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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">IJO</journal-id>
<journal-title-group>
<journal-title>International Journal of Oncology</journal-title></journal-title-group>
<issn pub-type="ppub">1019-6439</issn>
<issn pub-type="epub">1791-2423</issn>
<publisher>
<publisher-name>D.A. Spandidos</publisher-name></publisher></journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3892/ijo.2026.5848</article-id>
<article-id pub-id-type="publisher-id">ijo-68-03-05848</article-id>
<article-categories>
<subj-group>
<subject>Review</subject></subj-group></article-categories>
<title-group>
<article-title>Unveiling sex differences in pancreatic ductal adenocarcinoma: Current evidence and future directions (Review)</article-title></title-group>
<contrib-group>
<contrib contrib-type="author" equal-contrib="yes" corresp="yes">
<name><surname>Rauschenberg</surname><given-names>Sophie</given-names></name><xref rid="af1-ijo-68-03-05848" ref-type="aff">1</xref><xref rid="fn1-ijo-68-03-05848" ref-type="author-notes">&#x0002A;</xref><xref ref-type="corresp" rid="c1-ijo-68-03-05848"/></contrib>
<contrib contrib-type="author" equal-contrib="yes">
<name><surname>Orgler-Gasche</surname><given-names>Elisabeth</given-names></name><xref rid="af2-ijo-68-03-05848" ref-type="aff">2</xref><xref rid="fn1-ijo-68-03-05848" ref-type="author-notes">&#x0002A;</xref></contrib>
<contrib contrib-type="author">
<name><surname>Karakas Zeybek</surname><given-names>Didem</given-names></name><xref rid="af3-ijo-68-03-05848" ref-type="aff">3</xref></contrib>
<contrib contrib-type="author">
<name><surname>Regel</surname><given-names>Ivonne</given-names></name><xref rid="af2-ijo-68-03-05848" ref-type="aff">2</xref><xref rid="af4-ijo-68-03-05848" ref-type="aff">4</xref></contrib>
<contrib contrib-type="author">
<name><surname>L&#x000F6;hr</surname><given-names>J.-Matthias</given-names></name><xref rid="af5-ijo-68-03-05848" ref-type="aff">5</xref></contrib>
<contrib contrib-type="author">
<name><surname>&#x000D6;hlund</surname><given-names>Daniel</given-names></name><xref rid="af6-ijo-68-03-05848" ref-type="aff">6</xref></contrib>
<contrib contrib-type="author" equal-contrib="yes">
<name><surname>G&#x000FC;nther</surname><given-names>Michael</given-names></name><xref rid="af7-ijo-68-03-05848" ref-type="aff">7</xref><xref rid="fn1-ijo-68-03-05848" ref-type="author-notes">&#x0002A;</xref></contrib>
<contrib contrib-type="author" equal-contrib="yes">
<name><surname>Aguilera Munoz</surname><given-names>Lina</given-names></name><xref rid="af8-ijo-68-03-05848" ref-type="aff">8</xref><xref rid="fn1-ijo-68-03-05848" ref-type="author-notes">&#x0002A;</xref></contrib></contrib-group>
<aff id="af1-ijo-68-03-05848">
<label>1</label>Department for Internal Medicine I, University Hospital Halle (Saale), D-06120 Halle (Saale), Germany</aff>
<aff id="af2-ijo-68-03-05848">
<label>2</label>Department of Medicine II, University Hospital LMU Munich, D-81377 Munich, Germany</aff>
<aff id="af3-ijo-68-03-05848">
<label>3</label>Graduate School of Health, Medical Biotechnology, Acibadem University, 34752 Istanbul, Turkey</aff>
<aff id="af4-ijo-68-03-05848">
<label>4</label>Institute of Tumor Immunology, Medical Faculty, Martin-Luther University Halle-Wittenberg, D-06112 Halle (Saale), Germany</aff>
<aff id="af5-ijo-68-03-05848">
<label>5</label>Department of Clinical Sciences, Karolinska Institute, 18288 Stockholm, Sweden</aff>
<aff id="af6-ijo-68-03-05848">
<label>6</label>Department of Diagnostics and Intervention (Oncology) and Wallenberg Centre of Molecular Medicine, Ume&#x000E5; University, 90187 Ume&#x000E5;, Sweden</aff>
<aff id="af7-ijo-68-03-05848">
<label>7</label>Institute of General Pathology, Medical University of Innsbruck, A-6020 Innsbruck, Austria</aff>
<aff id="af8-ijo-68-03-05848">
<label>8</label>Department of Pancreatology and Digestive Oncology, Beaujon University Hospital, 92110 Clichy, France</aff>
<author-notes>
<corresp id="c1-ijo-68-03-05848">Correspondence to: Miss Sophie Rauschenberg, Department for Internal Medicine I, University Hospital Halle (Saale), Ernst-Grube-Stra&#x000DF;e 40, D-06120 Halle (Saale), Germany, E-mail: <email>sophie.rauschenberg@uk-halle.de</email></corresp>
<fn id="fn1-ijo-68-03-05848" fn-type="equal">
<label>&#x0002A;</label>
<p>Contributed equally</p></fn></author-notes>
<pub-date pub-type="collection">
<month>03</month>
<year>2026</year></pub-date>
<pub-date pub-type="epub">
<day>15</day>
<month>01</month>
<year>2026</year></pub-date>
<volume>68</volume>
<issue>3</issue>
<elocation-id>35</elocation-id>
<history>
<date date-type="received">
<day>08</day>
<month>10</month>
<year>2025</year></date>
<date date-type="accepted">
<day>08</day>
<month>12</month>
<year>2025</year></date></history>
<permissions>
<copyright-statement>Copyright: &#x000A9; 2026 Rauschenberg et al.</copyright-statement>
<copyright-year>2026</copyright-year>
<license license-type="open-access">
<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-nc-nd/4.0/">Creative Commons Attribution-NonCommercial-NoDerivs License</ext-link>, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.</license-p></license></permissions>
<abstract>
<p>Pancreatic ductal adenocarcinoma (PDAC) is the seventh leading cause of cancer-related death worldwide in both men and women. While sex-specific differences are increasingly recognized as critical determinants of health and disease, particularly in oncology, they remain markedly underexplored in PDAC. Emerging evidence suggests that sex differences influence numerous aspects of PDAC, including treatment response and prognosis. This knowledge gap represents a notable barrier to the development of effective, personalized therapeutic strategies for both sexes. The present review provides a comprehensive overview of the current knowledge on sex-based differences in PDAC, encompassing epidemiology, risk factors, chemotherapy pharmacokinetics and toxicity, prognosis, therapeutic response, immune interactions, tumor microenvironment, tumor microbiota and molecular biomarkers.</p></abstract>
<kwd-group>
<kwd>pancreatic cancer</kwd>
<kwd>pancreatic ductal adenocarcinoma</kwd>
<kwd>sex-based medicine</kwd>
<kwd>sex differences</kwd>
<kwd>precision oncology</kwd></kwd-group>
<funding-group>
<funding-statement>Not applicable.</funding-statement></funding-group></article-meta></front>
<body>
<sec sec-type="intro">
<label>1.</label>
<title>Introduction</title>
<p>Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive malignancies, characterized by late-stage diagnosis, limited therapeutic options and poor prognosis. Despite advancements in oncology, the 5-year survival rate remains dismal at ~13% (<xref rid="b1-ijo-68-03-05848" ref-type="bibr">1</xref>). While substantial research has focused on genetic and environmental risk factors, molecular changes and novel treatment options for PDAC, the influence of biological sex on disease incidence, progression and treatment response remains insufficiently understood.</p>
<p>Sex- and gender-specific factors are increasingly recognized as important determinants of disease susceptibility, progression, and treatment outcomes. Sex refers to biological attributes, while gender encompasses socially constructed roles and behaviors (<xref rid="b2-ijo-68-03-05848" ref-type="bibr">2</xref>). Both biological and sociocultural components of sex and gender can profoundly influence healthcare delivery from prevention and screening to diagnosis and therapy, highlighting the need for more individualized sex- and gender-specific approaches (<xref rid="b3-ijo-68-03-05848" ref-type="bibr">3</xref>,<xref rid="b4-ijo-68-03-05848" ref-type="bibr">4</xref>). Despite recent efforts, women remain underrepresented in clinical studies, often due to inclusion biases related to fertility concerns and hormonal variability (<xref rid="b5-ijo-68-03-05848" ref-type="bibr">5</xref>). In oncology, these disparities remain insufficiently addressed, hindering progress toward truly personalized and effective treatment strategies (<xref rid="b6-ijo-68-03-05848" ref-type="bibr">6</xref>). How sex-specific factors shape disease biology and outcomes is particularly evident in colorectal cancer. Although it affects both sexes, women over the age of 65 have higher mortality rates and a lower 5-year survival rate compared with age-matched men (<xref rid="b7-ijo-68-03-05848" ref-type="bibr">7</xref>). This survival disadvantage may, at least in part, be related to the higher likelihood of women developing right-sided colon cancer, which is often associated with more aggressive tumor phenotypes, and to their greater susceptibility to treatment-related toxicity (<xref rid="b7-ijo-68-03-05848" ref-type="bibr">7</xref>,<xref rid="b8-ijo-68-03-05848" ref-type="bibr">8</xref>). These findings underscore the clinical relevance of sex-based differences in cancer biology and outcomes and highlight opportunities to develop strategies that optimize treatment based on sex-specific factors.</p>
<p>By contrast, sex-specific differences in PDAC remain poorly studied, resulting in limited evidence for sex-based variations in pathophysiology and a lack of precision medicine approaches tailored to both men and women. The present review summarizes current evidence on the epidemiological, biological and clinical aspects of sex differences in PDAC. By identifying key disparities, the present review aims to highlight the need for sex-specific strategies in prevention, diagnosis and treatment, which could advance personalized and effective care, while offering approaches to improve the integration of these variables into basic and clinical research.</p></sec>
<sec sec-type="other">
<label>2.</label>
<title>Epidemiology</title>
<p>PDAC displays a slightly higher incidence in men than in women, with 269,709 vs. 241,283 respective new cases reported in 2022, ranking it as the 15th and 16th most common cancer in men and women, respectively (<xref rid="b9-ijo-68-03-05848" ref-type="bibr">9</xref>). Globally, PDAC incidence rates are rising, with a disproportionately steeper increase observed in women. Between 1975 and 2016, incidence rates increased annually by 1.1% in women compared with 0.38% in men, highlighting a growing burden of PDAC among women (<xref rid="b10-ijo-68-03-05848" ref-type="bibr">10</xref>). The highest incidence rates are reported in highly developed regions, likely due to lifestyle and environmental factors, with Western Europe currently exhibiting the highest lifetime risk of PDAC (<xref rid="b11-ijo-68-03-05848" ref-type="bibr">11</xref>).</p>
