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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Immunol.</journal-id>
<journal-title>Frontiers in Immunology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Immunol.</abbrev-journal-title>
<issn pub-type="epub">1664-3224</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fimmu.2025.1626135</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Immunology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Temporal trends in malignancy incidence and outcomes among kidney transplantation recipients: a multi-center real-world evidence study using the TriNetX network (2000&#x2013;2010 vs. 2010&#x2013;2021)</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Lai</surname>
<given-names>Gu-Shun</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/3033894/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/software/"/>
<role content-type="https://credit.niso.org/contributor-roles/conceptualization/"/>
<role content-type="https://credit.niso.org/contributor-roles/resources/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
<role content-type="https://credit.niso.org/contributor-roles/visualization/"/>
<role content-type="https://credit.niso.org/contributor-roles/funding-acquisition/"/>
<role content-type="https://credit.niso.org/contributor-roles/validation/"/>
<role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
<role content-type="https://credit.niso.org/contributor-roles/supervision/"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/project-administration/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Li</surname>
<given-names>Jian-Ri</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/361367/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Chen</surname>
<given-names>Chuan-Shu</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1138558/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Shian-Shiang</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1067507/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Lin</surname>
<given-names>Chia-Yen</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Yang</surname>
<given-names>Che-Jui</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref> <role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ho</surname>
<given-names>Hao-Chung</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Hung</surname>
<given-names>Sheng-Chun</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/431288/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Chiu</surname>
<given-names>Kun-Yuan</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref> <role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Yang</surname>
<given-names>Cheng-Kuang</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff7">
<sup>7</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1719087/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Institute of Medicine, Chung Shan Medical University</institution>, <addr-line>Taichung</addr-line>,&#xa0;<country>Taiwan</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Department of Urology, Taichung Veterans General Hospital</institution>, <addr-line>Taichung</addr-line>,&#xa0;<country>Taiwan</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Department of Medicine and Nursing, Hungkuang University</institution>, <addr-line>Taichung</addr-line>,&#xa0;<country>Taiwan</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Department of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University</institution>, <addr-line>Taichung</addr-line>,&#xa0;<country>Taiwan</country>
</aff>
<aff id="aff5">
<sup>5</sup>
<institution>Department of Applied Chemistry, National Chi Nan University</institution>, <addr-line>Nantou</addr-line>,&#xa0;<country>Taiwan</country>
</aff>
<aff id="aff6">
<sup>6</sup>
<institution>College of Medicine, National Yang Ming Chiao Tung University</institution>, <addr-line>Taipei</addr-line>,&#xa0;<country>Taiwan</country>
</aff>
<aff id="aff7">
<sup>7</sup>
<institution>Jenteh Junior College of Medicine, Nursing and Management</institution>, <addr-line>Miaoli</addr-line>,&#xa0;<country>Taiwan</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Al&#xed;cia Molina-And&#xfa;jar, Hospital Clinic de Barcelona, Spain</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1260476/overview">Sheron Latcha</ext-link>, Memorial Sloan Kettering Cancer Center, United States</p>
<p>M&#xf3;nica Bolufer, Hospital Germans Trias i Pujol, Spain</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Cheng-Kuang Yang, <email xlink:href="mailto:yangck@icloud.com">yangck@icloud.com</email>
</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>02</day>
<month>10</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2025</year>
</pub-date>
<volume>16</volume>
<elocation-id>1626135</elocation-id>
<history>
<date date-type="received">
<day>10</day>
<month>05</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>17</day>
<month>09</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2025 Lai, Li, Chen, Wang, Lin, Yang, Ho, Hung, Chiu and Yang.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Lai, Li, Chen, Wang, Lin, Yang, Ho, Hung, Chiu and Yang</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec>
<title>Abbreviations</title>
<p>BMI, body mass index; CI, confidence interval; ESRD, end stage renal disease; HR, hazard ratio; IRB, Institutional Review Board; ICD, International Classification of Diseases; KTX, kidney transplantation; mTOR, mammalian target of rapamycin; PSM, propensity scoring matching; PTM: post-transplantation malignancy; SIR, standardized incidence ratio; SMR, standardized mortality rate.</p>
</sec>
<sec>
<title>Objective</title>
<p>Malignancy is a main cause of mortality and morbidity in kidney transplantation recipients. Advancements in cancer surveillance and treatment may contribute to increased incidence and improved clinical outcomes. This study aimed to investigate the trends and clinical outcomes of post-transplantation malignancies over the past two decades.</p>
</sec>
<sec>
<title>Methods</title>
<p>We conducted a retrospective cohort study using the TriNetX network. Common post-transplantation malignancies were identified, and outcomes were assessed using Kaplan&#x2013;Meier survival analysis with propensity score matching. We compared two transplantation cohorts (2000&#x2013;2010 and 2011&#x2013;2021) to assess potential changes in malignancy incidence, graft survival, and patient mortality.</p>
