Early diagnosis of pancreatic cancer: current diagnostic methods and the role of primary care physicians in improving outcomes - a narrative review
DOI:
https://doi.org/10.12775/JEHS.2026.95.73648Keywords
Pancreatic cancer, early diagnosis, screening, biomarkers, imaging, liquid biopsy, artificial intelligence, primary care, early detectionAbstract
Pancreatic cancer is one of the most aggressive malignancies and a leading cause of cancer-related mortality worldwide. Prognosis remains poor due to late diagnosis, as early-stage disease is usually asymptomatic or presents with non-specific symptoms, and the lack of effective screening results in most patients being diagnosed at an advanced stage. This review evaluates challenges in pancreatic cancer diagnosis, summarizes available diagnostic methods, and highlights the role of primary care physicians in early detection. Evidence published between 2015 and 2026 was analyzed. A structured literature search was conducted using PubMed and Google Scholar. Search terms included "pancreatic cancer", "early diagnosis", "screening", "biomarkers", "imaging", "liquid biopsy", "circulating tumor DNA", and "artificial intelligence". Original studies, reviews, and clinical guidelines were included. CT remains the primary imaging modality, though sensitivity decreases for small lesions. Endoscopic ultrasound improves detection and enables tissue sampling. CA 19-9 has limited early diagnostic value. Liquid biopsy methods show promise but remain under validation. Radiomics and AI may enhance detection of subtle imaging features. Primary care physicians are essential for recognizing suspicious symptoms and ensuring timely referral. Early diagnosis remains challenging due to non-specific symptoms, limited screening, and diagnostic shortcomings. A multimodal approach combining imaging, biomarkers, and emerging technologies is needed. Greater awareness among primary care physicians and continued development of liquid biopsy and AI tools may improve outcomes.
References
1. Siegel RL, Giaquinto AN, Jemal A.: Cancer statistics, 2024. CA: A Cancer Journal for Clinician. 2024;74(1):17–48. https://doi.org/10.3322/caac.21820
2. McGuigan A, Kelly P, Turkington RC, Jones C, Coleman HG, McCain RS.: Pancreatic cancer: A review of clinical diagnosis, epidemiology, treatment and outcomes. World Journal of Gastroenterology. 2018;24(43):4846–4861. https://doi.org/10.3748/wjg.v24.i43.4846
3. Rawla P, Sunkara T, Gaduputi V.: Epidemiology of pancreatic cancer: Global trends, etiology and risk factors. World Journal of Oncology. 2019;10(1):10–27. https://doi.org/10.14740/wjon1166
4. Ilic M, Ilic I.: Epidemiology of pancreatic cancer. World Journal of Gastroenterology. 2016;22(44):9694–9705. http://doi.org/10.3748/wjg.v22.i44.9694
5. Ballehaninna U, Chamberlain R.: Serum CA 19-9 as a biomarker for pancreatic cancer - A comprehensive review. Indian Journal of Surgical Oncology. 2011;2(2):88–100.https://doi.org/10.1007/s13193-011-0042-1
6. Haab BB, Huang Y, Balasenthil S, Partyka K, Tang H, Anderson M, et al.: Definitive Characterization of CA 19-9 in Resectable Pancreatic Cancer Using a Reference Set of Serum and Plasma Specimens. PLoS One. 2015;10(10):e0139049. https://doi.org/10.1371/journal.pone.0139049
7. Wang K, Wang X, Pan Q, Zhao B.: Liquid biopsy techniques and pancreatic cancer: diagnosis, monitoring, and evaluation. Molecular Cancer. 2023;22:167. https://doi.org/10.1186/s12943-023-01870-3
8. Chen W, Zhou Y, Asadpour V, Parker R, Puttock E, Lustigova E, Wu B.: Quantitative radiomic features from computed tomography can predict pancreatic cancer up to 36 months before diagnosis. Clinical and Translational Gastroenterology. 2023;14(1):e00548. https://doi.org/10.14309/ctg.0000000000000548
9. Ferlay J, Ervik M, Lam F, Colombet M, Mery L, Piñeros M, et al.: Global Cancer Observatory: Cancer Today. International Agency for Research on Cancer (IARC). Available from: https://gco.iarc.who.int/today (accessed 10 May 2026).
10. Partyka O, Pajewska M, Kwaśniewska D, Czerw AI, Deptała A, Budzik M, et al.: Overview of pancreatic cancer epidemiology in Europe and recommendations for screening in high-risk populations. Cancers. 2023;15(14):3634. https://doi.org/10.3390/cancers15143634
11. Surveillance, Epidemiology, and End Results (SEER) Program. Pancreatic Cancer-Cancer Stat Facts. National Cancer Institute. Available from: https://seer.cancer.gov/statfacts/html/pancreas.html (accessed 12 May 2026).
