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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Endocrinol.</journal-id>
<journal-title>Frontiers in Endocrinology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Endocrinol.</abbrev-journal-title>
<issn pub-type="epub">1664-2392</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fendo.2025.1635630</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Endocrinology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Clinical characteristics and survival outcomes of extrapulmonary neuroendocrine carcinomas: a retrospective study</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Xu</surname>
<given-names>Junhao</given-names>
</name>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2712589/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Li</surname>
<given-names>Yuanyuan</given-names>
</name>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Xu</surname>
<given-names>Benjie</given-names>
</name>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Lian</surname>
<given-names>Jie</given-names>
</name>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1997208/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Lu</surname>
<given-names>Haibo</given-names>
</name>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<xref ref-type="author-notes" rid="fn004">
<sup>&#x2021;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1331862/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
</contrib-group>
<aff id="aff1">
<institution>Department of Outpatient Chemotherapy, Harbin Medical University Cancer Hospital</institution>, <addr-line>Harbin</addr-line>,&#xa0;<country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1415438/overview">Dunpeng Cai</ext-link>, University of Missouri, United States</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2236656/overview">Anna La Salvia</ext-link>, National Institute of Health (ISS), Italy</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1802128/overview">Xiang Ying</ext-link>, Sixth Medical Center of PLA General Hospital, China</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Haibo Lu, <email xlink:href="mailto:luhaibo@hrbmu.edu.cn">luhaibo@hrbmu.edu.cn</email>; Jie Lian, <email xlink:href="mailto:lianjie@hrbmu.edu.cn">lianjie@hrbmu.edu.cn</email>
</p>
</fn>
<fn fn-type="equal" id="fn003">
<p>&#x2020;These authors have contributed equally to this work</p>
</fn>
<fn fn-type="other" id="fn004">
<p>&#x2021;ORCID: Haibo Lu, <uri xlink:href="https://orcid.org/0009-0007-3128-1385">orcid.org/0009-0007-3128-1385</uri>
</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>27</day>
<month>10</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2025</year>
</pub-date>
<volume>16</volume>
<elocation-id>1635630</elocation-id>
<history>
<date date-type="received">
<day>26</day>
<month>05</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>13</day>
<month>10</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2025 Xu, Li, Xu, Lian and Lu.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Xu, Li, Xu, Lian and Lu</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec>
<title>Background</title>
<p>Extrapulmonary neuroendocrine carcinomas (EPNECs) are rare, heterogeneous, and aggressive malignancies with limited evidence to guide management. This study aimed to investigate the clinical characteristics, prognostic factors, and treatment outcomes of EPNEC patients.</p>
</sec>
<sec>
<title>Methods</title>
<p>We retrospectively analyzed 343 EPNEC patients treated at Harbin Medical University Cancer Hospital from May 2011 to December 2023. Data on demographics, primary tumor sites, tumor markers (CEA and NSE), treatments, and survival were collected. Kaplan&#x2013;Meier and Cox proportional hazards models were used to evaluate prognostic factors, and subgroup analyses were performed for treatment modalities.</p>
</sec>
<sec>
<title>Results</title>
<p>The median overall survival (OS) for the cohort was 23.7 months. Prognosis varied significantly by primary site, with genitourinary tumors showing the most favorable outcomes and hepatopancreatobiliary tumors the poorest. Independent predictors of worse survival included advanced stage (HR = 1.94, <italic>p</italic> &lt; 0.001), lymph node metastasis (HR = 1.48, <italic>p</italic> = 0.02), elevated CEA (HR = 1.49, <italic>p</italic> = 0.04), and elevated NSE (HR = 1.48, <italic>p</italic> = 0.03). Patients with both CEA and NSE levels elevated had the shortest OS (<italic>p</italic> &lt; 0.0001). Treatment effects were stage-specific: surgery improved survival only in stage I/II patients (HR = 0.26, <italic>p</italic> = 0.01), whereas chemotherapy (HR = 0.67, <italic>p</italic> = 0.02) and radiotherapy (HR = 0.45, <italic>p</italic> &lt; 0.001) provided significant benefits in stage III/IV patients. Radiotherapy showed consistent benefit across most subgroups, including those with elevated biomarkers.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>EPNEC prognosis is influenced by tumor site, stage, lymph node involvement, and biomarker levels. Surgery is optimal for early-stage disease (I/II), while chemotherapy and radiotherapy provide survival benefits in advanced-stage (III/IV) patients. Combined CEA and NSE elevation indicates a particularly poor prognosis. These findings highlight the importance of individualized, stage- and biomarker-driven therapeutic strategies for EPNECs.</p>
</sec>
</abstract>
<kwd-group>
<kwd>extrapulmonary neuroendocrine carcinoma</kwd>
<kwd>survival analysis</kwd>
<kwd>CEA</kwd>
<kwd>NSE</kwd>
<kwd>prognostic factors</kwd>
</kwd-group>
<counts>
<fig-count count="6"/>
<table-count count="2"/>
<equation-count count="0"/>
<ref-count count="29"/>
<page-count count="14"/>
<word-count count="5473"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-in-acceptance</meta-name>
<meta-value>Cancer Endocrinology</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>Neuroendocrine neoplasms (NENs) are a diverse group of cancers primarily originating from neuroendocrine cells in the gastrointestinal and bronchopulmonary systems (<xref ref-type="bibr" rid="B1">1</xref>). These tumors are characterized by neuroendocrine features, including the secretion of peptides through autocrine or paracrine mechanisms that may stimulate tumor growth. According to the World Health Organization (WHO) classification, NENs are subdivided into well-differentiated neuroendocrine tumors (NETs), graded as G1 (Ki-67 &lt;3% or &lt;2 mitoses/10 high-power fields[HPF]), G2 (Ki-67 3&#x2013;20% or 2&#x2013;20 mitoses/10 HPF), and G3 (Ki-67 &gt;20% with well-differentiated morphology), and poorly differentiated neuroendocrine carcinomas (NECs), which are inherently high-grade (G3) with small- or large-cell morphology. Both NETs and NECs most commonly arise in the gastrointestinal tract, pancreas, and lungs (<xref ref-type="bibr" rid="B2">2</xref>). As a subset of NENs, NECs are characterized by aggressive biological behavior, poor differentiation, and an overall unfavorable prognosis. The majority of NECs arise in the pulmonary system, most commonly presenting as small-cell carcinomas (<xref ref-type="bibr" rid="B3">3</xref>). However, a smaller proportion originates outside the lungs, referred to as extrapulmonary NECs (EPNECs), which pose unique clinical challenges due to their rarity and heterogeneity. According to a recent comparative analysis from the National Cancer Institute&#x2019;s Surveillance, Epidemiology, and End Results (SEER) database, 8.7% of NECs are classified as EPNECs (<xref ref-type="bibr" rid="B3">3</xref>).</p>
