 (13.5%)</td>
<td align="left">72 (12.5%)</td>
<td align="left">-</td>
<td align="left">194 (13.1%)</td>
<td align="left">49 (14.2%)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">Long-standing persistent</td>
<td align="left">300 (16.8%)</td>
<td align="left">86 (14.9%)</td>
<td align="left">-</td>
<td align="left">228 (15.4%)</td>
<td align="left">70 (20.3%)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">LVEF categorised by 40%<xref ref-type="table-fn" rid="Tfn30">
<sup>k</sup>
</xref>
</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">0.27</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">0.22</td>
</tr>
<tr>
<td align="left">&#x3c;40%</td>
<td align="left">61 (3.4%)</td>
<td align="left">24 (4.2%)</td>
<td align="left">-</td>
<td align="left">58 (3.9%)</td>
<td align="left">8 (2.3%)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">&#x2265;40%</td>
<td align="left">950 (53.1%)</td>
<td align="left">323 (55.9%)</td>
<td align="left">-</td>
<td align="left">717 (48.5%)</td>
<td align="left">180 (52.2%)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">Perceived frailty, n (%)</td>
<td align="left">50 (2.8%)</td>
<td align="left">58 (10.0%)</td>
<td align="left">&#x3c;0.001</td>
<td align="left">151 (10.2%)</td>
<td align="left">25 (7.2%)</td>
<td align="left">0.11</td>
</tr>
<tr>
<td align="left">COPD<xref ref-type="table-fn" rid="Tfn31">
<sup>l</sup>
</xref>, n (%)</td>
<td align="left">75 (4.2%)</td>
<td align="left">35 (6.1%)</td>
<td align="left">0.08</td>
<td align="left">81 (5.5%)</td>
<td align="left">25 (7.2%)</td>
<td align="left">0.26</td>
</tr>
<tr>
<td align="left">Hypertension<xref ref-type="table-fn" rid="Tfn32">
<sup>m</sup>
</xref>, n (%)</td>
<td align="left">1,362 (76.1%)</td>
<td align="left">428 (74.0%)</td>
<td align="left">0.35</td>
<td align="left">1,019 (68.9%)</td>
<td align="left">261 (75.7%)</td>
<td align="left">0.02</td>
</tr>
<tr>
<td align="left">Heart failure<xref ref-type="table-fn" rid="Tfn33">
<sup>n</sup>
</xref>, n (%)</td>
<td align="left">251 (14.0%)</td>
<td align="left">115 (19.9%)</td>
<td align="left">&#x3c;0.001</td>
<td align="left">255 (17.2%)</td>
<td align="left">41 (11.9%)</td>
<td align="left">0.02</td>
</tr>
<tr>
<td align="left">Diabetes mellitus<xref ref-type="table-fn" rid="Tfn34">
<sup>o</sup>
</xref>, n (%)</td>
<td align="left">506 (28.3%)</td>
<td align="left">147 (25.4%)</td>
<td align="left">0.20</td>
<td align="left">355 (24.0%)</td>
<td align="left">97 (28.1%)</td>
<td align="left">0.13</td>
</tr>
<tr>
<td align="left">Dyslipidaemia<xref ref-type="table-fn" rid="Tfn35">
<sup>p</sup>
</xref>, n (%)</td>
<td align="left">498 (27.8%)</td>
<td align="left">124 (21.5%)</td>
<td align="left">0.003</td>
<td align="left">337 (22.8%)</td>
<td align="left">96 (27.8%)</td>
<td align="left">0.06</td>
</tr>
<tr>
<td align="left">Valvular disease<xref ref-type="table-fn" rid="Tfn36">
<sup>q</sup>
</xref>, n (%)</td>
<td align="left">85 (4.7%)</td>
<td align="left">32 (5.5%)</td>
<td align="left">0.52</td>
<td align="left">108 (7.3%)</td>
<td align="left">23 (6.7%)</td>
<td align="left">0.77</td>
</tr>
<tr>
<td align="left">History of ischaemic stroke, n (%)</td>
<td align="left">124 (6.9%)</td>
<td align="left">59 (10.2%)</td>
<td align="left">0.01</td>
<td align="left">111 (7.5%)</td>
<td align="left">22 (6.4%)</td>
<td align="left">0.54</td>
</tr>
<tr>
<td align="left">History of TIA, n (%)</td>
<td align="left">43 (2.4%)</td>
<td align="left">18 (3.1%)</td>
<td align="left">0.43</td>
<td align="left">29 (2.0%)</td>
<td align="left">10 (2.9%)</td>
<td align="left">0.38</td>
</tr>
<tr>
<td align="left">History of major or CRNM bleeding, n (%)</td>
<td align="left">25 (1.4%)</td>
<td align="left">7 (1.2%)</td>
<td align="left">0.90</td>
<td align="left">19 (1.3%)</td>
<td align="left">1 (0.3%)</td>
<td align="left">0.15</td>
</tr>
<tr>
<td align="left">History of major bleeding, n (%)</td>
<td align="left">23 (1.3%)</td>
<td align="left">5 (0.9%)</td>
<td align="left">0.55</td>
<td align="left">16 (1.1%)</td>
<td align="left">1 (0.3%)</td>
<td align="left">0.22</td>
</tr>
<tr>
<td align="left">Economic region, n (%)</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">&#x3c;0.001</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
<td align="left">0.03</td>
</tr>
<tr>
<td align="left">East</td>
<td align="left">960 (53.6%)</td>
<td align="left">217 (37.5%)</td>
<td align="left">-</td>
<td align="left">683 (46.2%)</td>
<td align="left">190 (55.1%)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">Middle</td>
<td align="left">530 (29.6%)</td>
<td align="left">249 (43.1%)</td>
<td align="left">-</td>
<td align="left">563 (38.1%)</td>
<td align="left">107 (31.0%)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">Northeast</td>
<td align="left">181 (10.1%)</td>
<td align="left">60 (10.4%)</td>
<td align="left">-</td>
<td align="left">80 (5.4%)</td>
<td align="left">18 (5.2%)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">West</td>
<td align="left">119 (6.7%)</td>
<td align="left">52 (9.0%)</td>
<td align="left">-</td>
<td align="left">153 (10.3%)</td>
<td align="left">30 (8.7%)</td>
<td align="left">-</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="Tfn20">
<label>
<sup>a</sup>
</label>
<p>Based on judgeable patients (N &#x3d; 4,192), not including 685 patients with non-judgable dosing.</p>
