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Mistakes in biomarkers for IBD and how to avoid them

James C. Lee, Chris Palmer-Jones

Summary

AI Generated

An article reviews common mistakes in biomarker development, interpretation, and application for inflammatory bowel disease, addressing the challenge of disease heterogeneity that drives trial-and-error treatment approaches.

  • IBD complexity arises from heterogeneity in Crohn's disease and ulcerative colitis, leading to differences in disease course, complications, and treatment responses among patients.
  • Current IBD treatment strategies rely on a trial-and-error approach, creating a need for personalized therapy.
  • Efforts have been made to develop reliable prognostic and predictive biomarkers to overcome disease heterogeneity.
  • The article discusses common mistakes in biomarker work and draws on evidence-based insights and lessons from other fields.
  • Clinicians and researchers focused on IBD biomarker development or personalized treatment strategies would benefit from this material.
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Thanks for your feedback.

This summary was generated by an AI large language model based on the content transcript. It is for informational purposes only and should not be considered a substitute for clinical judgment. Always rely on your professional expertise and the full clinical context when making clinical decisions.

References

Mistakes
References
Mistake 1 Mistake 2 Mistake 3 Mistake 4 Mistake 5 Mistake 6 Mistake 7 Mistake 8
1.
Verstockt, B., Parkes, M. & Lee, J. C. How Do We Predict a Patient's Disease Course and Whether They Will Respond to Specific Treatments? Gastroenterology 162, 1383-1395, doi:10.1053/j.gastro.2021.12.245 (2022). [Link]
2.
Jess, T. et al. Changes in clinical characteristics, course, and prognosis of inflammatory bowel disease during the last 5 decades: a population-based study from Copenhagen, Denmark. Inflamm Bowel Dis 13, 481-489, doi:10.1002/ibd.20036 (2007). [Link]
3.
Solberg, I. C. et al. Clinical course in Crohn's disease: results of a Norwegian population-based ten-year follow-up study. Clin Gastroenterol Hepatol 5, 1430-1438, doi:S1542-3565(07)00888-9 [pii]10.1016/j.cgh.2007.09.002 (2007). [Link]
4.
Alsoud, D., Verstockt, B., Fiocchi, C. & Vermeire, S. Breaking the therapeutic ceiling in drug development in ulcerative colitis. Lancet Gastroenterol Hepatol 6, 589-595, doi:10.1016/S2468-1253(21)00065-0 (2021). [Link]
5.
Colombel, J. F., D'Haens, G., Lee, W. J., Petersson, J. & Panaccione, R. Outcomes and Strategies to Support a Treat-to-target Approach in Inflammatory Bowel Disease: A Systematic Review. J Crohns Colitis 14, 254-266, doi:10.1093/ecco-jcc/jjz131 (2020). [Link]
6.
Sparano, J. A. et al. Adjuvant Chemotherapy Guided by a 21-Gene Expression Assay in Breast Cancer. N Engl J Med 379, 111-121, doi:10.1056/NEJMoa1804710 (2018). [Link]
7.
Cardoso, F. et al. 70-Gene Signature as an Aid to Treatment Decisions in Early-Stage Breast Cancer. N Engl J Med 375, 717-729, doi:10.1056/NEJMoa1602253 (2016). [Link]
8.
Hart, A. L. et al. What Are the Top 10 Research Questions in the Treatment of Inflammatory Bowel Disease? A Priority Setting Partnership with the James Lind Alliance. J Crohns Colitis 11, 204-211, doi:10.1093/ecco-jcc/jjw144 (2017). [Link]
9.
Noor, N. M., Verstockt, B., Parkes, M. & Lee, J. C. Personalised medicine in Crohn's disease. Lancet Gastroenterol Hepatol 5, 80-92, doi:10.1016/S2468-1253(19)30340-1 (2020). [Link]
10.
Wolters, F. L. et al. Phenotype at diagnosis predicts recurrence rates in Crohn's disease. Gut 55, 1124-1130, doi:10.1136/gut.2005.084061 (2006). [Link]
11.
Beaugerie, L., Seksik, P., Nion-Larmurier, I., Gendre, J. P. & Cosnes, J. Predictors of Crohn's disease. Gastroenterology 130, 650-656, doi:S0016-5085(05)02529-1 [pii]10.1053/j.gastro.2005.12.019 (2006). [Link]
12.
Loly, C., Belaiche, J. & Louis, E. Predictors of severe Crohn's disease. Scand J Gastroenterol 43, 948-954 (2008). [Link]
13.
Torres, J. et al. Predicting Outcomes to Optimize Disease Management in Inflammatory Bowel Diseases. J Crohns Colitis 10, 1385-1394, doi:10.1093/ecco-jcc/jjw116 (2016). [Link]
14.
Cosnes, J. et al. Factors affecting outcomes in Crohn's disease over 15 years. Gut 61, 1140-1145, doi:10.1136/gutjnl-2011-301971 (2012). [Link]
15.
Solberg, I. C. et al. Clinical course during the first 10 years of ulcerative colitis: results from a population-based inception cohort (IBSEN Study). Scand J Gastroenterol 44, 431-440, doi:907045459 [pii]10.1080/00365520802600961 (2009). [Link]
16.
Ananthakrishnan, A. N. et al. History of medical hospitalization predicts future need for colectomy in patients with ulcerative colitis. Inflamm Bowel Dis 15, 176-181, doi:10.1002/ibd.20639 (2009). [Link]
17.
Targownik, L. E., Singh, H., Nugent, Z. & Bernstein, C. N. The epidemiology of colectomy in ulcerative colitis: results from a population-based cohort. Am J Gastroenterol 107, 1228-1235, doi:10.1038/ajg.2012.127 (2012). [Link]
18.
Dulai, P. S. et al. Development and Validation of a Scoring System to Predict Outcomes of Vedolizumab Treatment in Patients With Crohn's Disease. Gastroenterology 155, 687-695 e610, doi:10.1053/j.gastro.2018.05.039 (2018). [Link]
19.
Molnar, T. et al. Predictors of relapse in patients with Crohn's disease in remission after 1 year of biological therapy. Aliment Pharmacol Ther 37, 225-233, doi:10.1111/apt.12160 (2013). [Link]
20.
Billiet, T. et al. A Matrix-based Model Predicts Primary Response to Infliximab in Crohn's Disease. J Crohns Colitis 9, 1120-1126, doi:jjv156 [pii]10.1093/ecco-jcc/jjv156 (2015). [Link]
21.
Gibson, G. Going to the negative: genomics for optimized medical prescription. Nat Rev Genet 20, 1-2, doi:10.1038/s41576-018-0061-7 (2019). [Link]
22.
Lee, J. C. et al. Genome-wide association study identifies distinct genetic contributions to prognosis and susceptibility in Crohn's disease. Nat Genet 49, 262-268, doi:10.1038/ng.3755 (2017). [Link]
23.
Biasci, D. et al. A blood-based prognostic biomarker in IBD. Gut 68, 1386-1395, doi:10.1136/gutjnl-2019-318343 (2019). [Link]
24.
Kugathasan, S. et al. Prediction of complicated disease course for children newly diagnosed with Crohn's disease: a multicentre inception cohort study. Lancet 389, 1710-1718, doi:10.1016/S0140-6736(17)30317-3 (2017). [Link]
25.
Taylor, A. E. et al. Investigating the possible causal association of smoking with depression and anxiety using Mendelian randomisation meta-analysis: the CARTA consortium. BMJ Open 4, e006141, doi:10.1136/bmjopen-2014-006141 (2014). [Link]
26.
Ferrante, M. et al. New serological markers in inflammatory bowel disease are associated with complicated disease behaviour. Gut 56, 1394-1403, doi:gut.2006.108043 [pii]10.1136/gut.2006.108043 (2007). [Link]
27.
Amre, D. K., Lu, S. E., Costea, F. & Seidman, E. G. Utility of serological markers in predicting the early occurrence of complications and surgery in pediatric Crohn's disease patients. Am J Gastroenterol 101, 645-652, doi:AJG468 [pii]10.1111/j.1572-0241.2006.00468.x (2006). [Link]
28.
Seow, C. H. et al. Novel anti-glycan antibodies related to inflammatory bowel disease diagnosis and phenotype. Am J Gastroenterol 104, 1426-1434, doi:ajg200979 [pii]10.1038/ajg.2009.79 (2009). [Link]
29.
Israeli, E. et al. Anti-Saccharomyces cerevisiae and antineutrophil cytoplasmic antibodies as predictors of inflammatory bowel disease. Gut 54, 1232-1236, doi:54/9/1232 [pii]10.1136/gut.2004.060228 (2005). [Link]
30.
Bodecker-Zingmark, L., Widbom, L., Hultdin, J., Eriksson, C. & Karling, P. Anti-Saccharomyces cerevisiae Antibodies Are Only Modestly More Common in Subjects Later Developing Crohn's Disease. Dig Dis Sci 68, 608-615, doi:10.1007/s10620-022-07630-5 (2023). [Link]
31.
Arnott, I. D. et al. Sero-reactivity to microbial components in Crohn's disease is associated with disease severity and progression, but not NOD2/CARD15 genotype. Am J Gastroenterol 99, 2376-2384, doi:10.1111/j.1572-0241.2004.40417.x (2004). [Link]
32.
Choung, R. S. et al. Serologic microbial associated markers can predict Crohn's disease behaviour years before disease diagnosis. Aliment Pharmacol Ther 43, 1300-1310, doi:10.1111/apt.13641 (2016). [Link]
33.
Subramanian, J. & Simon, R. Overfitting in prediction models - is it a problem only in high dimensions? Contemp Clin Trials 36, 636-641, doi:10.1016/j.cct.2013.06.011 (2013). [Link]
34.
Ransohoff, D. F. Rules of evidence for cancer molecular-marker discovery and validation. Nat Rev Cancer 4, 309-314, doi:10.1038/nrc1322 (2004). [Link]
35.
Kern, S. E. Why your new cancer biomarker may never work: recurrent patterns and remarkable diversity in biomarker failures. Cancer Res 72, 6097-6101, doi:10.1158/0008-5472.CAN-12-3232 (2012). [Link]
36.
Argmann, C. et al. Biopsy and blood-based molecular biomarker of inflammation in IBD. Gut, doi:10.1136/gutjnl-2021-326451 (2022). [Link]
37.
Duffy, M. J. et al. Validation of new cancer biomarkers: a position statement from the European group on tumor markers. Clin Chem 61, 809-820, doi:10.1373/clinchem.2015.239863 (2015). [Link]
38.
Lee, J. C., Lyons, P. A. & McKinney, E. F. Analytical Mistakes Confound Attempted Validation: A Response to 'Transcription and DNA Methylation Patterns of Blood-Derived CD8+ T Cells Are Associated With Age and Inflammatory Bowel Disease But Do Not Predict Prognosis'. Gastroenterology 160, 2210-2211, doi:10.1053/j.gastro.2021.01.021 (2021). https://pubmed.ncbi.nlm.nih.gov/33453231/ [Link]
39.
Fagerlin, A., Zikmund-Fisher, B. J. & Ubel, P. A. Helping patients decide: ten steps to better risk communication. J Natl Cancer Inst 103, 1436-1443, doi:10.1093/jnci/djr318 (2011). [Link]
40.
Paling, J. Strategies to help patients understand risks. BMJ 327, 745-748, doi:10.1136/bmj.327.7417.745 (2003). [Link]
41.
Kumar, M., Garand, M. & Al Khodor, S. Integrating omics for a better understanding of Inflammatory Bowel Disease: a step towards personalized medicine. J Transl Med 17, 419, doi:10.1186/s12967-019-02174-1 (2019). [Link]
42.
Fan, J., Han, F. & Liu, H. Challenges of Big Data Analysis. Natl Sci Rev 1, 293-314, doi:10.1093/nsr/nwt032 (2014). [Link]
43.
Lee, J. C. et al. Gene expression profiling of CD8+ T cells predicts prognosis in patients with Crohn disease and ulcerative colitis. J Clin Invest 121, 4170-4179 (2011). [Link]
44.
McKinney, E. F., Lee, J. C., Jayne, D. R., Lyons, P. A. & Smith, K. G. T-cell exhaustion, co-stimulation and clinical outcome in autoimmunity and infection. Nature 523, 612-616, doi:nature14468 [pii]10.1038/nature14468 (2015). [Link]
45.
Lemaitre, M. et al. Association Between Use of Thiopurines or Tumor Necrosis Factor Antagonists Alone or in Combination and Risk of Lymphoma in Patients With Inflammatory Bowel Disease. JAMA 318, 1679-1686, doi:10.1001/jama.2017.16071 (2017). [Link]
46.
Tottrup, A., Erichsen, R., Svaerke, C., Laurberg, S. & Srensen, H. T. Thirty-day mortality after elective and emergency total colectomy in Danish patients with inflammatory bowel disease: a population-based nationwide cohort study. BMJ Open 2, e000823, doi:10.1136/bmjopen-2012-000823 (2012). [Link]

