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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Transpl. Int.</journal-id>
<journal-title-group>
<journal-title>Transplant International</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Transpl. Int.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1432-2277</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">15709</article-id>
<article-id pub-id-type="doi">10.3389/ti.2025.15709</article-id>
<article-version article-version-type="Version of Record" vocab="NISO-RP-8-2008"/>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Original Research</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Simultaneous Pancreas&#x2013;Kidney Versus Kidney Transplant Alone: Real-World Outcomes in a Propensity-Matched Global Cohort</article-title>
<alt-title alt-title-type="left-running-head">Catarinella et al.</alt-title>
<alt-title alt-title-type="right-running-head">SPKT Vs. DDKT Outcomes</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Catarinella</surname>
<given-names>Davide</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/3131875"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Williford</surname>
<given-names>Sarah</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Rusconi</surname>
<given-names>Francesca</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Caldara</surname>
<given-names>Rossana</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1685213"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Piemonti</surname>
<given-names>Lorenzo</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/182191"/>
</contrib>
</contrib-group>
<aff id="aff1">
<label>1</label>
<institution>Diabetes Research Institute, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Ospedale San Raffaele</institution>, <city>Milan</city>, <country country="IT">Italy</country>
</aff>
<aff id="aff2">
<label>2</label>
<institution>TriNetX LLC</institution>, <city>Cambridge</city>, <country country="US">MA, United States</country>
</aff>
<aff id="aff3">
<label>3</label>
<institution>TriNetX Europe BV</institution>, <city>Sint-Martens-Latem</city>, <country country="BE">Belgium</country>
</aff>
<aff id="aff4">
<label>4</label>
<institution>Diabetes Research Institute, Universita Vita Salute San Raffaele</institution>, <city>Milan</city>, <country country="IT">Italy</country>
</aff>
<author-notes>
<corresp id="c001">
<label>&#x2a;</label>Correspondence: Lorenzo Piemonti, <email xlink:href="mailto:piemonti.lorenzo@hsr.it">piemonti.lorenzo@hsr.it</email>
</corresp>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2025-12-30">
<day>30</day>
<month>12</month>
<year>2025</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2025</year>
</pub-date>
<volume>38</volume>
<elocation-id>15709</elocation-id>
<history>
<date date-type="received">
<day>08</day>
<month>10</month>
<year>2025</year>
</date>
<date date-type="rev-recd">
<day>13</day>
<month>11</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>16</day>
<month>12</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2025 Catarinella, Williford, Rusconi, Caldara and Piemonti.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Catarinella, Williford, Rusconi, Caldara and Piemonti</copyright-holder>
<license>
<ali:license_ref start_date="2025-12-30">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>
<p>The true comparative effectiveness of simultaneous pancreas&#x2013;kidney transplantation (SPKT) versus kidney transplantation alone (KTA) in patients with diabetes and end-stage renal disease remains incompletely defined. Using the TriNetX Global Collaborative Network (2010&#x2013;2024), we identified 3,679 SPKT and 27,062 KTA recipients aged 18&#x2013;59&#xa0;years. In unmatched comparisons, SPKT recipients showed lower mortality, fewer cardiovascular events, and improved kidney graft survival relative to KTA recipients, but also higher early rejection, infection, and readmission rates. After 1:1 propensity score matching, the cohorts were well balanced across all measured covariates, and long-term estimates for survival (HR 1.00, 95% CI 0.90&#x2013;1.10), kidney graft failure (HR 0.99, 95% CI 0.94&#x2013;1.04), and cardiovascular events (HR 0.99, 95% CI 0.94&#x2013;1.05) no longer differed over 10 years. In contrast, SPKT recipients maintained significantly lower HbA1c levels throughout follow-up (mean 6.2% vs. 6.6% at 5&#xa0;years; p &#x3c; 0.001), reflecting sustained physiologic glycaemic control and a high probability of insulin independence. Sensitivity analyses restricted to type 1 diabetes and non-obese recipients yielded consistent results. After accounting for measured differences between recipients, we did not detect a long-term survival advantage of SPKT over KTA, whereas durable metabolic benefits persisted. Because key donor and immunologic characteristics were not available, a modest intrinsic survival benefit cannot be excluded. These findings highlight the major role of patient selection and support individualised use of SPKT for metabolic indications and quality-of-life improvement rather than survival gain alone.</p>
</abstract>
<abstract abstract-type="graphical">
<title>Graphical Abstract</title>
<p>
<fig>
<graphic xlink:href="TI_ti-2025-15709_wc_abs.tif" position="anchor">
<alt-text content-type="machine-generated">Cohort comparison graphic for simultaneous pancreas-kidney transplant (SPKT) versus kidney transplant alone (KTA) with 27,062 KTA and 3,679 SPKT patients. Propensity matching results in two equal cohorts of 3,679. Graphs show all-cause mortality and HbA1c outcomes, with SPKT providing a metabolic benefit but higher early complications. Survival, graft, and cardiovascular outcomes are comparable. SPKT should be individualized for metabolic and quality-of-life improvements. Published by Catarinella et al. in Transpl. Int. 2025. DOI is provided at the bottom.</alt-text>
