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484 citation(s) found for "Ivan, SJ".

Integrating metabolomics and histopathology: A method for metabolite recovery from fixed tissue specimens
Vučković, Ivan, Meloche, Ryan , Mishra, Prasanna K. , Zhang, S, Dzeja, Petras , Macura, Slobodan , Mishra, Prasanna K. , Zhang, Song , Vučković, Ivan , Meloche, Ryan , Vuckovic, Ivan , Zhang, Song , Irazabal, Maria V , Macura, Slobodan I , Dzeja, Petras P. , Irazabal, María V.

Structural Dynamics | May 1, 2026 | Volume: 13 | Issue: 3 | Pages: No page available

10.1063/4.0001205 | PMID 42079840 Get It

Combined histopathological and metabolomic analysis of the same tissue specimen can reduce biological variability compared to independent analyses of similar samples. However, conventional workflows are incompatible: tissue fixation leads to metabolite loss through dilution and chemical reactions with fixative, while metabolomic extraction typically destroys the specimen. We propose a method that reconciles these conflicting requirements by enabling metabolite recovery from fixative while preserving tissue for histopathology. In this approach, tissue is initially fixed in a small volume of fixative; an aliquot of the fixative is then collected for nuclear magnetic resonance-based metabolomic analysis before additional fixative is added for standard processing. As a proof-of-concept, mouse kidneys from the same subject were analyzed using two protocols: standard perchloric acid extraction (ensuring complete metabolite recovery but destroying tissue) and metabolite extraction from fixative. Several metabolites were fully recoverable from the fixative, others partially, while some were lost due to chemical reactions. Despite some limitations, this strategy may be useful for analyzing precious specimens, such as human biopsies, that must remain intact for further studies. Moreover, using the same specimen for dual analyses reduces the number of animals required and enhances statistical robustness.
Artificial intelligence-enabled analysis of radiology reports: epidemiology and outcomes of incidental thyroid findings
Larios, Felipe , Borras-Osorio, Mariana, Wu, Yuqi, Claros, Ana Gabriela, Toro-Tobon, David, Cabezas, Esteban , Loor-Torres, Ricardo, Chavez, Maria Mateo , Maldonado, Kerly Guevara, Andrango, Luis Vilatuna, Jiménez, María Camila , Alzamora, Ivan Mateo , Zahidy, Misk Al, Montero, Marcelo, Proano, Ana Cristina , Jacome, Cristian Soto , Ponce-Ponte, Oscar J, Larios, Felipe , Mateo Chavez, Maria, Guevara Maldonado, Kerly, Vilatuna Andrango, Luis, Lizarazo Jimenez, Maria, Al Zahidy, Misk, Fan, Jungwei W, Branda, Megan E. , Singh Ospina, Naykky , Brito, Juan P , Mateo Chavez, Maria B , Borras-Osorio, Mariana , Claros, Ana Gabriela , Toro-Tobón, David , Loor-Torres, Ricardo , Guevara, Kerly , Fan, Jungwei , Ponte, Oscar Ponce, Ospina, Naykky Singh , Brito, Juan P.

The Journal of Clinical Endocrinology & Metabolism | April 23, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1210/clinem/dgag186 | PMID 42037237 Get It