</fn>
<fn id="Tfn21">
<label>
<sup>b</sup>
</label>
<p>Body weight was missing for six patients.</p>
</fn>
<fn id="Tfn22">
<label>
<sup>c</sup>
</label>
<p>BMI, was missing for 53 patients.</p>
</fn>
<fn id="Tfn23">
<label>
<sup>d</sup>
</label>
<p>The CrCl calculation was based on the CG, formula and was missing for 251 patients.</p>
</fn>
<fn id="Tfn24">
<label>
<sup>e</sup>
</label>
<p>eGFR, was calculated by the Du Bois and Du Boi method; it was missing for 300 patients.</p>
</fn>
<fn id="Tfn25">
<label>
<sup>f</sup>
</label>
<p>Derived variables of the CHA<sub>2</sub>DS<sub>2</sub>-VASc, score, CHA<sub>2</sub>DS<sub>2</sub>-VA, score and HAS-BLED, score. 113 patients had a missing CHA<sub>2</sub>DS<sub>2</sub>-VASc, score.</p>
</fn>
<fn id="Tfn26">
<label>
<sup>g</sup>
</label>
<p>134 patients had a missing CHA<sub>2</sub>DS<sub>2</sub>-VA, score.</p>
</fn>
<fn id="Tfn27">
<label>
<sup>h</sup>
</label>
<p>The HAS-BLED, score was calculated without &#x2018;labile INR&#x2019;; the renal impairment item was derived instead of investigator reported; alcohol abuse was defined as &#x3e;1 drink/d; missing for 246 patients.</p>
</fn>
<fn id="Tfn28">
<label>
<sup>i</sup>
</label>
<p>DOAC, score was missing for 282 patients.</p>
</fn>
<fn id="Tfn29">
<label>
<sup>j</sup>
</label>
<p>AF, type was missing for 13 patients.</p>
</fn>
<fn id="Tfn30">
<label>
<sup>k</sup>
</label>
<p>LVEF, data were missing for 1871 patients. <sup>k</sup>Perceived frailty was missing for 714 patients.</p>
</fn>
<fn id="Tfn31">
<label>
<sup>l</sup>
</label>
<p>COPD, was missing for 70 patients.</p>
</fn>
<fn id="Tfn32">
<label>
<sup>m</sup>
</label>
<p>Hypertension was unknown in 14 patients.</p>
</fn>
<fn id="Tfn33">
<label>
<sup>n</sup>
</label>
<p>Patients were considered as heart failure with documented congestive HF, documented ischaemic cardiomyopathy, LVEF &#x3c;40%, or frequent dyspnoea (&#x2265;1/d) without COPD, and at least one of the following: documented severe valvular heart disease, documented CAD, post-myocardial infarction, valve replacement or documented hypertension treated with at least three drugs.</p>
</fn>
<fn id="Tfn34">
<label>
<sup>o</sup>
</label>
<p>Diabetes mellitus was unknown for 24 patients.</p>
</fn>
<fn id="Tfn35">
<label>
<sup>p</sup>
</label>
<p>Dyslipidaemia was unknown for 88 patients.</p>
</fn>
<fn id="Tfn36">
<label>
<sup>q</sup>
</label>
<p>Valvular disease was unknown for 90 patients. <italic>P</italic> values were calculated by comparing Recommended 60&#xa0;mg vs. Non-Recommended 30&#xa0;mg and Recommended 30&#xa0;mg vs. Non-Recommended 60&#xa0;mg dose levels.</p>
</fn>
<fn>
<p>AF, atrial fibrillation; BMI, body mass index; COPD, chronic obstructive pulmonary disease; CrCl, creatinine clearance; CRNM, clinically relevant non-major; eGFR, estimated glomerular filtration rate; LVEF, left ventricular ejection fraction; TIA, transient ischaemic attack; SD, standard deviation.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>When compared with the patients receiving the recommended 60&#xa0;mg, the patients receiving non-recommended 30&#xa0;mg edoxaban OD were older (mean 71.4&#xa0;years vs. 67.0&#xa0;years), had a higher proportion of patients with perceived frailty (10.0% vs. 2.8%) and HF (19.9% vs. 14.0%), had higher CHA<sub>2</sub>DS<sub>2</sub>-VASc score (3.0 vs. 2.5), CHA<sub>2</sub>DS<sub>2</sub>-VA score (3.1 vs. 2.7), modified HAS-BLED score (1.9 vs. 1.5), DOAC score (4.4 vs. 3.5), and a greater percentage of impaired renal function (CrCl &#x3c;80&#xa0;mL/min: 65.2% vs. 48.6%; all <italic>P</italic> &#x3c; 0.001).</p>
<p>Similarly, patients receiving the recommended 30-mg edoxaban OD at baseline were older (mean 74.2&#xa0;years vs. 71.5&#xa0;years; <italic>P</italic> &#x3c; 0.001), had higher CHA<sub>2</sub>DS<sub>2</sub>-VASc score (3.4 vs. 3.1; <italic>P</italic> &#x3c; 0.001), DOAC score (5.4 vs. 4.7; <italic>P</italic> &#x3c; 0.001), and a greater percentage of impaired renal function (CrCl &#x3c;80&#xa0;mL/min: 80.1% vs. 75.1%; <italic>P</italic> &#x3d; 0.002) than those receiving the non-recommended 60&#xa0;mg (<xref ref-type="table" rid="T2">Table 2</xref>).</p>
</sec>
<sec id="s3-2">
<label>3.2</label>
<title>Dosing adjustment and persistence pattern</title>
<p>Overall, a majority of patients (60&#xa0;mg: 1,938 [73.1%], 30&#xa0;mg: 1,626 [73.0%]) completed the 1-year follow-up while continuing to use edoxaban (<xref ref-type="table" rid="T3">Table 3</xref>; <xref ref-type="sec" rid="s13">Supplementary Figure S3</xref>). A lesser proportion of patients treated with edoxaban 30&#xa0;mg OD initially at baseline switched to 60&#xa0;mg OD (32; 1.4%) than from 60&#xa0;mg at baseline to 30&#xa0;mg OD (158; 6.0%).</p>
<table-wrap id="T3" position="float">
<label>TABLE 3</label>
<caption>
<p>Dosing adjustments in edoxaban-treated patients with AF during a 1-year follow-up period.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Dosing adjustment pattern</th>
<th align="left">Total [<italic>n</italic> &#x3d; 4,877]<xref ref-type="table-fn" rid="Tfn37">
<sup>a</sup>
</xref>
</th>
<th align="left">60&#xa0;mg [<italic>n</italic> &#x3d; 2,650]</th>
<th align="left">30&#xa0;mg [<italic>n</italic> &#x3d; 2,227]</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Continuing edoxaban use<xref ref-type="table-fn" rid="Tfn38">
<sup>b</sup>
</xref>