<p>Notably, the incidence and mortality of PDAC peak at different ages between sexes: In men, the highest number of cases and deaths occurs between ages 65-69 years, whereas in women, it peaks between ages 75-79 years (<xref rid="b12-ijo-68-03-05848" ref-type="bibr">12</xref>). Of particular concern is the rising incidence of PDAC among women &lt;40 years, who now show higher rates compared with age-matched men (<xref rid="b13-ijo-68-03-05848" ref-type="bibr">13</xref>,<xref rid="b14-ijo-68-03-05848" ref-type="bibr">14</xref>). A study by Cavazzani <italic>et al</italic> (<xref rid="b13-ijo-68-03-05848" ref-type="bibr">13</xref>) reported the greatest increase in PDAC incidence among women aged 18-26 years, with an average annual percentage change (AAPC) of 9.37% &#x0005B;95% confidence interval (CI), 7.36-11.41%; P&lt;0.0001&#x0005D;, compared with an AAPC of 4.43% in men of the same age group. Survival rates remain poor for both sexes, with a 5-year survival of ~13% (<xref rid="b1-ijo-68-03-05848" ref-type="bibr">1</xref>). While the age-standardized mortality rate is higher in men overall, this varies by age group. The most pronounced sex difference in relative survival is observed in patients &lt;44 years, with survival rates of 24.37% in women vs. 18.03% in men. However, this difference diminishes with age, and survival rates become comparable in individuals &gt;65 years (4.68% in women vs. 4.44% in men) (<xref rid="b15-ijo-68-03-05848" ref-type="bibr">15</xref>).</p>
<p>PDAC represents a growing global public health challenge. The disproportionately steeper rise in incidence among women, particularly at younger ages, highlights the urgent need for sex-specific strategies in prevention, early detection, and treatment.</p></sec>
<sec sec-type="other">
<label>3.</label>
<title>Risk factors</title>
<p>Multiple risk factors for PDAC have been well established, including tobacco smoking, alcohol consumption, obesity, diabetes mellitus, chronic pancreatitis, and genetic predisposition (<xref rid="b14-ijo-68-03-05848" ref-type="bibr">14</xref>). However, sex-based differences are often overlooked. This section provides an overview of sex-specific variations in non-genetic PDAC risk factors.</p>
<sec>
<title>Cigarette smoking</title>
<p>Cigarette smoking is a well-documented risk factor for PDAC, with a reported OR of 1.77 (95% CI, 1.38-2.26) for current smokers compared with never smokers, and a dose- and duration-dependent increase in risk (<xref rid="b16-ijo-68-03-05848" ref-type="bibr">16</xref>). However, evidence regarding sex differences in smoking-related PDAC risk remains conflicting. A large meta-analysis found no significant difference in smoking-related PDAC risk between men and women (<xref rid="b16-ijo-68-03-05848" ref-type="bibr">16</xref>). By contrast, a multiethnic cohort study involving 192,035 participants reported a notably higher risk in women who began smoking before age 20 years, with a 71% increased PDAC risk &#x0005B;hazard ratio (HR), 1.71; 95% CI, 1.14-2.57&#x0005D;, compared with a 49% increase in men (HR, 1.49; 95% CI, 1.03-2.15) (<xref rid="b17-ijo-68-03-05848" ref-type="bibr">17</xref>). These findings are supported by data from the International Pancreatic Cancer Case-Control Consortium, which reported a particularly elevated risk among female smokers &lt;65 years of age (<xref rid="b18-ijo-68-03-05848" ref-type="bibr">18</xref>). Although smoking cessation significantly reduces PDAC risk, the benefit appears to be less pronounced in women. A pooled analysis from Japan found that female former smokers remained at elevated risk, whereas the risk normalized in men after quitting (<xref rid="b19-ijo-68-03-05848" ref-type="bibr">19</xref>,<xref rid="b20-ijo-68-03-05848" ref-type="bibr">20</xref>).</p>
<p>These findings suggest that smoking may pose a particularly strong and persistent risk for younger women, even when cessation occurs later in life. Thus, although smoking is a well-established PDAC risk factor, sex- and age-related differences, are not yet firmly supported and warrant further high-quality prospective research. Key studies reporting sex-specific differences in smoking-related PDAC risk are summarized in <xref rid="tI-ijo-68-03-05848" ref-type="table">Table I</xref>.</p></sec>
<sec>
<title>Body mass index (BMI) and obesity</title>
<p>Obesity is recognized as a modifiable risk factor for PDAC, with growing evidence suggesting that women may be particularly vulnerable to obesity-related risk (<xref rid="b20-ijo-68-03-05848" ref-type="bibr">20</xref>). A study reported that women with a BMI &#x02265;40 had more than double the risk of PDAC &#x0005B;relative risk (RR), 2.76; 95% CI, 1.74-4.36&#x0005D; (<xref rid="b21-ijo-68-03-05848" ref-type="bibr">21</xref>). A pooled analysis from the PanScan Consortium further emphasized that central adiposity, measured by the waist-to-hip ratio, is more strongly associated with PDAC risk in women than in men (<xref rid="b22-ijo-68-03-05848" ref-type="bibr">22</xref>). This finding suggests that fat distribution may play a more critical role in PDAC risk among women. An additional study indicated that components of metabolic syndrome, defined as abdominal obesity, diabetes, hypertension and dyslipidemia, increase PDAC risk more significantly in women (<xref rid="b23-ijo-68-03-05848" ref-type="bibr">23</xref>). Conversely, obesity during early adulthood appears to be more closely associated with PDAC mortality in men, highlighting the potential influence of both timing and age of weight gain (<xref rid="b24-ijo-68-03-05848" ref-type="bibr">24</xref>).</p>
<p><xref rid="tII-ijo-68-03-05848" ref-type="table">Table II</xref> provides an overview of sex-specific effects of overweight and obesity on PDAC risk. In summary, multiple large, prospective cohort and pooled analyses support that obesity, particularly central or severe obesity, confers a greater PDAC risk in women than in men, although age and timing of weight gain may modify this relationship. Further research should clarify the underlying sex-specific metabolic and hormonal factors driving this vulnerability.</p></sec>
<sec>
<title>Diabetes mellitus</title>
<p>The association between diabetes mellitus and PDAC appears to be largely independent of sex. While a study has reported a higher prevalence of PDAC among male diabetic patients (<xref rid="b25-ijo-68-03-05848" ref-type="bibr">25</xref>), others found no statistically significant difference in overall PDAC risk between men and women (<xref rid="b25-ijo-68-03-05848" ref-type="bibr">25</xref>-<xref rid="b28-ijo-68-03-05848" ref-type="bibr">28</xref>). Although sex alone may not significantly modify PDAC risk in diabetic patients, lifestyle factors and comorbidity patterns, which often differ by sex, may still influence overall risk and should be considered in prevention strategies (<xref rid="b26-ijo-68-03-05848" ref-type="bibr">26</xref>-<xref rid="b28-ijo-68-03-05848" ref-type="bibr">28</xref>).</p></sec>
<sec>
<title>Alcohol</title>
<p>Heavy alcohol consumption (defined as &#x02265;9 drinks per day) is associated with an increased risk of PDAC, particularly in men (<xref rid="b29-ijo-68-03-05848" ref-type="bibr">29</xref>). Several large studies and pooled analyses have shown that the association between heavy alcohol intake and PDAC is more pronounced in men than in women (<xref rid="b29-ijo-68-03-05848" ref-type="bibr">29</xref>-<xref rid="b31-ijo-68-03-05848" ref-type="bibr">31</xref>). However, this apparent sex difference may partly reflect a statistical limitation: Female heavy drinkers are often underrepresented in study cohorts, limiting the ability to accurately assess risk in women (<xref rid="b31-ijo-68-03-05848" ref-type="bibr">31</xref>). Nonetheless, a pooled analysis of 14 prospective cohort studies (n=2,187 PDAC cases) found a statistically significant association between alcohol intake &#x02265;30 g/day and PDAC in women (RR, 1.41; 95% CI, 1.07-1.85) (<xref rid="b30-ijo-68-03-05848" ref-type="bibr">30</xref>). At even higher intake levels, the risk was more substantial in men. Notably, the study could not assess the impact of very high alcohol intake in women due to the small number of female participants consuming &#x02265;45 g/day (<xref rid="b30-ijo-68-03-05848" ref-type="bibr">30</xref>). In regions with higher socioeconomic status, a growing trend of alcohol consumption has been observed among young women (<xref rid="b32-ijo-68-03-05848" ref-type="bibr">32</xref>). If this trend continues, alcohol may become an important contributor to an increased PDAC incidence among women in the coming years.</p></sec>
<sec>
<title>Chronic pancreatitis (CP)</title>
<p>CP significantly increases the risk of PDAC, with a reported 16- to 22-fold elevation, particularly within the first 2 years following a CP diagnosis (<xref rid="b33-ijo-68-03-05848" ref-type="bibr">33</xref>,<xref rid="b34-ijo-68-03-05848" ref-type="bibr">34</xref>). CP is more commonly diagnosed in men, who also tend to develop the disease at a younger age compared with women (<xref rid="b33-ijo-68-03-05848" ref-type="bibr">33</xref>). This male predominance is largely attributed to higher rates of alcohol consumption and smoking (<xref rid="b33-ijo-68-03-05848" ref-type="bibr">33</xref>,<xref rid="b35-ijo-68-03-05848" ref-type="bibr">35</xref>). However, to date and to the best of our knowledge, no significant sex-based differences have been observed in the magnitude of PDAC risk among patients with CP (<xref rid="b33-ijo-68-03-05848" ref-type="bibr">33</xref>-<xref rid="b35-ijo-68-03-05848" ref-type="bibr">35</xref>).</p></sec>
<sec>
<title>Hormonal factors</title>
<p>There is growing evidence suggesting that female sex hormones may exert a protective effect against the development of PDAC. However, studies examining hormone-related exposures have yielded conflicting results (<xref rid="tIII-ijo-68-03-05848" ref-type="table">Table III</xref>). A recent systematic review and meta-analysis of 21 observational studies involving 7,700 PDAC cases adds important context: Ever-use of oral contraceptives (OCs) was associated with a modest but statistically significant reduction in PDAC risk (RR, 0.85; 95% CI, 0.73-0.98) (<xref rid="b36-ijo-68-03-05848" ref-type="bibr">36</xref>). This inverse association was particularly evident in high-quality studies and European cohorts, while no clear effect emerged in studies from Asia or America (<xref rid="b36-ijo-68-03-05848" ref-type="bibr">36</xref>). Notably, no dose-response relationship was observed, as PDAC risk did not vary by duration of OC use (<xref rid="b36-ijo-68-03-05848" ref-type="bibr">36</xref>). Despite notable heterogeneity, the meta-analysis supports a potential protective role of exogenous estrogen.</p>