</graphic>
</fig>
</p>
</abstract>
<kwd-group>
<kwd>simultaneous pancreas&#x2013;kidney transplantation</kwd>
<kwd>kidney transplantation</kwd>
<kwd>diabetes mellitus</kwd>
<kwd>end-stage renal disease</kwd>
<kwd>patient survival</kwd>
</kwd-group>
<funding-group>
<funding-statement>The author(s) declared that financial support was not received for this work and/or its publication.</funding-statement>
</funding-group>
<counts>
<fig-count count="2"/>
<table-count count="1"/>
<equation-count count="0"/>
<ref-count count="60"/>
<page-count count="9"/>
</counts>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="s1">
<title>Introduction</title>
<p>Simultaneous pancreas&#x2013;kidney transplantation (SPKT) is a consolidated therapeutic option for patients with diabetes mellitus and end-stage renal disease (ESRD) who are eligible for pancreas transplantation [<xref ref-type="bibr" rid="B1">1</xref>&#x2013;<xref ref-type="bibr" rid="B3">3</xref>]. By replacing both organs simultaneously, SPKT provides restoration of renal function together with endogenous insulin secretion, offering the potential for insulin independence and durable metabolic control [<xref ref-type="bibr" rid="B4">4</xref>&#x2013;<xref ref-type="bibr" rid="B7">7</xref>]. Kidney transplantation alone (KTA) remains the most common approach worldwide due to its broader applicability, lower surgical complexity, and higher availability of organs, but it does not address the underlying diabetes or its long-term complications [<xref ref-type="bibr" rid="B8">8</xref>]. The theoretical advantages of SPKT extend beyond kidney graft survival and patient longevity [<xref ref-type="bibr" rid="B9">9</xref>]. Normalization of glycaemic control after successful pancreas transplantation improves HbA1c and reduces glycaemic variability, thereby decreasing the risk of acute metabolic decompensation and potentially preventing or slowing the progression of microvascular and macrovascular complications of diabetes [<xref ref-type="bibr" rid="B10">10</xref>&#x2013;<xref ref-type="bibr" rid="B15">15</xref>]. Several observational studies have suggested that SPKT recipients achieve superior metabolic outcomes and quality of life compared with patients undergoing KTA, who remain insulin-dependent and often face suboptimal glucose control despite advances in medical therapy [<xref ref-type="bibr" rid="B16">16</xref>]. Despite these potential benefits, the impact of SPKT on hard clinical outcomes has been debated. Some registry-based analyses and single-centre reports have described lower mortality and cardiovascular events among SPKT recipients [<xref ref-type="bibr" rid="B17">17</xref>&#x2013;<xref ref-type="bibr" rid="B22">22</xref>], particularly in type 1 diabetes [<xref ref-type="bibr" rid="B23">23</xref>, <xref ref-type="bibr" rid="B24">24</xref>], while others have failed to confirm a survival advantage once differences in baseline risk profiles are accounted for [<xref ref-type="bibr" rid="B25">25</xref>&#x2013;<xref ref-type="bibr" rid="B30">30</xref>]. Moreover, SPKT carries higher perioperative morbidity, increased immunosuppression, and greater risk of early complications, raising concerns about the overall balance of risks and benefits [<xref ref-type="bibr" rid="B31">31</xref>&#x2013;<xref ref-type="bibr" rid="B33">33</xref>]. In the recent era, with improvements in surgical techniques [<xref ref-type="bibr" rid="B34">34</xref>&#x2013;<xref ref-type="bibr" rid="B36">36</xref>], perioperative care [<xref ref-type="bibr" rid="B37">37</xref>&#x2013;<xref ref-type="bibr" rid="B40">40</xref>], immunosuppressive strategies [<xref ref-type="bibr" rid="B41">41</xref>&#x2013;<xref ref-type="bibr" rid="B43">43</xref>], and diabetes management [<xref ref-type="bibr" rid="B44">44</xref>], it remains unclear whether the historical advantages of SPKT over KTA persist in real-world practice. Importantly, while survival and graft outcomes are critical endpoints, the ability of SPKT to provide superior long-term glycaemic control represents a distinctive and clinically meaningful outcome that may translate into downstream benefits for patients. Large-scale real-world data may help clarify these uncertainties. TriNetX, a federated network of healthcare organizations, aggregates longitudinal electronic health records and enables comparative effectiveness research across diverse populations with robust analytic tools, including propensity score methods to mitigate baseline imbalances [<xref ref-type="bibr" rid="B45">45</xref>]. The objective of this study was to compare long-term outcomes of SPKT versus KTA in patients with diabetes and ESRD using the TriNetX Global Collaborative Network. We evaluated survival, kidney and pancreas graft outcomes, cardiovascular events, diabetes-related acute and chronic complications, malignancies, and mental health, with a particular focus on whether the improved glycaemic control achieved by SPKT translates into clinical benefit in the new era of transplantation.</p>
</sec>
<sec sec-type="materials|methods" id="s2">
<title>Materials and Methods</title>
<sec id="s2-1">
<title>Data Source and Ethics</title>
<p>We performed a retrospective cohort study using the TriNetX Global Collaborative Network (2010&#x2013;2024, access date 23 September 2025), which aggregates de-identified EHR data from &#x3e;150 healthcare organizations worldwide. The network provides demographics, diagnoses, procedures, laboratory values, medications, and vitals. Data are de-identified per HIPAA and GDPR; institutional review board approval and informed consent were not required for analyses of de-identified data.</p>
</sec>
<sec id="s2-2">
<title>Study Population</title>