Abstract

The complexity of managing inflammatory bowel disease (IBD) stems from the heterogeneity of Crohn’s disease and ulcerative colitis. This leads to differences in disease course, complications, and treatment responses among patients. Current treatment strategies rely on a trial-and-error approach, but there's a need for personalized therapy. Efforts have been made to develop reliable prognostic and predictive biomarkers to overcome disease heterogeneity. This article discusses common mistakes in biomarker development, interpretation, and application in IBD, emphasizing evidence-based insights and lessons learned from other fields.

Topics

IBD

Citation

: Palmer-Jones C. and Lee J. C. Mistakes in biomarkers for IBD and how to avoid them. UEG Education 2023; 23: 8-11.

Published

2023

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UEG Mistakes In Articles
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Mistakes in the management of peritoneal malignancies and how to avoid them

Francesco Saverio Papadia, Matteo Santoliquido, Andrea Barberis, Tarkan Jäger, Charlotte Rabl

Summary

AI Generated

Summary is not available for this content yet.

Download PDF

Was this helpful?

Thanks for your feedback.

This summary was generated by an AI large language model based on the content transcript. It is for informational purposes only and should not be considered a substitute for clinical judgment. Always rely on your professional expertise and the full clinical context when making clinical decisions.

References

Mistakes
References
Mistake 1 Mistake 2 Mistake 3 Mistake 4 Mistake 5 Mistake 6 Mistake 7 Mistake 8
1.
Verstockt, B., Parkes, M. & Lee, J. C. How Do We Predict a Patient's Disease Course and Whether They Will Respond to Specific Treatments? Gastroenterology 162, 1383-1395, doi:10.1053/j.gastro.2021.12.245 (2022). [Link]
2.
Jess, T. et al. Changes in clinical characteristics, course, and prognosis of inflammatory bowel disease during the last 5 decades: a population-based study from Copenhagen, Denmark. Inflamm Bowel Dis 13, 481-489, doi:10.1002/ibd.20036 (2007). [Link]
3.
Solberg, I. C. et al. Clinical course in Crohn's disease: results of a Norwegian population-based ten-year follow-up study. Clin Gastroenterol Hepatol 5, 1430-1438, doi:S1542-3565(07)00888-9 [pii]10.1016/j.cgh.2007.09.002 (2007). [Link]
4.
Alsoud, D., Verstockt, B., Fiocchi, C. & Vermeire, S. Breaking the therapeutic ceiling in drug development in ulcerative colitis. Lancet Gastroenterol Hepatol 6, 589-595, doi:10.1016/S2468-1253(21)00065-0 (2021). [Link]
5.
Colombel, J. F., D'Haens, G., Lee, W. J., Petersson, J. & Panaccione, R. Outcomes and Strategies to Support a Treat-to-target Approach in Inflammatory Bowel Disease: A Systematic Review. J Crohns Colitis 14, 254-266, doi:10.1093/ecco-jcc/jjz131 (2020). [Link]
6.
Sparano, J. A. et al. Adjuvant Chemotherapy Guided by a 21-Gene Expression Assay in Breast Cancer. N Engl J Med 379, 111-121, doi:10.1056/NEJMoa1804710 (2018). [Link]
7.
Cardoso, F. et al. 70-Gene Signature as an Aid to Treatment Decisions in Early-Stage Breast Cancer. N Engl J Med 375, 717-729, doi:10.1056/NEJMoa1602253 (2016). [Link]
8.
Hart, A. L. et al. What Are the Top 10 Research Questions in the Treatment of Inflammatory Bowel Disease? A Priority Setting Partnership with the James Lind Alliance. J Crohns Colitis 11, 204-211, doi:10.1093/ecco-jcc/jjw144 (2017). [Link]
9.
Noor, N. M., Verstockt, B., Parkes, M. & Lee, J. C. Personalised medicine in Crohn's disease. Lancet Gastroenterol Hepatol 5, 80-92, doi:10.1016/S2468-1253(19)30340-1 (2020). [Link]
10.
Wolters, F. L. et al. Phenotype at diagnosis predicts recurrence rates in Crohn's disease. Gut 55, 1124-1130, doi:10.1136/gut.2005.084061 (2006). [Link]
11.
Beaugerie, L., Seksik, P., Nion-Larmurier, I., Gendre, J. P. & Cosnes, J. Predictors of Crohn's disease. Gastroenterology 130, 650-656, doi:S0016-5085(05)02529-1 [pii]10.1053/j.gastro.2005.12.019 (2006). [Link]
12.
Loly, C., Belaiche, J. & Louis, E. Predictors of severe Crohn's disease. Scand J Gastroenterol 43, 948-954 (2008). [Link]
13.
Torres, J. et al. Predicting Outcomes to Optimize Disease Management in Inflammatory Bowel Diseases. J Crohns Colitis 10, 1385-1394, doi:10.1093/ecco-jcc/jjw116 (2016). [Link]
14.
Cosnes, J. et al. Factors affecting outcomes in Crohn's disease over 15 years. Gut 61, 1140-1145, doi:10.1136/gutjnl-2011-301971 (2012). [Link]
15.
Solberg, I. C. et al. Clinical course during the first 10 years of ulcerative colitis: results from a population-based inception cohort (IBSEN Study). Scand J Gastroenterol 44, 431-440, doi:907045459 [pii]10.1080/00365520802600961 (2009). [Link]
16.
Ananthakrishnan, A. N. et al. History of medical hospitalization predicts future need for colectomy in patients with ulcerative colitis. Inflamm Bowel Dis 15, 176-181, doi:10.1002/ibd.20639 (2009). [Link]
17.
Targownik, L. E., Singh, H., Nugent, Z. & Bernstein, C. N. The epidemiology of colectomy in ulcerative colitis: results from a population-based cohort. Am J Gastroenterol 107, 1228-1235, doi:10.1038/ajg.2012.127 (2012). [Link]
18.
Dulai, P. S. et al. Development and Validation of a Scoring System to Predict Outcomes of Vedolizumab Treatment in Patients With Crohn's Disease. Gastroenterology 155, 687-695 e610, doi:10.1053/j.gastro.2018.05.039 (2018). [Link]
19.
Molnar, T. et al. Predictors of relapse in patients with Crohn's disease in remission after 1 year of biological therapy. Aliment Pharmacol Ther 37, 225-233, doi:10.1111/apt.12160 (2013). [Link]
20.
Billiet, T. et al. A Matrix-based Model Predicts Primary Response to Infliximab in Crohn's Disease. J Crohns Colitis 9, 1120-1126, doi:jjv156 [pii]10.1093/ecco-jcc/jjv156 (2015). [Link]
21.
Gibson, G. Going to the negative: genomics for optimized medical prescription. Nat Rev Genet 20, 1-2, doi:10.1038/s41576-018-0061-7 (2019). [Link]
22.
Lee, J. C. et al. Genome-wide association study identifies distinct genetic contributions to prognosis and susceptibility in Crohn's disease. Nat Genet 49, 262-268, doi:10.1038/ng.3755 (2017). [Link]
23.
Biasci, D. et al. A blood-based prognostic biomarker in IBD. Gut 68, 1386-1395, doi:10.1136/gutjnl-2019-318343 (2019). [Link]
24.
Kugathasan, S. et al. Prediction of complicated disease course for children newly diagnosed with Crohn's disease: a multicentre inception cohort study. Lancet 389, 1710-1718, doi:10.1016/S0140-6736(17)30317-3 (2017). [Link]
25.
Taylor, A. E. et al. Investigating the possible causal association of smoking with depression and anxiety using Mendelian randomisation meta-analysis: the CARTA consortium. BMJ Open 4, e006141, doi:10.1136/bmjopen-2014-006141 (2014). [Link]
26.