</td>
<td align="left">3,564 (73.1%)</td>
<td align="left">1,938 (73.1%)</td>
<td align="left">1,626 (73.0%)</td>
</tr>
<tr>
<td align="left">Dosing adjustments</td>
<td align="left">190 (3.9%)</td>
<td align="left">&#x200b;</td>
<td align="left">&#x200b;</td>
</tr>
<tr>
<td align="left">Switching to 30&#xa0;mg OD<xref ref-type="table-fn" rid="Tfn39">
<sup>c</sup>
</xref>
</td>
<td align="left">-</td>
<td align="left">158 (6.0%)</td>
<td align="left">-</td>
</tr>
<tr>
<td align="left">Switching to 60&#xa0;mg OD<xref ref-type="table-fn" rid="Tfn39">
<sup>c</sup>
</xref>
</td>
<td align="left">-</td>
<td align="left">-</td>
<td align="left">32 (1.4%)</td>
</tr>
<tr>
<td colspan="4" align="left">Persistence pattern</td>
</tr>
<tr>
<td align="left">&#x2003;Study drug suspension<xref ref-type="table-fn" rid="Tfn40">
<sup>d</sup>
</xref>
</td>
<td align="left">495 (10.1%)</td>
<td align="left">277 (10.5%)</td>
<td align="left">218 (9.8%)</td>
</tr>
<tr>
<td align="left">&#x2003;Discontinuation from study drug<xref ref-type="table-fn" rid="Tfn41">
<sup>e</sup>
</xref>
</td>
<td align="left">777 (15.9%)</td>
<td align="left">380 (14.3%)</td>
<td align="left">397 (17.8%)</td>
</tr>
<tr>
<td colspan="4" align="left">Immediate switching to other OAC<xref ref-type="table-fn" rid="Tfn42">
<sup>f</sup>
</xref>
</td>
</tr>
<tr>
<td align="left">&#x2003;Warfarin</td>
<td align="left">32 (0.7%)</td>
<td align="left">16 (0.6%)</td>
<td align="left">16 (0.7%)</td>
</tr>
<tr>
<td align="left">&#x2003;Apixaban</td>
<td align="left">1 (0.02%)</td>
<td align="left">-</td>
<td align="left">1 (0.04%)</td>
</tr>
<tr>
<td align="left">&#x2003;Dabigatran</td>
<td align="left">13 (0.3%)</td>
<td align="left">9 (0.3%)</td>
<td align="left">4 (0.2%)</td>
</tr>
<tr>
<td align="left">&#x2003;Rivaroxaban</td>
<td align="left">47 (1.0%)</td>
<td align="left">23 (0.9%)</td>
<td align="left">24 (1.1%)</td>
</tr>
<tr>
<td align="left">&#x2003;Suspension and discontinuation from study drug<xref ref-type="table-fn" rid="Tfn43">
<sup>g</sup>
</xref>
</td>
<td align="left">76 (1.6%)</td>
<td align="left">37 (1.4%)</td>
<td align="left">39 (1.8%)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="Tfn37">
<label>
<sup>a</sup>
</label>
<p>Based on full analysis set (FAS).</p>
</fn>
<fn id="Tfn38">
<label>
<sup>b</sup>
</label>
<p>Continued edoxaban use: continuously using edoxaban during 1-year follow-up however allowing for interruptions &#x2264;3&#xa0;days and for a switch of dose &#x3c;90&#xa0;days before the 1&#xa0;year cut-off.</p>
</fn>
<fn id="Tfn39">
<label>
<sup>c</sup>
</label>
<p>Switching to 30&#xa0;mg or 60&#xa0;mg: switch to another dose of edoxaban after baseline with a duration of &#x2265;90&#xa0;days or until 1-year follow-up.</p>
</fn>
<fn id="Tfn40">
<label>
<sup>d</sup>
</label>
<p>Study drug suspension: stopped edoxaban for &#x3e;3&#xa0;days and restarted in &#x2264;90&#xa0;days.</p>
</fn>
<fn id="Tfn41">
<label>
<sup>e</sup>
</label>
<p>Discontinuation from study drug: stopped edoxaban for &#x3e;3&#xa0;days, not continued in &#x2264;90&#xa0;days at the end of 1-year follow-up.</p>
</fn>
<fn id="Tfn42">
<label>
<sup>f</sup>
</label>
<p>Immediate switching to other OAC: discontinuation from edoxaban, switch to other OAC, in &#x2264;7&#xa0;days.</p>
</fn>
<fn id="Tfn43">
<label>
<sup>g</sup>
</label>
<p>Suspend and discontinuation from study drug: stopped edoxaban for &#x3e;3&#xa0;days, restarted edoxaban in &#x2264;90&#xa0;days, but discontinued at the end of 1-year follow-up.</p>
</fn>
<fn>
<p>OAC, oral anticoagulants; OD, once daily.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>In the 60&#xa0;mg group, 277 (10.5%) patients suspended edoxaban and 380 patients (14.3%) discontinued the drug during 1-year follow-up. Similarly, in the 30&#xa0;mg group, edoxaban was suspended in 218 patients (9.8%), whereas 397 patients (17.8%) discontinued. Within each group, the percentages of patients who discontinued edoxaban and immediately switched to another OAC were less than or &#x223c;1% (60&#xa0;mg: warfarin 16 [0.6%], dabigatran 9 [0.3%] and rivaroxaban 23 [0.9%]; 30&#xa0;mg: warfarin 16 [0.7%], apixaban 1 [0.04%], dabigatran 4 [0.2%] and rivaroxaban 24 [1.1%]). Suspension or discontinuation of edoxaban was observed in 37 patients (1.4%) in the 60&#xa0;mg group and in 39 patients (1.8%) in the 30&#xa0;mg group.</p>
</sec>
<sec id="s3-3">
<label>3.3</label>
<title>Mortality, bleeding, and CV clinical outcomes</title>
<p>The overall annualised event rate of all-cause death was 2.30%/y in the total population (<xref ref-type="fig" rid="F1">Figure 1</xref>). The overall annualised rates were low for CV death (0.62%/y), major bleeding (1.04%/y), ICH (0.21%/y), and major GI bleeding (0.44%/y). Stroke/SEE occurred in 49 patients (1.13%/y), of whom 28 patients (0.65%/y) had ischaemic stroke and seven patients (0.16%/y) had haemorrhagic stroke. The incidences of TIA and MI were 0.35%/y and 0.25%/y, respectively, in the overall patient population.</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>Annualised event rates<sup>&#x23;</sup> (%/y) of: <bold>(A)</bold> Death outcomes, <bold>(B)</bold> Safety outcomes and <bold>(C)</bold> Effectiveness outcomes in the overall population<sup>&#x2a;</sup> classified by edoxaban dose at baseline during the 1-year follow-up. &#x2a;Based on full analysis set (FAS), N &#x3d; 4,877. &#x23;Patients with no official clinic visit date during 12&#xa0;months of follow-up were censored at last-available events or hospitalisations or AEs record date. <sup>&#x2b;</sup>Included haemorrhagic stroke or epidural/subdural haematoma. CV, cardiovascular; CRNM, clinically relevant non-major; ICH, intracranial haemorrhage; GI, gastrointestinal; SEE, systemic embolic event; TIA, transient ischaemic attack. </p>