<p>EPNECs are rare and aggressive tumors with a poor prognosis, and their epidemiological characteristics have gained increasing attention in recent years. Population-based studies from the Netherlands and the United States have reported a rising incidence of EPNECs, most commonly originating in the bladder and gastrointestinal tract, with survival strongly dependent on disease stage (<xref ref-type="bibr" rid="B4">4</xref>, <xref ref-type="bibr" rid="B5">5</xref>). Given their pathological similarities to small-cell lung cancer (SCLC), serum biomarkers such as CEA and NSE may also hold prognostic value in EPNECs, although evidence remains limited (<xref ref-type="bibr" rid="B6">6</xref>). International guidelines, including those from the European Neuroendocrine Tumor Society (ENETS) and the National Comprehensive Cancer Network (NCCN), provide recommendations for the diagnosis, staging, and treatment of NENs, emphasizing the importance of tumor differentiation, stage, and primary site in guiding therapeutic decisions (<xref ref-type="bibr" rid="B7">7</xref>, <xref ref-type="bibr" rid="B8">8</xref>). Although significant progress has been made in the treatment of NENs, including targeted therapy and peptide receptor radionuclide therapy (PRRT), chemotherapy continues to play a central role in poorly differentiated NECs (<xref ref-type="bibr" rid="B9">9</xref>, <xref ref-type="bibr" rid="B10">10</xref>). For EPNECs, therapeutic strategies remain highly dependent on the primary tumor site and often involve a combination of surgery, chemotherapy, radiotherapy, or targeted therapy (<xref ref-type="bibr" rid="B11">11</xref>).</p>
<p>Overall, the incidence of EPNECs is rising globally, with prognosis influenced by tumor site, stage, and biomarkers such as CEA and NSE. Given the rarity and heterogeneity of EPNECs, optimal treatment strategies remain unclear. This study aims to evaluate the clinical characteristics, prognostic factors, and impact of different treatment modalities on survival in EPNEC patients.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<label>2</label>
<title>Materials and methods</title>
<p>We retrospectively collected the medical records of patients diagnosed with EPNEC at Harbin Medical University Cancer Hospital from May 2011 to December 2023. A graphical abstract summarizing the overall study design and analysis workflow is provided in the <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Materials</bold>
</xref> (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Figure A</bold>
</xref>). All included patients were 18 years or older and had no concurrent malignancies of other types. For each patient, the following data were collected: age, gender, primary tumor site, primary tumor size, lymph node metastasis, tumor staging, levels of tumor markers (CEA and NSE) at the time of diagnosis, treatment modalities, and overall survival (OS). The size of the primary tumor and the presence of lymph node metastasis were determined based on imaging data or postoperative pathology. Tumor staging was performed according to the 8th edition of the AJCC Cancer Staging Manual. The normal reference values for tumor markers CEA and NSE were 0&#x2013;5 ng/ml and 0&#x2013;15.2 ng/ml, respectively, according to the laboratory standards at our institution. OS was defined as the time from the date of diagnosis to the date of death or the last follow-up. Other prognostic factors were also analyzed. Patients who received chemotherapy were all treated with platinum-based or taxane-based combination regimens. Demographic and tumor characteristics were expressed as frequencies (percentages) for categorical variables, and group differences were compared using the Pearson chi-square test. Survival was analyzed using the Kaplan-Meier method with log-rank tests. Univariate and multivariate Cox proportional hazards models were used to estimate hazard ratios (HRs) for OS. Adjusted hazard ratios (aHRs) controlling for age, sex, stage, lymphatic status, and serum biomarkers (CEA and NSE) were calculated, and subgroup analyses were performed based on these adjusted models, examining different treatment strategies. A two-sided <italic>p</italic> value &lt;0.05 was considered statistically significant. All analyses and plots were conducted in R version 4.2.2.</p>
<p>This study was conducted according to the Declaration of Helsinki and approved by the Medical Ethics Committee of Harbin Medical University Cancer Hospital. Given its retrospective nature, the requirement for informed consent was waived.</p>
</sec>
<sec id="s3" sec-type="results">
<label>3</label>
<title>Results</title>
<sec id="s3_1">
<label>3.1</label>
<title>Clinical and demographic baseline characteristics</title>
<p>A total of 343 patients with EPNECs across diverse anatomic sites were included in this retrospective cohort (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>). The distribution of cases was as follows: genitourinary (72, 21.0%), esophagus (65, 18.9%), gastroduodenal (61, 17.8%), mediastinum (36, 10.5%), colorectal (31, 9.0%), head and neck (28, 8.2%), hepatopancreatobiliary (28, 8.2%), and other sites (22, 6.4%) (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1A</bold>
</xref>). The &#x201c;Other Sites&#x201d; category includes the abdominal cavity, pelvic cavity, chest wall, brain, and other locations. Among the 343 diagnosed cases of EPNEC, the median age was 59 years, with 221 male patients (64.5%). Significant heterogeneity in demographic, clinicopathological, and therapeutic features was observed across anatomic sites.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Patient characteristics and treatment patterns.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" rowspan="2" align="center">
</th>
<th valign="middle" colspan="9" align="center">Anatomic site of tumor (N=343)</th>
</tr>
<tr>
<th valign="middle" align="center">Genitourinary</th>
<th valign="middle" align="center">Esophagus</th>
<th valign="middle" align="center">Gastroduodenal</th>
<th valign="middle" align="center">Mediastinum</th>
<th valign="middle" align="center">Colorectum</th>
<th valign="middle" align="center">Head and neck</th>
<th valign="middle" align="center">Hepatopancreatobiliary</th>
<th valign="middle" align="center">Other Sites</th>
<th valign="middle" align="center">
<italic>p</italic>
</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="center">
<bold>All patients [n (%)]</bold>
</td>
<td valign="middle" align="center">72 (100)</td>
<td valign="middle" align="center">65 (100)</td>
<td valign="middle" align="center">61 (100)</td>
<td valign="middle" align="center">36 (100)</td>
<td valign="middle" align="center">31 (100)</td>
<td valign="middle" align="center">28 (100)</td>
<td valign="middle" align="center">28 (100)</td>
<td valign="middle" align="center">22 (100)</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">
<bold>Age</bold>
</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center">
<bold>
<italic>0.016</italic>
</bold>
</td>
</tr>
<tr>
<td valign="middle" align="center">&lt;59</td>
<td valign="middle" align="center">48 (66.7)</td>
<td valign="middle" align="center">30 (46.2)</td>
<td valign="middle" align="center">23 (37.3)</td>
<td valign="middle" align="center">13 (36.1)</td>
<td valign="middle" align="center">14 (45.2)</td>
<td valign="middle" align="center">14 (50.0)</td>
<td valign="middle" align="center">14 (50.0)</td>
<td valign="middle" align="center">7 (31.8)</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">&#x2265;59</td>
<td valign="middle" align="center">24 (33.3)</td>
<td valign="middle" align="center">35 (53.8)</td>
<td valign="middle" align="center">38 (62.3)</td>
<td valign="middle" align="center">23 (63.9)</td>
<td valign="middle" align="center">17 (54.8)</td>
<td valign="middle" align="center">14 (50.0)</td>
<td valign="middle" align="center">14 (50.0)</td>
<td valign="middle" align="center">15 (68.2)</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">
<bold>Sex</bold>
</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center">
<bold>
<italic>&lt; 0.001</italic>
</bold>
</td>
</tr>
<tr>
<td valign="middle" align="center">Male</td>