Ferrante, M. et al. New serological markers in inflammatory bowel disease are associated with complicated disease behaviour. Gut 56, 1394-1403, doi:gut.2006.108043 [pii]10.1136/gut.2006.108043 (2007). [Link]
27.
Amre, D. K., Lu, S. E., Costea, F. & Seidman, E. G. Utility of serological markers in predicting the early occurrence of complications and surgery in pediatric Crohn's disease patients. Am J Gastroenterol 101, 645-652, doi:AJG468 [pii]10.1111/j.1572-0241.2006.00468.x (2006). [Link]
28.
Seow, C. H. et al. Novel anti-glycan antibodies related to inflammatory bowel disease diagnosis and phenotype. Am J Gastroenterol 104, 1426-1434, doi:ajg200979 [pii]10.1038/ajg.2009.79 (2009). [Link]
29.
Israeli, E. et al. Anti-Saccharomyces cerevisiae and antineutrophil cytoplasmic antibodies as predictors of inflammatory bowel disease. Gut 54, 1232-1236, doi:54/9/1232 [pii]10.1136/gut.2004.060228 (2005). [Link]
30.
Bodecker-Zingmark, L., Widbom, L., Hultdin, J., Eriksson, C. & Karling, P. Anti-Saccharomyces cerevisiae Antibodies Are Only Modestly More Common in Subjects Later Developing Crohn's Disease. Dig Dis Sci 68, 608-615, doi:10.1007/s10620-022-07630-5 (2023). [Link]
31.
Arnott, I. D. et al. Sero-reactivity to microbial components in Crohn's disease is associated with disease severity and progression, but not NOD2/CARD15 genotype. Am J Gastroenterol 99, 2376-2384, doi:10.1111/j.1572-0241.2004.40417.x (2004). [Link]
32.
Choung, R. S. et al. Serologic microbial associated markers can predict Crohn's disease behaviour years before disease diagnosis. Aliment Pharmacol Ther 43, 1300-1310, doi:10.1111/apt.13641 (2016). [Link]
33.
Subramanian, J. & Simon, R. Overfitting in prediction models - is it a problem only in high dimensions? Contemp Clin Trials 36, 636-641, doi:10.1016/j.cct.2013.06.011 (2013). [Link]
34.
Ransohoff, D. F. Rules of evidence for cancer molecular-marker discovery and validation. Nat Rev Cancer 4, 309-314, doi:10.1038/nrc1322 (2004). [Link]
35.
Kern, S. E. Why your new cancer biomarker may never work: recurrent patterns and remarkable diversity in biomarker failures. Cancer Res 72, 6097-6101, doi:10.1158/0008-5472.CAN-12-3232 (2012). [Link]
36.
Argmann, C. et al. Biopsy and blood-based molecular biomarker of inflammation in IBD. Gut, doi:10.1136/gutjnl-2021-326451 (2022). [Link]
37.
Duffy, M. J. et al. Validation of new cancer biomarkers: a position statement from the European group on tumor markers. Clin Chem 61, 809-820, doi:10.1373/clinchem.2015.239863 (2015). [Link]
38.
Lee, J. C., Lyons, P. A. & McKinney, E. F. Analytical Mistakes Confound Attempted Validation: A Response to 'Transcription and DNA Methylation Patterns of Blood-Derived CD8+ T Cells Are Associated With Age and Inflammatory Bowel Disease But Do Not Predict Prognosis'. Gastroenterology 160, 2210-2211, doi:10.1053/j.gastro.2021.01.021 (2021). https://pubmed.ncbi.nlm.nih.gov/33453231/ [Link]
39.
Fagerlin, A., Zikmund-Fisher, B. J. & Ubel, P. A. Helping patients decide: ten steps to better risk communication. J Natl Cancer Inst 103, 1436-1443, doi:10.1093/jnci/djr318 (2011). [Link]
40.
Paling, J. Strategies to help patients understand risks. BMJ 327, 745-748, doi:10.1136/bmj.327.7417.745 (2003). [Link]
41.
Kumar, M., Garand, M. & Al Khodor, S. Integrating omics for a better understanding of Inflammatory Bowel Disease: a step towards personalized medicine. J Transl Med 17, 419, doi:10.1186/s12967-019-02174-1 (2019). [Link]
42.
Fan, J., Han, F. & Liu, H. Challenges of Big Data Analysis. Natl Sci Rev 1, 293-314, doi:10.1093/nsr/nwt032 (2014). [Link]
43.
Lee, J. C. et al. Gene expression profiling of CD8+ T cells predicts prognosis in patients with Crohn disease and ulcerative colitis. J Clin Invest 121, 4170-4179 (2011). [Link]
44.
McKinney, E. F., Lee, J. C., Jayne, D. R., Lyons, P. A. & Smith, K. G. T-cell exhaustion, co-stimulation and clinical outcome in autoimmunity and infection. Nature 523, 612-616, doi:nature14468 [pii]10.1038/nature14468 (2015). [Link]
45.
Lemaitre, M. et al. Association Between Use of Thiopurines or Tumor Necrosis Factor Antagonists Alone or in Combination and Risk of Lymphoma in Patients With Inflammatory Bowel Disease. JAMA 318, 1679-1686, doi:10.1001/jama.2017.16071 (2017). [Link]
46.
Tottrup, A., Erichsen, R., Svaerke, C., Laurberg, S. & Srensen, H. T. Thirty-day mortality after elective and emergency total colectomy in Danish patients with inflammatory bowel disease: a population-based nationwide cohort study. BMJ Open 2, e000823, doi:10.1136/bmjopen-2012-000823 (2012). [Link]

Abstract

Peritoneal malignancies represent a complex and often misjudged clinical challenge. Historically synonymous with a terminal diagnosis, the advent of cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) radically altered the prognosis for selected patients. However, progress has been jeopardised by a series of recurring and preventable errors in diagnosis, staging, and treatment selection. This article delineates the ten most critical pitfalls in managing peritoneal surface malignancies. For each pitfall, we provide evidence-based explanations, concrete clinical examples, and strategic recommendations for avoidance. We emphasise the pivotal role of early multidisciplinary discussion, precise imaging, and timely referral to high-volume expert centres to optimise patient outcomes and offer curative intent where previously there was none.

Topics

Digestive Oncology Surgery

Published

2026

More Like This:

Mistakes in the management of peritoneal malignancies and how to avoid them

Mistakes in the management of peritoneal malignancies and how to avoid them

Charlotte Rabl Charlotte Rabl, Tarkan Jäger, Andrea Barberis, Matteo Santoliquido, Francesco Saverio Papadia

Mistakes in Pancreatic exocrine insufficiency and how to avoid them

Mistakes in Pancreatic exocrine insufficiency and how to avoid them

Matthias Löhr Matthias Löhr, J. Enrique Domínguez Muñoz, Miroslav Vujasinovic

Coeliac disease with David Sanders

Coeliac disease with David Sanders

Pradeep Mundre Pradeep Mundre, David S. Sanders

Mistakes in abdominal distension and how to avoid them

Mistakes in abdominal distension and how to avoid them

Alberto Ezquerra-Durán Alberto Ezquerra-Durán, Elizabeth Barba Orozco

Mistakes in hepatitis C and how to avoid them

Mistakes in hepatitis C and how to avoid them

Gonçalo Alexandrino Gonçalo Alexandrino, Ana Catarina Garcia

Mistakes in gastrostomy insertion in children and adolescents and how to avoid them

Mistakes in gastrostomy insertion in children and adolescents and how to avoid them

Christos Tzivinikos Christos Tzivinikos, Matjaz Homan, Jorge Amil Dias, Ilse Broekaert

UEG Mistakes In Articles
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Mistakes in Pancreatic exocrine insufficiency and how to avoid them