</caption>
<graphic xlink:href="fphar-17-1739246-g001.tif">
<alt-text content-type="machine-generated">Bar charts compare annualized event rates for different conditions across three groups: Total, Edoxaban 60mg, and Edoxaban 30mg. Chart A shows rates for all-cause death and cardiovascular death; Chart B for major bleeding, CRNM bleeding, ICH, and major GI bleeding; Chart C for stroke/SEE, ischemic stroke, hemorrhagic stroke, TIA, and myocardial infarction. Rates, expressed as annual rate expressed as percentages/year, vary across groups.</alt-text>
</graphic>
</fig>
<p>Unadjusted annualised event rates, which should be interpreted with caution due to significant baseline differences between dose groups (<xref ref-type="table" rid="T1">Table 1</xref>), showed that during the 1-year follow-up period, the overall annualised rates of all-cause death in the 30&#xa0;mg and 60&#xa0;mg edoxaban remained constant over time (<xref ref-type="fig" rid="F2">Figure 2A</xref>). Patients receiving 30&#xa0;mg edoxaban had a higher risk of all-cause death as well as CV death when compared with patients receiving 60&#xa0;mg edoxaban (all-cause death: 3.73%/y vs. 1.13%/y, log-rank P&#x3c;0.0001; CV deaths: 0.92%/y vs. 0.38%/y, <italic>P</italic> &#x3d; 0.024; <xref ref-type="fig" rid="F2">Figures 2A,B</xref>). A larger proportion of patients in the 30&#xa0;mg edoxaban group than 60&#xa0;mg edoxaban group experienced major bleeding (1.59%/y vs. 0.59%/y, <italic>P</italic> &#x3d; 0.001; <xref ref-type="fig" rid="F2">Figure 2C</xref>). No significant differences in the annualised rates of stroke/SEE, or TIA between the dose groups were observed (<xref ref-type="fig" rid="F2">Figure 2D</xref>; <italic>P</italic> &#x3e; 0.05).</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption>
<p>Cumulative incidence for <bold>(A)</bold> all-cause death, <bold>(B)</bold> cardiovascular death, <bold>(C)</bold> major bleeding, <bold>(D)</bold> stroke/SEE/TIA in patients<sup>&#x2a;</sup> with AF at 1-year follow-up classified by edoxaban dose. &#x2a;Based on full analysis set (FAS), N &#x3d; 4,877. <italic>P</italic> value was calculated by log-rank test. AF, atrial fibrillation; SEE, systemic embolic event; TIA, transient ischaemic attack.</p>
</caption>
<graphic xlink:href="fphar-17-1739246-g002.tif">
<alt-text content-type="machine-generated">Four line graphs compare Edoxaban 30 mg and 60 mg over 360 days for different outcomes: A) All-cause death shows higher rates for 30 mg (p&#x3C;0.0001); B) Cardiovascular death shows higher rates for 30 mg (p=0.024); C) Major bleeding shows higher rates for 30 mg (p=0.001); D) Stroke/TIA/SEE shows higher rates for 30 mg (p=0.093). All graphs indicate cumulative rates over time.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3-4">
<label>3.4</label>
<title>Predictors and outcomes by dosing groups</title>
<p>The factors associated with all-cause death, CV death, all stroke/SEE/TIA, and major bleeding were significant if <italic>P</italic> &#x3c; 0.05 of univariable analysis (<xref ref-type="sec" rid="s13">Supplementary Tables S2&#x2013;S5</xref>). The selected factors were further adjusted by fixing edoxaban dosing (60 and 30&#xa0;mg) in a stepwise multivariable Cox regression model (<xref ref-type="fig" rid="F3">Figure 3</xref>). A CrCl &#x3c;30&#xa0;mL/min (HR: 5.79, 95% CI: 2.53&#x2013;12.71; P&#x3c;0.0001), underweight (BMI &#x3c; 18.5; HR: 2.94, 95% CI: 1.52&#x2013;5.69; <italic>P</italic> &#x3d; 0.001), CHA<sub>2</sub>DS<sub>2</sub>-VASc scores (HR: 1.33, 95% CI: 1.11&#x2013;1.58; P &#x3d; 0.002), long-standing persistent AF (HR: 3.14, 95% CI: 1.64&#x2013;5.99; P&#x3c;0.0001) and permanent AF (HR: 3.30, 95% CI: 1.76&#x2013;6.19; <italic>P</italic>&#x3c;0.0001) were the main clinically significant factors related to all-cause death (<xref ref-type="fig" rid="F3">Figure 3A</xref>). Male gender (HR: 3.09, 95% CI: 1.93&#x2013;4.96; P&#x3c;0.0001), perceived frailty (HR: 2.14, 95% CI: 1.20&#x2013;3.83; P&#x3c;0.0001), and economic regions of Northeast (HR: 3.10, 95% CI: 1.66&#x2013;5.80; P&#x3c;0.0001) were further identified as the predictors of all-cause death. Similarly, CrCl &#x3c;30&#xa0;mL/min (HR: 10.85, 95% CI: 2.46&#x2013;47.90; <italic>P</italic> &#x3d; 0.002) and perceived frailty (HR: 2.94, 95% CI: 1.16&#x2013;7.46; <italic>P</italic> &#x3d; 0.023) were also associated with CV death (<xref ref-type="fig" rid="F3">Figure 3B</xref>). The persistent AF type (HR: 4.18, 95% CI: 1.70&#x2013;10.30; <italic>P</italic> &#x3d; 0.002) was a strong predictor of major bleeding events, in addition to permanent AF (HR: 3.61, 95% CI: 1.28&#x2013;10.19; <italic>P</italic> &#x3d; 0.015), BMI of &#x3c;18.5 (HR: 3.75, 95% CI: 1.38&#x2013;10.17; <italic>P</italic> &#x3d; 0.009), HAS-BLED scores (HR: 1.60, 95% CI: 1.12&#x2013;2.30; <italic>P</italic> &#x3d; 0.011) and CHA<sub>2</sub>DS<sub>2</sub>-VASc scores (HR: 1.35, 95% CI: 1.05&#x2013;1.73; <italic>P</italic> &#x3d; 0.020) (<xref ref-type="fig" rid="F3">Figure 3C</xref>). For stroke/SEE/TIA, HAS-BLED score (HR: 1.69, 95% CI: 1.31&#x2013;2.18; <italic>P</italic>&#x3c;0.0001) and HF (HR: 1.96, 95% CI: 1.12&#x2013;3.44; <italic>P</italic> &#x3d; 0.019) were relevant predictors (<xref ref-type="fig" rid="F3">Figure 3D</xref>).</p>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption>
