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International Journal of Colorectal Disease

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01-10-2019 | Anemia | Original Article

Predictive parameters for the clinical course of Crohn’s disease: development of a simple and reliable risk model

Authors: Andreas Stallmach, Bernd Bokemeyer, Ulf Helwig, Andreas Lügering, Niels Teich, Imma Fischer, Stefan Rath, Dorothee Lang, Carsten Schmidt, on behalf of the EPIC Study Group

Published in: International Journal of Colorectal Disease | Issue 10/2019

Abstract

Purpose

The aim of our study was to identify clinical parameters in recently diagnosed Crohn’s disease (CD) patients for prediction of their disease course.

Methods

EPIC (Early Predictive parameters of Immunosuppressive therapy in Crohn’s disease) is a prospective, observational study in 341 patients with a recent CD diagnosis (≤ 6 months), and naïve to immunosuppressants (IS) and anti-tumor necrosis factor α (TNF) agents. Patient characteristics were documented up to 2 years. In line with national and international guidelines, a complicated disease course was defined as need for immunosuppressants and/or anti-TNF agents, and CD-related hospitalization with or without immunosuppressants and/or anti-TNF agents.

Results

A total of 212 CD patients were analyzed of whom 57 (27%) had an uncomplicated disease within 24 months, while 155 (73%) had a complicated disease course: need for IS and/or anti-TNF agents (N = 115), CD-related hospitalization with or without IS/anti-TNF agents (N = 40). Identified risk predictors for a complicated disease were as follows: age at onset < 40 years (OR 2.3; 95% CI 1.2–4.5), anemia (OR 2.1; 95% CI 1.1–4.2), and treatment with systemic corticosteroids at first flare (OR 2.2; 95% CI 1.1–4.7). These three parameters were used to develop a risk model allowing prediction of the future disease course.

Conclusion

Our three-parameter model enables an assessment of each CD patient’s risk to develop a complicated disease course. Due to the easy accessibility of these parameters, this model can be utilized in daily clinical care to assist selecting the initial treatment for each individual patient.

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Cosnes J, Cattan S, Blain A, Beaugerie L, Carbonnel F, Parc R, Gendre JP (2002) Long-term evolution of disease behavior of Crohn’s disease. Inflamm Bowel Dis 8(4):244–250CrossRefPubMed

Henriksen M, Jahnsen J, Lygren I, Aadland E, Schulz T, Vatn MH, Moum B (2007) Clinical course in Crohn’s disease: results of a five-year population-based follow-up study (the IBSEN study). Scand J Gastroenterol 42(5):602–610. https://doi.org/10.1080/00365520601076124 CrossRefPubMed

Jess T, Riis L, Vind I, Winther KV, Borg S, Binder V, Langholz E, Thomsen OO, Munkholm P (2007) 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(4):481–489. https://doi.org/10.1002/ibd.20036 CrossRefPubMed

D'Haens G, Baert F, van Assche G, Caenepeel P, Vergauwe P, Tuynman H, De Vos M, van Deventer S, Stitt L, Donner A, Vermeire S, Van de Mierop FJ, Coche JC, van der Woude J, Ochsenkuhn T, van Bodegraven AA, Van Hootegem PP, Lambrecht GL, Mana F, Rutgeerts P, Feagan BG, Hommes D (2008) Early combined immunosuppression or conventional management in patients with newly diagnosed Crohn’s disease: an open randomised trial. Lancet 371(9613):660–667. https://doi.org/10.1016/s0140-6736(08)60304-9 CrossRefPubMed

Sandborn WJ (2008) Current directions in IBD therapy: what goals are feasible with biological modifiers? Gastroenterology 135(5):1442–1447. https://doi.org/10.1053/j.gastro.2008.09.053 CrossRefPubMed

Preiss JC, Bokemeyer B, Buhr HJ, Dignass A, Hauser W, Hartmann F, Herrlinger KR, Kaltz B, Kienle P, Kruis W, Kucharzik T, Langhorst J, Schreiber S, Siegmund B, Stallmach A, Stange EF, Stein J, Hoffmann JC (2014) Updated German clinical practice guideline on “Diagnosis and treatment of Crohn’s disease” 2014. Z Gastroenterol 52(12):1431–1484. https://doi.org/10.1055/s-0034-1385199 CrossRefPubMed