Miroslav Vujasinovic, J. Enrique Domínguez Muñoz, Matthias Löhr

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References

Mistakes
References
Mistake 1 Mistake 2 Mistake 3 Mistake 4 Mistake 5 Mistake 6 Mistake 7 Mistake 8
1.
Verstockt, B., Parkes, M. & Lee, J. C. How Do We Predict a Patient's Disease Course and Whether They Will Respond to Specific Treatments? Gastroenterology 162, 1383-1395, doi:10.1053/j.gastro.2021.12.245 (2022). [Link]
2.
Jess, T. et al. Changes in clinical characteristics, course, and prognosis of inflammatory bowel disease during the last 5 decades: a population-based study from Copenhagen, Denmark. Inflamm Bowel Dis 13, 481-489, doi:10.1002/ibd.20036 (2007). [Link]
3.
Solberg, I. C. et al. Clinical course in Crohn's disease: results of a Norwegian population-based ten-year follow-up study. Clin Gastroenterol Hepatol 5, 1430-1438, doi:S1542-3565(07)00888-9 [pii]10.1016/j.cgh.2007.09.002 (2007). [Link]
4.
Alsoud, D., Verstockt, B., Fiocchi, C. & Vermeire, S. Breaking the therapeutic ceiling in drug development in ulcerative colitis. Lancet Gastroenterol Hepatol 6, 589-595, doi:10.1016/S2468-1253(21)00065-0 (2021). [Link]
5.
Colombel, J. F., D'Haens, G., Lee, W. J., Petersson, J. & Panaccione, R. Outcomes and Strategies to Support a Treat-to-target Approach in Inflammatory Bowel Disease: A Systematic Review. J Crohns Colitis 14, 254-266, doi:10.1093/ecco-jcc/jjz131 (2020). [Link]
6.
Sparano, J. A. et al. Adjuvant Chemotherapy Guided by a 21-Gene Expression Assay in Breast Cancer. N Engl J Med 379, 111-121, doi:10.1056/NEJMoa1804710 (2018). [Link]
7.
Cardoso, F. et al. 70-Gene Signature as an Aid to Treatment Decisions in Early-Stage Breast Cancer. N Engl J Med 375, 717-729, doi:10.1056/NEJMoa1602253 (2016). [Link]
8.
Hart, A. L. et al. What Are the Top 10 Research Questions in the Treatment of Inflammatory Bowel Disease? A Priority Setting Partnership with the James Lind Alliance. J Crohns Colitis 11, 204-211, doi:10.1093/ecco-jcc/jjw144 (2017). [Link]
9.
Noor, N. M., Verstockt, B., Parkes, M. & Lee, J. C. Personalised medicine in Crohn's disease. Lancet Gastroenterol Hepatol 5, 80-92, doi:10.1016/S2468-1253(19)30340-1 (2020). [Link]
10.
Wolters, F. L. et al. Phenotype at diagnosis predicts recurrence rates in Crohn's disease. Gut 55, 1124-1130, doi:10.1136/gut.2005.084061 (2006). [Link]
11.
Beaugerie, L., Seksik, P., Nion-Larmurier, I., Gendre, J. P. & Cosnes, J. Predictors of Crohn's disease. Gastroenterology 130, 650-656, doi:S0016-5085(05)02529-1 [pii]10.1053/j.gastro.2005.12.019 (2006). [Link]
12.
Loly, C., Belaiche, J. & Louis, E. Predictors of severe Crohn's disease. Scand J Gastroenterol 43, 948-954 (2008). [Link]
13.
Torres, J. et al. Predicting Outcomes to Optimize Disease Management in Inflammatory Bowel Diseases. J Crohns Colitis 10, 1385-1394, doi:10.1093/ecco-jcc/jjw116 (2016). [Link]
14.
Cosnes, J. et al. Factors affecting outcomes in Crohn's disease over 15 years. Gut 61, 1140-1145, doi:10.1136/gutjnl-2011-301971 (2012). [Link]
15.
Solberg, I. C. et al. Clinical course during the first 10 years of ulcerative colitis: results from a population-based inception cohort (IBSEN Study). Scand J Gastroenterol 44, 431-440, doi:907045459 [pii]10.1080/00365520802600961 (2009). [Link]
16.
Ananthakrishnan, A. N. et al. History of medical hospitalization predicts future need for colectomy in patients with ulcerative colitis. Inflamm Bowel Dis 15, 176-181, doi:10.1002/ibd.20639 (2009). [Link]
17.
Targownik, L. E., Singh, H., Nugent, Z. & Bernstein, C. N. The epidemiology of colectomy in ulcerative colitis: results from a population-based cohort. Am J Gastroenterol 107, 1228-1235, doi:10.1038/ajg.2012.127 (2012). [Link]
18.
Dulai, P. S. et al. Development and Validation of a Scoring System to Predict Outcomes of Vedolizumab Treatment in Patients With Crohn's Disease. Gastroenterology 155, 687-695 e610, doi:10.1053/j.gastro.2018.05.039 (2018). [Link]
19.
Molnar, T. et al. Predictors of relapse in patients with Crohn's disease in remission after 1 year of biological therapy. Aliment Pharmacol Ther 37, 225-233, doi:10.1111/apt.12160 (2013). [Link]
20.
Billiet, T. et al. A Matrix-based Model Predicts Primary Response to Infliximab in Crohn's Disease. J Crohns Colitis 9, 1120-1126, doi:jjv156 [pii]10.1093/ecco-jcc/jjv156 (2015). [Link]
21.
Gibson, G. Going to the negative: genomics for optimized medical prescription. Nat Rev Genet 20, 1-2, doi:10.1038/s41576-018-0061-7 (2019). [Link]
22.
Lee, J. C. et al. Genome-wide association study identifies distinct genetic contributions to prognosis and susceptibility in Crohn's disease. Nat Genet 49, 262-268, doi:10.1038/ng.3755 (2017). [Link]
23.
Biasci, D. et al. A blood-based prognostic biomarker in IBD. Gut 68, 1386-1395, doi:10.1136/gutjnl-2019-318343 (2019). [Link]
24.
Kugathasan, S. et al. Prediction of complicated disease course for children newly diagnosed with Crohn's disease: a multicentre inception cohort study. Lancet 389, 1710-1718, doi:10.1016/S0140-6736(17)30317-3 (2017). [Link]
25.
Taylor, A. E. et al. Investigating the possible causal association of smoking with depression and anxiety using Mendelian randomisation meta-analysis: the CARTA consortium. BMJ Open 4, e006141, doi:10.1136/bmjopen-2014-006141 (2014). [Link]
26.
Ferrante, M. et al. New serological markers in inflammatory bowel disease are associated with complicated disease behaviour. Gut 56, 1394-1403, doi:gut.2006.108043 [pii]10.1136/gut.2006.108043 (2007). [Link]
27.
Amre, D. K., Lu, S. E., Costea, F. & Seidman, E. G. Utility of serological markers in predicting the early occurrence of complications and surgery in pediatric Crohn's disease patients. Am J Gastroenterol 101, 645-652, doi:AJG468 [pii]10.1111/j.1572-0241.2006.00468.x (2006). [Link]
28.
Seow, C. H. et al. Novel anti-glycan antibodies related to inflammatory bowel disease diagnosis and phenotype. Am J Gastroenterol 104, 1426-1434, doi:ajg200979 [pii]10.1038/ajg.2009.79 (2009). [Link]
29.
Israeli, E. et al. Anti-Saccharomyces cerevisiae and antineutrophil cytoplasmic antibodies as predictors of inflammatory bowel disease. Gut 54, 1232-1236, doi:54/9/1232 [pii]10.1136/gut.2004.060228 (2005). [Link]
30.
Bodecker-Zingmark, L., Widbom, L., Hultdin, J., Eriksson, C. & Karling, P. Anti-Saccharomyces cerevisiae Antibodies Are Only Modestly More Common in Subjects Later Developing Crohn's Disease. Dig Dis Sci 68, 608-615, doi:10.1007/s10620-022-07630-5 (2023). [Link]
31.
Arnott, I. D. et al. Sero-reactivity to microbial components in Crohn's disease is associated with disease severity and progression, but not NOD2/CARD15 genotype. Am J Gastroenterol 99, 2376-2384, doi:10.1111/j.1572-0241.2004.40417.x (2004). [Link]
32.
Choung, R. S. et al. Serologic microbial associated markers can predict Crohn's disease behaviour years before disease diagnosis. Aliment Pharmacol Ther 43, 1300-1310, doi:10.1111/apt.13641 (2016). [Link]
33.
Subramanian, J. & Simon, R. Overfitting in prediction models - is it a problem only in high dimensions? Contemp Clin Trials 36, 636-641, doi:10.1016/j.cct.2013.06.011 (2013). [Link]
34.
Ransohoff, D. F. Rules of evidence for cancer molecular-marker discovery and validation. Nat Rev Cancer 4, 309-314, doi:10.1038/nrc1322 (2004). [Link]
35.
Kern, S. E. Why your new cancer biomarker may never work: recurrent patterns and remarkable diversity in biomarker failures. Cancer Res 72, 6097-6101, doi:10.1158/0008-5472.CAN-12-3232 (2012). [Link]
36.
Argmann, C. et al. Biopsy and blood-based molecular biomarker of inflammation in IBD. Gut, doi:10.1136/gutjnl-2021-326451 (2022). [Link]
37.
Duffy, M. J. et al. Validation of new cancer biomarkers: a position statement from the European group on tumor markers. Clin Chem 61, 809-820, doi:10.1373/clinchem.2015.239863 (2015). [Link]
38.
Lee, J. C., Lyons, P. A. & McKinney, E. F. Analytical Mistakes Confound Attempted Validation: A Response to 'Transcription and DNA Methylation Patterns of Blood-Derived CD8+ T Cells Are Associated With Age and Inflammatory Bowel Disease But Do Not Predict Prognosis'. Gastroenterology 160, 2210-2211, doi:10.1053/j.gastro.2021.01.021 (2021). https://pubmed.ncbi.nlm.nih.gov/33453231/ [Link]
39.
Fagerlin, A., Zikmund-Fisher, B. J. & Ubel, P. A. Helping patients decide: ten steps to better risk communication. J Natl Cancer Inst 103, 1436-1443, doi:10.1093/jnci/djr318 (2011). [Link]
40.
Paling, J. Strategies to help patients understand risks. BMJ 327, 745-748, doi:10.1136/bmj.327.7417.745 (2003). [Link]
41.
Kumar, M., Garand, M. & Al Khodor, S. Integrating omics for a better understanding of Inflammatory Bowel Disease: a step towards personalized medicine. J Transl Med 17, 419, doi:10.1186/s12967-019-02174-1 (2019). [Link]
42.
Fan, J., Han, F. & Liu, H. Challenges of Big Data Analysis. Natl Sci Rev 1, 293-314, doi:10.1093/nsr/nwt032 (2014). [Link]
43.
Lee, J. C. et al. Gene expression profiling of CD8+ T cells predicts prognosis in patients with Crohn disease and ulcerative colitis. J Clin Invest 121, 4170-4179 (2011). [Link]
44.
McKinney, E. F., Lee, J. C., Jayne, D. R., Lyons, P. A. & Smith, K. G. T-cell exhaustion, co-stimulation and clinical outcome in autoimmunity and infection. Nature 523, 612-616, doi:nature14468 [pii]10.1038/nature14468 (2015). [Link]
45.
Lemaitre, M. et al. Association Between Use of Thiopurines or Tumor Necrosis Factor Antagonists Alone or in Combination and Risk of Lymphoma in Patients With Inflammatory Bowel Disease. JAMA 318, 1679-1686, doi:10.1001/jama.2017.16071 (2017). [Link]
46.
Tottrup, A., Erichsen, R., Svaerke, C., Laurberg, S. & Srensen, H. T. Thirty-day mortality after elective and emergency total colectomy in Danish patients with inflammatory bowel disease: a population-based nationwide cohort study. BMJ Open 2, e000823, doi:10.1136/bmjopen-2012-000823 (2012). [Link]