<p>Multivariable cox regression analysis<sup>&#x23;</sup> of dosing and characteristics associated with <bold>(A)</bold> all-cause death, <bold>(B)</bold> cardiovascular death, <bold>(C)</bold> major bleeding and <bold>(D)</bold> stroke/TIA/SEE outcomes of overall population<sup>&#x2a;</sup> during the 1-year follow-up. &#x23;Multivariable cox regression analysis by fixing edoxaban dosing (60&#xa0;mg and 30&#xa0;mg) and all characteristics in a stepwise regression model. &#x2a;Based on full analysis set (FAS), N &#x3d; 4,877. Forest plots represented data as HRs with a 95% CI. AF, atrial fibrillation; BMI, body mass index; COPD, chronic obstructive pulmonary disease; CI, confidence interval; HR, hazard ratio; SEE, systemic embolic event; TIA, transient ischaemic attack.</p>
</caption>
<graphic xlink:href="fphar-17-1739246-g003.tif">
<alt-text content-type="machine-generated">Forest plots illustrating hazard ratios (HR) with 95% confidence intervals for clinical outcomes. Panel A shows factors associated with all-cause death. Panel B details variables linked to cardiovascular death. Panel C focuses on major bleeding risks, while Panel D highlights stroke/TIA/SEE risks. Each panel includes variables such as creatinine clearance, CHA&#x2082;DS&#x2082;-VASc score, HAS-BLED score, and more, indicating increased or decreased risk based on HR and p-values. Arrows at the x-axis denote the direction of risk change. Significant p-values are bolded.</alt-text>
</graphic>
</fig>
<p>Upon performing the step-wise multivariable cox regression analysis of recommended/non-recommended doses, patients on non-recommended doses (both under- and over-dosing) often had worse outcomes, likely reflecting their higher baseline risk profile rather than a direct effect of the dosing itself (<xref ref-type="sec" rid="s13">Supplementary Table S6</xref>).</p>
</sec>
<sec id="s3-5">
<label>3.5</label>
<title>Outcomes in the recommended versus non-recommended dose subgroups</title>
<p>After 1-year follow-up, patients who were prescribed the non-recommended 30&#xa0;mg dose of edoxaban had higher risks of all-cause mortality (HR: 2.49, 95% CI: 1.27&#x2013;4.91; <italic>P</italic> &#x3d; 0.006), major bleeding (HR: 3.54, 95% CI: 1.37&#x2013;9.17, <italic>P</italic> &#x3d; 0.005), and major GI bleeding (HR: 5.22, 95% CI: 1.25&#x2013;21.85, <italic>P</italic> &#x3d; 0.01) compared with the recommended 60&#xa0;mg dose (<xref ref-type="sec" rid="s13">Supplementary Figure S4</xref>). Patients receiving the non-recommended 60&#xa0;mg versus the recommended 30&#xa0;mg had lower annualised event rates of all-cause mortality (HR: 0.40, 95% CI: 0.16&#x2013;0.99; <italic>P</italic> &#x3d; 0.04). The rates of stroke/SEE/TIA and ischaemic stroke were similar between non-recommended 30&#xa0;mg versus recommended 60&#xa0;mg or non-recommended 60&#xa0;mg versus recommended 30-mg dose groups (all <italic>P</italic> &#x3e; 0.05).</p>
</sec>
</sec>
<sec sec-type="discussion" id="s4">
<label>4</label>
<title>Discussion</title>
<p>The 1-year follow-up data from the ETNA-AF China study initially reported the effectiveness and safety of edoxaban in a large Chinese population with AF. The results demonstrated low rates of all stroke/SEE (1.13%/y) and major bleeding events (1.04%/y) in consistency with the international, prospective, and noninterventional Global ETNA-AF programme, complementing the pivotal trials by encompassing the non-selected Chinese a population in real-world setting. This report also highlights various predictors of all-cause and CV death, major bleeding, and stroke events in patients treated with recommended/non-recommended 30&#xa0;mg and 60&#xa0;mg doses of edoxaban, indicating integrated AF care through risk factor modification.</p>
<p>The current results from China though not yet pooled with the full global database highlight the similarities as well as regional differences between other ETNA studies. At the 1-year follow-up, patients from Europe, Japan, the Chinese Mainland, South Korea, and Taiwan (China) displayed similar annualised rates of stroke or SEE (0.82%, 1.43%, 1.13%, 1.27% [any stroke], 1.52% [any stroke]) and major bleeding events (1.05%, 1.08%, 1.04%, 0.99%, 1.37%) with analogous CHA<sub>2</sub>DS<sub>2</sub>-VASc and HAS-BLED score categories (<xref ref-type="bibr" rid="B41">Yamashita et al., 2020</xref>; <xref ref-type="bibr" rid="B9">Choi et al., 2021</xref>; <xref ref-type="bibr" rid="B10">Choi et al., 2024</xref>; <xref ref-type="bibr" rid="B14">De Groot et al., 2021</xref>). The annualised all-cause and CV death rates were notably lower in our study (2.30% and 0.62%, respectively) compared with the 1-year outcome of the ETNA-AF-Europe study (3.50% and 1.63%, respectively) (<xref ref-type="bibr" rid="B14">De Groot et al., 2021</xref>). The younger age (70.3&#xa0;years vs. 73.6&#xa0;years), lower average body weight (67.2&#xa0;kg vs. 81.0&#xa0;kg) and lower perceived frailty (6.3% vs. 10.6%) characteristics could