Abstract Context Incidental thyroid findings (ITFs) are increasingly detected on imaging performed for non-thyroid indications. Their prevalence, features, and consequences remain undefined. Objective To develop, validate, and deploy a natural language processing (NLP) pipeline to identify ITFs in radiology reports and assess their prevalence, features, and clinical outcomes. Design Retrospective cohort study. Setting Mayo Clinic sites (Rochester, Arizona, Florida, Mayo Clinic Health System). Participants Adults without prior thyroid disease undergoing thyroid-capturing imaging from July 1, 2017, to September 30, 2023. A transformer-based NLP pipeline identified ITFs and extracted nodule characteristics from image reports from multiple modalities and body regions. Outcomes ITF prevalence, downstream thyroid ultrasound, biopsy, thyroidectomy, and cancer diagnosis. Logistic regression identified demographic and imaging-related factors. Results Among 115 683 patients (mean age, 56.8 [SD 17.2]; 52.9% women), 9077 (7.8%) had an ITF (92.9% nodular). ITFs were more likely in women, older adults, higher BMI, and in imaging ordered by specialties different from Emergency Medicine. Compared with chest CT, ITFs were more likely via neck CT, PET, and nuclear medicine scans. Nodule characteristics were poorly documented, with size reported in 44% and other features in fewer than 15%. Compared with patients without ITFs, those with ITFs had higher odds of thyroid nodule diagnosis (OR 45, 95%CI 41.1-49.3), biopsy (OR 46.8, 95%CI 39.0-56.2) thyroidectomy (OR 55.8, 95%CI 31.3-99.3), and thyroid cancer diagnosis (OR 61.7, 95%CI 38.6-98.5). Most cancers were papillary (88.5%) and larger when detected after ITFs (2 cm SD 1.4) vs no ITF (1.3 cm SD 0.8). Conclusion ITFs were common and strongly associated with cascades leading to the detection of small, low-risk cancers, highlighting their role in overdiagnosis and the need for standardized reporting and more selective follow-up.
Ketamine Use in Critically Ill Patients: Insights into Depressive Symptoms and Hemodynamic Changes
Patel, Vrutti , Sujanyal, Saurabh Ashok , Raavi, Lekhya , Blumenfeld, Sophia G. , Saleem, Faiz , Bateh, Said , Hanson, Abby , Jena, Anek , Isha, Shahin , Pietrzak, Katheleen A. Rottman, Ojard, Michelle, Shah, Sadia Z. , Sanghavi, Devang , Anna, Shapiro, Sujanyal, Saurabh , Rottman Pietrzak, Katheleen A, Ojard, Michelle M , Huespe, Ivan Alfredo , Moreno Franco, Pablo , Edwards, Michael A. , Chauhan, Mohit , Sanghavi, Devang K , Shahin, Isha , Kunze, Katie L. , Johnson, Patrick W. , Pietrzak, Katheleen A., Huespe, Iván , Franco, Pablo Moreno , Chauhan, Mohit

Journal of Intensive Care Medicine | April 16, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1177/08850666261438474 | PMID 41989186 Get It

Background Ketamine has demonstrated efficacy in treatment-resistant depression, primarily in psychiatric or outpatient populations. Its use in ICU patients remains underexplored, with limited data beyond case reports and small series. This study evaluated the association between subanesthetic ketamine infusions and improvement in depressive symptoms and hemodynamic changes in ICU patients. Methods We conducted a retrospective study of adults admitted to the ICU who received IV ketamine (0.3-0.75 mg/kg over 40 min on three consecutive days) for depressive symptoms. Changes in depressive symptoms were assessed using routine clinical documentation by physicians, nurses, and occupational and physical therapists. Hemodynamic parameters (blood pressure and heart rate) were recorded before and up to 120 min after infusion. The primary outcome was to evaluate depressive symptoms while the secondary outcome was to assess hemodynamic changes post transfusion. Results Thirty-four patients met criteria, including 18 solid organ transplant recipients. Median age was 59 years; 61.8% were male. Ketamine was associated with improvement in apparent sadness (90.0% vs 52.2%, P < .05) and reported sadness (95.0% vs 59.1%, P < .05). In transplant recipients, improvement in apparent sadness remained significant (80.0% vs 41.7%, P < .05). Hemodynamic parameters remained stable; heart rate increased transiently at 15-30 min post-infusion, returning to baseline by 60-90 min. Adverse effects observed were anxiety (12.5%), restlessness and/or agitation (10.4%), and dissociation (8.16%). Conclusion Subanesthetic ketamine improved specific depressive symptoms in critically ill ICU patients without significant hemodynamic instability. These findings support its potential as a rapid-acting antidepressant in the ICU, warranting further prospective trials.
T-cell activation and fibroblastic BMP4-Gremlin dysregulation indicate disease severity in acute myocarditis
Joachimbauer, Anna , Perez-Shibayama, Christian Ivan, Payne, Emily, Hanka, Isabella, Stadler, Roman, Papadopoulou, Iliana , Rickli, Hans , Maeder, Micha T, Zdanytė, Monika , Cooper, Leslie, Matter, Christian M. , Wilzeck, Verena C, Manka, Robert, Saguner, Ardan M, Ruschitzka, Frank, Schmidt, Dörthe, Gil-Cruz, Cristina Del Carmen, Perez‐Shibayama, Christian , Stadler, Roman, Maeder, Micha T. , Borst, Oliver , Cooper, Leslie, Flatz, Lukas , Wilzeck, Verena , Manka, Robert , Saguner, Ardan M. , Ruschitzka, Frank T. , Ludewig, Burkhard , Gil‐Cruz, Cristina