<p>In this context, findings from individual studies illustrate the variability across hormone-related exposures. Several studies investigating exogenous hormone therapy (HRT) reported reduced PDAC risk: A Swedish cohort study of 17,035 women linked high estrogen levels and HRT use to lower PDAC risk (<xref rid="b37-ijo-68-03-05848" ref-type="bibr">37</xref>), and another large cohort likewise found a protective association with estrogen therapy (<xref rid="b38-ijo-68-03-05848" ref-type="bibr">38</xref>). However, these results were not replicated in an American cohort of 37,459 women, in which HRT showed no association with PDAC risk (<xref rid="b39-ijo-68-03-05848" ref-type="bibr">39</xref>).</p>
<p>Studies assessing endogenous estrogen exposure show similar inconsistency. In the American cohort, later menopause was related to a lower PDAC risk and a significant inverse relationship was observed between age at menopause and risk, suggesting a protective effect of longer endogenous estrogen exposure (<xref rid="b39-ijo-68-03-05848" ref-type="bibr">39</xref>). However, a separate case-control study reported the opposite: An increased PDAC risk was associated with later menopause (<xref rid="b40-ijo-68-03-05848" ref-type="bibr">40</xref>). To date and to the best of our knowledge, no consistent association has been observed between PDAC risk and other reproductive factors such as parity (number of children) or breastfeeding (<xref rid="b37-ijo-68-03-05848" ref-type="bibr">37</xref>-<xref rid="b39-ijo-68-03-05848" ref-type="bibr">39</xref>,<xref rid="b41-ijo-68-03-05848" ref-type="bibr">41</xref>). In conclusion, current data suggest that higher lifetime estrogen exposure may reduce PDAC risk, though results are inconsistent and often lose significance after adjustment, indicating potential residual confounding or differences in population characteristics, hormone formulations or follow-up duration. Overall, evidence is moderately strong but lacks consistency and mechanistic clarity. While estrogen may have a protective role, current data are insufficient to confirm causality, warranting further research integrating hormonal and genetic markers.</p></sec></sec>
<sec sec-type="other">
<label>4.</label>
<title>Pharmacokinetics and toxicity of chemotherapy</title>
<p>Chemotherapeutic drugs are commonly prescribed at standardized doses based on body weight or body surface area, although therapeutic efficacy is more closely related to circulating drug concentrations than to the administered dose (<xref rid="b6-ijo-68-03-05848" ref-type="bibr">6</xref>). As a result, interindividual variations in drug metabolism can lead to suboptimal outcomes, including reduced efficacy or increased toxicity (<xref rid="b6-ijo-68-03-05848" ref-type="bibr">6</xref>). Pharmacokinetics and pharmacodynamics differ between the sexes, yet this is often overlooked in clinical dosing strategies. Factors such as higher body fat percentage in women (<xref rid="b42-ijo-68-03-05848" ref-type="bibr">42</xref>), greater renal function in men (<xref rid="b6-ijo-68-03-05848" ref-type="bibr">6</xref>), and differences in muscle mass, total body water, cardiac output, and liver perfusion (<xref rid="b4-ijo-68-03-05848" ref-type="bibr">4</xref>) all influence drug distribution and metabolism. A recent systematic review identified significant sex-specific pharmacokinetic differences for several drugs, including 5-fluorouracil (5-FU) and paclitaxel, both of which are integral components of standard PDAC treatment regimens (<xref rid="b4-ijo-68-03-05848" ref-type="bibr">4</xref>,<xref rid="b43-ijo-68-03-05848" ref-type="bibr">43</xref>). 5-FU, a key drug in the FOLFIRINOX regimen (leucovorin, 5-FU, irinotecan, and oxaliplatin) (<xref rid="b43-ijo-68-03-05848" ref-type="bibr">43</xref>), is cleared &gt;20% more rapidly in men than in women. Consequently, equivalent dosing may lead to increased toxicity in women and a potential risk of underdosing in men (<xref rid="b44-ijo-68-03-05848" ref-type="bibr">44</xref>). Notably, this sex difference in clearance remains significant even after adjusting for age and dose (<xref rid="b45-ijo-68-03-05848" ref-type="bibr">45</xref>). The difference may be partially explained by sex-specific variation in the activity of dihydropyrimidine dehydrogenase, the primary enzyme responsible for metabolizing 5-FU (<xref rid="b45-ijo-68-03-05848" ref-type="bibr">45</xref>). In addition, genetic variants of methylenetetrahydrofolate reductase, an enzyme that influences 5-FU cytotoxicity, have demonstrated sex-dependent effects, suggesting that female patients may require lower 5-FU doses to avoid toxicity (<xref rid="b42-ijo-68-03-05848" ref-type="bibr">42</xref>). In line with these findings, a study on colorectal cancer has shown that women experience a significantly higher rate of side effects from 5-FU-based therapies, both in the adjuvant and metastatic settings (<xref rid="b4-ijo-68-03-05848" ref-type="bibr">4</xref>). In the treatment of colorectal cancer, increased toxicity has been reported not only in combination regimens but also with 5-FU monotherapy (<xref rid="b4-ijo-68-03-05848" ref-type="bibr">4</xref>).</p>
<p>Sex-related pharmacokinetic differences for oxaliplatin are inconsistent. While a study has reported a 40% lower clearance in women (<xref rid="b46-ijo-68-03-05848" ref-type="bibr">46</xref>), another found no significant sex-based differences (<xref rid="b47-ijo-68-03-05848" ref-type="bibr">47</xref>). Data on irinotecan are similarly mixed. Certain studies suggest that women may have lower clearance, reduced volume of distribution and decreased bioavailability, potentially influencing both efficacy and toxicity (<xref rid="b48-ijo-68-03-05848" ref-type="bibr">48</xref>,<xref rid="b49-ijo-68-03-05848" ref-type="bibr">49</xref>). However, another investigation attributed this variability primarily to liver function, with minimal differences attributable to sex (<xref rid="b50-ijo-68-03-05848" ref-type="bibr">50</xref>). Although 5-FU, irinotecan, and oxaliplatin are administered in combination in PDAC treatment, the interactions and cumulative pharmacokinetic effects of these drugs remain poorly understood. Although pharmacokinetic findings imply differing toxicity risks, few studies have systematically evaluated chemotherapy-related adverse events in PDAC by sex. Existing data are often limited by small sample sizes or single-center designs. Some report higher toxicity rates in women, such as constipation, hand-foot syndrome and epigastric pain (<xref rid="b51-ijo-68-03-05848" ref-type="bibr">51</xref>), and an increased incidence of febrile neutropenia and agranulocytosis during FOLFIRINOX treatment (<xref rid="b52-ijo-68-03-05848" ref-type="bibr">52</xref>). Others, including a prospective Korean study, found no significant overall differences but noted more frequent dose reductions among female patients (<xref rid="b53-ijo-68-03-05848" ref-type="bibr">53</xref>), suggesting lower tolerance or heightened susceptibility to toxicity.</p>
<p>Gemcitabine, either as a monotherapy or in combination with nab-paclitaxel, is another well-established PDAC treatment regimen for PDAC. To date and to the best of our knowledge, no clinical evidence supports a sex-specific difference in gemcitabine pharmacokinetics (<xref rid="b54-ijo-68-03-05848" ref-type="bibr">54</xref>,<xref rid="b55-ijo-68-03-05848" ref-type="bibr">55</xref>). While sex has been shown to influence the clearance and toxicity of solvent-based paclitaxel (<xref rid="b56-ijo-68-03-05848" ref-type="bibr">56</xref>,<xref rid="b57-ijo-68-03-05848" ref-type="bibr">57</xref>), this effect is not observed with nab-paclitaxel, which displays no sex-related differences in elimination (<xref rid="b58-ijo-68-03-05848" ref-type="bibr">58</xref>), suggesting a distinct pharmacological mechanism.</p>
<p>In summary, pharmacokinetic studies of 5-FU, irinotecan and oxaliplatin suggest that standardized dosing does not adequately account for sex-specific variability, with men at risk of potential underdosing and women at higher risk of toxicity. Major PDAC trials rarely stratify adverse events by sex, underscoring the need for comprehensive, sex-disaggregated toxicity analyses. Addressing this through novel therapy concepts is essential to optimize therapeutic efficacy, minimize adverse events and advance sex-sensitive treatment strategies in pancreatic cancer.</p></sec>
<sec sec-type="other">
<label>5.</label>
<title>Prognosis and therapy response</title>