explain the lower mortality events in the Chinese population compared with the European population. ETNA-AF Japan and ETNA-AF Other Asia studies reported slightly lower 1-year interim all-cause death rates (1.22% and 1.78%, respectively) (<xref ref-type="bibr" rid="B41">Yamashita et al., 2020</xref>). Patients from Japan had the highest adherence rate on label-recommended doses of 85.2% among all ETNA-AF programmes (Europe: 83%; Chinese Mainland: 78.0%; South Korea/Taiwan: 70.8%), which may contribute to the better survival outcomes (<xref ref-type="bibr" rid="B7">Chao et al., 2023</xref>). On one hand, the 1-year interim annualised rates of major or CRNM bleeding were also observed to be the highest in ETNA-AF Japan (Japan: 3.83%, Europe: 2.35%, Chinese Mainland: 2.54%, and Other Asia: 2.18%). On the other hand, ETNA-AF Other Asia reported the highest rates of ischaemic stroke, haemorrhagic stroke, major bleeding, ICH, as well as major GI bleeding. This may be attributed to Asian patients having a higher bleeding risk and lower body weight than other populations (<xref ref-type="bibr" rid="B17">Giugliano et al., 2013</xref>; <xref ref-type="bibr" rid="B5">Chan et al., 2016</xref>; <xref ref-type="bibr" rid="B4">Cha et al., 2017</xref>; <xref ref-type="bibr" rid="B10">Choi et al., 2024</xref>).</p>
<p>A comparison of outcomes between two dose groups revealed a higher risk of all-cause death, CV death, and major bleeding in patients receiving edoxaban 30&#xa0;mg OD than those on 60&#xa0;mg OD. This may be overwhelmingly attributed to the poorer health status of 30&#xa0;mg edoxaban group, who were generally older (mean age: 73.4 vs. 67.6&#xa0;years), had higher CHA<sub>2</sub>DS<sub>2</sub>-VASc (mean: 3.3 vs. 2.6) and CHA<sub>2</sub>DS<sub>2</sub>-VA scores (mean: 3.1 vs. 2.6), had higher DOAC score (mean: 5.1 vs. 3.6), had a greater prevalence of frailty (9.9% vs. 3.4%) and had further impaired renal function (CrCl &#x3c;80&#xa0;mL/min, 70.5% vs. 42.8%). These 1-year interim results are consistent with that of the 1-year results of ETNA-AF Europe and Japan (<xref ref-type="bibr" rid="B41">Yamashita et al., 2020</xref>; <xref ref-type="bibr" rid="B14">De Groot et al., 2021</xref>).</p>
<p>The annualised rates of stroke/SEE and major bleeding in our study were relatively low compared with other real-world registries of Asian patients (<xref ref-type="sec" rid="s13">Supplementary Table S7</xref>). At 1-year follow-up, the rates of stroke/SEE and major bleeding were lower in ETNA-AF-China in comparison with the XANAP and XAPASS studies (<xref ref-type="bibr" rid="B26">Kim et al., 2018</xref>; <xref ref-type="bibr" rid="B23">Ikeda et al., 2019</xref>). In addition, our findings were consistent with the GLORIA-AF Asian cohort, in which the incidences of all strokes and major bleeding were both 0.90/100 PY after 2-year dabigatran treatment (HAS-BLED score of 1.1) (<xref ref-type="bibr" rid="B31">Mazurek et al., 2019</xref>). Notably, comparing event rates between 1-year and 2-year treatments shows variations, with lower rates being observed in the second year. The 1-year event rates of stroke/SEE and major bleeding of Chinese patients using edoxaban were on par with NOACs in Asian or global patients (<xref ref-type="bibr" rid="B33">Okumura et al., 2018</xref>; <xref ref-type="bibr" rid="B2">Bassand et al., 2019</xref>).</p>
<p>The exploration of CV risk factors for outcomes of mortality, bleeding and stroke may help enlighten the clinical management of AF (<xref ref-type="bibr" rid="B27">Kirchhof et al., 2022</xref>). Renal impairment categorised by CrCl value was identified as a significant dose-adjusted factor for all-cause death (CrCl &#x3c;30&#xa0;mL/min: HR: 5.79, 95% CI: 2.53&#x2013;12.71; <italic>P</italic> &#x3c; 0.001), and CV death HR: 10.85, 95% CI: 2.46&#x2013;47.90; <italic>P</italic> &#x3d; 0.002). Furthermore, the type of AF, specifically permanent and persistent AF (persistent AF vs. paroxysmal AF, HR: 4.18, 95% CI: 1.70&#x2013;10.30; <italic>P</italic> &#x3d; 0.002), BMI (BMI &#x3c;18.5 vs. BMI &#x2265;18.5&#x2013;&#x3c;25, HR: 3.75, 95% CI: 1.38&#x2013;10.17; <italic>P</italic> &#x3d; 0.009), and baseline CHA<sub>2</sub>DS<sub>2</sub>-VASc score (HR: 1.35, 95% CI: 1.05&#x2013;1.73; <italic>P</italic> &#x3d; 0.020) were also identified as significant dose-adjusted risk factors for major bleeding and all-cause death ([long-standing persistent AF vs. paroxysmal AF] HR: 3.14, 95% CI: 1.64&#x2013;5.99; P &#x3c; 0.001; [persistent AF vs. paroxysmal AF]; HR: 3.30, 95% CI: 1.76&#x2013;6.19; <italic>P</italic> &#x3c; 0.001; [BMI &#x3c;18.5 vs. BMI &#x2265;18.5&#x2013;&#x3c;25]; HR: 2.94, 95% CI: 1.52&#x2013;5.69; <italic>P</italic> &#x3d; 0.001; [CHA<sub>2</sub>DS<sub>2</sub>-VASc score] HR: 1.33, 95% CI: 1.11&#x2013;1.58; <italic>P</italic> &#x3d; 0.002). On par with our study, the ENGAGE AF-TIMI 48 trial showed higher incidences of all-cause death and major adverse cardiovascular events (MACE) in persistent and permanent AF (<xref ref-type="bibr" rid="B28">Link et al., 2017</xref>). However, in the sub-group analysis of the ENTRUST-AF PCI trial and ENSURE-AF study, paroxysmal AF was associated with a higher occurrence of MI (<xref ref-type="bibr" rid="B18">Goette et al., 2020</xref>; <xref ref-type="bibr" rid="B19">Goette et al., 2021</xref>). The EAST-AFNET four trial reported