<p>Adults aged 18&#x2013;59&#xa0;years with diabetes and end-stage renal disease who underwent either simultaneous pancreas&#x2013;kidney transplantation (SPKT) or kidney transplantation alone (KTA) were identified by transplant procedure codes. Exclusions: paediatric (&#x3c;18&#xa0;years) or older adults (&#x3e;59&#xa0;years), living-donor or multi-organ transplants, and records lacking a valid index date. The unmatched cohorts comprised 3,679 SPKT and 27,062 KTA recipients.</p>
</sec>
<sec id="s2-3">
<title>Exposure, Index Event and Follow-Up</title>
<p>The exposure was transplant type (SPKT vs. KTA). The index event was the date of transplantation. For survival analyses (Kaplan&#x2013;Meier and Cox regression), outcomes were assessed from 90&#xa0;days post-transplant. For fixed-timepoint estimates, 1-year outcomes were calculated including events from day 10 post-transplant, while 5- and 10-year outcomes were calculated including events from day 90 onwards.</p>
</sec>
<sec id="s2-4">
<title>Outcomes</title>
<p>Primary outcomes were (i) all-cause mortality, (ii) kidney graft failure, and (iii) death-censored graft failure. Secondary outcomes included: major adverse kidney events (MAKE: dialysis dependence, eGFR &#x3c;15&#xa0;mL/min/1.73&#xa0;m<sup>2</sup>, transplant complications, or graft failure), transplant-related complications (ICD-10 T86.x), cardiovascular events (composite and components: acute myocardial infarction, stroke, heart failure, cardiac arrest, revascularization), infections/sepsis, treated acute rejection, 1-year hospital readmission, metabolic complications (hypoglycaemia; ketoacidosis/hyperosmolarity), microvascular complications (new-onset neuropathy; retinopathy), mental health (post-transplant depression/anxiety), and oncologic outcomes (PTLD/other neoplasms). Laboratory endpoints were most recent HbA1c and eGFR.</p>
<p>Detailed definitions of all outcomes, including the exact ICD-10 and procedure code lists used to define exposures, comorbidities and endpoints (e.g., cardiovascular events, rejection, infection, neuropathy), are provided in the Supplementary Methods. These definitions were pre-specified before any outcome analyses.</p>
</sec>
<sec id="s2-5">
<title>Statistical Analysis</title>
<p>Comparative analyses between cohorts were performed using risk difference, risk ratio, and odds ratio with 95% confidence intervals, as well as Kaplan&#x2013;Meier curves with log-rank tests and Cox proportional hazards regression. Propensity score matching (1:1 nearest-neighbour with caliper 0.1) was applied to balance baseline demographic, clinical, and laboratory covariates. For all Cox models we assessed the proportional hazards assumption visually and using Schoenfeld residuals; no major violations were detected. Further details on cohort definitions, index event and time windows, analytic settings, outcome definitions (including ICD, CPT, and laboratory codes), and propensity score methodology are reported in the Supplementary Methods.</p>
</sec>
</sec>
<sec sec-type="results" id="s3">
<title>Result</title>
<sec id="s3-1">
<title>Baseline Characteristics</title>
<p>A total of 3,679 SPKT and 27,062 KTA recipients were identified. Before matching, SPKT recipients were younger, more often type 1 diabetic, and carried fewer cardiovascular comorbidities, whereas KTA recipients were more frequently of Black or Hispanic ethnicity and more commonly had ischemic heart disease, heart failure, dyslipidaemia, and obesity (<xref ref-type="sec" rid="s11">Supplementary Table S1</xref>). After 1:1 propensity score matching, well-balanced pairs were generated with excellent covariate balance (all SMD &#x3c;0.1; <xref ref-type="sec" rid="s11">Supplementary Table S1</xref>; <xref ref-type="sec" rid="s11">Supplementary Figures S1&#x2013;S2</xref>). Median follow-up was &#x223c;6&#xa0;years in both groups. At the most recent assessment, HbA1c values were lower in SPKT compared with KTA recipients, both before matching (6.23% &#xb1; 1.68% vs. 7.11% &#xb1; 1.77%; p &#x3c; 0.0001) and after matching (6.23% &#xb1; 1.68% vs. 6.58% &#xb1; 1.78%; p &#x3c; 0.0001), although the difference was attenuated after adjustment. A similar pattern was seen for kidney function: eGFR was higher among SPKT recipients before matching (48.5 &#xb1; 29.3 vs. 44.1 &#xb1; 28.8&#xa0;mL/min/1.73&#xa0;m<sup>2</sup>; p &#x3c; 0.0001), with only a modest residual difference after matching (48.5 &#xb1; 29.3 vs. 46.7 &#xb1; 29.0&#xa0;mL/min/1.73&#xa0;m<sup>2</sup>; p &#x3d; 0.013).</p>
</sec>
<sec id="s3-2">
<title>Primary Outcomes</title>
<p>In the unmatched cohorts, SPKT recipients experienced significantly lower mortality compared with KTA, with hazard ratios well below unity and consistently favourable risk estimates at both 5 and 10&#xa0;years (<xref ref-type="table" rid="T1">Table 1</xref>; <xref ref-type="sec" rid="s11">Supplementary Tables S3&#x2013;S4</xref>). Kaplan&#x2013;Meier curves confirmed superior survival in SPKT (<xref ref-type="fig" rid="F1">Figure 1</xref>). After propensity score matching, however, survival probabilities became virtually identical, and the risk of death did not differ between groups across all time points (<xref ref-type="sec" rid="s11">Supplementary Tables S3&#x2013;S4</xref>). Unadjusted Kaplan&#x2013;Meier analysis suggested a modest advantage for SPKT, with lower cumulative incidence of graft loss over time (<xref ref-type="table" rid="T1">Table 1</xref>; <xref ref-type="fig" rid="F1">Figure 1</xref>). However, risk estimates at 5 and 10&#xa0;years indicated only minimal differences between groups, with relative risks close to unity (<xref ref-type="sec" rid="s11">Supplementary Tables S3, S4</xref>). After propensity score matching, graft outcomes were fully comparable, with no evidence of a significant difference at any time point (<xref ref-type="sec" rid="s11">Supplementary Tables S3, S4</xref>). In contrast, death-censored analyses showed less favourable outcomes for SPKT. In the unmatched population, the risk of death-censored graft failure was slightly higher in SPKT, particularly in the early post-transplant period, with relative risks favouring KTA (<xref ref-type="sec" rid="s11">Supplementary Tables S3, S4</xref>). Kaplan&#x2013;Meier curves showed largely overlapping trajectories (<xref ref-type="fig" rid="F1">Figure 1</xref>). After matching, the differences disappeared, with similar risks of death-censored graft loss between groups (<xref ref-type="table" rid="T1">Table 1</xref>; <xref ref-type="sec" rid="s11">Supplementary Tables S3, S4</xref>).</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Longitudinal outcomes (Kaplan&#x2013;Meier and Cox models): SPKT vs. KTA.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Outcome</th>
