Real-time tool to display the predicted disease course and treatment response for children with Crohn's disease

Corey A. Siegel, Lori S. Siegel, Jeffrey S. Hyams, Subra Kugathasan, James Markowitz, Joel Rosh, Neal Leleiko, David R. MacK, Wallace Crandall, Jonathan Evans, David J. Keljo, Anthony R. Otley, Maria Oliva-Hemker, Sharmayne Farrior, Christine R. Langton, Iwona T. Wrobel, Ghassan Wahbeh, J. Antonio Quiros, Gary Silber, Ron J. Bahar & 2 others Bruce E. Sands, Marla C. Dubinsky

Research output: Contribution to journalArticle

53 Citations (Scopus)

Abstract

Background: Immunomodulators and biologics are effective treatments for children with Crohn's disease (CD). The challenge of communicating the anticipated disease course with and without therapy to patients and parents is a barrier to the timely use of these agents. The aim of this project was to develop a tool to graphically display the predicted risks of CD and expected benefits of therapy. Methods: Using prospectively collected data from 796 pediatric CD patients we developed a model using system dynamics analysis (SDA). The primary model outcome is the probability of developing a CD-related complication. Input variables include patient and disease characteristics, magnitude of serologic immune responses expressed as the quartile sum score (QSS), and exposure to medical treatments. Results: Multivariate Cox proportional analyses show variables contributing a significant increase in the hazard ratio (HR) for a disease complication include female gender, older age at diagnosis, small bowel or perianal disease, and a higher QSS. As QSS increases, the HR for early use of corticosteroids increases, in contrast to a decreasing HR with early use of immunomodulators, early or late biologics, and early combination therapy. The concordance index for the model is 0.81. Using SDA, results of the Cox analyses are transformed into a simple graph displaying a real-time individualized probability of disease complication and treatment response. Conclusions: We have developed a tool to predict and communicate individualized risks of CD complications and how this is modified by treatment. Once validated, it can be used at the bedside to facilitate patient decision making.

Original languageEnglish (US)
Pages (from-to)30-38
Number of pages9
JournalInflammatory Bowel Diseases
Volume17
Issue number1
DOIs
StatePublished - Jan 1 2011
Externally publishedYes

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Crohn Disease
Immunologic Factors
Systems Analysis
Biological Products
Therapeutics
Secondary Prevention
Decision Making
Adrenal Cortex Hormones
Parents

All Science Journal Classification (ASJC) codes

  • Immunology and Allergy
  • Gastroenterology

Cite this

Siegel, C. A., Siegel, L. S., Hyams, J. S., Kugathasan, S., Markowitz, J., Rosh, J., ... Dubinsky, M. C. (2011). Real-time tool to display the predicted disease course and treatment response for children with Crohn's disease. Inflammatory Bowel Diseases, 17(1), 30-38. https://doi.org/10.1002/ibd.21386
Siegel, Corey A. ; Siegel, Lori S. ; Hyams, Jeffrey S. ; Kugathasan, Subra ; Markowitz, James ; Rosh, Joel ; Leleiko, Neal ; MacK, David R. ; Crandall, Wallace ; Evans, Jonathan ; Keljo, David J. ; Otley, Anthony R. ; Oliva-Hemker, Maria ; Farrior, Sharmayne ; Langton, Christine R. ; Wrobel, Iwona T. ; Wahbeh, Ghassan ; Quiros, J. Antonio ; Silber, Gary ; Bahar, Ron J. ; Sands, Bruce E. ; Dubinsky, Marla C. / Real-time tool to display the predicted disease course and treatment response for children with Crohn's disease. In: Inflammatory Bowel Diseases. 2011 ; Vol. 17, No. 1. pp. 30-38.
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author = "Siegel, {Corey A.} and Siegel, {Lori S.} and Hyams, {Jeffrey S.} and Subra Kugathasan and James Markowitz and Joel Rosh and Neal Leleiko and MacK, {David R.} and Wallace Crandall and Jonathan Evans and Keljo, {David J.} and Otley, {Anthony R.} and Maria Oliva-Hemker and Sharmayne Farrior and Langton, {Christine R.} and Wrobel, {Iwona T.} and Ghassan Wahbeh and Quiros, {J. Antonio} and Gary Silber and Bahar, {Ron J.} and Sands, {Bruce E.} and Dubinsky, {Marla C.}",
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Siegel, CA, Siegel, LS, Hyams, JS, Kugathasan, S, Markowitz, J, Rosh, J, Leleiko, N, MacK, DR, Crandall, W, Evans, J, Keljo, DJ, Otley, AR, Oliva-Hemker, M, Farrior, S, Langton, CR, Wrobel, IT, Wahbeh, G, Quiros, JA, Silber, G, Bahar, RJ, Sands, BE & Dubinsky, MC 2011, 'Real-time tool to display the predicted disease course and treatment response for children with Crohn's disease', Inflammatory Bowel Diseases, vol. 17, no. 1, pp. 30-38. https://doi.org/10.1002/ibd.21386