that patients with first-diagnosed AF were at a higher risk of hospitalization because of acute coronary syndrome (ACS; incidence rate ratio: 1.50; 95% CI: 0.83&#x2013;2.69) when compared with paroxysmal and persistent AF (<xref ref-type="bibr" rid="B20">Goette et al., 2022</xref>). In the present study, patients with different AF type reported no significant difference on 1-year event rate of ACS (<italic>P</italic> &#x3e; 0.05), whereas those with permanent AF (4 [0.68%]) and paroxysmal AF (5 [0.32%]) reported numerically the highest rate of MI (<italic>P</italic> &#x3d; 0.08) (<xref ref-type="sec" rid="s13">Supplementary Figure S5</xref>). This may be attributed to the small ASC event (including MI) amount occurred during 1-year follow-up. Perceived frailty was also reported as a predictor for all-cause death (HR: 2.14, 95% CI: 1.20&#x2013;3.83; <italic>P</italic> &#x3d; 0.010) and CV death (HR: 2.94, 95% CI: 1.16&#x2013;7.46; <italic>P</italic> &#x3d; 0.023), respectively. Furthermore, HF (HR: 1.96, 95% CI: 1.12&#x2013;3.44; <italic>P</italic> &#x3d; 0.019) was identified as a factor for stroke/SEE/TIA. This focus from the ETNA-AF-China study provides valuable insights into the nuanced factors that influence the outcomes in patients with AF, warranting a further careful assessment of the stroke and bleeding risks.</p>
<p>Overall, worse clinical benefits were recognised in the non-recommended low dose by exploratory analysis. It was found that the non-recommended 30&#xa0;mg was associated with a higher risk of all-cause death (HR: 2.43, 95% CI: 1.222&#x2013;4.82; <italic>P</italic> &#x3d; 0.011) and major bleeding (HR: 2.90, 95% CI: 1.10&#x2013;7.66; <italic>P</italic> &#x3d; 0.032) vs. recommended 60&#xa0;mg edoxaban in multivariable cox regression model. However, residual confounding is likely and the observed results may be attributed to the baseline characteristics of this group representing the &#x201c;&#x201c;sicker&#x201d;&#x201c; patients, such as lower body weight, renal impairment, advanced age, higher CHA<sub>2</sub>DS<sub>2</sub>-VASc scores, and higher modified HAS-BLED scores, where the non-recommended dose is a marker of severity, not necessarily the cause of the poor outcome. Long-term monitoring is needed to better understand the risks and benefits of non-recommended dosing, particularly for higher doses in Asian patients. Studies have also shown different outcomes in recommended vs. non-recommended doses of NOACs based on regional and ethnic differences, underscoring the importance of individualized dose selection and patient-tailored decision-making to optimize clinical outcomes and minimize bleeding risk (<xref ref-type="bibr" rid="B6">Chan et al., 2023</xref>; <xref ref-type="bibr" rid="B29">Lip et al., 2023</xref>).</p>
<sec id="s4-1">
<label>4.1</label>
<title>Strengths and limitations</title>
<p>The strengths of the ETNA-AF-China study were the inclusion of 4,877 patients and the presentation of comprehensive 1-year follow-up data by interim cut-off, which provided significant insights into the demographic, clinical characteristics, safety, and effectiveness outcomes of patients with AF prescribed edoxaban at the beginning of the study. This study fully collected dose reduction criteria of edoxaban (including renal function), which can provide information for judgment of recommended and non-recommended dosing regimens of NOACs in clinical management of AF. The reflection of real-world conditions, including the extensive sample size, its prospective study design, and the autonomy of physicians in making therapeutic choices, enhances the reliability and applicability of the gathered data in the ETNA-AF-China study.</p>
<p>This study, however, has certain limitations. Owing to its observational and open-label design, detailed data on laboratory tests and other assessments were not collected. The single-arm study design only reported the effectiveness and safety of edoxaban, not a comparison or control against other anticoagulants such as NOAC or VKA. In addition, patients were assigned to the 30&#xa0;mg or 60&#xa0;mg edoxaban dose based on clinical characteristics rather than randomization, making direct comparisons between dose groups potentially confounded by indication and underlying health differences rather than the drug&#x2019;s effect alone. Therefore, the reported <italic>P</italic> values should be interpreted in an exploratory or descriptive manner, since no adjustment for multiple testing was made. The subgroup analyses are further limited by their small sample size, multiple testing, and potential instability of the model due to small event numbers. Moreover, the annualised event rates were estimated by censoring those lost to follow-up or premature termination (11.2%), which may lead to underreported events or co-medications. As this is a real-world, observational study, there was no mandatory requirement for participants or investigators to complete follow-up. This inherent lack of compulsion may have led to incomplete data capture. Furthermore, the current data of ETNA-AF China are not mature enough to be pooled with the global ETNA-AF database, as analyses are still undergoing alignment to standardize results across ETNA-AF studies.</p>
</sec>
</sec>
<sec sec-type="conclusion" id="s5">
<label>5</label>
<title>Conclusion</title>