<th align="center">Cohort</th>
<th align="center">Hazard ratio (95% CI)</th>
<th align="center">KM log-rank p</th>
<th align="center">Direction</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td rowspan="2" align="left">All-cause mortality</td>
<td align="left">PS-matched</td>
<td align="center">1.00 (0.91&#x2013;1.11)</td>
<td align="center">0.97</td>
<td align="left">Neutral</td>
</tr>
<tr>
<td align="left">Pre-matching</td>
<td align="center">0.76 (0.71&#x2013;0.83)</td>
<td align="center">&#x3c;0.001</td>
<td align="left">Favors SPKT</td>
</tr>
<tr>
<td rowspan="2" align="left">Kidney graft failure</td>
<td align="left">PS-matched</td>
<td align="center">0.97 (0.91&#x2013;1.04)</td>
<td align="center">0.38</td>
<td align="left">Neutral</td>
</tr>
<tr>
<td align="left">Pre-matching</td>
<td align="center">0.92 (0.87&#x2013;0.97)</td>
<td align="center">0.001</td>
<td align="left">Favors SPKT</td>
</tr>
<tr>
<td rowspan="2" align="left">Death-censored graft failure</td>
<td align="left">PS-matched</td>
<td align="center">0.99 (0.92&#x2013;1.07)</td>
<td align="center">0.79</td>
<td align="left">Neutral</td>
</tr>
<tr>
<td align="left">Pre-matching</td>
<td align="center">1.05 (0.99&#x2013;1.11)</td>
<td align="center">0.11</td>
<td align="left">Neutral</td>
</tr>
<tr>
<td rowspan="2" align="left">MAKE</td>
<td align="left">PS-matched</td>
<td align="center">0.96 (0.91&#x2013;1.01)</td>
<td align="center">0.10</td>
<td align="left">Neutral</td>
</tr>
<tr>
<td align="left">Pre-matching</td>
<td align="center">0.82 (0.79&#x2013;0.85)</td>
<td align="center">&#x3c;0.001</td>
<td align="left">Favors SPKT</td>
</tr>
<tr>
<td rowspan="2" align="left">Post-transplant cardiovascular events</td>
<td align="left">PS-matched</td>
<td align="center">0.98 (0.91&#x2013;1.05)</td>
<td align="center">0.55</td>
<td align="left">Neutral</td>
</tr>
<tr>
<td align="left">Pre-matching</td>
<td align="center">0.73 (0.69&#x2013;0.77)</td>
<td align="center">&#x3c;0.001</td>
<td align="left">Favors SPKT</td>
</tr>
<tr>
<td rowspan="2" align="left">Treated acute rejection</td>
<td align="left">PS-matched</td>
<td align="center">1.02 (0.95&#x2013;1.11)</td>
<td align="center">0.57</td>
<td align="left">Neutral</td>
</tr>
<tr>
<td align="left">Pre-matching</td>
<td align="center">1.16 (1.09&#x2013;1.23)</td>
<td align="center">&#x3c;0.001</td>
<td align="left">Favors KTA</td>
</tr>
<tr>
<td rowspan="2" align="left">Acute myocardial infarction (first event)</td>
<td align="left">PS-matched</td>
<td align="center">1.09 (0.94&#x2013;1.25)</td>
<td align="center">0.26</td>
<td align="left">Neutral</td>
</tr>
<tr>
<td align="left">Pre-matching</td>
<td align="center">0.89 (0.80&#x2013;0.99)</td>
<td align="center">0.04</td>
<td align="left">Favors SPKT</td>
</tr>
<tr>
<td rowspan="2" align="left">Heart failure (first event)</td>
<td align="left">PS-matched</td>
<td align="center">0.94 (0.84&#x2013;1.05)</td>
<td align="center">0.25</td>
<td align="left">Neutral</td>
</tr>
<tr>
<td align="left">Pre-matching</td>
<td align="center">0.70 (0.64&#x2013;0.76)</td>
<td align="center">&#x3c;0.001</td>
<td align="left">Favors SPKT</td>
</tr>
<tr>
<td rowspan="2" align="left">Stroke (first event)</td>
<td align="left">PS-matched</td>
<td align="center">1.05 (0.87&#x2013;1.25)</td>
<td align="center">0.63</td>
<td align="left">Neutral</td>
</tr>
<tr>
<td align="left">Pre-matching</td>
<td align="center">0.87 (0.76&#x2013;1.00)</td>
<td align="center">0.05</td>
<td align="left">Favors SPKT</td>
</tr>
<tr>
<td rowspan="2" align="left">Infection or sepsis</td>
<td align="left">PS-matched</td>
<td align="center">1.00 (0.92&#x2013;1.08)</td>
<td align="center">0.98</td>
<td align="left">Neutral</td>
</tr>
<tr>
<td align="left">Pre-matching</td>
<td align="center">0.87 (0.82&#x2013;0.93)</td>
<td align="center">&#x3c;0.001</td>
<td align="left">Favors SPKT</td>
</tr>
<tr>
<td rowspan="2" align="left">Hypoglycaemia</td>
<td align="left">PS-matched</td>
<td align="center">1.00 (0.89&#x2013;1.12)</td>
<td align="center">0.93</td>
<td align="left">Neutral</td>
</tr>
<tr>
<td align="left">Pre-matching</td>
<td align="center">0.89 (0.81&#x2013;0.97)</td>
<td align="center">0.01</td>
<td align="left">Favors SPKT</td>
</tr>
<tr>
<td rowspan="2" align="left">Ketoacidosis/hyperosmolarity</td>
<td align="left">PS-matched</td>
<td align="center">0.95 (0.83&#x2013;1.09)</td>
<td align="center">0.50</td>
<td align="left">Neutral</td>
</tr>
<tr>
<td align="left">Pre-matching</td>
<td align="center">1.20 (1.08&#x2013;1.33)</td>
<td align="center">0.001</td>
<td align="left">Favors KTA</td>
</tr>
<tr>
<td rowspan="2" align="left">Depression/Anxiety onset post-Tx</td>
<td align="left">PS-matched</td>
<td align="center">0.99 (0.89&#x2013;1.11)</td>
<td align="center">0.87</td>
<td align="left">Neutral</td>
</tr>
<tr>
<td align="left">Pre-matching</td>
<td align="center">1.07 (0.98&#x2013;1.16)</td>
<td align="center">0.13</td>
<td align="left">Neutral</td>
</tr>