</sec>
<sec>
<title>Results</title>
<p>A total of 184,267 kidney transplantation recipients were included. Compared to the general population, transplantation recipients exhibited a higher risk of malignancy [standardized incidence ratio (SIR) 1.635; 95% confidence interval (CI), 1.600&#x2013;1.670] and mortality [hazard ratio (HR) 1.115; 95% CI, 1.071&#x2013;1.763; <italic>P</italic> &lt; 0.0001]. The overall incidence of post-transplantation malignancies remained stable over the past two decades. Significant reductions in graft failure (HR 0.442; 95% CI, 0.413&#x2013;0.473; <italic>P</italic> &lt; 0.0001) and all-cause mortality (HR 0.755; 95% CI, 0.713&#x2013;0.801; <italic>P</italic> &lt; 0.0001) were observed in the recent decade.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>Kidney transplantation recipients remain at increased risk for malignancies and associated mortality. While the incidence of malignancies has not changed significantly over the past two decades, both graft failure and mortality have declined in the recent decade, potentially reflecting improvements in post-transplantation care and cancer management.</p>
</sec>
</abstract>
<kwd-group>
<kwd>cancer</kwd>
<kwd>kidney transplantation</kwd>
<kwd>outcomes</kwd>
<kwd>trend</kwd>
<kwd>maligancy</kwd>
</kwd-group>
<counts>
<fig-count count="3"/>
<table-count count="3"/>
<equation-count count="0"/>
<ref-count count="43"/>
<page-count count="9"/>
<word-count count="4040"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-in-acceptance</meta-name>
<meta-value>Alloimmunity and Transplantation</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<title>Introduction</title>
<p>Kidney transplantation (KTX) is a standard treatment for patients with end stage renal disease (ESRD). For patients under dialysis, KTX prolonged overall survival (OS) and improved life quality (<xref ref-type="bibr" rid="B1">1</xref>, <xref ref-type="bibr" rid="B2">2</xref>). Malignancy, infection and cardiovascular disease are the leading causes of mortality and morbidity in KTX recipients (<xref ref-type="bibr" rid="B3">3</xref>&#x2013;<xref ref-type="bibr" rid="B7">7</xref>).</p>
<p>KTX recipients have a cancer incidence rate approximately twofold to fourfold higher than the age- and gender- matched general population. The main mechanisms of an elevated malignancy incidence rate are likely the long-term immunosuppress agents use, carcinogenic virus infection, and donor transmission (<xref ref-type="bibr" rid="B8">8</xref>&#x2013;<xref ref-type="bibr" rid="B17">17</xref>). Immunosuppressants use with an increasing risk of carcinogenic virus infection may be the cause of post-transplantation cancer occurrence, such as liver cancer caused by hepatitis B virus. Risk increased for common cancers in the general population, for example, skin, lung and kidney cancer, which may be attributable to multi-factors, including immunosuppression, carcinogenic medication, or end stage renal disease (<xref ref-type="bibr" rid="B18">18</xref>&#x2013;<xref ref-type="bibr" rid="B20">20</xref>). Certain cancer types (breast and prostate cancer) have decreased incidence after kidney transplantation for unknown reasons (<xref ref-type="bibr" rid="B12">12</xref>, <xref ref-type="bibr" rid="B13">13</xref>).</p>
<p>Improvement in post-kidney transplantation care results in a longer graft survival and a reduction in recipient mortality caused by infection or cardiovascular events (<xref ref-type="bibr" rid="B3">3</xref>&#x2013;<xref ref-type="bibr" rid="B7">7</xref>). Meanwhile, a longer survival may contribute to an increased incidence of post-transplantation malignancy. Despite recent advancement in cancer management, it is challenging in managing transplantation recipients with cancer when preserving renal function at the same time (<xref ref-type="bibr" rid="B21">21</xref>&#x2013;<xref ref-type="bibr" rid="B28">28</xref>).</p>
<p>In view of the increased risk of post-kidney transplantation malignancy and improved cancer treatment, we conducted here a cohort study to evaluate the variation in cancer incidence and outcomes for kidney transplantation recipients in the past two decades.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<title>Materials and methods</title>
<sec id="s2_1">
<title>Data source and study population</title>
<p>We conducted a retrospective cohort study on the TriNetX network, a database with more than 275 million population around the world. The TriNetX platform provided real-world and updated data on demographics, diagnosis, laboratory values, medications and procedures. Within the database, we used the US Collaborative Network, which is a sub-database of the network including 57 US healthcare organizations. Data retrieval and analysis were carried out in June, 2024.</p>
<p>We included patients aged &#x2265;18 years who had received kidney transplantation during the period from January 1, 2000 to December 31, 2021. Patients with kidney transplantation were included and identified using the International Classification of Diseases, 10th edition, Clinical Modification (ICD-10-CM): ICD-10-CM Z94.0, as well as other ICD-10-CM codes to confirm the diagnosis of cancer (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Data 1</bold>
</xref>). The index date was set at the date of kidney transplantation when evaluating time from transplantation to cancer diagnosis, and cancer diagnosis when calculating graft failure and overall mortality. To ensure the inclusion of all post-transplant cancer cases while minimizing discrepancies in registration timing in the database, post-transplantation malignancy (PTM) was defined as a diagnosis made at least one month following the transplantation. Recipients with cancer diagnosis before KTX were excluded, since our aim was to investigate <italic>de novo</italic> malignancy after KTX.</p>
</sec>
<sec id="s2_2">
<title>Statistical analyses</title>