Real-time tool to display the predicted disease course and treatment response for children with Crohn's disease. / Siegel, Corey A.; Siegel, Lori S.; Hyams, Jeffrey S.; Kugathasan, Subra; Markowitz, James; Rosh, Joel; Leleiko, Neal; MacK, David R.; Crandall, Wallace; Evans, Jonathan; Keljo, David J.; Otley, Anthony R.; Oliva-Hemker, Maria; Farrior, Sharmayne; Langton, Christine R.; Wrobel, Iwona T.; Wahbeh, Ghassan; Quiros, J. Antonio; Silber, Gary; Bahar, Ron J.; Sands, Bruce E.; Dubinsky, Marla C.

In: Inflammatory Bowel Diseases, Vol. 17, No. 1, 01.01.2011, p. 30-38.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Real-time tool to display the predicted disease course and treatment response for children with Crohn's disease

AU - Siegel, Corey A.

AU - Siegel, Lori S.

AU - Hyams, Jeffrey S.

AU - Kugathasan, Subra

AU - Markowitz, James

AU - Rosh, Joel

AU - Leleiko, Neal

AU - MacK, David R.

AU - Crandall, Wallace

AU - Evans, Jonathan

AU - Keljo, David J.

AU - Otley, Anthony R.

AU - Oliva-Hemker, Maria

AU - Farrior, Sharmayne

AU - Langton, Christine R.

AU - Wrobel, Iwona T.

AU - Wahbeh, Ghassan

AU - Quiros, J. Antonio

AU - Silber, Gary

AU - Bahar, Ron J.

AU - Sands, Bruce E.

AU - Dubinsky, Marla C.

PY - 2011/1/1

Y1 - 2011/1/1

N2 - Background: Immunomodulators and biologics are effective treatments for children with Crohn's disease (CD). The challenge of communicating the anticipated disease course with and without therapy to patients and parents is a barrier to the timely use of these agents. The aim of this project was to develop a tool to graphically display the predicted risks of CD and expected benefits of therapy. Methods: Using prospectively collected data from 796 pediatric CD patients we developed a model using system dynamics analysis (SDA). The primary model outcome is the probability of developing a CD-related complication. Input variables include patient and disease characteristics, magnitude of serologic immune responses expressed as the quartile sum score (QSS), and exposure to medical treatments. Results: Multivariate Cox proportional analyses show variables contributing a significant increase in the hazard ratio (HR) for a disease complication include female gender, older age at diagnosis, small bowel or perianal disease, and a higher QSS. As QSS increases, the HR for early use of corticosteroids increases, in contrast to a decreasing HR with early use of immunomodulators, early or late biologics, and early combination therapy. The concordance index for the model is 0.81. Using SDA, results of the Cox analyses are transformed into a simple graph displaying a real-time individualized probability of disease complication and treatment response. Conclusions: We have developed a tool to predict and communicate individualized risks of CD complications and how this is modified by treatment. Once validated, it can be used at the bedside to facilitate patient decision making.

AB - Background: Immunomodulators and biologics are effective treatments for children with Crohn's disease (CD). The challenge of communicating the anticipated disease course with and without therapy to patients and parents is a barrier to the timely use of these agents. The aim of this project was to develop a tool to graphically display the predicted risks of CD and expected benefits of therapy. Methods: Using prospectively collected data from 796 pediatric CD patients we developed a model using system dynamics analysis (SDA). The primary model outcome is the probability of developing a CD-related complication. Input variables include patient and disease characteristics, magnitude of serologic immune responses expressed as the quartile sum score (QSS), and exposure to medical treatments. Results: Multivariate Cox proportional analyses show variables contributing a significant increase in the hazard ratio (HR) for a disease complication include female gender, older age at diagnosis, small bowel or perianal disease, and a higher QSS. As QSS increases, the HR for early use of corticosteroids increases, in contrast to a decreasing HR with early use of immunomodulators, early or late biologics, and early combination therapy. The concordance index for the model is 0.81. Using SDA, results of the Cox analyses are transformed into a simple graph displaying a real-time individualized probability of disease complication and treatment response. Conclusions: We have developed a tool to predict and communicate individualized risks of CD complications and how this is modified by treatment. Once validated, it can be used at the bedside to facilitate patient decision making.

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