<td valign="middle" align="center">12 (16.7)</td>
<td valign="middle" align="center">60 (92.3)</td>
<td valign="middle" align="center">52 (85.2)</td>
<td valign="middle" align="center">21 (58.3)</td>
<td valign="middle" align="center">22 (71.0)</td>
<td valign="middle" align="center">20 (71.4)</td>
<td valign="middle" align="center">16 (57.1)</td>
<td valign="middle" align="center">18 (81.8)</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">Female</td>
<td valign="middle" align="center">60 (83.3)</td>
<td valign="middle" align="center">5 (7.7)</td>
<td valign="middle" align="center">9 (18.4)</td>
<td valign="middle" align="center">15 (41.7)</td>
<td valign="middle" align="center">9 (29.0)</td>
<td valign="middle" align="center">8 (28.6)</td>
<td valign="middle" align="center">12 (42.9)</td>
<td valign="middle" align="center">4 (18.2)</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">
<bold>Tumor Size</bold>
</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center">
<bold>
<italic>&lt;0.001</italic>
</bold>
</td>
</tr>
<tr>
<td valign="middle" align="center">&lt;3cm</td>
<td valign="middle" align="center">31 (43.1)</td>
<td valign="middle" align="center">13 (20.0)</td>
<td valign="middle" align="center">10 (16.4)</td>
<td valign="middle" align="center">13 (36.1)</td>
<td valign="middle" align="center">16 (51.6)</td>
<td valign="middle" align="center">21 (75.0)</td>
<td valign="middle" align="center">13 (46.4)</td>
<td valign="middle" align="center">17 (77.3)</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">&#x2265;3cm</td>
<td valign="middle" align="center">41 (56.9)</td>
<td valign="middle" align="center">52 (80.0)</td>
<td valign="middle" align="center">51 (83.6)</td>
<td valign="middle" align="center">23 (63.9)</td>
<td valign="middle" align="center">15 (48.4)</td>
<td valign="middle" align="center">7 (25.0)</td>
<td valign="middle" align="center">15 (53.6)</td>
<td valign="middle" align="center">5 (22.7)</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">
<bold>Lymphatic metastasis</bold>
</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center">
<bold>
<italic>&lt; 0.001</italic>
</bold>
</td>
</tr>
<tr>
<td valign="middle" align="center">Yes</td>
<td valign="middle" align="center">13 (18.1)</td>
<td valign="middle" align="center">42 (64.6)</td>
<td valign="middle" align="center">41 (67.2)</td>
<td valign="middle" align="center">15 (41.7)</td>
<td valign="middle" align="center">9 (29.0)</td>
<td valign="middle" align="center">6 (21.4)</td>
<td valign="middle" align="center">7 (25.0)</td>
<td valign="middle" align="center">7 (31.8)</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">No</td>
<td valign="middle" align="center">59 (81.9)</td>
<td valign="middle" align="center">23 (35.4)</td>
<td valign="middle" align="center">20 (32.8)</td>
<td valign="middle" align="center">21 (58.3)</td>
<td valign="middle" align="center">22 (71.0)</td>
<td valign="middle" align="center">22 (78.6)</td>
<td valign="middle" align="center">21 (75.0)</td>
<td valign="middle" align="center">15 (68.2)</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">
<bold>Stage</bold>
</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center">
<bold>
<italic>&lt;0.001</italic>
</bold>
</td>
</tr>
<tr>
<td valign="middle" align="center">I</td>
<td valign="middle" align="center">32 (44.4)</td>
<td valign="middle" align="center">7 (10.8)</td>
<td valign="middle" align="center">0 (0)</td>
<td valign="middle" align="center">2 (5.6)</td>
<td valign="middle" align="center">2 (6.5)</td>
<td valign="middle" align="center">5 (17.9)</td>
<td valign="middle" align="center">1 (3.6)</td>
<td valign="middle" align="center">2 (9.1)</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">II</td>
<td valign="middle" align="center">10 (13.9)</td>
<td valign="middle" align="center">6 (9.2)</td>
<td valign="middle" align="center">11 (18.0)</td>
<td valign="middle" align="center">0 (0)</td>
<td valign="middle" align="center">5 (16.1)</td>
<td valign="middle" align="center">5 (17.9)</td>
<td valign="middle" align="center">9 (32.1)</td>
<td valign="middle" align="center">2 (9.1)</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">III</td>
<td valign="middle" align="center">19 (26.4)</td>
<td valign="middle" align="center">23 (35.4)</td>
<td valign="middle" align="center">32 (52.5)</td>
<td valign="middle" align="center">4 (11.1)</td>
<td valign="middle" align="center">11 (35.5)</td>
<td valign="middle" align="center">5 (17.9)</td>
<td valign="middle" align="center">4 (14.3)</td>
<td valign="middle" align="center">2 (9.1)</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">IV</td>
<td valign="middle" align="center">11 (15.3)</td>
<td valign="middle" align="center">29 (44.6)</td>
<td valign="middle" align="center">18 (29.5)</td>
<td valign="middle" align="center">30 (83.3)</td>
<td valign="middle" align="center">13 (41.9)</td>
<td valign="middle" align="center">13 (46.3)</td>
<td valign="middle" align="center">14 (50.0)</td>
<td valign="middle" align="center">16 (72.7)</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">
<bold>Surgery</bold>
</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center">
<bold>
<italic>&lt;0.001</italic>
</bold>
</td>
</tr>
<tr>
<td valign="middle" align="center">Yes</td>
<td valign="middle" align="center">64 (88.9)</td>
<td valign="middle" align="center">40 (61.5)</td>
<td valign="middle" align="center">58 (95.1)</td>
<td valign="middle" align="center">15 (41.7)</td>
<td valign="middle" align="center">27 (87.1)</td>
<td valign="middle" align="center">22 (78.6)</td>
<td valign="middle" align="center">24 (85.7)</td>
<td valign="middle" align="center">16 (72.7)</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">No</td>
<td valign="middle" align="center">8 (11.1)</td>
<td valign="middle" align="center">25 (38.5)</td>
<td valign="middle" align="center">3 (4.9)</td>
<td valign="middle" align="center">21 (58.3)</td>
<td valign="middle" align="center">4 (12.9)</td>
<td valign="middle" align="center">6 (21.4)</td>
<td valign="middle" align="center">4 (14.3)</td>
<td valign="middle" align="center">6 (27.3)</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">
<bold>Radiotherapy</bold>
</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center">
<bold>
<italic>&lt;0.001</italic>
</bold>
</td>
</tr>
<tr>
<td valign="middle" align="center">Yes</td>
<td valign="middle" align="center">17 (23.6)</td>
<td valign="middle" align="center">15 (23.1)</td>
<td valign="middle" align="center">4 (6.6)</td>
<td valign="middle" align="center">11 (30.6)</td>
<td valign="middle" align="center">5 (16.1)</td>
<td valign="middle" align="center">12 (42.9)</td>
<td valign="middle" align="center">1 (3.6)</td>
<td valign="middle" align="center">3(13.6)</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">No</td>
<td valign="middle" align="center">55 (76.4)</td>
<td valign="middle" align="center">50 (76.9)</td>
<td valign="middle" align="center">57 (93.4)</td>
<td valign="middle" align="center">2 5 (69.4)</td>
<td valign="middle" align="center">2 6 (83.9)</td>
<td valign="middle" align="center">16 (57.1)</td>
<td valign="middle" align="center">27 (96.4)</td>
<td valign="middle" align="center">19 (86.4)</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">
<bold>Chemotherapy</bold>
</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center">
<bold>
<italic>&lt; 0.001</italic>
</bold>
</td>
</tr>
<tr>
<td valign="middle" align="center">Yes</td>
<td valign="middle" align="center">47 (65.3)</td>
<td valign="middle" align="center">36 (55.4)</td>
<td valign="middle" align="center">28 (45.9)</td>
<td valign="middle" align="center">21 (58.3)</td>
<td valign="middle" align="center">16 (51.6)</td>
<td valign="middle" align="center">15 (53.6)</td>
<td valign="middle" align="center">11 (39.3)</td>
<td valign="middle" align="center">10 (45.5)</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">No</td>