Abstract

Pancreatic exocrine insufficiency (PEI) is a common yet frequently under-recognised cause of maldigestion, malabsorption, and malnutrition. Although traditionally associated with primary pancreatic disorders such as chronic pancreatitis, cystic fibrosis, pancreatic cancer, or pancreatic surgery, it is now evident that PEI also occurs in a wide range of extra-pancreatic conditions and clinical settings. Advances in diagnostic testing and expanding clinical awareness have improved detection; however, significant misconceptions persist regarding when to suspect PEI; how to interpret diagnostic tests; and how to initiate, optimise, and monitor pancreatic enzyme replacement therapy (PERT). In everyday practice, these errors may lead to delayed diagnosis, inappropriate treatment, persistent symptoms, and preventable nutritional deficiencies. This “Mistakes in…” article highlights common pitfalls in the diagnosis and management of PEI, focusing on inappropriate reliance on faecal elastase testing, failure to recognise secondary causes, undertreatment with PERT, and inadequate nutritional assessment. By addressing these frequent mistakes, we aim to promote a more structured, patient-centred, and evidence-informed approach to PEI that improves clinical outcomes and quality of life.

Topics

Pancreas

Published

2026

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UEG Podcast Episode
UEG Podcast
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Coeliac disease with David Sanders

David S. Sanders, Pradeep Mundre

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This summary was generated by an AI large language model based on the content transcript. It is for informational purposes only and should not be considered a substitute for clinical judgment. Always rely on your professional expertise and the full clinical context when making clinical decisions.

Abstract

Topics

Small Intestine & Nutrition

Published

2026

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UEG Mistakes In Articles
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Mistakes in abdominal distension and how to avoid them

Elizabeth Barba Orozco, Alberto Ezquerra-Durán

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Summary is not available for this content yet.

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Thanks for your feedback.

This summary was generated by an AI large language model based on the content transcript. It is for informational purposes only and should not be considered a substitute for clinical judgment. Always rely on your professional expertise and the full clinical context when making clinical decisions.

References

Mistakes
References
Mistake 1 Mistake 2 Mistake 3 Mistake 4 Mistake 5 Mistake 6 Mistake 7 Mistake 8
1.
Verstockt, B., Parkes, M. & Lee, J. C. How Do We Predict a Patient's Disease Course and Whether They Will Respond to Specific Treatments? Gastroenterology 162, 1383-1395, doi:10.1053/j.gastro.2021.12.245 (2022). [Link]
2.
Jess, T. et al. Changes in clinical characteristics, course, and prognosis of inflammatory bowel disease during the last 5 decades: a population-based study from Copenhagen, Denmark. Inflamm Bowel Dis 13, 481-489, doi:10.1002/ibd.20036 (2007). [Link]
3.
Solberg, I. C. et al. Clinical course in Crohn's disease: results of a Norwegian population-based ten-year follow-up study. Clin Gastroenterol Hepatol 5, 1430-1438, doi:S1542-3565(07)00888-9 [pii]10.1016/j.cgh.2007.09.002 (2007). [Link]
4.
Alsoud, D., Verstockt, B., Fiocchi, C. & Vermeire, S. Breaking the therapeutic ceiling in drug development in ulcerative colitis. Lancet Gastroenterol Hepatol 6, 589-595, doi:10.1016/S2468-1253(21)00065-0 (2021). [Link]
5.
Colombel, J. F., D'Haens, G., Lee, W. J., Petersson, J. & Panaccione, R. Outcomes and Strategies to Support a Treat-to-target Approach in Inflammatory Bowel Disease: A Systematic Review. J Crohns Colitis 14, 254-266, doi:10.1093/ecco-jcc/jjz131 (2020). [Link]
6.
Sparano, J. A. et al. Adjuvant Chemotherapy Guided by a 21-Gene Expression Assay in Breast Cancer. N Engl J Med 379, 111-121, doi:10.1056/NEJMoa1804710 (2018). [Link]
7.
Cardoso, F. et al. 70-Gene Signature as an Aid to Treatment Decisions in Early-Stage Breast Cancer. N Engl J Med 375, 717-729, doi:10.1056/NEJMoa1602253 (2016). [Link]
8.
Hart, A. L. et al. What Are the Top 10 Research Questions in the Treatment of Inflammatory Bowel Disease? A Priority Setting Partnership with the James Lind Alliance. J Crohns Colitis 11, 204-211, doi:10.1093/ecco-jcc/jjw144 (2017). [Link]
9.
Noor, N. M., Verstockt, B., Parkes, M. & Lee, J. C. Personalised medicine in Crohn's disease. Lancet Gastroenterol Hepatol 5, 80-92, doi:10.1016/S2468-1253(19)30340-1 (2020). [Link]
10.
Wolters, F. L. et al. Phenotype at diagnosis predicts recurrence rates in Crohn's disease. Gut 55, 1124-1130, doi:10.1136/gut.2005.084061 (2006). [Link]
11.
Beaugerie, L., Seksik, P., Nion-Larmurier, I., Gendre, J. P. & Cosnes, J. Predictors of Crohn's disease. Gastroenterology 130, 650-656, doi:S0016-5085(05)02529-1 [pii]10.1053/j.gastro.2005.12.019 (2006). [Link]
12.
Loly, C., Belaiche, J. & Louis, E. Predictors of severe Crohn's disease. Scand J Gastroenterol 43, 948-954 (2008). [Link]
13.
Torres, J. et al. Predicting Outcomes to Optimize Disease Management in Inflammatory Bowel Diseases. J Crohns Colitis 10, 1385-1394, doi:10.1093/ecco-jcc/jjw116 (2016). [Link]
14.
Cosnes, J. et al. Factors affecting outcomes in Crohn's disease over 15 years. Gut 61, 1140-1145, doi:10.1136/gutjnl-2011-301971 (2012). [Link]
15.
Solberg, I. C. et al. Clinical course during the first 10 years of ulcerative colitis: results from a population-based inception cohort (IBSEN Study). Scand J Gastroenterol 44, 431-440, doi:907045459 [pii]10.1080/00365520802600961 (2009). [Link]
16.
Ananthakrishnan, A. N. et al. History of medical hospitalization predicts future need for colectomy in patients with ulcerative colitis. Inflamm Bowel Dis 15, 176-181, doi:10.1002/ibd.20639 (2009). [Link]
17.
Targownik, L. E., Singh, H., Nugent, Z. & Bernstein, C. N. The epidemiology of colectomy in ulcerative colitis: results from a population-based cohort. Am J Gastroenterol 107, 1228-1235, doi:10.1038/ajg.2012.127 (2012). [Link]
18.
Dulai, P. S. et al. Development and Validation of a Scoring System to Predict Outcomes of Vedolizumab Treatment in Patients With Crohn's Disease. Gastroenterology 155, 687-695 e610, doi:10.1053/j.gastro.2018.05.039 (2018). [Link]
19.
Molnar, T. et al. Predictors of relapse in patients with Crohn's disease in remission after 1 year of biological therapy. Aliment Pharmacol Ther 37, 225-233, doi:10.1111/apt.12160 (2013). [Link]
20.
Billiet, T. et al. A Matrix-based Model Predicts Primary Response to Infliximab in Crohn's Disease. J Crohns Colitis 9, 1120-1126, doi:jjv156 [pii]10.1093/ecco-jcc/jjv156 (2015). [Link]
21.
Gibson, G. Going to the negative: genomics for optimized medical prescription. Nat Rev Genet 20, 1-2, doi:10.1038/s41576-018-0061-7 (2019). [Link]
22.
Lee, J. C. et al. Genome-wide association study identifies distinct genetic contributions to prognosis and susceptibility in Crohn's disease. Nat Genet 49, 262-268, doi:10.1038/ng.3755 (2017). [Link]
23.
Biasci, D. et al. A blood-based prognostic biomarker in IBD. Gut 68, 1386-1395, doi:10.1136/gutjnl-2019-318343 (2019). [Link]
24.
Kugathasan, S. et al. Prediction of complicated disease course for children newly diagnosed with Crohn's disease: a multicentre inception cohort study. Lancet 389, 1710-1718, doi:10.1016/S0140-6736(17)30317-3 (2017). [Link]
25.
Taylor, A. E. et al. Investigating the possible causal association of smoking with depression and anxiety using Mendelian randomisation meta-analysis: the CARTA consortium. BMJ Open 4, e006141, doi:10.1136/bmjopen-2014-006141 (2014). [Link]
26.
Ferrante, M. et al. New serological markers in inflammatory bowel disease are associated with complicated disease behaviour. Gut 56, 1394-1403, doi:gut.2006.108043 [pii]10.1136/gut.2006.108043 (2007). [Link]
27.
Amre, D. K., Lu, S. E., Costea, F. & Seidman, E. G. Utility of serological markers in predicting the early occurrence of complications and surgery in pediatric Crohn's disease patients. Am J Gastroenterol 101, 645-652, doi:AJG468 [pii]10.1111/j.1572-0241.2006.00468.x (2006). [Link]
28.
Seow, C. H. et al. Novel anti-glycan antibodies related to inflammatory bowel disease diagnosis and phenotype. Am J Gastroenterol 104, 1426-1434, doi:ajg200979 [pii]10.1038/ajg.2009.79 (2009). [Link]
29.
Israeli, E. et al. Anti-Saccharomyces cerevisiae and antineutrophil cytoplasmic antibodies as predictors of inflammatory bowel disease. Gut 54, 1232-1236, doi:54/9/1232 [pii]10.1136/gut.2004.060228 (2005). [Link]
30.
Bodecker-Zingmark, L., Widbom, L., Hultdin, J., Eriksson, C. & Karling, P. Anti-Saccharomyces cerevisiae Antibodies Are Only Modestly More Common in Subjects Later Developing Crohn's Disease. Dig Dis Sci 68, 608-615, doi:10.1007/s10620-022-07630-5 (2023). [Link]
31.
Arnott, I. D. et al. Sero-reactivity to microbial components in Crohn's disease is associated with disease severity and progression, but not NOD2/CARD15 genotype. Am J Gastroenterol 99, 2376-2384, doi:10.1111/j.1572-0241.2004.40417.x (2004). [Link]
32.
Choung, R. S. et al. Serologic microbial associated markers can predict Crohn's disease behaviour years before disease diagnosis. Aliment Pharmacol Ther 43, 1300-1310, doi:10.1111/apt.13641 (2016). [Link]
33.
Subramanian, J. & Simon, R. Overfitting in prediction models - is it a problem only in high dimensions? Contemp Clin Trials 36, 636-641, doi:10.1016/j.cct.2013.06.011 (2013). [Link]
34.
Ransohoff, D. F. Rules of evidence for cancer molecular-marker discovery and validation. Nat Rev Cancer 4, 309-314, doi:10.1038/nrc1322 (2004). [Link]
35.
Kern, S. E. Why your new cancer biomarker may never work: recurrent patterns and remarkable diversity in biomarker failures. Cancer Res 72, 6097-6101, doi:10.1158/0008-5472.CAN-12-3232 (2012). [Link]
36.
Argmann, C. et al. Biopsy and blood-based molecular biomarker of inflammation in IBD. Gut, doi:10.1136/gutjnl-2021-326451 (2022). [Link]
37.
Duffy, M. J. et al. Validation of new cancer biomarkers: a position statement from the European group on tumor markers. Clin Chem 61, 809-820, doi:10.1373/clinchem.2015.239863 (2015). [Link]
38.
Lee, J. C., Lyons, P. A. & McKinney, E. F. Analytical Mistakes Confound Attempted Validation: A Response to 'Transcription and DNA Methylation Patterns of Blood-Derived CD8+ T Cells Are Associated With Age and Inflammatory Bowel Disease But Do Not Predict Prognosis'. Gastroenterology 160, 2210-2211, doi:10.1053/j.gastro.2021.01.021 (2021). https://pubmed.ncbi.nlm.nih.gov/33453231/ [Link]
39.
Fagerlin, A., Zikmund-Fisher, B. J. & Ubel, P. A. Helping patients decide: ten steps to better risk communication. J Natl Cancer Inst 103, 1436-1443, doi:10.1093/jnci/djr318 (2011). [Link]
40.
Paling, J. Strategies to help patients understand risks. BMJ 327, 745-748, doi:10.1136/bmj.327.7417.745 (2003). [Link]
41.
Kumar, M., Garand, M. & Al Khodor, S. Integrating omics for a better understanding of Inflammatory Bowel Disease: a step towards personalized medicine. J Transl Med 17, 419, doi:10.1186/s12967-019-02174-1 (2019). [Link]
42.
Fan, J., Han, F. & Liu, H. Challenges of Big Data Analysis. Natl Sci Rev 1, 293-314, doi:10.1093/nsr/nwt032 (2014). [Link]
43.
Lee, J. C. et al. Gene expression profiling of CD8+ T cells predicts prognosis in patients with Crohn disease and ulcerative colitis. J Clin Invest 121, 4170-4179 (2011). [Link]
44.
McKinney, E. F., Lee, J. C., Jayne, D. R., Lyons, P. A. & Smith, K. G. T-cell exhaustion, co-stimulation and clinical outcome in autoimmunity and infection. Nature 523, 612-616, doi:nature14468 [pii]10.1038/nature14468 (2015). [Link]
45.
Lemaitre, M. et al. Association Between Use of Thiopurines or Tumor Necrosis Factor Antagonists Alone or in Combination and Risk of Lymphoma in Patients With Inflammatory Bowel Disease. JAMA 318, 1679-1686, doi:10.1001/jama.2017.16071 (2017). [Link]
46.
Tottrup, A., Erichsen, R., Svaerke, C., Laurberg, S. & Srensen, H. T. Thirty-day mortality after elective and emergency total colectomy in Danish patients with inflammatory bowel disease: a population-based nationwide cohort study. BMJ Open 2, e000823, doi:10.1136/bmjopen-2012-000823 (2012). [Link]