<p>Few studies, albeit with large populations, have explored sex differences in treatment allocation and prognostic outcomes in PDAC. Notably, the Dutch Pancreatic Cancer Group conducted two large retrospective studies analyzing sex-based differences in tumor characteristics, treatment decisions, and survival outcomes in both stage I-III and metastatic PDAC cohorts, each including &gt;6,000 patients (<xref rid="b59-ijo-68-03-05848" ref-type="bibr">59</xref>,<xref rid="b60-ijo-68-03-05848" ref-type="bibr">60</xref>). In both cohorts, female patients were older, had worse performance status but fewer comorbidities and were less likely to receive systemic chemotherapy compared with male patients. The primary reason for this disparity was a higher preference among women for best supportive care across all disease stages. No sex-based difference was observed in the likelihood of undergoing surgical resection in resectable PDAC, except among women aged &#x02265;80 years, who were less frequently offered surgery (<xref rid="b59-ijo-68-03-05848" ref-type="bibr">59</xref>,<xref rid="b60-ijo-68-03-05848" ref-type="bibr">60</xref>). By contrast, two additional studies reported a lower likelihood of curative treatment planning for female patients. The first was a preliminary analysis of 100 patients from the Chemotherapy, Host Response and Molecular dynamics in Periampullary cancer (CHAMP) study, which includes both pancreatic and periampullary adenocarcinomas. The second was a nationwide Swedish cohort study of 5,677 patients with periampullary tumors, which similarly reported that fewer women were planned for curative treatment (<xref rid="b61-ijo-68-03-05848" ref-type="bibr">61</xref>,<xref rid="b62-ijo-68-03-05848" ref-type="bibr">62</xref>). However, in the Swedish cohort, this difference disappeared after adjustment for age and tumor location, unlike in the CHAMP study. This discrepancy may be explained by the inclusion of other periampullary tumors, such as duodenal adenocarcinomas, which have different surgical and prognostic profiles and may influence treatment decisions. The largest study to date, conducted by the American College of Surgeons and including 22,993 patients, identified male sex as a risk factor for major morbidity following pancreaticoduodenectomy (<xref rid="b63-ijo-68-03-05848" ref-type="bibr">63</xref>). These findings highlight that sex disparities in treatment outcomes are not unequivocal and must be interpreted with caution. Most available studies are retrospective and heterogeneous in design, with varying inclusion criteria, treatment eras and adjustment for confounders, which limits the strength of causal inference. Observed associations between sex and prognosis in PDAC likely reflect the interplay of multiple factors, including age, performance status, comorbidities, socioeconomic status, access to specialized care and patient preferences, rather than biological sex alone. Few studies have stratified analyses or applied sensitivity models to disentangle these sociocultural and clinical variables from intrinsic biological differences. Nevertheless, several studies have identified female sex as an independent prognostic factor for improved overall survival (OS) in PDAC (<xref rid="b59-ijo-68-03-05848" ref-type="bibr">59</xref>,<xref rid="b60-ijo-68-03-05848" ref-type="bibr">60</xref>,<xref rid="b64-ijo-68-03-05848" ref-type="bibr">64</xref>). Large cohort studies have reported a statistically significant increase, or at least a trend toward, increased OS in women, even after adjusting for confounders. However, in the end, only two studies have directly examined sex differences in response to FOLFIRINOX. A small cohort study by Hohla <italic>et al</italic> (<xref rid="b65-ijo-68-03-05848" ref-type="bibr">65</xref>), which included 49 patients with unresectable PDAC, found a significantly higher disease control rate in female patients treated with FOLFIRINOX compared with males. Similarly, the PRODIGE 4/ACCORD 11 randomized trial observed a trend toward longer median OS in female patients with metastatic disease receiving FOLFIRINOX, although this did not reach statistical significance (<xref rid="b64-ijo-68-03-05848" ref-type="bibr">64</xref>). These findings again raise important questions about whether differences in chemotherapy toxicity and metabolism contribute to improved survival outcomes in women, underscoring the need for prospective studies with sex-stratified analyses and standardized reporting to improve the assessment of the biological vs. sociocultural determinants of treatment response in PDAC (<xref rid="b3-ijo-68-03-05848" ref-type="bibr">3</xref>).</p></sec>
<sec sec-type="other">
<label>6.</label>
<title>Immune response and the tumor microenvironment (TME)</title>
<p>Sex-based biological differences, particularly within the immune system, are well recognized across multiple diseases, including cancer (<xref rid="b66-ijo-68-03-05848" ref-type="bibr">66</xref>-<xref rid="b68-ijo-68-03-05848" ref-type="bibr">68</xref>). Generally, women exhibit stronger innate and adaptive immune responses, which has been linked to a higher prevalence of autoimmune disorders in women (<xref rid="b66-ijo-68-03-05848" ref-type="bibr">66</xref>,<xref rid="b67-ijo-68-03-05848" ref-type="bibr">67</xref>). The immune differences in men and women are regulated by both gonadal hormones, primarily estrogen and androgens and genetic mechanisms (<xref rid="b66-ijo-68-03-05848" ref-type="bibr">66</xref>,<xref rid="b69-ijo-68-03-05848" ref-type="bibr">69</xref>). Notably, stronger interferon signaling in women may result from two key mechanisms: i) Estrogen-mediated immune activation; and ii) X chromosome-linked differences. Estrogen enhances interferon production through Toll-like receptor 7 (TLR7) activation (<xref rid="b70-ijo-68-03-05848" ref-type="bibr">70</xref>,<xref rid="b71-ijo-68-03-05848" ref-type="bibr">71</xref>), and since TLR7 is encoded on the X chromosome, its expression and downstream immune responses are amplified in women (<xref rid="b72-ijo-68-03-05848" ref-type="bibr">72</xref>). In addition, T and B cells in women demonstrate enhanced signaling and antibody responses to infections and vaccinations (<xref rid="b67-ijo-68-03-05848" ref-type="bibr">67</xref>,<xref rid="b73-ijo-68-03-05848" ref-type="bibr">73</xref>), which may contribute to more effective tumor immune surveillance. Estrogen further shapes the TME by modulating T cell activation and immune checkpoint expression (<xref rid="b67-ijo-68-03-05848" ref-type="bibr">67</xref>,<xref rid="b68-ijo-68-03-05848" ref-type="bibr">68</xref>,<xref rid="b74-ijo-68-03-05848" ref-type="bibr">74</xref>). Across several cancer entities, the TMEs in women tend to display stronger immune activation than those of men (<xref rid="b68-ijo-68-03-05848" ref-type="bibr">68</xref>,<xref rid="b75-ijo-68-03-05848" ref-type="bibr">75</xref>).</p>
<p>In PDAC, the TME is a key contributor to immune evasion and poor prognosis; it is typically characterized by scarce cytotoxic T cell infiltration, abundant regulatory T cells and a dense, fibrotic stroma, which are features that also limit the response to immunotherapy (<xref rid="b76-ijo-68-03-05848" ref-type="bibr">76</xref>,<xref rid="b77-ijo-68-03-05848" ref-type="bibr">77</xref>). As a result, checkpoint inhibitors have shown limited efficacy in PDAC due to the inherently immunosuppressive nature of the tumor (<xref rid="b78-ijo-68-03-05848" ref-type="bibr">78</xref>). Nevertheless, emerging evidence indicates that sex differences do influence immune pathways and the TME in PDAC. For example, He <italic>et al</italic> (<xref rid="b79-ijo-68-03-05848" ref-type="bibr">79</xref>) identified a typically immunosuppressive subpopulation of formyl peptide receptor 2 (+) M2 macrophages that is specifically enriched in PDAC lesions from female patients. These tumor associated macrophages (TAMs), induced by estrogen, were associated with T cell exhaustion, reduced immune cell infiltration and poorer survival in women, suggesting a sex-specific immunosuppressive mechanism. In contrast to these findings, a recent study reported that female patients with PDAC exhibit higher levels of stromal biomarkers and increased tumor stiffness, both of which were associated with longer survival (<xref rid="b80-ijo-68-03-05848" ref-type="bibr">80</xref>). The researchers further showed that estrogen signaling shapes the TME by driving cancer-associated fibroblasts toward a more tumor-suppressive phenotype (<xref rid="b80-ijo-68-03-05848" ref-type="bibr">80</xref>). However, these estrogen-related effects were mediated not by systemic hormones but by locally produced estrogens within the tumor tissue and therefore do not fully explain the survival differences observed between women and men (<xref rid="b80-ijo-68-03-05848" ref-type="bibr">80</xref>). In another study investigating patients with treatment-naive PDAC, women exhibited elevated circulating levels of C-X-C motif chemokine ligand (CXCL)9, IL-1&#x003B2;, IL-6, IL-10 and IL-13, supporting the notion of enhanced systemic immune activation in women (<xref rid="b81-ijo-68-03-05848" ref-type="bibr">81</xref>).</p>
<p>Sex differences may also impact immune responses to chemotherapy. In a recent study by van Eijck <italic>et al</italic> (<xref rid="b82-ijo-68-03-05848" ref-type="bibr">82</xref>), female sex was an independent prognostic factor for 5-year OS in patients with localized PDAC treated with neoadjuvant gemcitabine-based chemotherapy followed by surgery (43% OS in females vs. 22% in males). Notably, after neoadjuvant therapy, the TME in female patients showed fewer immunosuppressive M2 macrophages (CD163<sup>+</sup>MRC1) and a distinct transcriptomic profile with higher expression of <italic>CXCL10</italic> and <italic>CXCL11</italic> and lower levels of <italic>CCL2</italic> and <italic>IL-34</italic>, suggesting an enhanced antitumor immune response (<xref rid="b82-ijo-68-03-05848" ref-type="bibr">82</xref>). Although data on sex differences in immune responses in PDAC remain limited and potentially confounded by complex interactions among hormones, drugs and genetics, current evidence suggests that women may exhibit a more immunosuppressive TME characterized by a higher abundance of estrogen-influenced immunosuppressive macrophages, contrary to the expected higher immune activation in women. Notably, gemcitabine appears to induce greater macrophage plasticity in women, indicating a potential pathway for immune activation. Together, these observations highlight that sex and sex hormones uniquely shape immune activity in the TME and modulate responses to chemotherapy. <xref rid="f1-ijo-68-03-05848" ref-type="fig">Fig. 1</xref> summarizes sex-related hormonal and genetic differences in PDAC, highlighting the distinct roles of estrogens and androgens in shaping tumor biology, immune responses and the TME in women and men. Although immune-targeted therapies have shown limited success in PDAC, emerging approaches such as neoantigen vaccination show promise and may enhance immune-based treatment strategies (<xref rid="b83-ijo-68-03-05848" ref-type="bibr">83</xref>). Accounting for sex-specific immune regulation will therefore be critical as immunotherapies for PDAC continue to advance.</p></sec>
<sec sec-type="other">
<label>7.</label>
<title>Tumor microbiota</title>