<p>For baseline characteristics, mean and standard deviation were used to represent continuous variables, and number (percentage) to represent categorical variables. To evaluate the risk of specific malignancy in KTX recipients, we evaluated the standardized incidence ratios (SIR) between recipients and the general population after adjusted with age, gender (male/female) and race (Caucasian/African American/Asian). When calculating SIR, the general population was identified using ICD-10: Z00.0 (encounter for general adult medical examination) and patients with history of transplantation were excluded. Kaplan-Meier method with propensity score matching (PSM) was used to evaluate the relative risk of mortality among patients with or without PTM, and the incidence and outcomes of PTM between two different periods (2000&#x2013;2010 and 2011-2021). To evaluate relative mortality, the control cohorts (the general population with cancer) were identified using corresponding ICD codes of malignancies, excluding patients with history of transplantation. For the trends over the past two decades, we compared the overall mortality and graft failure (ICD-10-CM: T86.12) between the two cohorts (2000&#x2013;2010 versus 2011-2021), using 2000&#x2013;2010 as a reference cohort. We performed all the statistical analyses on the platform. Statistically significance was set at P &lt;0.05.</p>
</sec>
<sec id="s2_3">
<title>Ethics in research</title>
<p>Our study was carried out after approval from the Institutional Review Board (IRB) of Taichung Veterans General Hospital (IRB number: SE:22220A). Since all data on the database was de-identified, informed consent was waived by the ethics committee.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<title>Results</title>
<sec id="s3_1">
<title>Patient characteristics</title>
<p>We studied a total of 184,267 patients who had received kidney transplantation in the period between 2000 and 2021. During the follow-up period, 30, 545 (16%) patients had developed <italic>de novo</italic> malignancy after kidney transplantation. When compared with those without cancer, patients who had developed cancer after kidney transplantation were older, with more male in gender, more white patients, higher body mass index (BMI), higher rates of rejection, smoking, comorbidities; they also had lower incomes, and lower serum Tacrolimus level (All P&lt;0.0001). <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref> shows the patients baseline demographics.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Baseline characteristics for patients with or without post-kidney transplantation malignancy.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left">
</th>
<th valign="middle" align="center">KTX with cancer n = 30,545</th>
<th valign="middle" align="center">KTX without cancer n=153,722</th>
<th valign="middle" align="center">P</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="left">Age at KTX, years</td>
<td valign="middle" align="center">56.8 (12.9)</td>
<td valign="middle" align="center">51.8 (15.5)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="left">Age at cancer diagnosis, years</td>
<td valign="middle" align="center">60.3 (12.6)</td>
<td valign="middle" align="center">none</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="left">Male Gender, n (%)</td>
<td valign="middle" align="center">16209 (57.9)</td>
<td valign="middle" align="center">78513 (54.4)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<th valign="middle" colspan="4" align="left">Race, n (%)</th>
</tr>
<tr>
<td valign="middle" align="center">White patients</td>
<td valign="middle" align="center">17857 (64)</td>
<td valign="middle" align="center">72104 (49.9)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="center">African American</td>
<td valign="middle" align="center">4133 (15)</td>
<td valign="middle" align="center">31935 (22.1)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="center">Asian patients</td>
<td valign="middle" align="center">915 (3)</td>
<td valign="middle" align="center">7460 (5)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="center">others/unknown</td>
<td valign="middle" align="center">7640 (25)</td>
<td valign="middle" align="center">37937 (25)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="left">History of rejection, n (%)</td>
<td valign="middle" align="center">9160 (33)</td>
<td valign="middle" align="center">30721 (21)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="left">Rejection before cancer, n (%)</td>
<td valign="middle" align="center">7230 (24)</td>
<td valign="middle" align="center">23490 (16.2)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="left">Serum Tacrolimus level, ng/ml</td>
<td valign="middle" align="center">5.94 (3.25)</td>
<td valign="middle" align="center">6.52 (3.4)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="left">Serum Tacrolimus level before cancer, ng/ml*</td>
<td valign="middle" align="center">6.4 (3.36)</td>
<td valign="middle" align="center">6.77 (3.3)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<th valign="middle" colspan="4" align="left">Induction therapies, n (%)</th>
</tr>
<tr>
<td valign="middle" align="center">Basiliximab</td>
<td valign="middle" align="center">666 (3)</td>
<td valign="middle" align="center">1699 (1)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="center">Anti-thymocyte globulin&#xa0;</td>
<td valign="middle" align="center">515 (2)</td>
<td valign="middle" align="center">3058 (2)</td>
<td valign="middle" align="center">0.2</td>
</tr>
<tr>
<td valign="middle" colspan="4" align="left">Maintenance Immunosuppression, n (%)</td>
</tr>
<tr>
<td valign="middle" align="center">Tacrolimus</td>
<td valign="middle" align="center">19328 (68)</td>
<td valign="middle" align="center">84900 (57)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="center">Cyclosporin</td>
<td valign="middle" align="center">3357 (12)</td>
<td valign="middle" align="center">8884 (6)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="center">Mycophenolate mofetil</td>
<td valign="middle" align="center">14712 (52)</td>
<td valign="middle" align="center">62851 (42)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="center">mTOR inhibitor</td>
<td valign="middle" align="center">4101 (14)</td>
<td valign="middle" align="center">6841 (5)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="center">Prednisolone</td>
<td valign="middle" align="center">20764 (73)</td>
<td valign="middle" align="center">84590 (57)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<th valign="middle" colspan="4" align="left">Comorbidities, n (%)</th>
</tr>
<tr>
<td valign="middle" align="center">Hypertension</td>
<td valign="middle" align="center">15901 (56)</td>