No container title available | April 12, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.64898/2026.04.10.26350598 Get It

Abstract Background and Aims Acute myocarditis (AM) is a T cell-mediated myocardial disease with clinical manifestations ranging from mild chest pain to cardiogenic shock. Reliable biomarkers to stratify patients and guide therapy are currently lacking. In particular, the extent of the dysregulation of inflammatory pathways, and the impact on myocardial dysfunction, remain elusive. Methods Serum analyses were performed in prospectively recruited AM patients (n = 103) from two independent cohorts. Multimodal data integration combining profiling of cytokine and chemokine dysregulation with clinical biomarkers was used to define clinical phenotypes with distinct inflammatory signatures. Machine-learning and regression models were applied to determine biomarkers that indicate clinical severity. Results Immuno-proteomic profiling revealed conserved inflammatory patterns across AM cohorts, dominated by T cell-related cytokines and chemokines. In addition, AM patients showed dysregulation of fibroblast-derived cytokines, including hepatocyte growth factor (HGF), bone morphogenic protein 4 (BMP4) and the BMP4 inhibitors Gremlin-1 (GREM1) and Gremlin-2 (GREM2). Data integration and unsupervised clustering revealed two immuno-clinical phenotypes, linking T cell activation and fibroblast dysregulation to disease severity. Machine learning-based analysis identified CXCL10, GREM2 and LVEF as critical parameters for stratifying disease severity. Conclusions These findings highlight a systemic T cell activation signature as diagnostic hallmark of AM. In addition, dysregulation of fibroblast-derived tissue cytokines serves as an indicator for distinct immuno-clinical phenotypes in myocardial inflammatory disease. Thus, the clinically relevant link between T cell-driven immune activation, myocardial inflammation and fibroblast-driven remodelling provides a versatile set of parameters to identify severe manifestations of AM. Graphical Abstract Key Question: Are serological immune signatures linked to clinical severity in acute myocarditis and do they enable patient stratification? Key Findings: T cell- and fibroblast associated proteomic signatures indicate disease severity in acute myocarditis. Novel immuno-clinical phenotypes stratify patients according to distinct immune responses and clinical manifestations. CXCL10, GREM2 and LVEF are the most important parameters to identify immuno-clinical phenotypes. Take Home Message: CXCL10, GREM2 and LVEF emerge as key determinants for a severe immuno-clinical phenotype in acute myocarditis, highlighting the role of T cell-fibroblast interaction in the disease process and linking T cell activation, fibroblastic tissue remodelling and impaired cardiac function.
Molecular-Based Ecosystem to Improve Personalized Medicine in Chronic Myelomonocytic Leukemia