<tr>
<td rowspan="2" align="left">Diabetic neuropathy (new onset)</td>
<td align="left">PS-matched</td>
<td align="center">1.11 (0.99&#x2013;1.24)</td>
<td align="center">0.06</td>
<td align="left">Neutral</td>
</tr>
<tr>
<td align="left">Pre-matching</td>
<td align="center">1.04 (0.96&#x2013;1.14)</td>
<td align="center">0.31</td>
<td align="left">Neutral</td>
</tr>
<tr>
<td rowspan="2" align="left">Diabetic retinopathy (new onset)</td>
<td align="left">PS-matched</td>
<td align="center">1.06 (0.93&#x2013;1.20)</td>
<td align="center">0.38</td>
<td align="left">Neutral</td>
</tr>
<tr>
<td align="left">Pre-matching</td>
<td align="center">1.11 (1.00&#x2013;1.22)</td>
<td align="center">0.04</td>
<td align="left">Favors KTA</td>
</tr>
<tr>
<td rowspan="2" align="left">PTLD/Neoplasm</td>
<td align="left">PS-matched</td>
<td align="center">1.01 (0.92&#x2013;1.11)</td>
<td align="center">0.87</td>
<td align="left">Neutral</td>
</tr>
<tr>
<td align="left">Pre-matching</td>
<td align="center">0.95 (0.88&#x2013;1.01)</td>
<td align="center">0.11</td>
<td align="left">Neutral</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Abbreviations. SPKT, simultaneous pancreas&#x2013;kidney transplant; KTA, kidney transplant alone; KM, Kaplan&#x2013;Meier; HR, hazard ratio; CI, confidence interval; PS-matched, propensity-score matched; MAKE, major adverse kidney events; PTLD, post-transplant lymphoproliferative disorder.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>Kaplan&#x2013;Meier survival curves and hazard ratios for SPKT versus KTA. <bold>(A)</bold> Kaplan&#x2013;Meier estimates are shown for patient survival, overall graft survival, death-censored graft survival, and cardiovascular outcomes (major adverse cardiovascular events, myocardial infarction, stroke, and heart failure), comparing simultaneous pancreas&#x2013;kidney transplantation (SPKT, purple) and kidney transplant alone (KTA, light blue). Curves are presented for unmatched cohorts (left column) and after 1:1 propensity score matching (right column). Follow-up extended up to 10&#xa0;years. <bold>(B)</bold> The forest plot summarizes hazard ratios (HR, dots) with 95% confidence intervals (bars) for each outcome, calculated at prespecified timepoints (1, 5, and 10&#xa0;years) in unmatched (red) and matched (blue) populations. HR values &#x3c;1 indicate lower risk with SPKT, whereas HR values &#x3e;1 indicate lower risk with KTA.</p>
</caption>
<graphic xlink:href="ti-38-15709-g001.tif">
<alt-text content-type="machine-generated">A set of graphs comparing survival probabilities and hazard ratios. Panel A displays survival curves for all-cause mortality, kidney graft failure, death-censored graft failure, and post-transplant cardiovascular events. Each metric compares pre-matching and post-matching scenarios with SPKT and KTA transplants. Panel B is a forest plot showing hazard ratios over time intervals of one, five, and ten years, comparing pre-matching and PS-matched results. SPKT is indicated in purple, KTA in light blue, with red and blue denoting pre-matching and PS-matched, respectively.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3-3">
<title>Secondary Outcomes</title>
<p>A consistent pattern was observed across early peri-transplant endpoints. In the unmatched cohorts, SPKT recipients had higher rates of treated acute rejection, kidney transplant&#x2013;related complications, and hospital readmission within the first year, all favouring KTA (<xref ref-type="sec" rid="s11">Supplementary Tables S2&#x2013;S4</xref>). After propensity score matching, the excess risk of acute rejection was no longer significant, whereas kidney transplant complications remained more frequent in SPKT, though with reduced effect sizes (<xref ref-type="sec" rid="s11">Supplementary Tables S3-S4</xref>). Conversely, major adverse kidney events (MAKE) consistently favoured SPKT before adjustment, with hazard ratios and relative risks below unity across all time horizons (<xref ref-type="table" rid="T1">Table 1</xref>; <xref ref-type="sec" rid="s11">Supplementary Tables S2&#x2013;S4</xref>). After propensity score matching, however, this advantage was limited to the first post-transplant year, with neutral risks thereafter (<xref ref-type="sec" rid="s11">Supplementary Table S2</xref>). In the unmatched cohorts, SPKT recipients showed lower risks of post-transplant cardiovascular events, with the advantage predominantly driven by a reduced incidence of heart failure (<xref ref-type="table" rid="T1">Table 1</xref>; <xref ref-type="sec" rid="s11">Supplementary Tables S3&#x2013;S4</xref>). Myocardial infarction and stroke occurred less frequently in SPKT as well, but the effect size was smaller. Kaplan&#x2013;Meier analyses confirmed fewer cumulative cardiovascular events in SPKT, largely attributable to the divergence in heart failure risk (<xref ref-type="fig" rid="F1">Figure 1</xref>). After propensity score matching, however, all differences were attenuated, and risks for the composite endpoint as well as for myocardial infarction, stroke, and heart failure became comparable between SPKT and KTA (<xref ref-type="sec" rid="s11">Supplementary Tables S2&#x2013;S4</xref>). In the unmatched cohorts, the profile of diabetes-related events was mixed. Diabetic ketoacidosis and hyperosmolar states were more frequent in SPKT, with relative risks favouring KTA (<xref ref-type="sec" rid="s11">Supplementary Tables S3&#x2013;S4</xref>). By contrast, severe hypoglycaemia occurred less often in SPKT, indicating a modest advantage for SPKT in this acute complication (<xref ref-type="sec" rid="s11">Supplementary Tables S3&#x2013;S4</xref>). For chronic complications, new-onset diabetic neuropathy and retinopathy were more frequent in SPKT, with risk estimates favouring KTA (<xref ref-type="sec" rid="s11">Supplementary