<td valign="middle" align="center">25 (34.7)</td>
<td valign="middle" align="center">29 (44.6)</td>
<td valign="middle" align="center">33 (54.1)</td>
<td valign="middle" align="center">15 (41.7)</td>
<td valign="middle" align="center">15 (48.4)</td>
<td valign="middle" align="center">13 (46.4)</td>
<td valign="middle" align="center">17 (60.7)</td>
<td valign="middle" align="center">12 (54.5)</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">
<bold>CEA</bold>
</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center">0.125</td>
</tr>
<tr>
<td valign="middle" align="center">Normal</td>
<td valign="middle" align="center">67 (93.1)</td>
<td valign="middle" align="center">53 (81.5)</td>
<td valign="middle" align="center">53 (86.9)</td>
<td valign="middle" align="center">30 (83.3)</td>
<td valign="middle" align="center">29 (93.5)</td>
<td valign="middle" align="center">28 (100)</td>
<td valign="middle" align="center">23 (82.1)</td>
<td valign="middle" align="center">18 (81.8)</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">Elevated</td>
<td valign="middle" align="center">5 (6.9)</td>
<td valign="middle" align="center">12 (18.5)</td>
<td valign="middle" align="center">8  (13.1)</td>
<td valign="middle" align="center">6 (16.7)</td>
<td valign="middle" align="center">2 (6.5)</td>
<td valign="middle" align="center">0 (0)</td>
<td valign="middle" align="center">5 (17.9)</td>
<td valign="middle" align="center">4 (18.2)</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">
<bold>NSE</bold>
</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center">
<bold>
<italic>&lt;0.001</italic>
</bold>
</td>
</tr>
<tr>
<td valign="middle" align="center">Normal</td>
<td valign="middle" align="center">62 (86.1)</td>
<td valign="middle" align="center">34 (52.3)</td>
<td valign="middle" align="center">56 (91.8)</td>
<td valign="middle" align="center">12 (33.3)</td>
<td valign="middle" align="center">25 (80.6)</td>
<td valign="middle" align="center">25 (89.3)</td>
<td valign="middle" align="center">20 (71.4)</td>
<td valign="middle" align="center">16 (72.7)</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">Elevated</td>
<td valign="middle" align="center">10 (13.9)</td>
<td valign="middle" align="center">31 (47.7)</td>
<td valign="middle" align="center">5 (8.2)</td>
<td valign="middle" align="center">24 (66.7)</td>
<td valign="middle" align="center">6 (19.4)</td>
<td valign="middle" align="center">3 (10.7)</td>
<td valign="middle" align="center">8 (28.6)</td>
<td valign="middle" align="center">6 (27.3)</td>
<td valign="middle" align="center"/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Data are represented as <italic>n</italic> (%).</p>
</fn>
<fn>
<p>
<italic>p</italic> values werecalculated using chi-square or Fisher's exact test for categorical variables; &lt;0.05 was considered statistically significant.</p>
</fn>
<fn>
<p>CEA, carcinoembryonic antigen; NSE, neuron-specific enolase.</p>
</fn>
<fn>
<p>Bold values were considered statistically significant.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>
<bold>(A)</bold> Distribution of the primary tumor sites in patients with EPNECs, shown as a pie chart with percentages. Due to rounding, the total may not add up to 100%. <bold>(B)</bold> Kaplan&#x2013;Meier survival curve showing OS for all 343 patients, with the number at risk displayed below the plot. <bold>(C)</bold> Treatment modalities across different tumor sites include chemotherapy, radiotherapy, and surgery.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-16-1635630-g001.tif">
<alt-text content-type="machine-generated">Panel A shows a pie chart illustrating tumor site distribution with percentages: colorectum (21%), esophagus (19%), gastroduodenal (18%), genitourinary (10%), head and neck (9%), hepatopancreatobiliary (8%), mediastinum (8%), other sites (6%). Panel B presents a survival curve with time in months against survival probability; median survival is 23.7 months for 343 patients. Panel C displays a bar chart comparing tumor sites by treatment types: chemotherapy, radiotherapy, and surgery, with variations in the number of patients for each treatment across different tumor sites.</alt-text>
</graphic>
</fig>
<p>Patients aged &#x2265; 59 years were predominant in gastroduodenal (62.3%), mediastinal (63.9%), and colorectal tumors (54.8%), while more than half of the cases in the genitourinary had an onset age younger than the median age (66.7%) (<italic>p</italic> = 0.016). Sex distribution varied markedly (<italic>p</italic> &lt; 0.001), with male predominance in esophageal (92.3%), gastroduodenal (85.2%), and head/neck tumors (71.4%), whereas females only constituted higher proportions in genitourinary (83.3%). Tumors &#x2265;3 cm were more frequent in esophageal (80.0%) and gastroduodenal sites (83.6%) (<italic>p</italic> &lt; 0.001). Lymph node metastasis was more commonly observed in the esophagus (64.6%) and gastroduodenal tumors (67.2%) (<italic>p</italic> &lt; 0.001). Advanced-stage (IV) disease predominated in mediastinal (83.3%), whereas stage I tumors were most common in the genitourinary cohort (44.4%) (<italic>p</italic> &lt; 0.001).</p>
<p>For patients at all tumor sites, the number of patients who underwent surgery and chemotherapy was higher than those who received radiotherapy (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1C</bold>
</xref>, <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Figure B</bold>
</xref>). Surgical resection rates were highest in gastroduodenal (95.1%), genitourinary (88.9%), and colorectal tumors (87.1%) but lower in mediastinal (41.7%) and esophageal tumors (61.5%) (<italic>p</italic> &lt; 0.001). Radiotherapy utilization peaked in head/neck (42.9%) and mediastinal tumors (30.6%), while being least frequent in hepatopancreatobiliary tumors (3.6%) (<italic>p</italic> &lt; 0.001). Chemotherapy was most administered in genitourinary (65.3%) and mediastinal tumors (58.3%) (<italic>p</italic> &lt; 0.001). Elevations in tumor markers also showed site-specific differences across various anatomical locations. Though no significant inter-site differences were observed in CEA elevation (<italic>p</italic> = 0.125), an increase in CEA was more commonly observed in esophagus tumors (18.5%), whereas no elevation in CEA was detected in head/neck tumors (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2A</bold>
</xref>). Elevated NSE levels were elevated in tumors from all sites, with the most significant prevalent in mediastinal tumors (66.7%) and esophageal (47.7%) (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2B</bold>
</xref>) (<italic>p</italic> &lt; 0.001).</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>
<bold>(A)</bold> Proportion of patients with elevated CEA across different primary tumor sites. <bold>(B)</bold> Proportion of patients with elevated NSE across different primary tumor sites.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-16-1635630-g002.tif">
<alt-text content-type="machine-generated">Bar charts displaying the proportion of CEA and NSE elevated in different tumor sites. Chart A shows CEA levels highest in the esophagus and other sites, both over 18 percent, and lowest in the head and neck at zero percent. Chart B shows NSE levels highest in the mediastinum at 66.7 percent and lowest in gastroduodenal at 8.2 percent.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>Survival analysis of different prognostic factors</title>
<p>The median OS (mOS) for all patients was 23.7 months (95% CI: 18.8 - 27.6 months; <xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1B</bold>