<td valign="middle" align="center">76408 (51)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="center">Diabetes Mellitus</td>
<td valign="middle" align="center">8822 (31)</td>
<td valign="middle" align="center">42472 (29)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="center">Insulin injection</td>
<td valign="middle" align="center">6695 (24)</td>
<td valign="middle" align="center">32204(22)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="center">Ischemic heart disease</td>
<td valign="middle" align="center">6303 (22)</td>
<td valign="middle" align="center">25946 (17)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="center">Cerebrovascular disease</td>
<td valign="middle" align="center">3207 (11)</td>
<td valign="middle" align="center">12027 (8)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="left">Body Mass Index, n (%)</td>
<td valign="middle" align="center">28.3(5.97)</td>
<td valign="middle" align="center">28.3 (6.09)</td>
<td valign="middle" align="center">0.86</td>
</tr>
<tr>
<td valign="middle" align="left">Smoking, n (%)</td>
<td valign="middle" align="center">3687 (13)</td>
<td valign="middle" align="center">14840 (10)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="left">Knorfsky performance status</td>
<td valign="middle" align="center">84.4 (15.3)</td>
<td valign="middle" align="center">85.3 (16.4)</td>
<td valign="middle" align="center">0.59</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>KTX, kidney transplantation; mTOR, mammalian target of rapamycin.</p>
</fn>
<fn>
<p>*Calculated at 2.54 years after KTX for patients without malignancy.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_2">
<title>Incidence of various cancers</title>
<p>Common types of cancer that had occurred following kidney transplantation are listed on <xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>. The most common PTM was non-melanoma skin cancer (31.4%), followed by kidney cancer (9.3%), prostate cancer (6.8%), leukemia (6.6%), non-Hodgkin lymphoma (NHL) (6.2%), lung cancer (5.3%), breast cancer (3.9%), liver cancer (3.2%), colon cancer (2.9%), and bladder cancer (2.8%). Median age at cancer diagnosis was 60.3 years. Patients with NHL (52 years old for KTX and 55.9 cancer diagnosis) were younger at both KTX and the diagnosis of cancer, while patients developing lung cancer (61 for KTX and 65 for cancer diagnosis) and prostate cancer (62.7 for KTX and 66.4 years for cancer diagnosis) were older. Median time from KTX to cancer diagnosis was 2.54 years, with colon cancer having the longest time (3.3 years), and liver cancer (2.16 years) having the shortest time.</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Malignancy distribution, incidence and outcomes in kidney transplantation recipients.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left"/>
<th valign="middle" align="center">Number (%)</th>
<th valign="middle" align="center">Male, n (%)</th>
<th valign="middle" align="center">Age at KTX, years</th>
<th valign="middle" align="center">Age at cancer diagnosis, years (SD)</th>
<th valign="middle" align="center">Median time to cancer, years (SD)</th>
<th valign="middle" align="center">SIR (95% CI)<xref ref-type="table-fn" rid="fnT2_1">
<sup>a</sup>
</xref>
</th>
<th valign="middle" align="center">P</th>
<th valign="middle" align="center">Mortality HR (95% CI)<xref ref-type="table-fn" rid="fnT2_2">
<sup>b</sup>
</xref>
</th>
<th valign="middle" align="center">P</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="left">Non-melanoma skin</td>
<td valign="middle" align="center">9611 (31.4)</td>
<td valign="middle" align="center">6301 (65.5)</td>
<td valign="middle" align="center">59.2 (10.8)</td>
<td valign="middle" align="center">63.1 (10.4)</td>
<td valign="middle" align="center">3</td>
<td valign="middle" align="center">2.346 (2.262-2.433)</td>
<td valign="middle" align="center">&lt;0.0001</td>
<td valign="middle" align="center">2.882 (2.699-3.007)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="left">Kidney</td>
<td valign="middle" align="center">2841 (9.3)</td>
<td valign="middle" align="center">1902 (67)</td>
<td valign="middle" align="center">55 (13.4)</td>
<td valign="middle" align="center">58.6 (13.1)</td>
<td valign="middle" align="center">2.39</td>
<td valign="middle" align="center">5.199 (4.785-5.68)</td>
<td valign="middle" align="center">&lt;0.001</td>
<td valign="middle" align="center">1.146 (1.049-1.251)</td>
<td valign="middle" align="center">0.0024</td>
</tr>
<tr>
<td valign="middle" align="left">Prostate</td>
<td valign="middle" align="center">2076 (6.8)</td>
<td valign="middle" align="center">1969 (100)</td>
<td valign="middle" align="center">62.7 (9.7)</td>
<td valign="middle" align="center">66.4 (9.15)</td>
<td valign="middle" align="center">2.75</td>
<td valign="middle" align="center">0.764 (0.722-0.809)</td>
<td valign="middle" align="center">&lt;0.0001</td>
<td valign="middle" align="center">1.53 (1.3-1.799)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="left">Leukemia</td>
<td valign="middle" align="center">2007 (6.6)</td>
<td valign="middle" align="center">1208 (60)</td>
<td valign="middle" align="center">55 (14.5)</td>
<td valign="middle" align="center">58.6 (14.5)</td>
<td valign="middle" align="center">2.72</td>
<td valign="middle" align="center">2.376 (2.18-2.556)</td>
<td valign="middle" align="center">&lt;0.0001</td>
<td valign="middle" align="center">1.218 (1.105-1.344)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="left">Non-Hodgkin lymphoma</td>
<td valign="middle" align="center">1906 (6.2)</td>
<td valign="middle" align="center">1140 (59.8)</td>
<td valign="middle" align="center">52.1 (16.1)</td>
<td valign="middle" align="center">55.9 (16.1)</td>
<td valign="middle" align="center">2.73</td>
<td valign="middle" align="center">2.818 (2.579-3.079)</td>
<td valign="middle" align="center">&lt;0.0001</td>
<td valign="middle" align="center">1.942 (1.734-2.174)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="left">Lung</td>
<td valign="middle" align="center">1621 (5.3)</td>
<td valign="middle" align="center">1011 (62.3)</td>
<td valign="middle" align="center">61 (10.5)</td>
<td valign="middle" align="center">65 (10.3)</td>
<td valign="middle" align="center">3.25</td>
<td valign="middle" align="center">1.138 (1.06-1.222)</td>
<td valign="middle" align="center">0.0003</td>