Tables S3&#x2013;S4</xref>). After propensity score matching, however, all these differences were attenuated, and risks of acute decompensation, hypoglycaemia, neuropathy, and retinopathy became largely comparable between groups (<xref ref-type="sec" rid="s11">Supplementary Tables S2&#x2013;S4</xref>). Patterns of infection and sepsis varied according to the time horizon. In the unmatched cohorts, Kaplan&#x2013;Meier estimates suggested slightly lower cumulative infection risk in SPKT over long-term follow-up (<xref ref-type="sec" rid="s11">Supplementary Tables S3, S4</xref>). In contrast, early events within the first year were more common in SPKT, favouring KTA. After propensity score matching, the survival curves became largely overlapping, but the excess of early infections in SPKT persisted, while long-term risks converged toward neutrality (<xref ref-type="sec" rid="s11">Supplementary Table S2</xref>). The incidence of post-transplant lymphoproliferative disease and other neoplasms was consistently similar between SPKT and KTA, both before and after adjustment (<xref ref-type="sec" rid="s11">Supplementary Tables S3, S4</xref>). As a proxy of quality of life, new-onset depression or anxiety was slightly less frequent in KTA before matching, but this apparent difference was not confirmed after adjustment. In the matched cohorts, risks were virtually identical (Neutral; <xref ref-type="sec" rid="s11">Supplementary Tables S2&#x2013;S4</xref>).</p>
</sec>
<sec id="s3-4">
<title>Sensitivity Analyses</title>
<p>To assess the robustness of our findings, we repeated all analyses in two restricted subgroups: (i) recipients with a primary diagnosis of type 1 diabetes (<xref ref-type="sec" rid="s11">Supplementary Table S5</xref>), and (ii) type 1 diabetes recipients with a body mass index &#x3c;30&#xa0;kg/m<sup>2</sup> at the time of transplantation (<xref ref-type="sec" rid="s11">Supplementary Table S6</xref>). Across both sensitivity analyses, the direction and magnitude of risk estimates were consistent with those observed in the overall study population.</p>
</sec>
</sec>
<sec sec-type="discussion" id="s4">
<title>Discussion</title>
<p>In this large, real-world analysis, SPKT recipients achieved consistently better glycaemic control than KTA recipients, as reflected by lower HbA1c levels both before and after propensity score matching. Despite this clear metabolic advantage, long-term patient survival, kidney graft survival, and cardiovascular outcomes were indistinguishable between SPKT and KTA once baseline differences were accounted for. The initial signals of improved survival and reduced cardiovascular risk in the unmatched cohorts were largely attributable to selection bias, with SPKT recipients being younger, predominantly affected by type 1 diabetes, and carrying fewer comorbidities at baseline. Importantly, SPKT was associated with higher early risks&#x2014;including treated acute rejection, hospital readmission, perioperative complications, and infection/sepsis within the first post-transplant year. These excess short-term risks did not translate into inferior long-term outcomes. The only remaining clinical difference was a modest reduction in MAKE during the first post-transplant year, suggesting a possible short-term renoprotective effect of improved glycaemic control, although without sustained long-term impact on major endpoints. Our findings differ from the earliest registry-based and single-centre reports, which consistently suggested a survival and cardiovascular advantage of SPKT over KTA [<xref ref-type="bibr" rid="B46">46</xref>&#x2013;<xref ref-type="bibr" rid="B49">49</xref>] particularly among younger recipients with type 1 diabetes [<xref ref-type="bibr" rid="B7">7</xref>, <xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B47">47</xref>, <xref ref-type="bibr" rid="B49">49</xref>&#x2013;<xref ref-type="bibr" rid="B51">51</xref>]. However, they align more closely with subsequent analyses that applied more comprehensive multivariable adjustment or propensity-based methods and reported attenuation or disappearance of these differences [<xref ref-type="bibr" rid="B25">25</xref>, <xref ref-type="bibr" rid="B52">52</xref>, <xref ref-type="bibr" rid="B53">53</xref>]. This pattern supports the interpretation that much of the apparent survival benefit of SPKT in historical cohorts may have reflected differences in recipient selection, donor quality, and the clinical context of earlier eras.</p>
<p>A notable result from our study is the persistently lower HbA1c observed in SPKT recipients after matching, despite the relatively small absolute difference (6.2% vs. 6.6%). Based on landmark trials such as DCCT/EDIC [<xref ref-type="bibr" rid="B54">54</xref>] and UKPDS [<xref ref-type="bibr" rid="B54">54</xref>], a 1% reduction in HbA1c corresponds to a 15%&#x2013;20% reduction in microvascular risk and a 10%&#x2013;15% reduction in cardiovascular events. Accordingly, the 0.3%&#x2013;0.4% difference in our study would be expected to confer only a 4%&#x2013;6% reduction in microvascular risk and a 3%&#x2013;5% reduction in cardiovascular risk&#x2014;an effect size insufficient to produce detectable long-term differences in survival or major cardiovascular outcomes in heterogeneous, real-world cohorts. This helps explain why improved glycaemic control after SPKT, while clinically relevant, did not translate into measurable survival advantages at a population level. These short-term risks associated with SPKT&#x2014;including perioperative morbidity, treated rejection, infections, and early hospital readmissions&#x2014;are well documented [<xref ref-type="bibr" rid="B31">31</xref>, <xref ref-type="bibr" rid="B32">32</xref>, <xref ref-type="bibr" rid="B36">36</xref>, <xref ref-type="bibr" rid="B55">55</xref>, <xref ref-type="bibr" rid="B56">56</xref>] and represent a recognised trade-off against the metabolic benefits. Furthermore, the therapeutic landscape has evolved substantially. Advances in continuous glucose monitoring, automated insulin delivery systems, and the availability of new agents such as SGLT2 inhibitors and GLP-1 receptor agonists have markedly improved glycaemic profiles and cardiovascular risk in patients with diabetes after kidney transplantation. These innovations have likely narrowed the incremental advantage of SPKT over KTA, further contextualising our findings of long-term similarity in hard outcomes.</p>