<p>Research on tumor microbiota has provided compelling insights into its role in modulating the TME (<xref rid="b84-ijo-68-03-05848" ref-type="bibr">84</xref>) and shaping systemic immune responses, thereby influencing various diseases (<xref rid="b85-ijo-68-03-05848" ref-type="bibr">85</xref>). In PDAC, the intratumoral microbiota significantly impacts prognosis and therapeutic efficacy, most notably by altering the TME (<xref rid="b86-ijo-68-03-05848" ref-type="bibr">86</xref>), influencing tumor phenotype (<xref rid="b87-ijo-68-03-05848" ref-type="bibr">87</xref>), and degrading chemotherapeutic agents such as gemcitabine (<xref rid="b88-ijo-68-03-05848" ref-type="bibr">88</xref>,<xref rid="b89-ijo-68-03-05848" ref-type="bibr">89</xref>). However, the influence of sex on the tumor microbiota remains unclear. To date, few studies have assessed bacterial species distribution by sex in patients with PDAC and none have reported significant differences (<xref rid="b86-ijo-68-03-05848" ref-type="bibr">86</xref>,<xref rid="b90-ijo-68-03-05848" ref-type="bibr">90</xref>). This is further supported by comparable rates of bacterial colonization in tumor tissue across sexes (<xref rid="b91-ijo-68-03-05848" ref-type="bibr">91</xref>), as well as a similar prevalence of intratumoral gram-negative bacteria in male and female patients (<xref rid="b89-ijo-68-03-05848" ref-type="bibr">89</xref>). Although it should be noted that none of the studies chose the investigation of sex-specific differences as their primary endpoint.</p>
<p>Nonetheless, sex-specific differences in the oral and gut microbiota have been reported in patients with PDAC compared with healthy controls (<xref rid="b92-ijo-68-03-05848" ref-type="bibr">92</xref>). These differences are also evident in murine models, where a recent study identified increased abundance of <italic>Ligilactobacillus</italic> and <italic>Acetatifactor</italic> in female mice with PDAC (<xref rid="b93-ijo-68-03-05848" ref-type="bibr">93</xref>). While intriguing, the implications of these findings for immune modulation or tumor progression remain unclear. Further illustrating the role of microbiota in therapy, antibiotic administration has been shown to enhance gemcitabine efficacy in advanced PDAC (<xref rid="b94-ijo-68-03-05848" ref-type="bibr">94</xref>), although this effect was not associated with patient sex. While current evidence does not show consistent sex-based differences in the tumor microbiota of PDAC, emerging findings in gut and oral microbiomes, as well as in preclinical models, underscore the need for further investigation. Understanding how sex may modulate the microbiome-immune-tumor axis could open new avenues for personalized therapeutic strategies.</p></sec>
<sec sec-type="other">
<label>8.</label>
<title>Biomarkers and genetics</title>
<sec>
<title>Serum Biomarkers</title>
<p>The most commonly used biomarker for PDAC is carbohydrate antigen 19-9 (CA19-9), although its specificity and sensitivity remain limited (<xref rid="b95-ijo-68-03-05848" ref-type="bibr">95</xref>). Few studies have examined sex-specific differences and results are inconsistent. A study reported more men (77.3%) with elevated CA19-9 serum levels than women (66.7%) (<xref rid="b96-ijo-68-03-05848" ref-type="bibr">96</xref>), although the clinical significance of this difference remains unclear. However, several novel biomarkers that are not used in clinical practice have shown sex-based differences in expression patterns. For example, tissue inhibitor of metalloproteinase 1 (TIMP1) has been shown to be associated with liver metastases and poorer survival specifically in male patients, a finding supported by mouse models showing earlier metastasis with higher TIMP1 levels in males (<xref rid="b97-ijo-68-03-05848" ref-type="bibr">97</xref>). In addition, thymidine kinase (TK) levels have been reported to be higher in men: In one study, 21 men vs. 9 women had TK levels above the median, while low TK levels showed no sex difference (<xref rid="b98-ijo-68-03-05848" ref-type="bibr">98</xref>). Moreover, the serum marker adiponectin has been shown to be associated with shorter survival in female patients only (<xref rid="b99-ijo-68-03-05848" ref-type="bibr">99</xref>). These findings indicate that certain biomarkers may have sex-specific prognostic value, although none are currently used in clinical routine, to the best of our knowledge. While some sex-related differences have been reported, most data remain exploratory and lack consistent validation. The continued absence of reliable biomarkers in PDAC remains a major challenge for early detection and personalized therapy, underscoring the need for large, well-designed studies that systematically incorporate sex as a biological variable.</p></sec>
<sec>
<title>Genetic alterations</title>
<p>The four major driver mutations in PDAC affecting <italic>KRAS, CDKN2A</italic>, <italic>TP53</italic> and <italic>SMAD4</italic> occur at similar frequencies in both male and female patients (<xref rid="b100-ijo-68-03-05848" ref-type="bibr">100</xref>,<xref rid="b101-ijo-68-03-05848" ref-type="bibr">101</xref>). However, other tumor-related genes show sex-specific mutation patterns; for example, alterations in <italic>CDKN2B</italic> and the androgen receptor (<italic>AR</italic>) gene are more frequently observed in female patients (<xref rid="b100-ijo-68-03-05848" ref-type="bibr">100</xref>). Additionally, AR and estrogen receptor binding sites in promoter regions contribute to distinct sex-specific gene expression patterns in PDAC (<xref rid="b102-ijo-68-03-05848" ref-type="bibr">102</xref>). A study found that among all upregulated genes in male PDAC samples, 24 contained androgen response elements (AREs), including <italic>EFNB2</italic>, <italic>BICD1</italic> and <italic>LAMA3</italic>, which strongly correlate with <italic>KRAS</italic> expression, as well as <italic>GLI2</italic>, a key transcription factor involved in carcinogenesis. These ARE-regulated genes in men are enriched in tumor-related pathways, such as axon guidance and extracellular matrix components, and are associated with poorer survival. By contrast, among all genes upregulated in female PDAC samples compared with normal tissue, only 3 genes, <italic>ELOVL6</italic>, <italic>SALL4</italic> and <italic>TFF1</italic>, are upregulated by estrogen response elements. Overall, this suggests that AR-driven transcription plays a more dominant and functionally relevant role in male PDAC biology (<xref rid="b102-ijo-68-03-05848" ref-type="bibr">102</xref>), while these sex-specific molecular effects do not appear to be linked to differential activity in the estrogen or pregnenolone pathways (<xref rid="b103-ijo-68-03-05848" ref-type="bibr">103</xref>). Furthermore, no sex-specific differences were described for single nucleotide polymorphisms (SNPs) of DNA repair genes (<xref rid="b104-ijo-68-03-05848" ref-type="bibr">104</xref>), although other SNPs had sex-specific effects. For instance, the leptin receptor SNP rs11585329 is associated with improved survival in men (<xref rid="b99-ijo-68-03-05848" ref-type="bibr">99</xref>), while the APC I1307K variant correlates with improved outcomes in women (<xref rid="b74-ijo-68-03-05848" ref-type="bibr">74</xref>). While these findings expand our understanding of sex-specific genomic features in PDAC, most evidence is derived from retrospective or database-driven analyses with limited functional validation. Linking these alterations to biological function and therapeutic vulnerability will be crucial to translate genomic sex differences into clinical relevance.</p></sec>
<sec>
<title>Transcriptional and epigenetic regulation</title>
<p>Notably, the expression of certain transcription factors contributes to sex-specific differences in tumor biology. For example, the transcription factor Kaiso has been linked to increased tumor invasiveness and poorer prognosis in male patients (<xref rid="b105-ijo-68-03-05848" ref-type="bibr">105</xref>). Additionally, the transcription factors FoxP1 and activin have been associated with the development of cachexia and sarcopenia, which appear to affect male patients with PDAC more severely (<xref rid="b106-ijo-68-03-05848" ref-type="bibr">106</xref>,<xref rid="b107-ijo-68-03-05848" ref-type="bibr">107</xref>). However, findings on sex-specific molecular tumor subtypes based on transcription profiles remain inconsistent. Some studies suggest a higher prevalence of the more aggressive quasi-mesenchymal or basal-like subtypes in men with resected PDAC, potentially explaining poorer outcomes (<xref rid="b108-ijo-68-03-05848" ref-type="bibr">108</xref>,<xref rid="b109-ijo-68-03-05848" ref-type="bibr">109</xref>). By contrast, other studies report no significant sex-based differences in gene expression signatures used to predict treatment response to gemcitabine and FOLFIRINOX (<xref rid="b110-ijo-68-03-05848" ref-type="bibr">110</xref>,<xref rid="b111-ijo-68-03-05848" ref-type="bibr">111</xref>). In the realm of epigenetics, evidence indicates that loss of the histone demethylase, lysine demethylase 6A (KDM6A), induces a squamous-like, metastatic PDAC subtype specifically in female patients (<xref rid="b112-ijo-68-03-05848" ref-type="bibr">112</xref>). In mouse models, male Kdm6a-knockouts retained cancer protection through UTY, a Y-chromosome-encoded homolog of Kdm6a, suggesting a sex-specific regulation of chromatin remodeling (<xref rid="b112-ijo-68-03-05848" ref-type="bibr">112</xref>). Hence, current evidence on transcriptional and epigenetic regulation indicate a potential impact of sex-differences, although data are scarce. Moreover, variable study designs and limited validation contribute to conflicting results. More specific approaches focusing on sex-differences will be essential to clarify whether currently described data represent true biological mechanisms or context-dependent findings.</p></sec>
<sec>
<title>Histopathology and tissue biomarkers</title>
<p>Thus far and to the best of our knowledge, there is no evidence that histopathological features, such as gland formation, stromal density or entosis differ significantly between male and female patients with PDAC (<xref rid="b113-ijo-68-03-05848" ref-type="bibr">113</xref>-<xref rid="b115-ijo-68-03-05848" ref-type="bibr">115</xref>). Similarly, the expression of multiple diagnostic tissue biomarkers for PDAC, including CK7, mucin-1 and SMAD4, does not show any sex-related variation in histopathological examinations (<xref rid="tIV-ijo-68-03-05848" ref-type="table">Table IV</xref>). Due to retrospective analyses, these results must be interpreted with caution. Up to now, to the best of our knowledge, no clinically validated sex-specific biomarkers for PDAC exist. Future studies incorporating sex as a biological variable, particularly through multi-omics approaches, are essential to uncover novel, personalized biomarkers in PDAC.</p></sec></sec>
<sec sec-type="other">
<label>9.</label>
<title>Discussion and future perspectives</title>