<td valign="middle" align="center">1.409 (1.283-1.543)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="left">Breast</td>
<td valign="middle" align="center">1181 (3.9)</td>
<td valign="middle" align="center">67 (5.6)</td>
<td valign="middle" align="center">56.6 (11.6)</td>
<td valign="middle" align="center">60.7 (11.2)</td>
<td valign="middle" align="center">2.18</td>
<td valign="middle" align="center">0.746 (0.69-0.808)</td>
<td valign="middle" align="center">&lt;0.0001</td>
<td valign="middle" align="center">2.17 (1.852-2.543)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="left">Liver</td>
<td valign="middle" align="center">965 (3.2)</td>
<td valign="middle" align="center">578 (64)</td>
<td valign="middle" align="center">56.8 (12.3)</td>
<td valign="middle" align="center">60.3 (12.2)</td>
<td valign="middle" align="center">2.16</td>
<td valign="middle" align="center">2.043 (1.82-2.293)</td>
<td valign="middle" align="center">&lt;0.0001</td>
<td valign="middle" align="center">0.407 (0.371-0.446)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="left">Colon</td>
<td valign="middle" align="center">898 (2.9)</td>
<td valign="middle" align="center">506 (56.3)</td>
<td valign="middle" align="center">57.4 (13.3)</td>
<td valign="middle" align="center">61.7 (12.8)</td>
<td valign="middle" align="center">3.36</td>
<td valign="middle" align="center">1.177 (1.063-1.304)</td>
<td valign="middle" align="center">0.0003</td>
<td valign="middle" align="center">1.653 (1.42-1.925)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="left">Bladder</td>
<td valign="middle" align="center">840 (2.8)</td>
<td valign="middle" align="center">567 (67.9)</td>
<td valign="middle" align="center">60.3 (12.8)</td>
<td valign="middle" align="center">63.9 (12.7)</td>
<td valign="middle" align="center">2.5</td>
<td valign="middle" align="center">1.291 (1.16-1.438)</td>
<td valign="middle" align="center">&lt;0.0001</td>
<td valign="middle" align="center">1.778 (1.552-2.078)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="middle" align="left">All types of cancer</td>
<td valign="middle" align="center">30,545</td>
<td valign="middle" align="center">16209 (57.9)</td>
<td valign="middle" align="center">56.8 (12.9)</td>
<td valign="middle" align="center">60.3 (12.6)</td>
<td valign="middle" align="center">2.54</td>
<td valign="middle" align="center">1.635 (1.6-1.67)</td>
<td valign="middle" align="center">&lt;0.0001</td>
<td valign="middle" align="center">1.115 (1.071-1.163)</td>
<td valign="middle" align="center">&lt;0.0001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>CI, confidence interval; HR, hazard ratio; KTX, kidney transplantation; SD, standard deviation; SIR, standardized incidence ratio.</p>
</fn>
<fn id="fnT2_1">
<label>a</label>
<p>Compare with the general population, adjusted with age, gender, and race.</p>
</fn>
<fn id="fnT2_2">
<label>b</label>
<p>Compare with the general population with cancer, adjusted with age, gender, and race.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>We further compared the cancer incidence between KTX patients and the general population after PSM. After PSM for age, gender and race, patients receiving KTX were associated with a higher risk for cancer development compared with the general population [SIR 1.635, 95% confidence interval (CI) 1.6-1.67]. In general, KTX patients had a higher risk for cancer occurrence for most of the cancer types. Among different sites of cancer, the highest risk of PTM was kidney cancer (SIR 5.199, 95% CI 4.785-5.68), followed by NHL (SIR 2.818, 95% CI 2.579-3.079) and leukemia (SIR 2.376, 95% CI 2.18-2.556).</p>
</sec>
<sec id="s3_3">
<title>Risk factors for malignancy</title>
<p>Through the multivariate cox regression analysis, factors revealed for PTM were as follows: older age (40&#x2013;60 years HR 1.934 95% CI 1.817-2.059 P&lt;0.0001, &gt; 60 years HR 4.674 95% CI 4.406-4.957 P&lt;0.0001), male gender (HR 1.193 95% CI 1.170-1.126 P&lt;0.0001), tacrolimus (HR 1.135 95% CI 1.098-1.173 P&lt;0.0001), cyclosporin (HR 1.284 95% CI 1.214-1.358 P&lt;0.0001), mTOR (HR 1.306 95% CI 1.218-1.401 P&lt;0.0001), and prednisolone (HR 1.112 95% CI 1.079-0.1.146 P&lt;0.0001). <xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref> presents the results of the multivariate analysis and forest plot on factors for PTM in kidney transplantation recipients.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Forest plot of multivariate analysis on risk factors for PTM. CI, confidence interval; HR, hazard ratio; KTX, kidney transplantation; OS, overall survival; PTM, post-transplant malignancy.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-16-1626135-g001.tif">
<alt-text content-type="machine-generated">Forest plot showing hazard ratios for factors impacting PTM risk post-kidney transplant. Variables include age at transplant, gender, rejection episodes, graft failure, and immunosuppressants. Hazard ratios range from 0.948 to 4.674. Notable factors with increased risk include being over 60 and using mTOR, with significant p-values (less than 0.0001). Confidence intervals are provided for each variable.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3_4">
<title>Trends for post-KTX malignancy</title>
<p>A total of 56,922 patients who received KTX in 2000&#x2013;2010 and 127,345 patients in 2011&#x2013;2021 were included. During the follow-up period, 12,921 (22.7%) patients in the 2000&#x2013;2010 cohort and 15,026 (11.8%) in the 2011&#x2013;2021 cohort experienced PTM. After adjusted for age, gender, and race, there was no change in overall cancer incidence over the past two decades (HR 1.003 95% CI 0.956-1.053, P = 0.892). Regarding the specific site of cancer, there was a decrease in incidence for leukemia (HR 0.615 95% CI 0.518-0.729, P &lt; 0.0001) and bladder cancer (HR 0.741 95% CI 0.576-0.954, P = 0.019). <xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref> shows the unadjusted and adjusted incidence hazard ratios of PTM between the 2000&#x2013;2010 and 2011&#x2013;2021 cohorts.</p>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Unadjusted and adjusted incidence hazard ratios for post-transplantation malignancy between patients receiving kidney transplantation at 2000-2010 or 2011-2021, using 2000-2010 cohort as a reference.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" rowspan="2" align="center"/>