</xref>). Significant differences were observed across the groups based on the anatomical site of the tumor, age, sex, lymphatic metastasis, and disease stage. Survival probabilities varied significantly across different tumor sites, with patients having tumors in the genitourinary demonstrating better survival outcomes while tumors originating from the hepatopancreatobiliary had a poorer OS. The Log-rank test confirmed a significant difference in survival between these groups (<italic>p</italic> = 0.00052) (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3A</bold>
</xref>). Further analysis show that the 1-year, 3-year, and 5-year survival rates for each site were as follows: genitourinary (73.1%, 51.7%, 44.3%), esophagus (63.2%, 26.1%, 21.8%), gastroduodenal (59.1%, 33.3%, 27.1%), mediastinum (64.3%, 35.2%, 22.0%), colorectum (76.0%, 35.1%, 17.5%), head and neck (95.8%, 59.0%, 47.2%), hepatopancreatobiliary (51.9%, 15.9%, 15.9%), and other sites (61.1%, 47.5%, not reached). Younger patients (&lt; 59 years) exhibited better survival compared to older patients (&#x2265; 59 years), with a statistically significant difference observed (<italic>p</italic> = 0.00083) (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3B</bold>
</xref>). Additionally, female patients had a significantly higher survival probability than male patients (<italic>p</italic> = 0.0033), as demonstrated by the Kaplan-Meier curves (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3C</bold>
</xref>). Patients without lymphatic metastasis at the time of diagnosis showed better survival outcomes compared to those with metastasis, with a highly significant difference (<italic>p</italic> &lt; 0.0001) (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3D</bold>
</xref>). Stage I and II patients had a significantly better survival rate compared to stage III and IV patients (<italic>p</italic> &lt; 0.0001) (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3E</bold>
</xref>), highlighting the prognostic importance of disease stage. These findings underscore the importance of tumor site, age, sex, lymphatic metastasis, and disease stage as significant predictors of survival outcomes in patients with EPNECs.</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Kaplan&#x2013;Meier survival curves of OS according to baseline clinicopathological characteristics. <bold>(A)</bold> Survival probabilities compared with the anatomic site of tumors. <bold>(B)</bold> Survival probabilities stratified by age (&lt;59 vs. &#x2265;59 years). <bold>(C)</bold> Survival probabilities stratified by sex (female vs. male). <bold>(D)</bold> Survival probabilities stratified by lymphatic metastasis at diagnosis (yes vs. no). <bold>(E)</bold> Survival probabilities stratified by clinical stage (I/II vs. III/IV).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-16-1635630-g003.tif">
<alt-text content-type="machine-generated">Kaplan-Meier survival curves showing survival probability versus time in months, segmented by various factors: (A) anatomic site of the tumor with multiple lines for sites such as stomach, esophagus, etc., with a significant log-rank p-value of 0.000052; (B) age groups under and over 9 years old with p-value 0.00083; (C) sex with distinct curves for females and males, p-value 0.0033; (D) presence of lymphatic metastasis with p-value less than 0.0001; (E) tumor stage, with stages zero and one, p-value less than 0.0001. Each panel includes a risk table.</alt-text>
</graphic>
</fig>
<p>Compared to untreated patients, there was a significant impact of surgery, chemotherapy, and radiotherapy on survival, with each treatment modality showing a clear survival benefit (<xref ref-type="fig" rid="f4">
<bold>Figures&#xa0;4A&#x2013;C</bold>
</xref>). Patients who underwent surgery had a significantly better survival probability than those who did not (<italic>p</italic> = 0.023) (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4A</bold>
</xref>). Surgical intervention positively affected patient outcomes, with the group undergoing surgery showing a prolonged survival period. Chemotherapy treatment was associated with improved survival, as evidenced by the significantly higher survival probability in patients who received chemotherapy than those who did not (<italic>p</italic> = 0.0048) (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4B</bold>
</xref>). These results suggest the beneficial role of chemotherapy in prolonging survival in this cohort. Similar to surgery and chemotherapy, radiotherapy also significantly improved survival outcomes (<italic>p</italic> = 0.0047) (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4C</bold>
</xref>). Patients who received radiotherapy exhibited a higher survival probability, indicating the positive effect of this treatment modality in extending patient survival.</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Kaplan&#x2013;Meier survival curves of OS according to treatment modalities. <bold>(A)</bold> Survival probabilities stratified by patients treated with surgery (yes vs. no). <bold>(B)</bold> Survival probabilities stratified by patients treated with chemotherapy (yes vs. no). <bold>(C)</bold> Survival probabilities stratified by patients treated with radiotherapy (yes vs. no).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-16-1635630-g004.tif">
<alt-text content-type="machine-generated">Kaplan-Meier survival curves depicting the impact of different treatments on survival probability over time. Chart A compares surgery versus no surgery, showing a significant difference with a p-value of 0.023. Chart B evaluates chemotherapy versus no chemotherapy, with a significant difference noted with a p-value of 0.0048. Chart C contrasts radiotherapy versus no radiotherapy, showing a significant difference with a p-value of 0.0047. Each chart includes plots of survival probability over 144 months, with tables indicating the number at risk at various time points.</alt-text>
</graphic>
</fig>
<p>The impact of tumor marker levels (CEA, NSE) and their combinations on patient survival was analyzed using Kaplan-Meier survival curves. Patients with normal CEA levels had significantly better survival compared to those with elevated CEA levels (<italic>p</italic> = 0.0033), and the survival curves clearly show that elevated CEA is associated with a poorer prognosis (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5A</bold>
</xref>). Similarly, elevated NSE levels were associated with significantly reduced survival compared to normal NSE levels (<italic>p</italic> &lt; 0.0001), indicating that elevated NSE is a strong negative prognostic factor in this cohort (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5B</bold>
</xref>). When considering both NSE and CEA levels together, patients with both markers elevated had the worst survival outcomes (<italic>p</italic> = 0.0014), which highlights the compounded effect of elevated tumor markers on survival (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5C</bold>
</xref>). The combined analysis of both tumor markers (CEA and NSE) demonstrated that patients with both markers normal had the best survival, followed by those with only one marker elevated. Patients with both CEA and NSE elevations had the poorest survival outcomes, with the difference being highly significant (<italic>p</italic> &lt; 0.0001) (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5D</bold>
</xref>). When patients were grouped based on tumor size, and survival analysis was performed, no statistically significant differences in survival were observed (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Figure C</bold>
</xref>).</p>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>Kaplan&#x2013;Meier survival curves of OS according to the levels of serum tumor markers. <bold>(A)</bold> Survival probabilities comparing patients with normal versus elevated CEA levels. <bold>(B)</bold> Survival probabilities comparing patients with normal versus elevated NSE levels. <bold>(C)</bold> Survival probabilities comparing patients with normal versus elevated combined NSE and CEA levels. <bold>(D)</bold> Survival probabilities among patients with different combinations of CEA and NSE levels (both normal, CEA elevated, NSE elevated, both elevated).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-16-1635630-g005.tif">