<p>PDAC exhibits clear sex-based differences across multiple dimensions, including incidence, risk factors, tumor biology, immune response and treatment outcomes. While men have historically shown higher incidence and mortality rates, the burden of disease is rising disproportionately in women, particularly in younger women, underscoring the importance of sex-specific research. Rising pancreatic cancer rates in young women likely result from a combination of sex-based biological vulnerability and gender-related behavioral patterns. Biologically, women appear more susceptible to the carcinogenic effects of obesity, central fat distribution and early-life smoking. Socially and behaviorally, earlier smoking initiation, rising obesity rates and increasing risky alcohol consumption intensify exposure to these factors. These combined dynamics highlight the need for targeted, sex- and gender-specific risk-prevention strategies.</p>
<p>Biological sex influences not only disease susceptibility but also chemotherapy pharmacokinetics, toxicity profiles, immune responses, and potentially tumor progression pathways. Women often experience greater treatment-related toxicity, while men may face subtherapeutic dosing, indicating that standardized treatment regimens may inadequately account for sex-based variability. In this context, existing therapeutic drug-monitoring approaches for agents such as 5-FU and irinotecan represent an important but underused opportunity; when applied consistently, these tools could facilitate more precise dose optimization for both sexes and help mitigate sex-related differences in exposure and toxicity. In addition, gender and sociocultural factors influence how cancer treatment is received and tolerated, yet they remain largely unaddressed in research and clinical practice. Despite accumulating evidence, most large clinical trials and translational studies still fail to stratify or analyze outcomes by sex, leaving a critical gap in our ability to personalize therapy.</p>
<p>To advance toward precision medicine in PDAC, sex must be systematically incorporated as a biological variable at every stage of research and clinical development. For instance, future PDAC trials should include sex as a predefined stratification factor or covariate in randomization and outcome analyses, ensuring adequate statistical power for sex-specific endpoints. Adaptive trial designs could prospectively test sex-based differences in efficacy or toxicity. Pharmacokinetic and pharmacogenomic studies should explicitly evaluate sex differences in drug metabolism, immune response, tolerance and exposure-response associations to guide individualized dosing strategies. Furthermore, translational studies should report biomarker performance and prognostic value separately for men and women, to identify sex-specific predictive signatures of response or resistance. Finally, in preclinical models, the development of sex-balanced patient-derived organoids and murine models should be considered for dissecting sex-dependent mechanisms and therapeutic vulnerabilities (<xref rid="f2-ijo-68-03-05848" ref-type="fig">Fig. 2</xref>).</p>
<p>It should be acknowledged that current evidence is largely derived from retrospective analyses with heterogeneous metho dologies and limited adjustment for confounders. Nevertheless, the present review highlights that sex-stratified data remain underreported in PDAC trials, and that preclinical systems rarely account for hormonal or chromosomal sex effects. Addressing these limitations will require coordinated efforts to standardize sex reporting, design prospective studies with balanced enrollment and integrate multi-omic datasets to unravel biological from sociocultural determinants of outcome. In conclusion, addressing sex disparities in PDAC is not merely a scientific objective but a prerequisite for equitable precision oncology. Incorporating sex-based insights into risk assessment, biomarker discovery and therapeutic design will be essential to optimize treatment efficacy and minimize toxicity, ultimately moving toward more personalized and effective care for all patients with PDAC.</p></sec></body>
<back>
<sec sec-type="data-availability">
<title>Availability of data and materials</title>
<p>Not applicable.</p></sec>
<sec sec-type="other">
<title>Authors' contributions</title>
<p>All authors contributed to the conception, drafting and critical revision of this review. SR, EOG, LAM, DKZ and MG performed the primary literature search and SR and EOG drafted the initial version of the manuscript. IR, JML and D&#x000D6; served as mentors and provided guidance, supervision and critical feedback throughout the preparation of the manuscript. SR and MG designed and prepared the tables and figures. DKZ, MG and LAM revised and finalized individual sections of the manuscript. All authors reviewed and edited the manuscript. All authors read and approved the final version of the manuscript. Data authentication is not applicable.</p></sec>
<sec sec-type="other">
<title>Ethics approval and consent to participate</title>
<p>Not applicable.</p></sec>
<sec sec-type="other">
<title>Patient consent for publication</title>
<p>Not applicable.</p></sec>
<sec sec-type="COI-statement">
<title>Competing interests</title>
<p>The authors declare that they have no competing interests.</p></sec>
<sec sec-type="other">
<title>Authors' information</title>
<p>ORCIDs: Sophie Rauschenberg, 0009-0004-3408-1862; Elisabeth Orgler-Gasche, 0000-0003-1904-2553; Didem Karakas Zeybek, 0000-0002-3781-6834; Ivonne Regel, 0000-0002-0206-4441; J.-Matthias L&#x000F6;hr, 0000-0002-7647-198X; Daniel &#x000D6;hlund, 0000-0002-5847-2778; Michael G&#x000FC;nther, 0009-0001-5091-5060; Lina Aguilera Munoz, 0000-0002-6317-8725.</p></sec>
<ack>
<title>Acknowledgments</title>
<p>This review was conducted as part of the Pancreas2000 program, the postgraduate educational program of the European Pancreas Club (EPC).</p></ack>
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<floats-group>
<fig id="f1-ijo-68-03-05848" position="float">
<label>Figure 1</label>
<caption>
<p>Overview of sex-related hormonal and genetic differences for PDAC. Estrogens significantly shape immune functions, including innate immune responsiveness through TLRs and the regulation of cytokine production. In PDAC, estrogens influence transcriptional subtypes and further modulate the TME by promoting the differentiation of CAFs toward a more tumor-suppressive phenotype. Conversely, estrogens can also affect TAMs, driving them toward a more immunosuppressive state. Notably, TAMs in women show greater plasticity following neoadjuvant chemoradiation with gemcitabine, which is associated with improved survival. By contrast, androgens are linked to carcinogenesis and cachexia. Notably, the effects of estrogens are not restricted to women; men can also produce estrogen locally within the tumor tissue, similarly promoting CAF differentiation toward a more tumor-suppressive TME. PDAC, pancreatic ductal adenocarcinoma; TME, tissue microenvironment; ERE, estrogen response element; ARE, androgen response element; AR, androgen receptor; TAM, tumor-associated macrophage; CAF, cancer-associated fibroblasts; TLR, Toll-like receptor; CDKN2B, cyclin-dependent kinase inhibitor 2B; TFF1, trefoil factor 1; KDM6A, lysine demethylase 6A; GLI2, zinc finger protein 2; EFNB2, ephrin B2; BICD1, bicaudal D cargo adaptor 1; LAMA3, laminin &#x003B1;3; ELOVL6, elongation-of-very-long-chain-fatty acids 6; SALL4, Sal-like protein 4.</p></caption>
<graphic xlink:href="ijo-68-03-05848-g00.jpg"/></fig>
<fig id="f2-ijo-68-03-05848" position="float">
<label>Figure 2</label>
<caption>
<p>Structured overview of sex-related differences in PDAC. The left panel summarizes aspects associated with female patients, including epidemiological patterns, relevant risk factors, prognostic considerations, immune-related features and molecular characteristics. The right panel presents the corresponding male-associated domains, following the same thematic categories for direct comparison. The lower section synthesizes overarching implications for future research, highlighting the need to integrate sex as a biological variable in study design and translational investigations. <sup>&#x0002A;</sup>trends have been shown, but further studies are needed. PDAC, pancreatic ductal adenocarcinoma; TAM, tumor-associated macrophage; AR, androgen receptor; CDKN2B, cyclin-dependent kinase inhibitor 2B.</p></caption>
<graphic xlink:href="ijo-68-03-05848-g01.jpg"/></fig>
<table-wrap id="tI-ijo-68-03-05848" position="float">
<label>Table I</label>
<caption>
<p>Comparative summary of studies on smoking and pancreatic ductal adenocarcinoma risk by sex.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="bottom" align="left">First author, year</th>
<th valign="bottom" align="center">Number of patients</th>
<th valign="bottom" align="center">Study design</th>
<th valign="bottom" align="center">Results</th>
<th valign="bottom" align="center">P-value</th>
<th valign="bottom" align="center">Evidence level<xref rid="tfn1-ijo-68-03-05848" ref-type="table-fn">a</xref></th>
<th valign="bottom" align="center">(Refs.)</th></tr></thead>
<tbody>
<tr>
<td valign="top" align="left">Gram <italic>et al</italic>, 2023</td>
<td valign="top" align="left">1,936</td>
<td valign="top" align="left">Prospective cohort study, followed participants aged 45-75 years for a mean of 19.2 years</td>
<td valign="top" align="left">Current smoker:<break/>&#x02640; HR, 1.49 (95% CI, 1.24 1.79)<break/>&#x02642; HR, 1.48 (95% CI, 1.22-1.79)<break/>Early smoking:<break/>&#x02640; HR, 1.71 (95% CI, 1.14-2.57)<break/>&#x02642; HR, 1.49 (95% CI, 1.03-2.15)</td>
<td valign="top" align="left">N/A for interaction by sex N/A for interaction by sex</td>
<td valign="top" align="center">B</td>
<td valign="top" align="center">(<xref rid="b17-ijo-68-03-05848" ref-type="bibr">17</xref>)</td></tr>
<tr>
<td valign="top" align="left">Bosetti <italic>et al</italic>, 2012</td>
<td valign="top" align="left">6,507 cases/12, 890 controls</td>
<td valign="top" align="left">Pooled case-control (PanC4 Consortium)</td>
<td valign="top" align="left">Current smoker (15 to &lt;25 cigarettes/day):<break/>&#x02640; OR, 2.60 (95% CI, 1.74-3.90)<break/>&#x02642; OR, 1.92 (95% CI, 1.55-2.38)<break/>High consumption (&#x02265;25 cigarettes/day):<break/>&#x02640; OR, 3.84 (95% CI, 2.73-5.42)<break/>&#x02642; OR, 2.92 (95% CI, 2.01-4.23)</td>