Lanino, Luca , Hunter, Anthony M. , Gagelmann, Nico, Robin, M., Dall'Olio, Daniele , Flamigni, Alice, Gurnari, Carmelo, Wang, Yu‐Hung , Pleyer, Lisa , Xicoy, B., Montalban-Bravo, Guillermo, Shih, Lee-Yung, Alsugair, Ali, Gregorio, Caterina, Platzbecker, Anne Sophie, Sallman, David A., Fariselli, Piero, Garcia-Manero, Guillermo, Platzbecker, U, Solé, Francesc Gessé, Díez-Campelo, María, Maciejewski, Jaroslaw, Bejar, Rafael, Thol, Felicitas, Kroger, N., Fenaux, Pierre, Sanz, G. F., Kordasti, S., Santini, Valeria, Zeidan, Amer M., Komrokji, Rami S., Haferlach, Torsten, Germing, Ulrich, Castellani, Gastone, D'Amico, Saverio, Patnaik, M., Ieva, F., Tefferi, Ayalew, Padron, Eric , Porta, Matteo Giovanni Della, Alliance, for the iCPSS, Haque, Tamanna, Abdel-Wahab, Omar, Geissler, Klaus, Bataller, Alex, Bazinet, Alexandre , Meggendorfer, Manja , Quintavalla, Mirco, Bruseghini, Alessandro , Carota, Luciana , Dall'Olio, Lorenzo, Travaglino, Erica , Zamora, Lurdes López, Quintela, David, Jerez, Andrés , Cornejo, Elena, Martín, Paloma García, Díaz-Beyá, Marina, Pita, Alejandro Avendano, Roldán, Verónica , Suarez, Dolly Viviana Fiallo, Velasco, Estefania Cerezo, Calabuig, Marisa , Such, Esperanza, Castilla-Llorente, Cristina, Bulabois, Claude Eric, Souchet, Laëtitia, Bernardi, Massimo, Chiusolo, Patrizia, Borin, Lorenza, Follo, Matilde Yung, Consagra, Angela , Passamonti, Francesco, Diral, Elisa , Vucinic, Vladan, Bergonzi, Gregorio Maria , Hou, Hsin-An, Russo, Antonio, Tentori, Cristina Astrid , Buizza, Alessandro , Ferrari, Ivan, Matteo, Maria Di, Crespi, Alessandra, Figini, Giulia , Delponte, Camilla, Zampini, Matteo, Riva, Elena, Delleani, Mattia , Iascone, Eleonora, Ficara, Francesca , Ventura, Denise, Pinocchio, Nicole, Santoro, Armando, Kiwan, Ahmad , Ali, Najla H. Al, Zeidan, Amer M. , Robin, Marie , Dall’Olio, Daniele , Riva, Elena , Gagelmann, Nico , Robin, Marie , Sala, Claudia , Gurnari, Carmelo , Wang, Yu-Hung , Shih, Lee‐Yung , Alsugair, Ali , Fathima, Saubia , Gregorio, Caterina , Rollo, Cesare , Platzbecker, Anne Sophie , Asti, Gianluca , Itzykson, Raphael , Sallman, David A , Fariselli, Piero , Kern, Wolfgang , Garcia-Manero, Guillermo , Platzbecker, Uwe , Solé, Francesc , Diez-Campelo, Maria , Maciejewski, Jaroslaw P , Bejar, Rafael , Thol, Felicitas , Savona, Michael R , Sanz, Guillermo F , Kordasti, Shahram , Santini, Valeria , Zeidan, Amer M , Komrokji, Rami S , Castellani, Gastone , D'Amico, Saverio , Patnaik, Mrinal , Ieva, Francesca , Solary, Eric , Padron, Eric , Della Porta, Matteo Giovanni , Buizza, Alessandro , Ficara, Francesca , Lanino, Luca , Gagelmann, Nico , Gurnari, Carmelo , Xicoy, Blanca , Montalban‐Bravo, Guillermo , Fathima, Saubia , Gregorio, Caterina , Palomo, Laura , Itzykson, Raphaël , Sallman, David A. , Kern, Wolfgang , Garcia‐Manero, Guillermo , Platzbecker, Uwe , Solé, Françesc , Díez‐Campelo, María , Thol, Felicitas , Kröger, Nicolaus , Savona, Michael R. , Fenaux, Pierre , Sanz, Guillermo , Santini, Valeria , Fontenay, Michaëla , Komrokji, Rami S. , Haferlach, Torsten , Germing, Ulrich , Solary, Éric , Tefferi, Ayalew , Haque, Tamanna , Bataller, Alex , Sauta, Elisabetta , Sanavia, Tiziana , Dall'Olio, Lorenzo, Díaz‐Beyá, Marina , Roldan, Veronica, Fiallo, Dolly Viviana , Such, Esperanza , Castilla‐Llorente, Cristina , Bulabois, Claude‐Eric , Awada, Hussein , Chiusolo, Patrizia , Curti, Antonio , Giaccone, Luisa , Finelli, Carlo , Casetti, Ilaria Carola , Onida, Francesco , Passamonti, Francesco , Vučinić, Vladan , Voso, Maria Teresa , Hou, Hsin-An, Chou, Wen‐Chien , Yao, Chi‐Yuan , Lin, Chien‐Chin , Tien, Hwei‐Fang , Campagna, Alessia , Ubezio, Marta , Todisco, Gabriele , Maggioni, Giulia , Matteo, Maria Di, Pesce, Francesco , Zampini, Matteo , Crisafulli, Laura , Ventura, Denise , Pinocchio, Nicole , Brindisi, Matteo , VanOudenhove, Jennifer , Ali, Najla H. Al, Graubert, Timothy Aaron , Thota, Swapna , Griffiths, Elizabeth A.