<alt-text content-type="machine-generated">Four Kaplan-Meier survival curves comparing survival probabilities over time in months. Chart A: CEA levels, normal vs elevated (log-rank P = 0.0033). Chart B: NSE levels, normal vs elevated (log-rank P &lt; 0.0001). Chart C: Both normal vs both elevated levels of NSE and CEA (log-rank P = 0.0014). Chart D: Combination of tumor markers with both normal, CEA elevated, NSE elevated, and both elevated (log-rank P &lt; 0.0001). Each graph includes a number at risk table.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3_3">
<label>3.3</label>
<title>Cox analyses of factors associated with survival</title>
<p>To further determine the impact of various factors on OS, Cox regression analysis was performed to evaluate the impact of factors on survival, both in univariate and multivariate models (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>). In the univariate analysis, age &#x2265;59 years was associated with a significantly worse survival (HR = 1.63, 95% CI: 1.22-2.19, <italic>p</italic> &lt; 0.001). However, in the multivariate model, age was not identified as an independent predictor of survival (aHR = 1.22, 95% CI: 0.81-1.54, <italic>p</italic> = 0.505). The male sex was associated with poorer survival in the univariate analysis (HR = 1.58, 95% CI: 1.16-2.15, <italic>p</italic> = 0.0036). However, in the multivariate analysis, this association was no longer significant (aHR = 1.15, 95% CI: 0.85-1.55, <italic>p</italic> = 0.378). The advanced stage (III/IV) was a strong negative prognostic factor in both univariate (HR = 2.50, 95% CI: 1.76&#x2013;3.56, <italic>p</italic> &lt; 0.001) and multivariate analyses (aHR = 1.94, 95% CI: 1.31&#x2013;2.85, <italic>p</italic> &lt; 0.001). Tumor size &#x2265;3 cm did not show a significant association with survival in univariate analysis (HR = 0.93, 95% CI: 0.70-1.24, <italic>p</italic> = 0.6353). In the univariate analysis, surgery was associated with improved survival (HR = 0.69, 95% CI: 0.50-0.95, <italic>p</italic> = 0.0235), but this was not significant in the multivariate analysis (aHR = 0.77, 95% CI: 0.50-1.20, <italic>p</italic> = 0.249). Radiotherapy significantly improved survival in both univariate (HR = 0.60, 95% CI: 0.41-0.86, <italic>p</italic> = 0.0052) and multivariate analyses (aHR = 0.53, 95% CI: 0.35-0.80, <italic>p</italic> = 0.003). Chemotherapy was significantly associated with improved survival in both univariate (HR = 0.66, 95% CI: 0.49-0.88, <italic>p</italic> = 0.005) and multivariate analyses (aHR = 0.65, 95% CI: 0.46-0.91, <italic>p</italic> = 0.01). Lymphatic metastasis was a strong negative prognostic factor in both univariate (HR = 1.97, 95% CI: 1.48-2.63, <italic>p</italic> &lt; 0.001) and multivariate analyses (aHR = 1.48, 95% CI: 1.07-2.04, <italic>p</italic> = 0.02). Elevated CEA levels were associated with worse survival in the univariate (HR = 1.77, 95% CI: 1.20-2.60, <italic>p</italic> = 0.0038) and multivariate analyses (aHR = 1.49, 95% CI: 1.02-2.22, <italic>p</italic> = 0.04). Elevated NSE levels also showed a significant negative impact on survival in both univariate (HR = 1.91, 95% CI: 1.41-2.59, <italic>p</italic> &lt; 0.001) and multivariate analyses (aHR = 1.48, 95% CI: 1.07-2.04, <italic>p</italic> = 0.03). These findings underscore the clinical relevance of advanced stage, radiation, chemotherapy, lymphatic metastasis, and tumor marker levels (CEA and NSE) as independent factors influencing survival in patients with EPNECs.</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Univariate and multivariate cox regression analysis.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" rowspan="2" align="center"/>
<th valign="middle" colspan="3" align="center">Univariate Cox regression analysis</th>
<th valign="middle" colspan="3" align="center">Multivariate Cox regression analysis</th>
</tr>
<tr>
<th valign="middle" align="center">HR</th>
<th valign="middle" align="center">95% CI</th>
<th valign="middle" align="center">
<italic>p</italic> value</th>
<th valign="middle" align="center">aHR</th>
<th valign="middle" align="center">95% CI</th>
<th valign="middle" align="center">
<italic>p</italic> value</th>
</tr>
</thead>
<tbody>
<tr>
<th valign="middle" colspan="7" align="left">Age</th>
</tr>
<tr>
<td valign="middle" align="center">&lt;59</td>
<td valign="middle" align="center">1.00</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">&#x2265;59</td>
<td valign="middle" align="center">1.63</td>
<td valign="middle" align="center">1.22-2.19</td>
<td valign="middle" align="center">
<bold>
<italic>&lt; 0.001*</italic>
</bold>
</td>
<td valign="middle" align="center">1.22</td>
<td valign="middle" align="center">0.81-1.54</td>
<td valign="middle" align="center">0.505</td>
</tr>
<tr>
<th valign="middle" colspan="7" align="left">Sex</th>
</tr>
<tr>
<td valign="middle" align="center">Male</td>
<td valign="middle" align="center">1.58</td>
<td valign="middle" align="center">1.16-2.15</td>
<td valign="middle" align="center">
<bold>
<italic>0.0036*</italic>
</bold>
</td>
<td valign="middle" align="center">1.15</td>
<td valign="middle" align="center">0.85-1.55</td>
<td valign="middle" align="center">0.378</td>
</tr>
<tr>
<td valign="middle" align="center">Female</td>
<td valign="middle" align="center">1.00</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
</tr>
<tr>
<th valign="middle" colspan="7" align="left">Stage</th>
</tr>
<tr>
<td valign="middle" align="center">I/II</td>
<td valign="middle" align="center">1.00</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">III/IV</td>
<td valign="middle" align="center">2.50</td>
<td valign="middle" align="center">1.76-3.56</td>
<td valign="middle" align="center">
<bold>
<italic>&lt;0.001*</italic>
</bold>
</td>
<td valign="middle" align="center">1.94</td>
<td valign="middle" align="center">1.31-2.85</td>
<td valign="middle" align="center">
<bold>
<italic>&lt;0.001*</italic>
</bold>
</td>
</tr>
<tr>
<th valign="middle" colspan="7" align="left">Tumor Size</th>
</tr>
<tr>
<td valign="middle" align="center">&lt;3cm</td>
<td valign="middle" align="center">1.00</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">&#x2265;3cm</td>
<td valign="middle" align="center">0.93</td>
<td valign="middle" align="center">0.70-1.24</td>
<td valign="middle" align="center">0.6353</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
</tr>
<tr>
<th valign="middle" colspan="7" align="left">Surgery</th>
</tr>
<tr>
<td valign="middle" align="center">Yes</td>
<td valign="middle" align="center">0.69</td>
<td valign="middle" align="center">0.50-0.95</td>
<td valign="middle" align="center">
<bold>
<italic>0.0235*</italic>
</bold>
</td>
<td valign="middle" align="center">0.77</td>
<td valign="middle" align="center">0.50-1.20</td>
<td valign="middle" align="center">0.249</td>
</tr>
<tr>
<td valign="middle" align="center">No</td>
<td valign="middle" align="center">1.00</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
</tr>
<tr>
<th valign="middle" colspan="7" align="left">Radiotherapy</th>
</tr>
<tr>
<td valign="middle" align="center">Yes</td>
<td valign="middle" align="center">0.60</td>
<td valign="middle" align="center">0.41-0.86</td>
<td valign="middle" align="center">
<bold>
<italic>0.0052*</italic>
</bold>
</td>
<td valign="middle" align="center">0.53</td>
<td valign="middle" align="center">0.35-0.80</td>
<td valign="middle" align="center">
<bold>
<italic>0.003*</italic>
</bold>
</td>
</tr>
<tr>
<td valign="middle" align="center">No</td>
<td valign="middle" align="center">1.00</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
</tr>
<tr>
<th valign="middle" colspan="7" align="left">Chemotherapy</th>
</tr>