<p>This finding warrants further clinical interpretation. In SPKT recipients, an HbA1c in the low-to-mid 6% range reflects physiological insulin secretion, typically associated with minimal risk of severe hypoglycaemia and lower glycaemic variability. In contrast, similar HbA1c values in insulin-treated KTA recipients may mask substantial hypoglycaemia burden, glycaemic fluctuations, and the cognitive and emotional load of intensive insulin management. Because our dataset did not include continuous glucose monitoring metrics&#x2014;such as time-in-range, glucose excursion indices, or asymptomatic hypoglycaemia&#x2014;the true metabolic benefit of SPKT is likely underestimated. These considerations reinforce that the metabolic advantage of SPKT remains clinically meaningful even in the absence of detectable long-term survival differences. Our findings should also be interpreted in the context of prior evidence, which for decades has consistently shown a survival advantage of SPKT over KTA. Several factors likely explain why our real-world findings differ from these earlier observations. First, historical cohorts reflect an era of higher dialysis mortality and less effective diabetes and cardiovascular management. Second, donor and recipient selection practices have evolved: SPKT recipients typically receive younger, lower-risk organs and enter transplantation earlier in the course of diabetic complications, whereas KTA recipients accumulate greater comorbidity and longer pre-transplant dialysis exposure. These factors likely amplified earlier survival signals. Third, improvements in perioperative care, modern immunosuppression, and cardiovascular therapy have narrowed the survival gap. Finally, because our dataset lacked key transplant-specific variables&#x2014;such as donor quality indices, HLA matching, cold ischaemia time, and immunosuppression&#x2014;an intrinsic survival benefit of SPKT cannot be excluded and may be masked by unmeasured confounding. Together, these considerations reconcile our findings with the broader literature and suggest that, in current practice, the dominant advantage of SPKT lies in its metabolic and quality-of-life benefits rather than in large differences in long-term survival.</p>
<p>This study has several important limitations First, despite rigorous propensity score matching, residual confounding is unavoidable because the TriNetX platform lacks key transplant-specific variables. Donor quality metrics such as Kidney Donor Profile Index (KDPI) and Pancreas Donor Risk Index (PDRI), which strongly influence kidney outcomes and differ systematically between SPKT and KTA, were not available. Similarly, no information was provided on HLA matching, panel reactive antibodies, donor-specific antibodies, cold ischaemia time, centre experience or detailed immunosuppression protocols. These unmeasured factors may attenuate or obscure a true intrinsic survival benefit of SPKT or, conversely, magnify early procedural risk. Second, exposures, comorbidities and outcomes were identified using ICD-10 and procedure codes. The complete lists of codes used in this study are provided in the Supplementary Methods. Although these coding-based definitions follow established conventions, they remain prone to misclassification, under-reporting and variability across institutions&#x2014;particularly for complex outcomes such as cardiovascular events, rejection, infection or neuropathy, for which clinical adjudication would be preferable. Third, the database does not capture patient-reported outcomes, continuous glucose monitoring metrics or hypoglycaemia burden&#x2014;elements that represent the most meaningful clinical benefits of SPKT for many patients [<xref ref-type="bibr" rid="B57">57</xref>, <xref ref-type="bibr" rid="B58">58</xref>]. As a result, the metabolic advantage observed in this study likely underestimates the full quality-of-life impact of successful pancreas transplantation [<xref ref-type="bibr" rid="B59">59</xref>, <xref ref-type="bibr" rid="B60">60</xref>]. Fourth, diabetes type was defined using diagnosis codes, which may misclassify insulin-treated type 2 diabetes as type 1. Although sensitivity analyses restricted to patients coded as type 1 diabetes and to non-obese recipients were performed, some residual misclassification may persist. Finally, because SPKT by definition requires a deceased donor, our comparison group included only deceased-donor KTA recipients. These findings cannot be extrapolated to living-donor kidney transplantation, which often provides superior survival and represents a distinct clinical pathway.</p>
<p>Taken together, these limitations suggest that while our findings demonstrate no detectable long-term survival advantage of SPKT after adjustment for measured variables, a modest true benefit cannot be excluded. Rather, our results underscore the extent to which survival outcomes are shaped by patient selection, donor quality, and centre-level variation. In this context, the principal justification for SPKT in contemporary practice lies in its profound metabolic and quality-of-life benefits, balanced against higher early procedural risks.</p>