12. Chu LC, Fishman EK.: Pancreatic ductal adenocarcinoma staging: a narrative review of radiologic techniques and advances. International Journal of Surgery. 2024;110(10):6052–6063. http://doi.org/10.1097/JS9.0000000000000899
13. Hussain A, Weimer D, Mani N.: Diagnosing pancreatic adenocarcinoma with contrast-enhanced ultrasonography: a literature review of research in Europe and Asia. Cureus. 2022;14(2):e22592. http://doi.org/10.7759/cureus.22080
14. Chen PT, Wu T, Wang P, et al..: Pancreatic cancer detection on CT scans with deep learning: a nationwide population-based study. Radiology. 2023;306(1):172–182. https://doi.org/10.1148/radiol.220152
15. Quingalahua E, Al-Hawary MM, Machicado JD.: The role of magnetic resonance imaging (MRI) in the diagnosis of pancreatic cystic lesions (PCLs). Diagnostics. 2023;13(4):585; https://doi.org/10.3390/diagnostics13040585
16. Yoshida T, Yamashita Y, Kitano M.: Endoscopic ultrasound for early diagnosis of pancreatic cancer. Diagnostics. 2019;9(3):81. https://doi.org/10.3390/diagnostics9030081
17. Ghidini M, Vuozzo M, Galassi B, Mapelli P, Ceccarossi V, Caccamo L, Picchio M, Dondossola D.: The role of positron emission tomography/CT for staging and disease response assessment in localized and locally advanced pancreatic cancer. Cancers. 2021;13(16):4155. https://doi.org/10.3390/cancers13164155
18. Huang S, Chong H, Sun X, Wu Z, Jia Q, Zhang Y, Lan X.: The value of 18F-FDG PET/CT in diagnosing pancreatic lesions: comparison with CA19-9, enhanced CT or enhanced MR. Frontiers in Medicine. 2021;8:668697. http://doi.org/10.3389/fmed.2021.668697
19. Ashida R, Tanaka S, Yamanaka H, et al.: The role of transabdominal ultrasound in the diagnosis of early stage pancreatic cancer: review and single-center experience. Diagnostics. 2019;9(1):2. http://doi.org/10.3390/diagnostics9010002
20. Hasan S, Jacob R, Manne U, Paluri R.: Advances in pancreatic cancer biomarkers. Oncology Reviews. 2019;13(1):410. http://doi.org/10.4081/oncol.2019.410
21. Azizian A, Rühlmann F, Krause T, Bernhardt M, Jo P, Ghadimi M, Gaedcke J.: CA19-9 for detecting recurrence of pancreatic cancer. Scientific Reports. 2020;10:1332. http://doi.org/10.1038/s41598-020-57930-x
22. Balaban DV, Marin FS, Manucu G, Zoican A, Ciochina M, Mina V, Patoni C, Vladut C, Bucurica S, Costache RS, Ionita-Radu F, Jinga M.: Clinical characteristics and outcomes in carbohydrate antigen 19-9 negative pancreatic cancer. World Journal of Clinical Oncology. 2022;13(7):630–640. http://doi.org/10.5306/wjco.v13.i7.630
23. Ramírez-Maldonado E, López Gordo S, Major Branco RP, Pavel MC, Estalella L, Llàcer-Millán E, Guerrero MA, López-Gordo E, Memba R, Jorba R.: Clinical application of liquid biopsy in pancreatic cancer: a narrative review. International Journal of Molecular Sciences. 2024;25(3):1640. http://doi.org/10.3390/ijms25031640
24. Macgregor-Das A, Yu J, Tamura K, Abe T, Suenaga M, Shindo K, Borges M, Koi C, Kohi S, Sadakari Y, Dal Molin M, Almario JA, Ford M, Chuidian M, Burkhart R, He J, Hruban RH, Eshleman JR, Klein AP, Wolfgang CL, Canto MI, Goggins M.: Detection of circulating tumor DNA in patients with pancreatic cancer using digital next-generation sequencing. Journal of Molecular Diagnostics. 2020;22(6):748–756. http://doi.org/10.1016/j.jmoldx.2020.02.010
25. Groot VP, Mosier S, Javed AA, Teinor JA, Gemenetzis G, Ding D, Haley LM, Yu J, Burkhart RA, Hasanain A, Debeljak M, Kamiyama H, Narang A, Laheru DA, Zheng L, Lin MT, Gocke CD, Fishman EK, Hruban RH, Goggins MG, Molenaar IQ, Cameron JL, Weiss MJ, Velculescu VE, He J, Wolfgang CL, Eshleman JR.: Circulating tumor DNA as a clinical test in resected pancreatic cancer. Clinical Cancer Research. 2019;25(16):4973–4984. http://doi.org/10.1158/1078-0432.CCR-19-0197
