Development of a Simple, Serum Biomarker-based Model Predictive of the Need for Early Biologic Therapy in Crohn's Disease

Danny Con, Nina Parthasarathy, Maria Bishara, Raphael P. Luber, Neetima Joshi, Anna Wan, James A. Rickard, Tony Long, Declan J. Connoley, Miles P. Sparrow, Peter R. Gibson, Daniel R. van Langenberg, Abhinav Vasudevan

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3 Citations (Scopus)

Abstract

BACKGROUND: Early or first-line treatment with biologics, as opposed to conventional immunomodulators, is not always necessary to achieve remission in Crohn's disease [CD] and may not be cost-effective. This study aimed to develop a simple model to predict the need for early biologic therapy, in order to risk-stratify CD patients and guide initial treatment selection. METHODS: A model-building study using supervised statistical learning methods was conducted using a retrospective cohort across two tertiary centres. All biologic-naïve CD patients who commenced an immunomodulator between January 1, 2004 and December 31, 2016, were included. A predictive score was derived using Cox regression modelling of immunomodulator failure, and was internally validated using bootstrap resampling. RESULTS: Of 410 patients [median age 37 years, 47% male, median disease duration 4.7 years], 229 [56%] experienced immunomodulator failure [39 required surgery, 24 experienced a new stricture, 44 experienced a new fistula/abscess, 122 required biologic escalation] with a median time to failure of 16 months. Independent predictors of treatment failure included raised C-reactive protein [CRP], low albumin, complex disease behaviour, younger age, and baseline steroids. Highest CRP and lowest albumin measured within the 3 months preceding immunomodulator initiation outperformed baseline measurements. After model selection, only highest CRP and lowest albumin remained and the resultant Crohn's Immunomodulator CRP-Albumin [CICA] index demonstrated robust optimism-corrected discriminative performance at 12, 24, and 36 months (area under the curve [AUC] 0.84, 0.83, 0.81, respectively). CONCLUSIONS: The derived CICA index based on simple, widely available markers is feasible, internally valid, and has a high utility in predicting immunomodulator failure. This requires external, prospective validation.

Original languageEnglish
Pages (from-to)583-593
Number of pages11
JournalJournal of Crohn's and Colitis
Volume15
Issue number4
DOIs
Publication statusPublished - 6 Apr 2021

Keywords

  • Precision medicine
  • prediction
  • predictive model
  • statistical learning

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