<th valign="middle" colspan="3" align="center">Unadjusted</th>
<th valign="middle" colspan="3" align="center">Adjusted<sup>a</sup>
</th>
</tr>
<tr>
<th valign="middle" align="center">HR</th>
<th valign="middle" align="center">95% CI</th>
<th valign="middle" align="center">P</th>
<th valign="middle" align="center">HR</th>
<th valign="middle" align="center">95% CI</th>
<th valign="middle" align="center">P</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="left">Non-melanoma skin</td>
<td valign="middle" align="center">1.036</td>
<td valign="middle" align="center">0.985-1.089</td>
<td valign="middle" align="center">0.17</td>
<td valign="middle" align="center">0.973</td>
<td valign="middle" align="center">0.905-1.047</td>
<td valign="middle" align="center">0.463</td>
</tr>
<tr>
<td valign="middle" align="left">Kidney</td>
<td valign="middle" align="center">1.312</td>
<td valign="middle" align="center">1.203-1.432</td>
<td valign="middle" align="center">&lt;0.0001</td>
<td valign="middle" align="center">1.04</td>
<td valign="middle" align="center">0.897-1.206</td>
<td valign="middle" align="center">0.605</td>
</tr>
<tr>
<td valign="middle" align="left">Prostate</td>
<td valign="middle" align="center">1.285</td>
<td valign="middle" align="center">1.16-1.424</td>
<td valign="middle" align="center">&lt;0.0001</td>
<td valign="middle" align="center">1.005</td>
<td valign="middle" align="center">0.837-1.207</td>
<td valign="middle" align="center">0.956</td>
</tr>
<tr>
<td valign="middle" align="left">Leukemia</td>
<td valign="middle" align="center">0.639</td>
<td valign="middle" align="center">0.547-0.713</td>
<td valign="middle" align="center">&lt; 0.0001</td>
<td valign="middle" align="center">0.615</td>
<td valign="middle" align="center">0.518-0.729</td>
<td valign="middle" align="center">&lt; 0.0001</td>
</tr>
<tr>
<td valign="middle" align="left">Non-Hodgkin lymphoma</td>
<td valign="middle" align="center">1.048</td>
<td valign="middle" align="center">0.926-1.186</td>
<td valign="middle" align="center">0.457</td>
<td valign="middle" align="center">0.981</td>
<td valign="middle" align="center">0.818-1.176</td>
<td valign="middle" align="center">0.835</td>
</tr>
<tr>
<td valign="middle" align="left">Lung</td>
<td valign="middle" align="center">1.14</td>
<td valign="middle" align="center">1.006-1.292</td>
<td valign="middle" align="center">0.04</td>
<td valign="middle" align="center">1.028</td>
<td valign="middle" align="center">0.858-1.232</td>
<td valign="middle" align="center">0.765</td>
</tr>
<tr>
<td valign="middle" align="left">Breast</td>
<td valign="middle" align="center">1.013</td>
<td valign="middle" align="center">0.871-1.179</td>
<td valign="middle" align="center">0.863</td>
<td valign="middle" align="center">0.848</td>
<td valign="middle" align="center">0.675-1.066</td>
<td valign="middle" align="center">0.157</td>
</tr>
<tr>
<td valign="middle" align="left">Liver</td>
<td valign="middle" align="center">1.252</td>
<td valign="middle" align="center">1.046-1.499</td>
<td valign="middle" align="center">0.014</td>
<td valign="middle" align="center">1.079</td>
<td valign="middle" align="center">0.835-1.396</td>
<td valign="middle" align="center">0.56</td>
</tr>
<tr>
<td valign="middle" align="left">Colon</td>
<td valign="middle" align="center">1.086</td>
<td valign="middle" align="center">0.922-1.279</td>
<td valign="middle" align="center">0.322</td>
<td valign="middle" align="center">0.976</td>
<td valign="middle" align="center">0.768-1.239</td>
<td valign="middle" align="center">0.848</td>
</tr>
<tr>
<td valign="middle" align="left">Bladder</td>
<td valign="middle" align="center">1.047</td>
<td valign="middle" align="center">0.892-1.229</td>
<td valign="middle" align="center">0.573</td>
<td valign="middle" align="center">0.741</td>
<td valign="middle" align="center">0.576-0.954</td>
<td valign="middle" align="center">0.019</td>
</tr>
<tr>
<td valign="middle" align="left">All types of cancer</td>
<td valign="middle" align="center">1.103</td>
<td valign="middle" align="center">1.069-1.139</td>
<td valign="middle" align="center">&lt;0.0001</td>
<td valign="middle" align="center">1.003</td>
<td valign="middle" align="center">0.956-1.053</td>
<td valign="middle" align="center">0.892</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>CI, confidence interval; HR, hazard ratio.</p>
</fn>
<fn>
<p>
<sup>*</sup>Adjusted for age, gender and race.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>Regarding the variation of outcomes (graft failure and mortality) for patients with PTM over the past two decades, we found a trend toward reduction in graft failure (HR 0.442 95% CI 0.413-0.473, P &lt; 0.000) and overall mortality (HR 0.755 95% CI 0.713-0.801, P &lt; 0.0001 for overall mortality). <xref ref-type="fig" rid="f2">
<bold>Figures&#xa0;2</bold>
</xref>, <xref ref-type="fig" rid="f3">
<bold>3</bold>
</xref> compares the graft failure and mortality rates for post-KTX malignancy between the 2000&#x2013;2010 and 2011&#x2013;2021 cohorts.</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Forest plots of graft failure and overall mortality for kidney transplantation recipients with malignancy who underwent KTX in 2000-2010 or 2011-2021 using 2000-2010 cohort as a reference. Adjusted for age, gender and race. KTX, kidney transplantation.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-16-1626135-g002.tif">
<alt-text content-type="machine-generated">Forest plot comparing graft failure and mortality between different cancer types for two periods: 2000-2010 and 2011-2021. Hazard ratios (HR), confidence intervals (CI), and p-values are presented for non-melanoma skin, kidney, prostate, leukemia, non-Hodgkin lymphoma, lung, breast, liver, colon, bladder, and all cancers. Graph shows better outcomes for 2011-2021 on the left side of the scale.</alt-text>
</graphic>
</fig>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Kaplan-Meier survival curve of overall <bold>(A)</bold> and graft survival <bold>(B)</bold> for recipients with post-KTX malignancy who underwent KTX in 2000-2010 or 2011-2021. KTX, kidney transplantation.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-16-1626135-g003.tif">