Journal of Clinical Oncology | March 27, 2026 | Volume: 44 | Issue: 17 | Pages: 1608-1623

10.1200/jco-25-02116 | PMID 41894646 Get It

PURPOSE Chronic myelomonocytic leukemia (CMML) is a rare myeloid neoplasm characterized by clinical heterogeneity and is associated with poor outcomes. To date, limited molecular information has been incorporated into disease classification and risk stratification. We aimed to integrate genomic features into the clinical decision-making process for CMML. PATIENTS AND METHODS We analyzed a retrospective cohort of 3013 patients with CMML (training set) and a prospective population of 516 patients (validation set). Using an innovative framework for multimodal data analysis, we developed molecular-based disease taxonomy and prognostication. RESULTS Unsupervised clustering identified nine entities with distinct genomic features and outcomes ( P < .001), including splicing machinery, transcription factors, signal transduction and tyrosine kinase pathways aberrations, and high-risk molecular signatures. Notably, 15% of patients showed molecular/clinical overlap with other myeloid neoplasms. We integrated molecular and clinical information to build the international CMML Prognostic Scoring System (iCPSS), incorporating mutations in nine genes together with hematologic parameters and cytogenetic abnormalities. The iCPSS identified five groups with distinct probability of overall and leukemia-free survival in both training and validation cohorts ( P < .001), outperforming existing prognostic models. Importantly, 55% of patients were reassigned to higher or lower risk groups by the iCPSS. Decision analysis demonstrated that iCPSS could refine the optimal timing of allogeneic transplantation at the individual level; compared with conventional prognostic tools, iCPSS-based decision modeling changed transplantation strategy in 31% of cases, resulting in a significant gain-in-life expectancy for eligible patient population ( P < .001). A federated learning platform was implemented to enable continuous, privacy-preserving model update across multiple centers. CONCLUSION Molecular information improves CMML classification and prognostication, supports more effective clinical decision making, and potentially refines the design of clinical trials.
Contemporary Adjuvant Chemotherapy for Intraductal Papillary Mucinous Neoplasms
Haugk, Beate , White, Steven, Marchegiani, Giovanni, Holmberg, Marcus, Zerbi, Alessandro, Lu, Zipeng , Inoue, Y., Choi, Munseok , Kang, Chang Moo, Visser, B., Corpelijn, Lieke, Andersson, Bodil, Bereza-Carlson, Paulina, Björnsson, Bergthor, Wennerblom, Johanna, Goh, Brian K. P., Hartman, V., Ahmad, Syed, Patel, Sameer, Berrevoet, Frederik, Mortensen, Kim Erlend, Roberts, K., Lynch, Calum, Gupta, Amit, Kleeff, Joerg, Addeo, Pietro, Friess, Helmut, Koea, Jonathan, Gomez, Dhanny , Gordon-Weeks, Alex, Doria, Cataldo, Tzimas, Georgios, Franklin, O., Månsson, C., Cabús, Santiago Sánchez, Bhogal, Ricky H. , Pathak, Samir, Honselmann, Kim