<tr>
<td valign="middle" align="center">Yes</td>
<td valign="middle" align="center">0.66</td>
<td valign="middle" align="center">0.49-0.88</td>
<td valign="middle" align="center">
<bold>
<italic>0.0050*</italic>
</bold>
</td>
<td valign="middle" align="center">0.65</td>
<td valign="middle" align="center">0.46-0.91</td>
<td valign="middle" align="center">
<bold>
<italic>0.01*</italic>
</bold>
</td>
</tr>
<tr>
<td valign="middle" align="center">No</td>
<td valign="middle" align="center">1.00</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
</tr>
<tr>
<th valign="middle" colspan="7" align="left">Lymphatic metastasis</th>
</tr>
<tr>
<td valign="middle" align="center">Yes</td>
<td valign="middle" align="center">1.97</td>
<td valign="middle" align="center">1.48-2.63</td>
<td valign="middle" align="center">
<bold>
<italic>&lt; 0.001*</italic>
</bold>
</td>
<td valign="middle" align="center">1.48</td>
<td valign="middle" align="center">1.07-2.04</td>
<td valign="middle" align="center">
<bold>
<italic>0.02*</italic>
</bold>
</td>
</tr>
<tr>
<td valign="middle" align="center">No</td>
<td valign="middle" align="center">1.00</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
</tr>
<tr>
<th valign="middle" colspan="7" align="left">CEA</th>
</tr>
<tr>
<td valign="middle" align="center">Normal</td>
<td valign="middle" align="center">1.00</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">Elevated</td>
<td valign="middle" align="center">1.77</td>
<td valign="middle" align="center">1.20-2.60</td>
<td valign="middle" align="center">
<bold>
<italic>0.0038*</italic>
</bold>
</td>
<td valign="middle" align="center">1.49</td>
<td valign="middle" align="center">1.02-2.22</td>
<td valign="middle" align="center">
<bold>
<italic>0.04*</italic>
</bold>
</td>
</tr>
<tr>
<th valign="middle" colspan="7" align="left">NSE</th>
</tr>
<tr>
<td valign="middle" align="center">Normal</td>
<td valign="middle" align="center">1.00</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="center">Elevated</td>
<td valign="middle" align="center">1.91</td>
<td valign="middle" align="center">1.41-2.59</td>
<td valign="middle" align="center">
<bold>
<italic>&lt; 0.001*</italic>
</bold>
</td>
<td valign="middle" align="center">1.48</td>
<td valign="middle" align="center">1.07-2.04</td>
<td valign="middle" align="center">
<bold>
<italic>0.03*</italic>
</bold>
</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>*<italic>p</italic> value &lt; 0.05 was considered statistically significant. aHR, adjusted hazard ratio.</p>
</fn>
<fn>
<p>Bold values were considered statistically significant.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_4">
<label>3.4</label>
<title>Subgroup analyses of treatment modalities</title>
<p>To further explore the robustness of treatment effects, we conducted subgroup analyses based on aHR derived from multivariable Cox proportional hazards models, with adjustment for other treatments, age, sex, stage, lymphatic metastasis, and serum biomarkers (CEA and NSE) as appropriate.</p>
<p>Surgery was associated with significantly improved OS in patients with stage I/II disease (aHR = 0.26, 95% CI 0.09&#x2013;0.74, <italic>p</italic> = 0.01). In contrast, no survival advantage was observed in stage III/IV or other subgroups (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6A</bold>
</xref>). Chemotherapy provided significant benefit in stage III/IV patients (aHR = 0.67, 95% CI 0.49&#x2013;0.93, <italic>p</italic> = 0.02), those aged &#x2265;59 years (aHR = 0.61, 95% CI 0.40&#x2013;0.93, <italic>p</italic> = 0.02), males (aHR = 0.57, 95% CI 0.39&#x2013;0.82, <italic>p</italic> &lt; 0.01), patients with lymphatic metastasis (aHR = 0.40, 95% CI 0.26&#x2013;0.63, <italic>p</italic> &lt; 0.01), and patients with normal CEA or NSE levels (both <italic>p</italic> &lt; 0.05) (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6B</bold>
</xref>). Radiotherapy showed the broadest and most consistent survival benefits across subgroups, including stage III/IV patients (aHR = 0.45, 95% CI 0.29&#x2013;0.67, <italic>p</italic> &lt; 0.01), those aged &#x2265;59 years (aHR = 0.40, 95% CI 0.22&#x2013;0.74, <italic>p</italic> &lt; 0.01), both sexes, patients with or without lymphatic metastasis, and those with normal or elevated tumor markers (all <italic>p</italic> &lt; 0.05), with the strongest effect observed in patients with elevated CEA (aHR = 0.11, 95% CI 0.03&#x2013;0.47, <italic>p</italic> &lt; 0.01) (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6C</bold>
</xref>).</p>
<fig id="f6" position="float">
<label>Figure&#xa0;6</label>
<caption>
<p>Subgroup analysis of treatment modalities on overall survival with multivariate adjustment. Forest plots showing the effects of <bold>(A)</bold> surgery, <bold>(B)</bold> chemotherapy, and <bold>(C)</bold> radiotherapy on overall survival across clinically relevant subgroups. Numbers indicate events/total patients in each subgroup. aHR, adjusted hazard ratio.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-16-1635630-g006.tif">
<alt-text content-type="machine-generated">Graphs showing forest plots of adjusted hazard ratios (aHR) with 95% confidence intervals for three treatments: surgery, chemotherapy, and radiotherapy. Each plot features subgroups based on stage, age, sex, lymphatic metastasis, CEA, and NSE. Results indicate risk associations, where ratios below one suggest lower risk. Significance levels are denoted by p-values, with asterisks marking significant findings.</alt-text>
</graphic>
</fig>
<p>In summary, subgroup analyses based on multivariable Cox models demonstrated that surgery provided a marked survival advantage only in patients with stage I/II disease, but not in advanced stages or other subgroups. Chemotherapy was effective primarily in stage III/IV patients, older individuals, males, those with lymphatic metastasis, and patients with normal tumor markers, highlighting its selective benefit in high-risk groups. By contrast, radiotherapy yielded the most consistent and broad survival improvements across clinical and biomarker-defined subgroups, with particularly strong effects in patients with elevated CEA levels.</p>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<label>4</label>
<title>Discussion</title>
<p>The 2022 WHO classification of NENs emphasizes the distinction between well-differentiated NETs and poorly differentiated NECs, which is critical for accurate diagnosis, prognostic stratification, and guiding treatment decisions (<xref ref-type="bibr" rid="B2">2</xref>). NECs, particularly EPNECs, represent a rare and biologically aggressive subset of NENs, characterized by poor differentiation, high proliferative indices, and generally unfavorable prognosis. Given the rising global incidence of EPNECs and their aggressive behavior, there is an urgent need for comprehensive studies to improve diagnostic strategies, prognostication, and treatment approaches. Our study provides a comprehensive analysis of 343 EPNEC patients, integrating demographic, clinicopathological, biomarker, and treatment-related variables to delineate prognostic factors and survival outcomes.</p>