Gomollon F, Dignass A, Annese V, Tilg H, Van Assche G, Lindsay JO, Peyrin-Biroulet L, Cullen GJ, Daperno M, Kucharzik T, Rieder F, Almer S, Armuzzi A, Harbord M, Langhorst J, Sans M, Chowers Y, Fiorino G, Juillerat P, Mantzaris GJ, Rizzello F, Vavricka S, Gionchetti P, Ecco (2017) 3rd European Evidence-based Consensus on the Diagnosis and Management of Crohn's Disease 2016: Part 1: diagnosis and medical management. J Crohns Colitis 11(1):3–25. https://doi.org/10.1093/ecco-jcc/jjw168 CrossRefPubMed

Beaugerie L, Seksik P, Nion-Larmurier I, Gendre JP, Cosnes J (2006) Predictors of Crohn’s disease. Gastroenterology 130(3):650–656. https://doi.org/10.1053/j.gastro.2005.12.019 CrossRefPubMed

Torres J, Caprioli F, Katsanos KH, Lobaton T, Micic D, Zeroncio M, Van Assche G, Lee JC, Lindsay JO, Rubin DT, Panaccione R, Colombel JF (2016) Predicting outcomes to optimize disease management in inflammatory bowel diseases. J Crohns Colitis 10(12):1385–1394. https://doi.org/10.1093/ecco-jcc/jjw116 CrossRefPubMedPubMedCentral

10.

Moon CM, Park DI, Kim ER, Kim YH, Lee CK, Lee SH, Kim JH, Huh KC, Jung SA, Yoon SM, Song HJ, Jang HJ, Kim YS, Lee KM, Shin JE (2014) Clinical features and predictors of clinical outcomes in Korean patients with Crohn’s disease: a Korean association for the study of intestinal diseases multicenter study. J Gastroenterol Hepatol 29(1):74–82. https://doi.org/10.1111/jgh.12369 CrossRefPubMed

11.

Niewiadomski O, Studd C, Hair C, Wilson J, Ding NS, Heerasing N, Ting A, McNeill J, Knight R, Santamaria J, Prewett E, Dabkowski P, Dowling D, Alexander S, Allen B, Popp B, Connell W, Desmond P, Bell S (2015) Prospective population-based cohort of inflammatory bowel disease in the biologics era: disease course and predictors of severity. J Gastroenterol Hepatol 30(9):1346–1353. https://doi.org/10.1111/jgh.12967 CrossRefPubMed

12.

Loly C, Belaiche J, Louis E (2008) Predictors of severe Crohn’s disease. Scand J Gastroenterol 43(8):948–954CrossRefPubMed

13.

Kruis W, Katalinic A, Klugmann T, Franke GR, Weismuller J, Leifeld L, Ceplis-Kastner S, Reimers B, Bokemeyer B (2013) Predictive factors for an uncomplicated long-term course of Crohn’s disease: a retrospective analysis. J Crohns Colitis 7(7):e263–e270. https://doi.org/10.1016/j.crohns.2012.10.012 CrossRefPubMed

14.

Yang CH, Ding J, Gao Y, Chen X, Yang ZB, Xiao SD (2011) Risk factors that predict the requirement of aggressive therapy among Chinese patients with Crohn’s disease. J Dig Dis 12(2):99–104. https://doi.org/10.1111/j.1751-2980.2011.00484.x CrossRefPubMed

15.

Wolters FL, Russel MG, Sijbrandij J, Ambergen T, Odes S, Riis L, Langholz E, Politi P, Qasim A, Koutroubakis I, Tsianos E, Vermeire S, Freitas J, van Zeijl G, Hoie O, Bernklev T, Beltrami M, Rodriguez D, Stockbrugger RW, Moum B (2006) Phenotype at diagnosis predicts recurrence rates in Crohn’s disease. Gut 55(8):1124–1130. https://doi.org/10.1136/gut.2005.084061 CrossRefPubMedPubMedCentral

16.

Solberg IC, Vatn MH, Hoie O, Stray N, Sauar J, Jahnsen J, Moum B, Lygren I (2007) Clinical course in Crohn’s disease: results of a Norwegian population-based ten-year follow-up study. Clin Gastroenterol Hepatol 5(12):1430–1438. https://doi.org/10.1016/j.cgh.2007.09.002 CrossRefPubMed

17.