Abstract

Abdominal distension and bloating are among the most frequently misunderstood complaints in gastroenterology. They are often used as interchangeable terms, a conceptual mistake that continues to drive diagnostic errors and ineffective treatment. According to Rome IV, bloating and distension may represent either a primary disorder of gut–brain interaction (DGBI) or occur as symptoms with other DGBIs, such as irritable bowel syndrome (IBS), functional dyspepsia (FD) or functional constipation (FC).

Topics

Neurogastroenterology & Motility

Citation

Barba E and Ezquerra-Durán A. Mistakes in abdominal distension and bloating and how to avoid them. UEG Education 2026; 26: 5-9.

Published

2026

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UEG Mistakes In Articles
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Mistakes in hepatitis C and how to avoid them

Ana Catarina Garcia, Gonçalo Alexandrino

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This summary was generated by an AI large language model based on the content transcript. It is for informational purposes only and should not be considered a substitute for clinical judgment. Always rely on your professional expertise and the full clinical context when making clinical decisions.

References

Mistakes
References
Mistake 1 Mistake 2 Mistake 3 Mistake 4 Mistake 5 Mistake 6 Mistake 7 Mistake 8
1.
Verstockt, B., Parkes, M. & Lee, J. C. How Do We Predict a Patient's Disease Course and Whether They Will Respond to Specific Treatments? Gastroenterology 162, 1383-1395, doi:10.1053/j.gastro.2021.12.245 (2022). [Link]
2.
Jess, T. et al. Changes in clinical characteristics, course, and prognosis of inflammatory bowel disease during the last 5 decades: a population-based study from Copenhagen, Denmark. Inflamm Bowel Dis 13, 481-489, doi:10.1002/ibd.20036 (2007). [Link]
3.
Solberg, I. C. et al. Clinical course in Crohn's disease: results of a Norwegian population-based ten-year follow-up study. Clin Gastroenterol Hepatol 5, 1430-1438, doi:S1542-3565(07)00888-9 [pii]10.1016/j.cgh.2007.09.002 (2007). [Link]
4.
Alsoud, D., Verstockt, B., Fiocchi, C. & Vermeire, S. Breaking the therapeutic ceiling in drug development in ulcerative colitis. Lancet Gastroenterol Hepatol 6, 589-595, doi:10.1016/S2468-1253(21)00065-0 (2021). [Link]
5.
Colombel, J. F., D'Haens, G., Lee, W. J., Petersson, J. & Panaccione, R. Outcomes and Strategies to Support a Treat-to-target Approach in Inflammatory Bowel Disease: A Systematic Review. J Crohns Colitis 14, 254-266, doi:10.1093/ecco-jcc/jjz131 (2020). [Link]
6.
Sparano, J. A. et al. Adjuvant Chemotherapy Guided by a 21-Gene Expression Assay in Breast Cancer. N Engl J Med 379, 111-121, doi:10.1056/NEJMoa1804710 (2018). [Link]
7.
Cardoso, F. et al. 70-Gene Signature as an Aid to Treatment Decisions in Early-Stage Breast Cancer. N Engl J Med 375, 717-729, doi:10.1056/NEJMoa1602253 (2016). [Link]
8.
Hart, A. L. et al. What Are the Top 10 Research Questions in the Treatment of Inflammatory Bowel Disease? A Priority Setting Partnership with the James Lind Alliance. J Crohns Colitis 11, 204-211, doi:10.1093/ecco-jcc/jjw144 (2017). [Link]
9.
Noor, N. M., Verstockt, B., Parkes, M. & Lee, J. C. Personalised medicine in Crohn's disease. Lancet Gastroenterol Hepatol 5, 80-92, doi:10.1016/S2468-1253(19)30340-1 (2020). [Link]
10.
Wolters, F. L. et al. Phenotype at diagnosis predicts recurrence rates in Crohn's disease. Gut 55, 1124-1130, doi:10.1136/gut.2005.084061 (2006). [Link]
11.
Beaugerie, L., Seksik, P., Nion-Larmurier, I., Gendre, J. P. & Cosnes, J. Predictors of Crohn's disease. Gastroenterology 130, 650-656, doi:S0016-5085(05)02529-1 [pii]10.1053/j.gastro.2005.12.019 (2006). [Link]
12.
Loly, C., Belaiche, J. & Louis, E. Predictors of severe Crohn's disease. Scand J Gastroenterol 43, 948-954 (2008). [Link]
13.
Torres, J. et al. Predicting Outcomes to Optimize Disease Management in Inflammatory Bowel Diseases. J Crohns Colitis 10, 1385-1394, doi:10.1093/ecco-jcc/jjw116 (2016). [Link]
14.
Cosnes, J. et al. Factors affecting outcomes in Crohn's disease over 15 years. Gut 61, 1140-1145, doi:10.1136/gutjnl-2011-301971 (2012). [Link]
15.
Solberg, I. C. et al. Clinical course during the first 10 years of ulcerative colitis: results from a population-based inception cohort (IBSEN Study). Scand J Gastroenterol 44, 431-440, doi:907045459 [pii]10.1080/00365520802600961 (2009). [Link]
16.
Ananthakrishnan, A. N. et al. History of medical hospitalization predicts future need for colectomy in patients with ulcerative colitis. Inflamm Bowel Dis 15, 176-181, doi:10.1002/ibd.20639 (2009). [Link]
17.
Targownik, L. E., Singh, H., Nugent, Z. & Bernstein, C. N. The epidemiology of colectomy in ulcerative colitis: results from a population-based cohort. Am J Gastroenterol 107, 1228-1235, doi:10.1038/ajg.2012.127 (2012). [Link]
18.
Dulai, P. S. et al. Development and Validation of a Scoring System to Predict Outcomes of Vedolizumab Treatment in Patients With Crohn's Disease. Gastroenterology 155, 687-695 e610, doi:10.1053/j.gastro.2018.05.039 (2018). [Link]
19.
Molnar, T. et al. Predictors of relapse in patients with Crohn's disease in remission after 1 year of biological therapy. Aliment Pharmacol Ther 37, 225-233, doi:10.1111/apt.12160 (2013). [Link]
20.
Billiet, T. et al. A Matrix-based Model Predicts Primary Response to Infliximab in Crohn's Disease. J Crohns Colitis 9, 1120-1126, doi:jjv156 [pii]10.1093/ecco-jcc/jjv156 (2015). [Link]
21.
Gibson, G. Going to the negative: genomics for optimized medical prescription. Nat Rev Genet 20, 1-2, doi:10.1038/s41576-018-0061-7 (2019). [Link]
22.
Lee, J. C. et al. Genome-wide association study identifies distinct genetic contributions to prognosis and susceptibility in Crohn's disease. Nat Genet 49, 262-268, doi:10.1038/ng.3755 (2017). [Link]
23.
Biasci, D. et al. A blood-based prognostic biomarker in IBD. Gut 68, 1386-1395, doi:10.1136/gutjnl-2019-318343 (2019). [Link]
24.
Kugathasan, S. et al. Prediction of complicated disease course for children newly diagnosed with Crohn's disease: a multicentre inception cohort study. Lancet 389, 1710-1718, doi:10.1016/S0140-6736(17)30317-3 (2017). [Link]
25.
Taylor, A. E. et al. Investigating the possible causal association of smoking with depression and anxiety using Mendelian randomisation meta-analysis: the CARTA consortium. BMJ Open 4, e006141, doi:10.1136/bmjopen-2014-006141 (2014). [Link]
26.
Ferrante, M. et al. New serological markers in inflammatory bowel disease are associated with complicated disease behaviour. Gut 56, 1394-1403, doi:gut.2006.108043 [pii]10.1136/gut.2006.108043 (2007). [Link]