<p>Routine treatment using edoxaban was found to be effective and safe across a broad spectrum of Chinese patients, with low overall annualised incidence rates of CV mortality, major bleeding (notably ICH), and major GI bleeding during the 1-year follow-up period. Edoxaban dosing (30&#xa0;mg/60&#xa0;mg, recommended/non-recommended doses), type of AF, BMI and baseline comorbidities (frailty, diabetes) were identified as potential risk factors of all-cause death and major bleeding, with edoxaban 30&#xa0;mg dose being appropriately prescribed to a higher-risk population in whom it appeared to have an acceptable risk-benefit profile. At the end of the 1-year follow-up, the majority of patients continued routinely using edoxaban.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="s6">
<title>Data availability statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, complying with local information security protection laws and regulations in China.</p>
</sec>
<sec sec-type="ethics-statement" id="s7">
<title>Ethics statement</title>
<p>The studies involving humans were approved by the institutional review boards and independent Ethics Committees from Beijing Anzhen Hospital (No. 2019-058D) and all participating centres. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.</p>
</sec>
<sec sec-type="author-contributions" id="s8">
<title>Author contributions</title>
<p>XG: Writing &#x2013; original draft, Writing &#x2013; review and editing, Methodology, Visualization, Formal Analysis. JD: Writing &#x2013; review and editing, Formal Analysis, Writing &#x2013; original draft, Visualization, Methodology, Conceptualization. YeY: Writing &#x2013; review and editing, Investigation, Validation, Visualization, Formal Analysis. HQ: Investigation, Validation, Writing &#x2013; review and editing, Formal Analysis, Visualization. ZJ: Investigation, Writing &#x2013; review and editing, Formal Analysis, Validation, Visualization. XJ: Investigation, Writing &#x2013; review and editing, Data curation. YZ: Investigation, Writing &#x2013; review and editing, Data curation. XL: Investigation, Data curation, Writing &#x2013; review and editing. BD: Writing &#x2013; review and editing, Investigation. JL: Investigation, Writing &#x2013; review and editing. JM: Investigation, Writing &#x2013; review and editing. CS: Investigation, Writing &#x2013; review and editing. HF: Investigation, Writing &#x2013; review and editing. SL: Investigation, Writing &#x2013; review and editing. JW: Investigation, Writing &#x2013; review and editing. YX: Investigation, Writing &#x2013; review and editing. LL: Investigation, Writing &#x2013; review and editing. JC: Investigation, Writing &#x2013; review and editing. ZH: Writing &#x2013; review and editing, Investigation. XC: Writing &#x2013; review and editing, Investigation. YaY: Validation, Writing &#x2013; review and editing, Writing &#x2013; original draft. ML: Validation, Writing &#x2013; review and editing, Writing &#x2013; original draft. CC: Validation, Writing &#x2013; review and editing. MU: Writing &#x2013; review and editing, Validation. CM: Conceptualization, Supervision, Methodology, Investigation, Funding acquisition, Writing &#x2013; review and editing.</p>
</sec>
<ack>
<title>Acknowledgements</title>
<p>The authors would like to thank all patients who participated in this study and all investigators from participating centres. The authors would also like to thank Ping Li, Sabine K&#xf6;hler for support on medical monitoring, Jiahui Xu, Dr. Eva-Maria Fronk for biostatistical analysis, Na Guo, Ting-ting Sun, Min Tao, Ye Chen, Ulrike Thee for clinical data collection and management, and Tracy Zeng, Yuechan Zhang, Hui Yang, Wenyi Ma and Yingzhe Yang for their support on medication safety monitoring.</p>
</ack>
<sec sec-type="COI-statement" id="s10">
<title>Conflict of interest</title>
<p>Author (s) JD, YaY, and ML were employed by Daiichi Sankyo (China) Holdings Co., Ltd. Author(s) CC and MU were employed by Daiichi Sankyo Inc. C.-S.M. has received honoraria from Bristol Myers Squibb, Pfizer, Johnson &#x0026; Johnson, Boehringer-Ingelheim, Bayer and Daiichi Sankyo for giving lectures. No fees are directly received personally.</p>
<p>The remaining author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
<p>The reviewer MW declared a shared affiliation with the authors XG &#x26; CM to the handling editor at the time of review.</p>
</sec>
<sec sec-type="ai-statement" id="s11">
<title>Generative AI statement</title>
<p>The author(s) declared that generative AI was not 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="s12">
<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="s13">
<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.2026.1739246/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fphar.2026.1739246/full&#x23;supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="DataSheet1.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/2214758/overview">Lukasz Pyka</ext-link>, Silesian Center for Heart Disease, Poland</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/1330415/overview">Mingfen Wu</ext-link>, Capital Medical University, China</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1796524/overview">Miroslav Zora Mihajlovic</ext-link>, University of Belgrade, Serbia</p>
</fn>
</fn-group>
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