Christin, Balakrishnan, Anita, Mann, Kulbir , Gill, Anthony J., Mittal, A, Samra, Jas, Athwal, Tejinderjit, Loveday, Benjamin, Bhardwaj, Neil, Menon, Krishna, Thapa, Prabin, Matsumoto, Ippei, Jamieson, Nigel, Rebours, Vinciane, Descourvières, Clémence, Davidson, BR, Soreide, Kjetil, Pandanaboyana, Sanjay, Collaborative, Adeno-IPMN2, Kumar, Ajit, González, Carol Natalia Clavijo, Lam, Shi, L’Official-German, Ivan, Bergner, Tina, Rosso, Edoardo , Giulianotti, Pier Cristoforo , Morreau, Mathew , Dili, Alexandra, Sotiropoulou, Maria , Kuzman, Matta , Büyükkasap, Ahmet Çağrı, Uludağ, Gökhan, McGuigan, Mari-Claire , Chouari, Tarak , Dogul, Ahmet, Doğu, Doğukan , Rebelo, Artur, Holewik, Franziska Bernadette, Plesa-Furda, Roxana, Revoredo, Fernando, Galanis, Ilias , Maharjan, Dhiresh, Ghorbani, Poya , Lind, Max, Ami, Katsuya , Vijayashanker, Aarathi , Alsaoudi, Tareq , Lundgren, Linda , Ellisa, Katrina, Hong, Paul , Gupta, Archit, MartinXu, Congde, Konstantoudakis, Georgios, Christophides, Thalis, Spurring, Eleanor Margaret, Iwao, Yasuhito, Pirklc, Martin, Vaitha, Ruhi , Tiwari, Navneet, Sheel, Andrea, Kotecha, Krishna , Stavrou, Gregor A., Patel, Rikhilroy, Misca, Mihaela , Hammond, John, Roalso, Marcus Thomas Thor, Soomro, Faiza H, Halimi, Asif , Kendall, Timothy, Patel, Visad, Stankic, Dunja, Dries, Pieter , Hein, Charlotte, Betram, Julia, Jacob, Rosetta, Wilson, Gregory, Redas, Souheil, Poškus, Augustas, Mosert, Paula Lucia, Šilinskaitė, Ugnė , Hirose, Yuki, Liu, Xue, Standaert, Lars, Kay, Tegan J, Nishida, Kenji, Peddakota, Vivek , Gupta, Amit , Kang, Chang Moo , Ven Fong, Zhi, Kang, Chang Moo , Lucocq, James E. , Marchegiani, Giovanni , Zerbi, Alessandro , Pagnanelli, Michele , Visser, B. , Andersson, Bodil , Bereza‐Carlson, Paulina , Björnsson, Bergþór , Wennerblom, Johanna Hansson , Labori, Knut Jørgen , Goh, Brian K P , Hartman, Vera , Berrevoet, Frederik Christiaan , Ausania, Fabio , Bertrand, Claude , Kleeff, Joerg, Addeo, Pietro , Bellotti, Ruben , Fong, Zhi Ven , Friess, Helmut , Koea, Jonathan , Gordon-Weeks, Alex Nicolas , Doria, Cataldo , Franklin, Oskar , Pathak, Samir , Honselmann, Kim C. , Balakrishnan, Anita , Harrison, Ewen M. , Gill, A J, Mittal, Anubhav, Samra, Jas , Athwal, Tejinderjit , Loveday, Benjamin P. T. , Teh, Catherine , Bhardwaj, Neil , Menon, Krishna, Matsumoto, Ippei , Jamieson, Nigel , Rebours, Vinciane , Søreide, Kjetil , Martlı, Hüseyin Fahri , Roeyen, Geert , Antonakis, Pantelis T. , Bramis, Konstantinos , Hall, Lewis A , Valle, Valentina , Connor, Saxon J. , Kapiris, Stylianos A. , Kerem, Mustafa , Rebelo, Artur , Plesa-Furda, R., Filho, Omero Pereira da Costa , Galanis, Ilias, Konstantoudakis, Georgios, Christophides, Thalis, McGuinness, Matthew James , Yaqub, Sheraz , Pellegrini, Riccardo , Perri, Giampaolo , Sheel, Andrea , Sheen, Amy , Evans, Daisy, Ghamarnejad, Omid , Karavias, Dimitrios D. , Roalsø, Marcus T. T. , Stankic, Dunja , Grubor, Nikica , Gulla, Aistė , Furukawa, Takaaki , Hirose, Yuki , Yin, Lingdi