27.
Amre, D. K., Lu, S. E., Costea, F. & Seidman, E. G. Utility of serological markers in predicting the early occurrence of complications and surgery in pediatric Crohn's disease patients. Am J Gastroenterol 101, 645-652, doi:AJG468 [pii]10.1111/j.1572-0241.2006.00468.x (2006). [Link]
28.
Seow, C. H. et al. Novel anti-glycan antibodies related to inflammatory bowel disease diagnosis and phenotype. Am J Gastroenterol 104, 1426-1434, doi:ajg200979 [pii]10.1038/ajg.2009.79 (2009). [Link]
29.
Israeli, E. et al. Anti-Saccharomyces cerevisiae and antineutrophil cytoplasmic antibodies as predictors of inflammatory bowel disease. Gut 54, 1232-1236, doi:54/9/1232 [pii]10.1136/gut.2004.060228 (2005). [Link]
30.
Bodecker-Zingmark, L., Widbom, L., Hultdin, J., Eriksson, C. & Karling, P. Anti-Saccharomyces cerevisiae Antibodies Are Only Modestly More Common in Subjects Later Developing Crohn's Disease. Dig Dis Sci 68, 608-615, doi:10.1007/s10620-022-07630-5 (2023). [Link]
31.
Arnott, I. D. et al. Sero-reactivity to microbial components in Crohn's disease is associated with disease severity and progression, but not NOD2/CARD15 genotype. Am J Gastroenterol 99, 2376-2384, doi:10.1111/j.1572-0241.2004.40417.x (2004). [Link]
32.
Choung, R. S. et al. Serologic microbial associated markers can predict Crohn's disease behaviour years before disease diagnosis. Aliment Pharmacol Ther 43, 1300-1310, doi:10.1111/apt.13641 (2016). [Link]
33.
Subramanian, J. & Simon, R. Overfitting in prediction models - is it a problem only in high dimensions? Contemp Clin Trials 36, 636-641, doi:10.1016/j.cct.2013.06.011 (2013). [Link]
34.
Ransohoff, D. F. Rules of evidence for cancer molecular-marker discovery and validation. Nat Rev Cancer 4, 309-314, doi:10.1038/nrc1322 (2004). [Link]
35.
Kern, S. E. Why your new cancer biomarker may never work: recurrent patterns and remarkable diversity in biomarker failures. Cancer Res 72, 6097-6101, doi:10.1158/0008-5472.CAN-12-3232 (2012). [Link]
36.
Argmann, C. et al. Biopsy and blood-based molecular biomarker of inflammation in IBD. Gut, doi:10.1136/gutjnl-2021-326451 (2022). [Link]
37.
Duffy, M. J. et al. Validation of new cancer biomarkers: a position statement from the European group on tumor markers. Clin Chem 61, 809-820, doi:10.1373/clinchem.2015.239863 (2015). [Link]
38.
Lee, J. C., Lyons, P. A. & McKinney, E. F. Analytical Mistakes Confound Attempted Validation: A Response to 'Transcription and DNA Methylation Patterns of Blood-Derived CD8+ T Cells Are Associated With Age and Inflammatory Bowel Disease But Do Not Predict Prognosis'. Gastroenterology 160, 2210-2211, doi:10.1053/j.gastro.2021.01.021 (2021). https://pubmed.ncbi.nlm.nih.gov/33453231/ [Link]
39.
Fagerlin, A., Zikmund-Fisher, B. J. & Ubel, P. A. Helping patients decide: ten steps to better risk communication. J Natl Cancer Inst 103, 1436-1443, doi:10.1093/jnci/djr318 (2011). [Link]
40.
Paling, J. Strategies to help patients understand risks. BMJ 327, 745-748, doi:10.1136/bmj.327.7417.745 (2003). [Link]
41.
Kumar, M., Garand, M. & Al Khodor, S. Integrating omics for a better understanding of Inflammatory Bowel Disease: a step towards personalized medicine. J Transl Med 17, 419, doi:10.1186/s12967-019-02174-1 (2019). [Link]
42.
Fan, J., Han, F. & Liu, H. Challenges of Big Data Analysis. Natl Sci Rev 1, 293-314, doi:10.1093/nsr/nwt032 (2014). [Link]
43.
Lee, J. C. et al. Gene expression profiling of CD8+ T cells predicts prognosis in patients with Crohn disease and ulcerative colitis. J Clin Invest 121, 4170-4179 (2011). [Link]
44.
McKinney, E. F., Lee, J. C., Jayne, D. R., Lyons, P. A. & Smith, K. G. T-cell exhaustion, co-stimulation and clinical outcome in autoimmunity and infection. Nature 523, 612-616, doi:nature14468 [pii]10.1038/nature14468 (2015). [Link]
45.
Lemaitre, M. et al. Association Between Use of Thiopurines or Tumor Necrosis Factor Antagonists Alone or in Combination and Risk of Lymphoma in Patients With Inflammatory Bowel Disease. JAMA 318, 1679-1686, doi:10.1001/jama.2017.16071 (2017). [Link]
46.
Tottrup, A., Erichsen, R., Svaerke, C., Laurberg, S. & Srensen, H. T. Thirty-day mortality after elective and emergency total colectomy in Danish patients with inflammatory bowel disease: a population-based nationwide cohort study. BMJ Open 2, e000823, doi:10.1136/bmjopen-2012-000823 (2012). [Link]

Abstract

Hepatitis C virus (HCV) infection remains an important global health concern. It is estimated that there are approximately 50 million people infected with HCV globally, with around 1 million new infections each year and about 242,000 deaths annually attributed to HCV-related complications. Most acute HCV infections (55–85%) become chronic due to the virus’s effective evasion strategies, with spontaneous clearance being rare once chronicity is established. This condition often progresses silently, with many individuals unaware of their infection until advanced liver damage has occurred. If left untreated, HCV can lead to severe complications, including liver cirrhosis and hepatocellular carcinoma (HCC). HCV transmission occurs mainly through percutaneous exposure to infected blood. HCV can also spread from mother to infant (vertical transmission) and, less frequently, via sexual contact.1,2 In recent years, the introduction of oral direct-acting antivirals (DAAs), with remarkable safety and effectiveness profiles, has led to a sustained virological response (SVR) in virtually all (>97%) HCV-infected patients, regardless of HCV genotype or disease stage. However, significant barriers remain, such as issues with diagnosis, access to treatment and awareness of the disease.

Here, we discuss some of the misconceptions in HCV management and provide a practical management approach grounded in evidence and clinical experience.

Topics

Hepatobiliary

Citation

Garcia A.C and Alexandrino G. Mistakes in hepatits C and how to avoid them. UEG Education 2025; 25: 14-17.

Published

2025

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UEG Mistakes In Articles
Share via Email Share on Facebook Share on X Share on LinkedIn Share on Bluesky

Log in to continue.

This content is part of Gutflix. Log in with your myUEG account, or create one free, to watch it.

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Not sure what you can access? Learn more about account types.

Mistakes in gastrostomy insertion in children and adolescents and how to avoid them

Christos Tzivinikos, Ilse Broekaert, Jorge Amil Dias, Matjaz Homan

Summary

AI Generated

Summary is not available for this content yet.

Download PDF

Was this helpful?

Thanks for your feedback.