26. Yeo D, Bastian A, Strauss H, Saxena P, Grimison P, Rasko JEJ.: Exploring the clinical utility of pancreatic cancer circulating tumor cells. International Journal of Molecular Sciences. 2022;23(3):1671. http://doi.org/10.3390/ijms23031671
27. Herreros-Villanueva M, Bujanda L.: Glypican-1 in exosomes as biomarker for early detection of pancreatic cancer. Annals of Translational Medicine. 2016;4(4):64. http://doi.org/10.3978/j.issn.2305-5839.2015.10.39
28. Cao Z, Liu C, Xu J, You L, Wang C, Lou W, Sun B, Miao Y, Liu X, Wang X, Zhang T, Zhao Y.: Plasma microRNA panels to diagnose pancreatic cancer: results from a multicenter study. Oncotarget. 2016;7(26):41575–41583. http://doi.org/10.18632/oncotarget.9491
29. Buscail E, Maulat C, Muscari F, Chiche L, Cordelier P, Dabernat S, Alix-Panabières C, Buscail L.: Liquid biopsy approach for pancreatic ductal adenocarcinoma. Cancers. 2019;11(6):852. http://doi.org/10.3390/cancers11060852
30. Kumar V, Gaddam M, Moustafa A, Iqbal R, Gala D, Shah M, Gayam VR, Bandaru P, Reddy M, Gadaputi V.: The utility of artificial intelligence in the diagnosis and management of pancreatic cancer. Cureus. 2023;15(11):e49560. http://doi.org/10.7759/cureus.49560
31. Shahul Hameed B, Krishnan UM.: Artificial intelligence-driven diagnosis of pancreatic cancer. Cancers. 2022;14(21):5382. http://doi.org/10.3390/cancers14215382
32. Placido D, Yuan B, Hjaltelin JX, Bhatt DL, Preisler L, Bjørnsson ES, Johansen JS, Tjønnfjord GE, Agerschou ED, Reinholt FP, Kvale D, Fagerberg T, Lund-Andersen H, Christoffersen T, Larsen SJ, Brunak S.: A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories. Nature Medicine. 2023;29(5):1113–1122. http://doi.org/10.1038/s41591-023-02332-5
33. Lyratzopoulos G, Vedsted P, Singh H.: Understanding missed opportunities for more timely diagnosis of cancer in symptomatic patients after presentation. British Journal of Cancer. 2015;112:S84–S91. https://doi.org/10.1038/bjc.2015.47
34. Stapley S, Peters TJ, Neal RD, Hamilton W.: The risk of pancreatic cancer in symptomatic patients in primary care: a large case-control study using electronic records. British Journal of Cancer. 2012;106(12):1940–1944. https://doi.org/10.1038/bjc.2012.190
35. Sharma A, Smyrk TC, Levy MJ, Topazian MA, Chari ST.: Fasting blood glucose levels provide estimate of duration and progression of pancreatic cancer before diagnosis. Gastroenterology. 2018;155(2):490–500.e2. https://doi.org/10.1053/j.gastro.2018.04.025
36. Chari ST, Leibson CL, Rabe KG, et al.: Pancreatic cancer–associated diabetes mellitus: prevalence and temporal association with diagnosis of cancer. Gastroenterology. 2008;134(1):95–101. https://doi.org/10.1053/j.gastro.2007.10.040
37. Claridge H, Cooke EA, Thomas SA, Greenwood N, Lemanska A.: Pancreatic cancer risk assessment tools in primary care: a mixed methods systematic review. Journal of Gastrointestinal Cancer. 2025;56(1):128. http://doi.org/10.1007/s12029-025-01229-5
38. Hippisley-Cox J, Coupland C.: Identifying patients with suspected pancreatic cancer in primary care: derivation and validation of an algorithm. British Journal of General Practice. 2012;62(594):e38–e45. https://doi.org/10.3399/bjgp12X616355
39. Pereira SP, Oldfield L, Ney A, Hart PA, Keane MG, Pandol SJ, Li D, Greenhalf W, Jeon CY, Koay EJ, Almario CV, Halloran C, Lennon AM, Costello E.: Early detection of pancreatic cancer. Lancet Gastroenterology and Hepatology. 2020;5(7):698–710. http://doi.org/10.1016/S2468-1253(19)30416-9
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Maria Sicińska, Małgorzata Katra, Mikołaj Szczęsny, Adrian Pal, Krzysztof Cienkowski, Patryk Cegiełka, Marcin Ślot, Weronika Kotnis, Izabella Głowacka, Aleksandra Adamczyk
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The periodical offers access to content in the Open Access system under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0
Stats
Number of views and downloads: 50
Number of citations: 0