<p>In summary, this large, contemporary real-world analysis shows that the apparent survival advantage of SPKT over KTA disappears after balancing for measurable clinical covariates. Because donor quality and other key transplant-specific factors were not captured, a residual survival benefit cannot be excluded. Nevertheless, SPKT provides durable metabolic benefits, including excellent glycaemic control and freedom from insulin. In the setting of comparable observed survival, decisions about SPKT should be individualised, considering each patient&#x2019;s preference for insulin independence, glycaemic stability, and quality-of-life improvement, as well as willingness to accept higher short-term risks. These findings also highlight a broader issue: despite clear metabolic and quality-of-life benefits, SPKT remains underutilised, and many eligible patients are not systematically referred to transplant centres. Variability in referral pathways, limited awareness among non-transplant clinicians, and the absence of structured evaluation frameworks likely prevent equitable access. In light of our results&#x2014;showing that the decision for SPKT increasingly centres on metabolic benefit and patient preference&#x2014;timely and systematic referral becomes critical. Strengthening referral pathways and enhancing collaboration between diabetologists, nephrologists, and transplant teams will be essential to ensure that all suitable candidates are appropriately evaluated.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="s5">
<title>Data Availability Statement</title>
<p>Individual participant data will not be made available. Study protocol, statistical analysis plan, and analytical code will be available from the time of publication in response to any reasonable request addressed to the corresponding author.</p>
</sec>
<sec sec-type="ethics-statement" id="s6">
<title>Ethics Statement</title>
<p>Ethical approval was not required for the study involving humans in accordance with the local legislation and institutional requirements. Written informed consent to participate in this study was not required from the participants or the participants&#x2019; legal guardians/next of kin in accordance with the national legislation and the institutional requirements.</p>
</sec>
<sec sec-type="author-contributions" id="s7">
<title>Author Contributions</title>
<p>LP conceived and supervised the study, had full access to all data, and takes responsibility for the integrity and accuracy of the analyses. DC and LP performed the data extraction and statistical analyses. FR, SW, RC, and DC contributed to study design, data interpretation, and manuscript drafting. All authors contributed to the conception, critical revision, and final approval of the manuscript, and agree to be accountable for all aspects of the work.</p>
</sec>
<sec sec-type="COI-statement" id="s9">
<title>Conflict of Interest</title>
<p>FR and SW were employed by TriNetX at the time of the study.</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>
</sec>
<sec sec-type="ai-statement" id="s10">
<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="supplementary-material" id="s11">
<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.frontierspartnerships.org/articles/10.3389/ti.2025.15709/full#supplementary-material">https://www.frontierspartnerships.org/articles/10.3389/ti.2025.15709/full&#x23;supplementary-material</ext-link>
</p>
<supplementary-material>
<label>SUPPLEMENTARY FIGURE S1</label>
<caption>
<p>Standardized mean differences (SMD) for baseline characteristics between SPKT and KTA recipients before (red circles) and after propensity score matching (blue squares). Variables include demographics, comorbidities, and diabetes type. Dashed vertical lines at &#xb1;0.1 indicate the threshold for acceptable balance. Matching achieved excellent covariate balance across all variables, with all post-matching SMDs &#x3c;0.1.</p>
</caption>
</supplementary-material>
<supplementary-material>
<label>SUPPLEMENTARY FIGURE S2</label>
<caption>
<p>Distribution of propensity scores, follow-up time, HbA1c, and eGFR before and after matching. The figure displays cumulative distribution curves of propensity scores (top panels), histograms of follow-up time (middle panels), and histograms of last available laboratory values for HbA1c (bottom left) and eGFR (bottom right) in SPKT and KTA recipients, shown separately for unmatched and propensity score&#x2013;matched cohorts.</p>
</caption>
</supplementary-material>
<supplementary-material xlink:href="Image3.jpeg" id="SM1" mimetype="application/jpeg" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Supplementaryfile1.docx" id="SM2" mimetype="application/docx" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Table1.docx" id="SM3" mimetype="application/docx" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Image1.jpeg" id="SM4" mimetype="application/jpeg" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Image2.jpeg" id="SM5" mimetype="application/jpeg" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
<fn-group>
<fn fn-type="abbr" id="abbrev1">
<label>Abbreviations:</label>
<p>AR, absolute risk; CI, confidence interval; DDKT, deceased donor kidney transplantation; EHR, electronic health records; eGFR, estimated glomerular filtration rate; ESRD, end-stage renal disease; HbA1c, glycated haemoglobin; HR, hazard ratio; KTA, kidney transplantation alone; KM, Kaplan&#x2013;Meier; MACE, major adverse cardiovascular events; MAKE, major adverse kidney events; OR, odds ratio; PS-matched, propensity score&#x2013;matched; PTLD, post-transplant lymphoproliferative disorder; RD, risk difference; RR, relative risk; SMD, standardized mean difference; SPKT, simultaneous pancreas&#x2013;kidney transplantation; T1D, type 1 diabetes; T2D, type 2 diabetes.</p>
</fn>
</fn-group>
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