This summary was generated by an AI large language model based on the content transcript. It is for informational purposes only and should not be considered a substitute for clinical judgment. Always rely on your professional expertise and the full clinical context when making clinical decisions.

References

Mistakes
References
Mistake 1 Mistake 2 Mistake 3 Mistake 4 Mistake 5 Mistake 6 Mistake 7 Mistake 8
1.
Verstockt, B., Parkes, M. & Lee, J. C. How Do We Predict a Patient's Disease Course and Whether They Will Respond to Specific Treatments? Gastroenterology 162, 1383-1395, doi:10.1053/j.gastro.2021.12.245 (2022). [Link]
2.
Jess, T. et al. Changes in clinical characteristics, course, and prognosis of inflammatory bowel disease during the last 5 decades: a population-based study from Copenhagen, Denmark. Inflamm Bowel Dis 13, 481-489, doi:10.1002/ibd.20036 (2007). [Link]
3.
Solberg, I. C. et al. Clinical course in Crohn's disease: results of a Norwegian population-based ten-year follow-up study. Clin Gastroenterol Hepatol 5, 1430-1438, doi:S1542-3565(07)00888-9 [pii]10.1016/j.cgh.2007.09.002 (2007). [Link]
4.
Alsoud, D., Verstockt, B., Fiocchi, C. & Vermeire, S. Breaking the therapeutic ceiling in drug development in ulcerative colitis. Lancet Gastroenterol Hepatol 6, 589-595, doi:10.1016/S2468-1253(21)00065-0 (2021). [Link]
5.
Colombel, J. F., D'Haens, G., Lee, W. J., Petersson, J. & Panaccione, R. Outcomes and Strategies to Support a Treat-to-target Approach in Inflammatory Bowel Disease: A Systematic Review. J Crohns Colitis 14, 254-266, doi:10.1093/ecco-jcc/jjz131 (2020). [Link]
6.
Sparano, J. A. et al. Adjuvant Chemotherapy Guided by a 21-Gene Expression Assay in Breast Cancer. N Engl J Med 379, 111-121, doi:10.1056/NEJMoa1804710 (2018). [Link]
7.
Cardoso, F. et al. 70-Gene Signature as an Aid to Treatment Decisions in Early-Stage Breast Cancer. N Engl J Med 375, 717-729, doi:10.1056/NEJMoa1602253 (2016). [Link]
8.
Hart, A. L. et al. What Are the Top 10 Research Questions in the Treatment of Inflammatory Bowel Disease? A Priority Setting Partnership with the James Lind Alliance. J Crohns Colitis 11, 204-211, doi:10.1093/ecco-jcc/jjw144 (2017). [Link]
9.
Noor, N. M., Verstockt, B., Parkes, M. & Lee, J. C. Personalised medicine in Crohn's disease. Lancet Gastroenterol Hepatol 5, 80-92, doi:10.1016/S2468-1253(19)30340-1 (2020). [Link]
10.
Wolters, F. L. et al. Phenotype at diagnosis predicts recurrence rates in Crohn's disease. Gut 55, 1124-1130, doi:10.1136/gut.2005.084061 (2006). [Link]
11.
Beaugerie, L., Seksik, P., Nion-Larmurier, I., Gendre, J. P. & Cosnes, J. Predictors of Crohn's disease. Gastroenterology 130, 650-656, doi:S0016-5085(05)02529-1 [pii]10.1053/j.gastro.2005.12.019 (2006). [Link]
12.
Loly, C., Belaiche, J. & Louis, E. Predictors of severe Crohn's disease. Scand J Gastroenterol 43, 948-954 (2008). [Link]
13.
Torres, J. et al. Predicting Outcomes to Optimize Disease Management in Inflammatory Bowel Diseases. J Crohns Colitis 10, 1385-1394, doi:10.1093/ecco-jcc/jjw116 (2016). [Link]
14.
Cosnes, J. et al. Factors affecting outcomes in Crohn's disease over 15 years. Gut 61, 1140-1145, doi:10.1136/gutjnl-2011-301971 (2012). [Link]
15.
Solberg, I. C. et al. Clinical course during the first 10 years of ulcerative colitis: results from a population-based inception cohort (IBSEN Study). Scand J Gastroenterol 44, 431-440, doi:907045459 [pii]10.1080/00365520802600961 (2009). [Link]
16.
Ananthakrishnan, A. N. et al. History of medical hospitalization predicts future need for colectomy in patients with ulcerative colitis. Inflamm Bowel Dis 15, 176-181, doi:10.1002/ibd.20639 (2009). [Link]
17.
Targownik, L. E., Singh, H., Nugent, Z. & Bernstein, C. N. The epidemiology of colectomy in ulcerative colitis: results from a population-based cohort. Am J Gastroenterol 107, 1228-1235, doi:10.1038/ajg.2012.127 (2012). [Link]
18.
Dulai, P. S. et al. Development and Validation of a Scoring System to Predict Outcomes of Vedolizumab Treatment in Patients With Crohn's Disease. Gastroenterology 155, 687-695 e610, doi:10.1053/j.gastro.2018.05.039 (2018). [Link]
19.
Molnar, T. et al. Predictors of relapse in patients with Crohn's disease in remission after 1 year of biological therapy. Aliment Pharmacol Ther 37, 225-233, doi:10.1111/apt.12160 (2013). [Link]
20.
Billiet, T. et al. A Matrix-based Model Predicts Primary Response to Infliximab in Crohn's Disease. J Crohns Colitis 9, 1120-1126, doi:jjv156 [pii]10.1093/ecco-jcc/jjv156 (2015). [Link]
21.
Gibson, G. Going to the negative: genomics for optimized medical prescription. Nat Rev Genet 20, 1-2, doi:10.1038/s41576-018-0061-7 (2019). [Link]
22.
Lee, J. C. et al. Genome-wide association study identifies distinct genetic contributions to prognosis and susceptibility in Crohn's disease. Nat Genet 49, 262-268, doi:10.1038/ng.3755 (2017). [Link]
23.
Biasci, D. et al. A blood-based prognostic biomarker in IBD. Gut 68, 1386-1395, doi:10.1136/gutjnl-2019-318343 (2019). [Link]
24.
Kugathasan, S. et al. Prediction of complicated disease course for children newly diagnosed with Crohn's disease: a multicentre inception cohort study. Lancet 389, 1710-1718, doi:10.1016/S0140-6736(17)30317-3 (2017). [Link]
25.
Taylor, A. E. et al. Investigating the possible causal association of smoking with depression and anxiety using Mendelian randomisation meta-analysis: the CARTA consortium. BMJ Open 4, e006141, doi:10.1136/bmjopen-2014-006141 (2014). [Link]
26.
Ferrante, M. et al. New serological markers in inflammatory bowel disease are associated with complicated disease behaviour. Gut 56, 1394-1403, doi:gut.2006.108043 [pii]10.1136/gut.2006.108043 (2007). [Link]
27.
Amre, D. K., Lu, S. E., Costea, F. & Seidman, E. G. Utility of serological markers in predicting the early occurrence of complications and surgery in pediatric Crohn's disease patients. Am J Gastroenterol 101, 645-652, doi:AJG468 [pii]10.1111/j.1572-0241.2006.00468.x (2006). [Link]
28.
Seow, C. H. et al. Novel anti-glycan antibodies related to inflammatory bowel disease diagnosis and phenotype. Am J Gastroenterol 104, 1426-1434, doi:ajg200979 [pii]10.1038/ajg.2009.79 (2009). [Link]
29.
Israeli, E. et al. Anti-Saccharomyces cerevisiae and antineutrophil cytoplasmic antibodies as predictors of inflammatory bowel disease. Gut 54, 1232-1236, doi:54/9/1232 [pii]10.1136/gut.2004.060228 (2005). [Link]
30.
Bodecker-Zingmark, L., Widbom, L., Hultdin, J., Eriksson, C. & Karling, P. Anti-Saccharomyces cerevisiae Antibodies Are Only Modestly More Common in Subjects Later Developing Crohn's Disease. Dig Dis Sci 68, 608-615, doi:10.1007/s10620-022-07630-5 (2023). [Link]
31.
Arnott, I. D. et al. Sero-reactivity to microbial components in Crohn's disease is associated with disease severity and progression, but not NOD2/CARD15 genotype. Am J Gastroenterol 99, 2376-2384, doi:10.1111/j.1572-0241.2004.40417.x (2004). [Link]
32.
Choung, R. S. et al. Serologic microbial associated markers can predict Crohn's disease behaviour years before disease diagnosis. Aliment Pharmacol Ther 43, 1300-1310, doi:10.1111/apt.13641 (2016). [Link]
33.
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Abstract

Adequate nutrition is essential for the homeostasis of fluids and nutrients, growth and thriving, especially in children. While the underlying principle of percutaneous endoscopic gastrostomy (PEG) placement is the same for both adults and children—providing a means of enteral feeding through the stomach—the indications, considerations and techniques differ owing to anatomical differences, age-dependent physiological concerns, and the age- and disease-specific needs of the child.

If feeding via nasogastric tube (NGT) or naso-jejunal tube (NJT) is necessary for a prolonged time, placement of a PEG or percutaneous endoscopic gastro-jejunal (PEG-J) tube should be considered. A PEG tube also allows the delivery of medications and venting of the stomach when needed. Nutrition via PEG facilitates the transition to out-of-hospital care and improves the quality of life (QoL) for children and families while improving the outcome of children with chronic diseases.

There are recent clinical guidelines providing guidance for PEG tube placement in children, but little advice on, e.g., choosing the right device for the right patient, details on postoperative management, removal of the PEG tube and other specific cases. The following article provides a combination of evidence-based data and the authors’ clinical experience.

Topics

Paediatrics Small Intestine & Nutrition Stomach & H. Pylori

Citation

Broekaert I.J, Dias J.A, Homan M and Tzivinikos C. Mistakes in gastrostomy insertion in children and adolescents and how to avoid them. UEG Education 2024; 24: 34-38.

Published

2024

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