<alt-text content-type="machine-generated">Kaplan-Meier survival curves illustrating survival probabilities over time. Panel A shows overall survival, while Panel B displays graft survival, comparing data from 2011-2021 (blue line) and 2000-2010 (orange line). Both panels indicate a significant difference with a Log Rank P value less than 0.0001. The number at risk is listed below each curve at various time intervals.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3_5">
<title>Impact of malignancy on outcomes for KTX recipients</title>
<p>Patients with PTM were associated with a higher risk of mortality (HR 1.115 95% CI 1.071-1.763 P &lt; 0.0001) compared with the general population with malignancy after PSM. For specific cancer: non-melanoma skin cancer (HR 2.88 95% CI 2.699-3.007) and breast cancer (HR 2.17 95% CI 1.852-2.543) were associated with the worst overall survival compared with the general population with cancers (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>).</p>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<title>Discussion</title>
<p>In this study, we found that patients with KTX were associated with a higher risk of malignancy when compared with the general population. Recipients with post-KTX malignancy had worse overall survival compared with the general population with malignancy. There was no significant change in cancer incidence for KTX recipients over the past 20 years, but graft failure and mortality rates decreased in the recent decade.</p>
<p>Previous studies reported higher malignancy risks of 2 to 4-fold in kidney transplantation recipients compared with the general population (<xref ref-type="bibr" rid="B8">8</xref>&#x2013;<xref ref-type="bibr" rid="B17">17</xref>). In this study, we found that such patients had an increased risk of developing malignancy following kidney transplantation (SIR:1.635) compared with the general population. The slightly lower SIR is likely related to the fact that we excluded patients with history of malignancy before transplantation. In general, most sites of cancer presented higher SIR compared with the general population. On the other hand, breast and prostate cancer did not show an elevated risk, the real reason was unclear, and this finding was consistent with the study conducted by Engels et&#xa0;al. (<xref ref-type="bibr" rid="B12">12</xref>).</p>
<p>A higher risk of malignancy for KTX recipients may be resulted from several factors (<xref ref-type="bibr" rid="B16">16</xref>). Immunosuppression may be the reason for virus induced cancers. For example, hepatitis B virus and hepatitis c virus for liver cancer, and human T cell lymphotropic virus for non-Hodgkin lymphoma. On the other hand, for non-virus mediated cancers, including common cancers in general population (lung, colon, breast, and prostate cancer) and ESRD patients (kidney and bladder cancer), closer cancer screening tests may have contributed to a higher incidence rate for those patients (<xref ref-type="bibr" rid="B18">18</xref>&#x2013;<xref ref-type="bibr" rid="B20">20</xref>).</p>
<p>The mortality rates between KTX patients with cancer and the general population with cancer were debatable. Kiberd et&#xa0;al. reported that there was no difference in cancer mortality between these two populations (<xref ref-type="bibr" rid="B29">29</xref>). However, some studies report a higher mortality rate for patients with PTM compared with the general population (<xref ref-type="bibr" rid="B30">30</xref>&#x2013;<xref ref-type="bibr" rid="B32">32</xref>). In this study, we found that the overall survival of KTX recipients was worse for those with PTM compared with the general population for most cancer types and overall malignancy (HR 1.115 95% CI 1.071-1.763 P &lt; 0.0001). The results indicated a challenging condition in treating these KTX recipients with malignancy under immunosuppressants, which may limit the use of chemotherapy or immunotherapy.</p>
<p>Previous reports on the median time from kidney transplantation (KTX) to cancer diagnosis have been limited and variable, ranging from 2.6 to 4 years (<xref ref-type="bibr" rid="B32">32</xref>, <xref ref-type="bibr" rid="B33">33</xref>). In our study, the interval from KTX to cancer diagnosis was comparatively shorter (2.54 years). This difference may be attributable to more intensive cancer screening following KTX as well as the increasing use of marginal donors and recipient. Importantly, these results highlight the need for closer surveillance for common post-transplant malignancies.</p>
<p>The use of mammalian target of rapamycin (mTOR) inhibitors has been associated with a reduced incidence of malignancy in several studies (<xref ref-type="bibr" rid="B28">28</xref>, <xref ref-type="bibr" rid="B34">34</xref>, <xref ref-type="bibr" rid="B35">35</xref>). However, conflicting evidence has been reported regarding the cancer risk associated with sirolimus use in recipients (<xref ref-type="bibr" rid="B36">36</xref>, <xref ref-type="bibr" rid="B37">37</xref>). A meta-analysis by Knoll et&#xa0;al. indicated that the anti-cancer benefits of sirolimus were primarily observed in patients who were converted from other immunosuppressive regimens, rather than in those who received <italic>de novo</italic> sirolimus (<xref ref-type="bibr" rid="B34">34</xref>). Furthermore, <italic>de novo</italic> use of sirolimus was associated with an increased risk of post-transplant lymphoproliferative disorder (<xref ref-type="bibr" rid="B38">38</xref>). In our study, multivariate analysis revealed that the use of mTOR inhibitors was associated with an increased risk of PTM (HR 1.306&#x2013;95 CI 1.218-1.401). Previous studies have shown that calcineurin inhibitors (CNIs), such as cyclosporin and tacrolimus, are associated with a heightened risk of PTM, potentially due to their immunosuppressive or carcinogenic properties (<xref ref-type="bibr" rid="B32">32</xref>, <xref ref-type="bibr" rid="B39">39</xref>). Consistent with these findings, multivariate analysis identified tacrolimus (HR 1.135&#x2013;95 CI 1.098-1.173) and cyclosporin (HR 1.284&#x2013;95 CI 1.214-1.358) as risk factors for PTM when used as maintenance immunosuppressive therapies. Notably, we did not observe a significant association between elevated serum tacrolimus levels and PTM. This may be attributed to the dynamic nature of tacrolimus serum levels and the lack of standardized timing for level measurement in the TriNetX database. These findings underscore that immunosuppression remains a key factor for PTM, regardless of the specific regimen used. Therefore, enhanced cancer surveillance is warranted in kidney transplant recipients (<xref ref-type="bibr" rid="B24">24</xref>, <xref ref-type="bibr" rid="B40">40</xref>, <xref ref-type="bibr" rid="B41">41</xref>).</p>