<td valign="top" align="left">0.195<break/>0.286</td>
<td valign="top" align="center">B</td>
<td valign="top" align="center">(<xref rid="b18-ijo-68-03-05848" ref-type="bibr">18</xref>)</td></tr>
<tr>
<td valign="top" align="left">Koyanagi <italic>et al</italic>, 2019</td>
<td valign="top" align="left">354,154</td>
<td valign="top" align="left">Pooled analysis of 10 prospective population-based cohort studies in Japan</td>
<td valign="top" align="left">Current smoker (compared with never smokers):<break/>&#x02640; HR, 1.81 (95% CI, 1.43-2.30)<break/>&#x02642; HR, 1.59 (95% CI, 1.32-1.91)<break/>Former smoker (compared with never smokers):<break/>&#x02640; HR, 1.77 (95% CI, 1.19-2.62)<break/>&#x02642; HR, 1.10 (95% CI, 0.89-1.36)<break/>Risk per 10 pack-years (compared with never smokers):<break/>&#x02640; HR, 1.06 (95% CI, 0.92-1.22)<break/>&#x02642; HR, 1.06 (95% CI, 1.03-1.10)</td>
<td valign="top" align="left">N/A for interaction by sex<break/>N/A for interaction by sex N/A for interaction by sex</td>
<td valign="top" align="center">A</td>
<td valign="top" align="center">(<xref rid="b19-ijo-68-03-05848" ref-type="bibr">19</xref>)</td></tr></tbody></table>
<table-wrap-foot>
<fn id="tfn1-ijo-68-03-05848">
<label>a</label>
<p>Evidence levels (A-C): A, high evidence: Randomized large, controlled trials, systematic reviews or meta-analyses, large prospective cohort studies, consistent results across multiple independent study groups or reproducible preclinical data with low risk of bias; B, moderate evidence: Non-randomized or small cohort studies, single RCTs, or preclinical data with some methodological limitations; and C, low evidence: Exploratory or descriptive studies (such as <italic>in vitro</italic> studies and case reports) with high bias risk or lacking controls. HR, hazard ratio; OR, odds ratio; CI, confidence interval; N/A, not available.</p></fn></table-wrap-foot></table-wrap>
<table-wrap id="tII-ijo-68-03-05848" position="float">
<label>Table II</label>
<caption>
<p>Comparative summary of studies on obesity and PDAC risk by sex.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="bottom" align="left">First author, year</th>
<th valign="bottom" align="center">Number of patients</th>
<th valign="bottom" align="center">Study design</th>
<th valign="bottom" align="center">Results</th>
<th valign="bottom" align="center">P-value</th>
<th valign="bottom" align="center">Evidence level<xref rid="tfn2-ijo-68-03-05848" ref-type="table-fn">a</xref></th>
<th valign="bottom" align="center">(Refs.)</th></tr></thead>
<tbody>
<tr>
<td valign="top" align="left">Genkinger <italic>et al</italic>, 2015</td>
<td valign="top" align="left">1,096,492</td>
<td valign="top" align="left">Pooled analysis of 20 prospective cohort studies from the NCI BMI and Mortality Cohort Consortium</td>
<td valign="top" align="left">Waist circumference (per 10 cm):<break/>&#x02640; HR, 1.09 (95% CI, 1.03-1.15)<break/>&#x02642; HR, 1.08 (95% CI, 1.02-1.15)<break/>Waist-to-hip ratio:<break/>&#x02640; HR, 1.10 (95% CI, 1.01-1.21)<break/>&#x02642; HR, 1.12 (95% CI, 1.02-1.23)<break/>BMI in early adulthood (per 5 kg/m<sup>2</sup>):<break/>&#x02640; HR, 1.11 (95% CI, 1.03-1.21)<break/>&#x02642; HR, 1.25 (95% CI, 1.15-1.35)</td>
<td valign="top" align="left">0.86<break/>0.80<break/>0.04</td>
<td valign="top" align="center">A</td>
<td valign="top" align="center">(<xref rid="b24-ijo-68-03-05848" ref-type="bibr">24</xref>)</td></tr>
<tr>
<td valign="top" align="left">Arslan <italic>et al</italic>, 2010</td>
<td valign="top" align="left">2,170 PDAC cases/2,209 matched controls</td>
<td valign="top" align="left">Pooled nested case-control study (Pancreatic Cancer Cohort Consortium-PanScan)</td>
<td valign="top" align="left">PDAC risk and body composition BMI:<break/>&#x02640; OR, 1.34 (95% CI, 1.05-1.70)<break/>&#x02642; OR, 1.33 (95% CI, 1.04-1.69)<break/>Waist-to-hip-ratio:<break/>&#x02640; OR, 1.87 (95% CI, 1.31-2.69)<break/>&#x02642; N/A, not significant</td>
<td valign="top" align="left">N/A for interaction by sex<break/>N/A for interaction by sex</td>
<td valign="top" align="center">A</td>
<td valign="top" align="center">(<xref rid="b22-ijo-68-03-05848" ref-type="bibr">22</xref>)</td></tr>
<tr>
<td valign="top" align="left">Calle <italic>et al</italic>, 2003</td>
<td valign="top" align="left">900,053</td>
<td valign="top" align="left">Prospective cohort study (Cancer Prevention Study II), Follow-up 16 years</td>
<td valign="top" align="left">PDAC mortality by BMI BMI, 25.0-29.9 kg/m<sup>2</sup>:<break/>&#x02640; RR, 1.11 (95% CI, 1.00-1.24)<break/>&#x02642; RR, 1.13 (95% CI, 1.03-1.25)<break/>BMI, 30.0-34.9 kg/m<sup>2</sup>:<break/>&#x02640; RR, 1.28 (95% CI, 1.07-1.52)<break/>&#x02642; RR, 1.41 (95% CI, 1.19-1.66)<break/>BMI, &#x02265;40.0 kg/m<sup>2</sup>:<break/>&#x02640; RR, 2.76 (95% CI, 1.74-4.36)<break/>&#x02642; RR, 1.49 (95% CI, 0.99-2.22)</td>
<td valign="top" align="left">N/A for interaction by sex<break/>N/A for interaction by sex<break/>N/A for interaction by sex</td>
<td valign="top" align="center">A</td>
<td valign="top" align="center">(<xref rid="b21-ijo-68-03-05848" ref-type="bibr">21</xref>)</td></tr>
<tr>
<td valign="top" align="left">Johansen <italic>et al</italic>, 2010</td>
<td valign="top" align="left">577,315/86 2 PDAC cases</td>
<td valign="top" align="left">Pooled prospective cohort study from the Metabolic Syndrome and Cancer Project (Me-Can)</td>
<td valign="top" align="left">PDAC risk and metabolic syndrome &#x0005B;sex-specific results (z-score-based HRs)&#x0005D;<break/>BMI:<break/>&#x02640; 0.92, (95% CI, 0.79-1.07)<break/>&#x02642; 0.90, (95% CI, 0.80-1.02)<break/>Mid-blood pressure:<break/>&#x02640; 1.34, (95% CI, 1.08-1.66)<break/>&#x02642; 1.15, (95% CI, 0.97-1.35)<break/>Glucose:<break/>&#x02640; 1.98, (95% CI, 1.41-2.76)<break/>&#x02642; 1.37, (95% CI, 1.01-1.85)<break/>Cholesterol:<break/>&#x02640; 1.16, (95% CI, 0.96-1.41)<break/>&#x02642; 0.81, (95% CI, 0.69-0.95)</td>
<td valign="top" align="left">0.45<break/>0.06<break/>0.02<break/>0.08</td>
<td valign="top" align="center">A</td>
<td valign="top" align="center">(<xref rid="b23-ijo-68-03-05848" ref-type="bibr">23</xref>)</td></tr>
<tr>
<td valign="top" align="left">Jiao <italic>et al</italic>, 2010</td>
<td valign="top" align="left">952,494/2, 639 PDAC cases</td>
<td valign="top" align="left">Pooled analysis of 7 prospective cohorts (US, Finland and China). Mean follow-up of 6.9 years</td>
<td valign="top" align="left">PDAC risk and BMI<break/>BMI (per 5 kg/m<sup>2</sup> increment):<break/>&#x02640; RR, 1.12 (95% CI, 1.05-1.19)<break/>&#x02642; RR, 1.06 (95% CI, 0.99-1.13)<break/>BMI, 30.0-34.9 kg/m<sup>2</sup>:<break/>&#x02640; RR, 1.34 (95% CI, 1.11-1.64)<break/>&#x02642; RR, 1.11 (95% CI, 0.95-1.30)</td>
<td valign="top" align="left">N/A for interaction by sex<break/>N/A for interaction by sex</td>
<td valign="top" align="center">A</td>
<td valign="top" align="center">(<xref rid="b20-ijo-68-03-05848" ref-type="bibr">20</xref>)</td></tr></tbody></table>
<table-wrap-foot>
<fn id="tfn2-ijo-68-03-05848">
<label>a</label>
<p>Evidence levels (A-C): A, high evidence: Randomized large, controlled trials, systematic reviews or meta-analyses, large prospective cohort studies, consistent results across multiple independent study groups or reproducible preclinical data with low risk of bias; B, moderate evidence: Non-randomized or small cohort studies, single RCTs or preclinical data with some methodological limitations; and C, low evidence: Exploratory or descriptive studies (such as <italic>in vitro</italic> studies and case reports) with high bias risk or lacking controls. HR, hazard ratio; OR, odds ratio; RR, relative risk; CI, confidence interval; N/A, not available; PDAC, pancreatic ductal adenocarcinoma; BMI, body mass index.</p></fn></table-wrap-foot></table-wrap>
<table-wrap id="tIII-ijo-68-03-05848" position="float">
<label>Table III</label>
<caption>
<p>Comparative summary of studies on female hormonal determinants and PDAC risk.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="bottom" align="left">First author/s, year</th>
<th valign="bottom" align="center">Number of patients</th>
<th valign="bottom" align="center">Study design</th>
<th valign="bottom" align="center">Results</th>
<th valign="bottom" align="center">P-value</th>
<th valign="bottom" align="center">Evidence level<xref rid="tfn3-ijo-68-03-05848" ref-type="table-fn">a</xref></th>
<th valign="bottom" align="center">(Refs.)</th></tr></thead>
<tbody>
<tr>
<td valign="top" align="left">Ilic <italic>et al</italic>, 2021</td>
<td valign="top" align="left">21 studies (10 case-control + 11 cohort), 7,700 PDAC cases</td>
<td valign="top" align="left">Systematic review and meta-analysis (Europe, America and Asia)</td>
<td valign="top" align="left">Ever use of OCs: RR, 0.85 (95% CI, 0.73-0.98) No dose-response relationship for duration: &lt;1 year: RR, 1.08 (95% CI, 0.91-1.29) &lt;5 years: RR, 1.07 (95% CI, 0.95-1.19) 5-10 years: RR, 1.08 (95% CI, 0.93-1.26)</td>
<td valign="top" align="left">0.03<break/>&gt;0.05 for all</td>
<td valign="top" align="center">A</td>
<td valign="top" align="center">(<xref rid="b36-ijo-68-03-05848" ref-type="bibr">36</xref>)</td></tr>
<tr>
<td valign="top" align="left">Andersson <italic>et al</italic>, 2018</td>
<td valign="top" align="left">17,035/110 PDAC cases</td>
<td valign="top" align="left">Prospective population-based cohort study (Sweden)</td>
<td valign="top" align="left">Age at menarche (continuous): HR, 1.17 (95% CI, 1.04-1.32) Ever use of any HRT: HR, 0.48 (95% CI, 0.23-1.00) Estrogen-only HRT: HR, 0.22 (95% CI, 0.05-0.90) Ever use of OC: HR, 0.68 (95% CI, 0.44-1.06) Parity, breastfeeding and menopause timing: HR, ~1.00</td>
<td valign="top" align="left">0.008<break/>0.049<break/>0.035<break/>0.091<break/>&gt;0.05 for all</td>
<td valign="top" align="center">B</td>
<td valign="top" align="center">(<xref rid="b37-ijo-68-03-05848" ref-type="bibr">37</xref>)</td></tr>
<tr>
<td valign="top" align="left">Lee <italic>et al</italic>, 2013</td>
<td valign="top" align="left">118,164/323 PDAC cases</td>
<td valign="top" align="left">Prospective cohort study (USA)</td>
<td valign="top" align="left">Estrogen-only HRT, current use: HR, 0.59 (95% CI, 0.42-0.84) Estrogen HRT &#x02265;20 years: HR, 0.55 (95% CI, 0.33-0.91) OC use &#x02265;10 years: HR, 1.72 (95% CI, 1.19-2.49) High dose OC use &#x02265;10 years: HR, 2.08 (95% CI, 1.05-4.12) Age at menarche, parity, menopause and breastfeeding HR, ~1.00</td>