JAMA Network Open | March 27, 2026 | Volume: 9 | Issue: 3 | Pages: e263688

10.1001/jamanetworkopen.2026.3688 | PMID 41893840 Get It

Importance Adjuvant chemotherapy regimens may be administered after pancreatic resection for adenocarcinoma arising from intraductal papillary mucinous neoplasms (A-IPMNs), although the evidence supporting their use is limited. Objective To evaluate the survival benefit associated with contemporary adjuvant chemotherapy regimens after resection in A-IPMNs between 2017 and 2023. Design, Setting, and Participants This retrospective cohort study was an international, multicenter study with 69 participating centers across Europe, North America, South America, and the Asia-Pacific region. Patients undergoing resection for A-IPMNs were included. Data were analyzed from May to August 2025. Intervention Contemporary adjuvant chemotherapy regimens, such as gemcitabine-capecitabine (GemCap); 5-fluorouracil, leucovorin, oxaliplatin, and irinotecan (FOLFIRINOX), modified FOLFIRINOX (mFOLFIRINOX), and S-1. Main Outcome and Measure Overall survival (months). Results Among 1321 patients (median [IQR] age 70 [63 to 76] years; 713 males [54.0%] and 608 females [46.0%]), 781 patients (59.1%) received adjuvant chemotherapy, while in 181 patients (13.7%) it was omitted due to poor patient fitness. Of patients who received adjuvant chemotherapy, 568 patients (72.6%) received contemporary regimens, including GemCap (232 patients [29.7%]), FOLFIRINOX (176 patients [22.5%]), mFOLFIRINOX (71 patients [9.1%]), and S-1 (70 patients [9.0%]). The median (IQR) follow-up for the cohort was 64.2 (40.4 to 85.0) months, and the median overall survival was 73.8 months (95% CI, 66.4 to 81.9 months). After 90-day landmark analysis and exclusion of patients ineligible for chemotherapy, adjuvant chemotherapy vs no adjuvant chemotherapy (propensity score–matched populations, 243:243 patients) was not associated with improved overall survival (median, 82.3 months; 95% CI, 78.2 months to not applicable [NA] vs not reached; 95% CI, 75.3 months to NA; P = .58). Contemporary regimens vs no adjuvant chemotherapy (propensity score–matched populations, 309:309 patients) was not associated with longer survival, and a mean survival benefit greater than 4.2 months over 5 years was excluded (difference in restricted mean survival, 1.26 months; 95%, −1.72 to 4.24 months). Treatment outcomes did not vary by chemotherapy regimen or disease characteristic (eg, N stage or carbohydrate antigen 19-9 level). Conclusions and Relevance In this study, contemporary adjuvant chemotherapy was not associated with improved overall survival in A-IPMNs, and a randomized clinical trial is indicated.