<p>Consistent with previous studies, EPNECs were observed across multiple anatomical sites, with the genitourinary system, esophagus, and gastroduodenal regions being the most frequent (<xref ref-type="bibr" rid="B12">12</xref>). Interestingly, our study revealed that genitourinary EPNECs presented at a younger age than tumors from other sites, aligning with prior population-based analyses (<xref ref-type="bibr" rid="B13">13</xref>&#x2013;<xref ref-type="bibr" rid="B15">15</xref>). Survival outcomes varied significantly by tumor site, with genitourinary tumors demonstrating the most favorable prognosis and hepatopancreatobiliary tumors the worst. These findings corroborate prior reports highlighting the prognostic relevance of primary tumor location in EPNECs (<xref ref-type="bibr" rid="B3">3</xref>, <xref ref-type="bibr" rid="B15">15</xref>&#x2013;<xref ref-type="bibr" rid="B17">17</xref>). Age and sex were significant predictors of survival in univariate analyses; however, neither factor retained statistical significance in multivariate models, suggesting that their prognostic effects may be confounded by tumor stage, lymphatic metastasis, biomarker status, or treatment modality. Lymph node involvement has been consistently associated with poorer prognosis across various cancers, including EPNECs (<xref ref-type="bibr" rid="B18">18</xref>&#x2013;<xref ref-type="bibr" rid="B20">20</xref>). In our study, lymphatic metastasis emerged as a strong independent negative prognostic factor, in line with previous findings in both EPNECs and other high-grade neuroendocrine malignancies, including SCLC (<xref ref-type="bibr" rid="B21">21</xref>&#x2013;<xref ref-type="bibr" rid="B23">23</xref>). Moreover, lymph node metastasis was significantly more frequent in tumors originating in the esophagus and gastroduodenal regions, which may reflect the more aggressive behavior of these tumor types at diagnosis. The advanced stage (III/IV) was a strong independent predictor of poor survival, reinforcing the critical importance of early detection and accurate staging.</p>
<p>CEA and NSE, two well-established biomarkers in SCLC (<xref ref-type="bibr" rid="B24">24</xref>, <xref ref-type="bibr" rid="B25">25</xref>), were evaluated for their diagnostic and prognostic value in EPNECs. In our study, we observed distinct differences in tumor marker levels among EPNECs originating from various anatomical sites. CEA elevation was more frequently seen in EPNECs from the esophagus, hepatopancreatobiliary, mediastinum, gastroduodenal, and other sites. In contrast, EPNECs originating from the genitourinary, colorectal, and head/neck regions showed relatively low rates of CEA elevation, with CEA elevation being absent in head/neck tumors. On the other hand, elevated NSE was common across most anatomical sites, particularly mediastinal EPNECs. Overall, NSE is frequently elevated in EPNECs, reflecting its utility in diagnosis and disease monitoring. Nonetheless, CEA retains an important role, particularly when NSE elevation is modest or absent. Evaluating both markers concurrently offers a more comprehensive assessment of EPNEC. Our survival analysis revealed that elevated CEA and NSE levels were associated with poorer prognosis, with the worst outcomes observed in patients exhibiting elevation of both markers. This combined elevation may reflect a more aggressive disease phenotype, highlighting the value of a multifaceted biomarker approach for prognostication in EPNECs.</p>
<p>Therapeutic strategies for EPNECs are largely extrapolated from SCLC (<xref ref-type="bibr" rid="B26">26</xref>), with international guidelines from ENETS and NCCN recommending multimodal treatment based on tumor differentiation, stage, and primary site (<xref ref-type="bibr" rid="B7">7</xref>, <xref ref-type="bibr" rid="B8">8</xref>). In line with these recommendations, our cohort demonstrated differential survival benefits across treatment modalities, which were further clarified through subgroup analyses adjusted for age, sex, stage, lymphatic metastasis, and tumor markers. Surgery conferred a significant survival advantage primarily in patients with stage I/II disease, but not in stage III/IV patients, underscoring its role as a potentially curative option in early-stage EPNECs, which was consistent with data from other studies that highlight the benefit of surgery in early-stage disease (<xref ref-type="bibr" rid="B16">16</xref>, <xref ref-type="bibr" rid="B27">27</xref>, <xref ref-type="bibr" rid="B28">28</xref>). Chemotherapy provided a significant survival benefit in stage III/IV patients, older individuals, males, patients with lymphatic metastasis, and those with normal CEA or NSE levels, supporting its selective efficacy in high-risk or advanced-stage patients (<xref ref-type="bibr" rid="B29">29</xref>). Regarding chemotherapy regimens, prior studies have demonstrated that platinum-based and taxane-based combinations remain standard first-line options for poorly differentiated NENs, offering meaningful response rates and progression-free survival (<xref ref-type="bibr" rid="B9">9</xref>, <xref ref-type="bibr" rid="B10">10</xref>, <xref ref-type="bibr" rid="B29">29</xref>). Our cohort exclusively received these regimens, and the observed survival benefits in advanced-stage patients align with published evidence, emphasizing the continued relevance of systemic chemotherapy despite advances in targeted therapies and PRRT (<xref ref-type="bibr" rid="B9">9</xref>, <xref ref-type="bibr" rid="B10">10</xref>). Radiotherapy exhibited the broadest and most consistent survival advantage across multiple clinical and biomarker-defined subgroups, including those with elevated CEA and NSE levels, suggesting its utility as an integral component of multimodal therapy, particularly for unresectable or advanced tumors.</p>
<p>This study has several limitations. The retrospective design from a single center introduces potential selection bias and confounding. Certain subgroups had limited sample sizes, which may reduce statistical power. Prospective, multicenter studies are needed to validate these findings and refine patient-specific therapeutic strategies. Additionally, the molecular profiling of EPNECs remains an area of active investigation, and future studies should explore the genetic and molecular characteristics of these tumors to provide more targeted therapeutic approaches.</p>
</sec>
<sec id="s5" sec-type="conclusions">
<label>5</label>
<title>Conclusion</title>
<p>In conclusion, EPNECs are clinically heterogeneous malignancies with survival influenced by tumor site, stage, lymphatic metastasis, tumor marker status, and treatment modality. Surgery offers substantial survival benefits in early-stage disease, whereas chemotherapy and radiotherapy are particularly beneficial in advanced-stage or high-risk patients. Elevated CEA and NSE are strong negative prognostic factors, and their combined assessment can guide risk stratification and treatment planning. Our findings provide a comprehensive framework for evidence-based management of EPNECs and underscore the need for individualized, stage- and biomarker-driven therapeutic strategies for this rare and aggressive cancer.</p>
</sec>
</body>
<back>
<sec id="s6" sec-type="data-availability">
<title>Data availability statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p>
</sec>
<sec id="s7" sec-type="ethics-statement">
<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 id="s8" sec-type="author-contributions">
<title>Author contributions</title>
<p>JX: Writing &#x2013; original draft. YL: Writing &#x2013; original draft. BX: Writing &#x2013; review &amp; editing. JL: Writing &#x2013; review &amp; editing. HL: Writing &#x2013; review &amp; editing.</p>
</sec>
<sec id="s9" sec-type="funding-information">
<title>Funding</title>
<p>The author(s) declare financial support was received for the research and/or publication of this article. This work was supported by the National Natural Science Foundation of China (grant no. 82303742, 62372141), China Postdoctoral Science Foundation (grant no.2022MD713747, 2024T170205), and Haiyan Foundation of Harbin Medical University Cancer Hospital (grant no. 04000480).</p>
</sec>
<sec id="s10" 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="s11" 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="s12" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec id="s13" 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/fendo.2025.1635630/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fendo.2025.1635630/full#supplementary-material</ext-link>
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