<td valign="top" align="left">0.003<break/>0.036<break/>0.014<break/>0.024<break/>&gt;0.05 for all</td>
<td valign="top" align="center">A</td>
<td valign="top" align="center">(<xref rid="b38-ijo-68-03-05848" ref-type="bibr">38</xref>)</td></tr>
<tr>
<td valign="top" align="left">Prizment <italic>et al</italic>, 2006</td>
<td valign="top" align="left">37,459/228 PDAC cases</td>
<td valign="top" align="left">Prospective population-based cohort study (USA)</td>
<td valign="top" align="left">Age at menopause &#x02265;55 vs. &lt;45 years: HR, 0.35 (95% CI, 0.18-0.68) Age at menopause (continuous, 5-year increase): HR, 0.81 (95% CI, 0.72-0.91) Ever use of any HRT: HR, 1.07 (95% CI, 0.82-1.40) Ever use of OC: HR, 0.90 (95% CI, 0.62-1.30) Parity, menarche and age at first birth HR, ~1.00</td>
<td valign="top" align="left">0.005<break/>0.001<break/>0.606<break/>0.566<break/>&gt;0.05 for all</td>
<td valign="top" align="center">B</td>
<td valign="top" align="center">(<xref rid="b39-ijo-68-03-05848" ref-type="bibr">39</xref>)</td></tr>
<tr>
<td valign="top" align="left">Duell and Holly, 2005</td>
<td valign="top" align="left">241 PDAC cases/818 controls</td>
<td valign="top" align="left">Population-based case-control study (USA)</td>
<td valign="top" align="left">Age at menopause &#x02265;55 vs. &lt;45 years: OR, 1.9 (95% CI, 1.2-2.8) Estrogen-only HRT: HR, 0.84 (95% CI, 0.62-1.1) Ever use of OC: HR, 0.95 (95% CI, 0.65-1.4)</td>
<td valign="top" align="left">0.003<break/>&gt;0.05<break/>&gt;0.05</td>
<td valign="top" align="center">B</td>
<td valign="top" align="center">(<xref rid="b40-ijo-68-03-05848" ref-type="bibr">40</xref>)</td></tr>
<tr>
<td valign="top" align="left">Stevens <italic>et al</italic>, 2009</td>
<td valign="top" align="left">995,1957/1,182 PDAC cases</td>
<td valign="top" align="left">Prospective cohort study (UK)</td>
<td valign="top" align="left">Parity (ever vs. never): RR, 0.88 (95% CI, 0.79-0.98) Age at menarche, age at birth, age at menopause, breastfeeding and number of children</td>
<td valign="top" align="left">0.01<break/>&gt;0.05 for all</td>
<td valign="top" align="center">A</td>
<td valign="top" align="center">(<xref rid="b41-ijo-68-03-05848" ref-type="bibr">41</xref>)</td></tr></tbody></table>
<table-wrap-foot>
<fn id="tfn3-ijo-68-03-05848">
<label>a</label>
<p>Evidence levels (A-C): A, high evidence: Randomized large, controlled trials, systematic reviews or meta-analyses, large prospective cohort studies, consistent results across multiple independent study groups or reproducible preclinical data with low risk of bias; B, moderate evidence: Non-randomized or small cohort studies, single RCTs, or preclinical data with some methodological limitations; and C, low evidence: Exploratory or descriptive studies (such as <italic>in vitro</italic> studies and case reports) with high bias risk or lacking controls. HR, hazard ratio; OR, odds ratio; RR, relative risk; CI, confidence interval; N/A, not available; PDAC, pancreatic ductal adenocarcinoma; HRT, hormone replacement therapy; OC, oral contraceptive.</p></fn></table-wrap-foot></table-wrap>
<table-wrap id="tIV-ijo-68-03-05848" position="float">
<label>Table IV</label>
<caption>
<p>Current evidence on biomarkers in pancreatic ductal adenocarcinoma: Sex-specific differences.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="bottom" align="left">First author, year</th>
<th valign="bottom" align="center">Marker</th>
<th valign="bottom" align="center">Number of patients</th>
<th valign="bottom" align="center">Clinical situation</th>
<th valign="bottom" align="center">Detection method</th>
<th valign="bottom" align="center">Results</th>
<th valign="bottom" align="center">Evidence level<xref rid="tfn4-ijo-68-03-05848" ref-type="table-fn">a</xref></th>
<th valign="bottom" align="center">(Refs.)</th></tr></thead>
<tbody>
<tr>
<td valign="top" align="left">Song <italic>et al</italic>, 2022</td>
<td valign="top" align="left">CK7</td>
<td valign="top" align="center">55</td>
<td valign="top" align="left">Resected</td>
<td valign="top" align="left">IHC</td>
<td valign="top" align="left">No significant sex difference</td>
<td valign="top" align="center">B</td>
<td valign="top" align="center">(<xref rid="b116-ijo-68-03-05848" ref-type="bibr">116</xref>)</td></tr>
<tr>
<td valign="top" align="left">Xiong <italic>et al</italic>, 2022</td>
<td valign="top" align="left">CK8</td>
<td valign="top" align="center">176</td>
<td valign="top" align="left">Resected</td>
<td valign="top" align="left">mRNA expression</td>
<td valign="top" align="left">No significant sex difference</td>
<td valign="top" align="center">B</td>
<td valign="top" align="center">(<xref rid="b117-ijo-68-03-05848" ref-type="bibr">117</xref>)</td></tr>
<tr>
<td valign="top" align="left">Qian <italic>et al</italic>, 2022</td>
<td valign="top" align="left">MUC1</td>
<td valign="top" align="center">420</td>
<td valign="top" align="left">Resected</td>
<td valign="top" align="left">IHC</td>
<td valign="top" align="left">No significant sex difference</td>
<td valign="top" align="center">B</td>
<td valign="top" align="center">(<xref rid="b118-ijo-68-03-05848" ref-type="bibr">118</xref>)</td></tr>
<tr>
<td valign="top" align="left">Ermiah <italic>et al</italic>, 2022</td>
<td valign="top" align="left">CEA</td>
<td valign="top" align="center">123</td>
<td valign="top" align="left">Resected and advanced</td>
<td valign="top" align="left">Electrochemiluminescence immunoassay</td>
<td valign="top" align="left">No significant sex difference</td>
<td valign="top" align="center">B</td>
<td valign="top" align="center">(<xref rid="b119-ijo-68-03-05848" ref-type="bibr">119</xref>)</td></tr>
<tr>
<td valign="top" align="left">Ermiah <italic>et al</italic>, 2022</td>
<td valign="top" align="left">CA19-9</td>
<td valign="top" align="center">123</td>
<td valign="top" align="left">Resected and advanced</td>
<td valign="top" align="left">Electrochemiluminescence immunoassay</td>
<td valign="top" align="left">No significant sex difference</td>
<td valign="top" align="center">B</td>
<td valign="top" align="center">(<xref rid="b119-ijo-68-03-05848" ref-type="bibr">119</xref>)</td></tr>
<tr>
<td valign="top" align="left">Qian <italic>et al</italic>, 2022</td>
<td valign="top" align="left">MUC5AC</td>
<td valign="top" align="center">407</td>
<td valign="top" align="left">Resected</td>
<td valign="top" align="left">IHC</td>
<td valign="top" align="left">No significant sex difference</td>
<td valign="top" align="center">B</td>
<td valign="top" align="center">(<xref rid="b118-ijo-68-03-05848" ref-type="bibr">118</xref>)</td></tr>
<tr>
<td valign="top" align="left">Sumiyoshi <italic>et al</italic>, 2024</td>
<td valign="top" align="left">CA19-9/DUPAN2</td>
<td valign="top" align="center">521</td>
<td valign="top" align="left">Resected</td>
<td valign="top" align="left">Serum level</td>
<td valign="top" align="left">No significant sex difference</td>
<td valign="top" align="center">B</td>
<td valign="top" align="center">(<xref rid="b120-ijo-68-03-05848" ref-type="bibr">120</xref>)</td></tr>
<tr>
<td valign="top" align="left">Liang <italic>et al</italic>, 2017</td>
<td valign="top" align="left">CA 125/ MUC16</td>
<td valign="top" align="center">160</td>
<td valign="top" align="left">Resected</td>
<td valign="top" align="left">mRNA expression</td>
<td valign="top" align="left">No significant sex difference</td>
<td valign="top" align="center">B</td>
<td valign="top" align="center">(<xref rid="b121-ijo-68-03-05848" ref-type="bibr">121</xref>)</td></tr>
<tr>
<td valign="top" align="left">Liang <italic>et al</italic>, 2017</td>
<td valign="top" align="left">CA125/ MUC16</td>
<td valign="top" align="center">110</td>
<td valign="top" align="left">Resected</td>
<td valign="top" align="left">IHC</td>
<td valign="top" align="left">No significant sex difference</td>
<td valign="top" align="center">B</td>
<td valign="top" align="center">(<xref rid="b121-ijo-68-03-05848" ref-type="bibr">121</xref>)</td></tr>
<tr>
<td valign="top" align="left">Xiao <italic>et al</italic>, 2014</td>
<td valign="top" align="left">CDX2</td>
<td valign="top" align="center">61</td>
<td valign="top" align="left">Resected</td>
<td valign="top" align="left">IHC</td>
<td valign="top" align="left">No significant sex difference</td>
<td valign="top" align="center">B</td>
<td valign="top" align="center">(<xref rid="b122-ijo-68-03-05848" ref-type="bibr">122</xref>)</td></tr>
<tr>
<td valign="top" align="left">Amal <italic>et al</italic>, 2024</td>
<td valign="top" align="left">SMAD4</td>
<td valign="top" align="center">60</td>
<td valign="top" align="left">Resected and advanced</td>
<td valign="top" align="left">IHC</td>
<td valign="top" align="left">No significant sex difference</td>
<td valign="top" align="center">B</td>
<td valign="top" align="center">(<xref rid="b123-ijo-68-03-05848" ref-type="bibr">123</xref>)</td></tr>
<tr>
<td valign="top" align="left">Amal <italic>et al</italic>, 2024</td>
<td valign="top" align="left">S100P</td>
<td valign="top" align="center">60</td>
<td valign="top" align="left">Resected and advanced</td>
<td valign="top" align="left">IHC</td>
<td valign="top" align="left">No significant sex difference</td>
<td valign="top" align="center">B</td>
<td valign="top" align="center">(<xref rid="b123-ijo-68-03-05848" ref-type="bibr">123</xref>)</td></tr></tbody></table>
<table-wrap-foot>
<fn id="tfn4-ijo-68-03-05848">
<label>a</label>
<p>Evidence levels (A-C): A, high evidence: Randomized large, controlled trials, systematic reviews or meta-analyses, large prospective cohort studies, consistent results across multiple independent study groups or reproducible preclinical data with low risk of bias; B, moderate evidence: Non-randomized or small cohort studies, single RCTs, or preclinical data with some methodological limitations; and C, low evidence: Exploratory or descriptive studies (such as <italic>in vitro</italic> studies and case reports) with high bias risk or lacking controls. CK7/8, cytokeratin 7/8; MUC1/5AC/16, mucin-1/5AC/16; CEA, carcinoembryonic antigen; CA19-9, carbohydrate antigen 19-9; DUPAN2, duke pancreatic monoclonal antigen type 2; CA125, cancer antigen 125; CDX2, caudal-related homeobox 2; SMAD4, mothers against decapentaplegic homolog 4; S100P, S100 calcium-binding protein P; IHC, immunohistochemistry.</p></fn></table-wrap-foot></table-wrap></floats-group></article>
