The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Metabolic biomarker signature to differentiate pancreatic ductal adenocarcinoma from chronic pancreatitis
Open accessAbstract
Objective: Current non-invasive diagnostic tests can distinguish between pancreatic cancer (pancreatic ductal adenocarcinoma (PDAC)) and chronic pancreatitis (CP) in only about two thirds of patients. We have searched for blood-derived metabolite biomarkers for this diagnostic purpose. Design: For a case–control study in three tertiary referral centres, 914 subjects were prospectively recruited with PDAC (n=271), CP (n=282), liver cirrhosis (n=100) or healthy as well as non-pancreatic disease controls (n=261) in three consecutive studies. Metabolomic profiles of plasma and serum samples were generated from 477 metabolites identified by gas chromatography–mass spectrometry and liquid chromatography–tandem mass spectrometry. Results: A biomarker signature (nine metabolites and additionally CA19-9) was identified for the differential diagnosis between PDAC and CP. The biomarker signature distinguished PDAC from CP in the training set with an area under the curve (AUC) of 0.96 (95% CI 0.93–0.98). The biomarker signature cut-off of 0.384 at 85% fixed specificity showed a sensitivity of 94.9% (95% CI 87.0%–97.0%). In the test set, an AUC of 0.94 (95% CI 0.91–0.97) and, using the same cut-off, a sensitivity of 89.9% (95% CI 81.0%–95.5%) and a specificity of 91.3% (95% CI 82.8%–96.4%) were achieved, successfully validating the biomarker signature. Conclusions: In patients with CP with an increased risk for pancreatic cancer (cumulative incidence 1.95%), the performance of this biomarker signature results in a negative predictive value of 99.9% (95% CI 99.7%–99.9%) (training set) and 99.8% (95% CI 99.6%–99.9%) (test set). In one third of our patients, the clinical use of this biomarker signature would have improved diagnosis and treatment stratification in comparison to CA19-9.
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Phases of Biomarker Development for Early Detection of Cancer
Pepe, M. S., Etzioni, R., Feng, Z., Potter, J. D., Thompson, M. L., Thornquist, M., Winget, M., & Yasui, Y. (2001) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/93.14.1054 · Cited by 1,686
Canto, M. I., Harinck, F., Hruban, R. H., Offerhaus, G. J., Poley, J.-W., Kamel, I., Nio, Y., Schulick, R. S., Bassi, C., Kluijt, I., et al. (2013) · Gut · doi:10.1136/gutjnl-2012-303108 · Cited by 784
Biomarkers for early diagnosis of pancreatic cancer
Jenkinson, C., Earl, J., Ghaneh, P., Halloran, C., Carrato, A., Greenhalf, W., Neoptolemos, J., & Costello, E. (2015) · Expert Review of Gastroenterology & Hepatology · doi:10.1586/17474124.2015.965145 · Cited by 42
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Applications of multi‐omics analysis in human diseases
Chen, C., Wang, J., Pan, D., Wang, X., Xu, Y., Yan, J., Wang, L., Yang, X., Yang, M., & Liu, G. (2023) · MedComm · doi:10.1002/mco2.315 · Cited by 545
Early screening and diagnosis strategies of pancreatic cancer: a comprehensive review
Yang, J., Xu, R., Wang, C., Qiu, J., Ren, B., & You, L. (2021) · Cancer Communications · doi:10.1002/cac2.12204 · Cited by 379
A Plasma-Derived Protein-Metabolite Multiplexed Panel for Early-Stage Pancreatic Cancer
Fahrmann, J. F., Bantis, L. E., Capello, M., Scelo, G., Dennison, J. B., Patel, N., Murage, E., Vykoukal, J., Kundnani, D. L., Foretova, L., et al. (2019) · JNCI: Journal of the National Cancer Institute · doi:10.1093/jnci/djy126 · Cited by 115
Recent advances in microfluidic methods in cancer liquid biopsy
Iliescu, F. S., Poenar, D. P., Yu, F., Ni, M., Chan, K. H., Cima, I., Taylor, H. K., Cima, I., & Iliescu, C. (2019) · Biomicrofluidics · doi:10.1063/1.5087690 · Cited by 51
Combined use of CEMIP and CA 19-9 enhances diagnostic accuracy for pancreatic cancer
Lee, H. S., Jang, C. Y., Kim, S. A., Park, S. B., Jung, D. E., Kim, B. O., Kim, H. Y., Chung, M. J., Park, J. Y., Bang, S., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-21823-x · Cited by 44
Metadata
- Authors
- Mayerle, J., Kalthoff, H., Reszka, R., Kamlage, B., Peter, E., Schniewind, B., González Maldonado, S., Pilarsky, C., Heidecke, C.-D., Schatz, P., Distler, M., Scheiber, J. A., Mahajan, U. M., Weiss, F. U., Grützmann, R., & Lerch, M. M.
- Venue
- Gut
- Publisher
- BMJ
- Published
- 2017-01-20
- Volume
- 67
- Issue
- 1
- Pages
- 128-137
- ISSN
- 0017-5749 (ISSN-L)
- 1468-3288
- OpenAlex
- W2575543752
- Cited by
- 307
- References
- 3
- FWCI
- 9.91
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Mayerle, J., Kalthoff, H., Reszka, R., Kamlage, B., Peter, E., Schniewind, B., González Maldonado, S., Pilarsky, C., Heidecke, C.-D., Schatz, P., Distler, M., Scheiber, J. A., Mahajan, U. M., Weiss, F. U., Grützmann, R., & Lerch, M. M. (2018). Metabolic biomarker signature to differentiate pancreatic ductal adenocarcinoma from chronic pancreatitis. Gut. https://doi.org/10.1136/gutjnl-2016-312432
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