<p>Blosser CD, et&#xa0;al. and Piselli P, et&#xa0;al. reported that there was no significant change in incidence of PTM over time (<xref ref-type="bibr" rid="B42">42</xref>, <xref ref-type="bibr" rid="B43">43</xref>). Our results align with previous evidence, indicating that the overall incidence of PTM has remained relatively stable over the last twenty years. In the unadjusted analysis, increased incidences of kidney, prostate, and overall cancer were observed. These findings may be attributable to the older age of recipients and the increased intensity of cancer screening in recent years. However, after adjusting for these factors, the overall cancer incidence did not show a significant increase over the past two decades. Blosser et&#xa0;al. previously reported no significant improvement in graft or patient survival among kidney transplant recipients with non-Hodgkin lymphoma (non-NHL) malignancies (<xref ref-type="bibr" rid="B42">42</xref>). In contrast, our study demonstrated a decline in both graft failure and patient mortality among recipients diagnosed with PTM over the past two decades. Although the exact mechanisms underlying these observations remain unclear, the trends may be partially attributable to improvements in post-transplantation care, including advancements in oncologic treatments and the management of infectious and cardiovascular complications, which could positively influence graft and patient survival.</p>
<p>This study has several limitations inherent to its retrospective design, including the possibility of residual confounding despite adjustment for known covariates. The use of the TriNetX database, while providing a large sample size, is limited by the absence of detailed cancer-specific outcome metrics such as tumor staging, histopathology, treatment modalities, and cause-specific mortality, which restricts the depth of interpretation. Additionally, the reliance on administrative coding may introduce misclassification bias in diagnoses and outcomes. Selection bias is also a concern, as the dataset represents patients from specific healthcare organizations and may not fully generalize to the broader transplant population. Furthermore, patients in the more recent transplant cohort may have shorter follow-up durations, potentially leading to an underestimation of cancer incidence in this group. Lastly, we defined PTM as any cancer diagnosis occurring &#x2265;1 month following kidney transplantation. It is acknowledged that this definition may inadvertently capture malignancies that were present but undiagnosed at the time of transplantation. Despite these limitations, our research was a population-based study with a large sample size, which may avoid some bias arising from its retrospective nature. Furthermore, data regarding the trends of PTM over the past decades was limited, and our research provided information on this topic.</p>
<p>In conclusion, KTX recipients exhibited a significantly higher risk of PTM compared with the general population. Moreover, the presence of PTM was associated with increased overall mortality. Although the incidence of PTM has remained stable over the past two decades, both graft failure and mortality risks among patients with PTM have shown a significant decline during the same period.</p>
</sec>
</body>
<back>
<sec id="s5" sec-type="data-availability">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Material</bold>
</xref>. Further inquiries can be directed to the corresponding author.</p>
</sec>
<sec id="s6" sec-type="ethics-statement">
<title>Ethics statement</title>
<p>The studies involving humans were approved by Institutional Review Board of Taichung Veterans General Hospital (IRB number: SE:22220A). The studies were conducted in accordance with the local legislation and institutional requirements. The ethics committee/institutional review board waived the requirement of written informed consent for participation from the participants or the participants' legal guardians/next of kin because All data on the database was de-identified.</p>
</sec>
<sec id="s7" sec-type="author-contributions">
<title>Author contributions</title>
<p>G-SL: Investigation, Software, Conceptualization, Resources, Writing &#x2013; original draft, Visualization, Funding acquisition, Validation, Formal analysis, Methodology, Supervision, Data curation, Project administration, Writing &#x2013; review &amp; editing. J-RL: Writing &#x2013; review &amp; editing. C-SC: Writing &#x2013; review &amp; editing. S-SW: Writing &#x2013; review &amp; editing. C-YL: Writing &#x2013; review &amp; editing. C-JY: Writing &#x2013; review &amp; editing. H-CH: Writing &#x2013; review &amp; editing. S-CH: Writing &#x2013; review &amp; editing. K-YC: Writing &#x2013; review &amp; editing. C-KY: Writing &#x2013; review &amp; editing.</p>
</sec>
<sec id="s8" sec-type="funding-information">
<title>Funding</title>
<p>The author(s) declare that no financial support was received for the research and/or publication of this article.</p>
</sec>
<ack>
<title>Acknowledgments</title>
<p>The data used in this study was retrieved from the TriNetX network.</p>
</ack>
<sec id="s9" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="s10" sec-type="ai-statement">
<title>Generative AI statement</title>
<p>The author(s) declare that no Generative AI was used in the creation of this manuscript.</p>
<p>Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If&#xa0;you identify any issues, please contact us.</p>
</sec>
<sec id="s11" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors&#xa0;and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec id="s12" sec-type="supplementary-material">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fimmu.2025.1626135/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fimmu.2025.1626135/full#supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="DataSheet1.csv" id="SM1" mimetype="text/csv"/>
<supplementary-material xlink:href="DataSheet2.csv" id="SM2" mimetype="text/csv"/>
<supplementary-material xlink:href="DataSheet3.csv" id="SM3" mimetype="text/csv"/>
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