Tarrant KM, Barclay ML, Frampton CM, Gearry RB (2008) Perianal disease predicts changes in Crohn’s disease phenotype-results of a population-based study of inflammatory bowel disease phenotype. Am J Gastroenterol 103(12):3082–3093. https://doi.org/10.1111/j.1572-0241.2008.02212.x CrossRefPubMed

18.

Romberg-Camps MJ, Dagnelie PC, Kester AD, Hesselink-van de Kruijs MA, Cilissen M, Engels LG, Van Deursen C, Hameeteman WH, Wolters FL, Russel MG, Stockbrugger RW (2009) Influence of phenotype at diagnosis and of other potential prognostic factors on the course of inflammatory bowel disease. Am J Gastroenterol 104(2):371–383. https://doi.org/10.1038/ajg.2008.38 CrossRefPubMed

19.

Thia KT, Sandborn WJ, Harmsen WS, Zinsmeister AR, Loftus EV Jr (2010) Risk factors associated with progression to intestinal complications of Crohn’s disease in a population-based cohort. Gastroenterology 139(4):1147–1155. https://doi.org/10.1053/j.gastro.2010.06.070 CrossRefPubMed

20.

Ramadas AV, Gunesh S, Thomas GA, Williams GT, Hawthorne AB (2010) Natural history of Crohn’s disease in a population-based cohort from Cardiff (1986-2003): a study of changes in medical treatment and surgical resection rates. Gut 59(9):1200–1206. https://doi.org/10.1136/gut.2009.202101 CrossRefPubMed

21.

Wenger S, Nikolaus S, Howaldt S, Bokemeyer B, Sturm A, Preiss JC, Schoepfer AM, Stallmach A, Schmidt C (2012) Predictors for subsequent need for immunosuppressive therapy in early Crohn’s disease. J Crohns Colitis 6(1):21–28. https://doi.org/10.1016/j.crohns.2011.06.006 CrossRefPubMed

22.

Mow WS, Vasiliauskas EA, Lin YC, Fleshner PR, Papadakis KA, Taylor KD, Landers CJ, Abreu-Martin MT, Rotter JI, Yang H, Targan SR (2004) Association of antibody responses to microbial antigens and complications of small bowel Crohn’s disease. Gastroenterology 126(2):414–424CrossRefPubMed

23.

Kiss LS, Papp M, Lovasz BD, Vegh Z, Golovics PA, Janka E, Varga E, Szathmari M, Lakatos PL (2012) High-sensitivity C-reactive protein for identification of disease phenotype, active disease, and clinical relapses in Crohn’s disease: a marker for patient classification? Inflamm Bowel Dis 18(9):1647–1654. https://doi.org/10.1002/ibd.21933 CrossRefPubMed

24.

Weersma RK, Stokkers PC, van Bodegraven AA, van Hogezand RA, Verspaget HW, de Jong DJ, van der Woude CJ, Oldenburg B, Linskens RK, Festen EA, van der Steege G, Hommes DW, Crusius JB, Wijmenga C, Nolte IM, Dijkstra G (2009) Molecular prediction of disease risk and severity in a large Dutch Crohn’s disease cohort. Gut 58(3):388–395. https://doi.org/10.1136/gut.2007.144865 CrossRefPubMed

25.

Billiet T, Ferrante M, Van Assche G (2014) The use of prognostic factors in inflammatory bowel diseases. Curr Gastroenterol Rep 16(11):416. https://doi.org/10.1007/s11894-014-0416-y CrossRefPubMed

Title: Predictive parameters for the clinical course of Crohn’s disease: development of a simple and reliable risk model
Authors: Andreas Stallmach
Bernd Bokemeyer
Ulf Helwig
Andreas Lügering
Niels Teich
Imma Fischer
Stefan Rath
Dorothee Lang
Carsten Schmidt
on behalf of the EPIC Study Group
Publication date: 01-10-2019
Publisher: Springer Berlin Heidelberg
Keywords: Anemia
Crohn's Disease
Published in: International Journal of Colorectal Disease / Issue 10/2019
Print ISSN: 0179-1958
Electronic ISSN: 1432-1262
DOI: https://doi.org/10.1007/s00384-019-03369-0

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Predictive parameters for the clinical course of Crohn’s disease: development of a simple and reliable risk model

Abstract

Purpose

Methods

Results

Conclusion

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Purpose

Methods

Results

Conclusion

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