LIAISON ® Calprotectin for the prediction of relapse in quiescent ulcerative colitis: The EuReCa study
Abstract
Introduction: Fecal calprotectin (FC) is established as a diagnostic marker to differentiate between inflammatory bowel diseases and non-inflammatory conditions. Furthermore, it may be effective in monitoring response to treatment, and to predict relapse during maintenance therapy. Design: This was a prospective longitudinal study carried out in Italy, France and Spain. The primary objective was to correlate the LIAISON® Calprotectin assay measurements to quiescent ulcerative colitis (UC) or relapse as assessed by clinical data. Patients were assessed every 3 months for 12 months, and at 18 months. Results: The last FC measured prior to relapse was the variable that predicted relapse in a statistically significant manner. With a 62.3 μg/g cut-off the area under the curve was 0.619, and the sensitivity was 62.9% (95% Confidence Interval [CI] 44.9%-78.5%) and specificity 63.0% (95% CI 53.1%-72.1%). Using machine learning methods, the last FC measurement was shown to have the largest impact in predicting relapse. An algorithm was developed that included other variables available following a clinician's visit, which resulted in an area under the curve of 0.754 for predicting relapse. Conclusion: In the present study FC measured by the LIAISON® Calprotectin assay on the visit before relapse is predictive of relapse in patients with quiescent UC. In a proof of concept, the accuracy of prediction can further be improved including other variables in an algorithm developed by machine learning. Trial registration: The trial is registered at clinicaltrials.gov with reference number NCT05168917.
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BibTeX
@article{fiorino2026liaison,
title = {{LIAISON ® Calprotectin for the prediction of relapse in quiescent ulcerative colitis: The EuReCa study}},
author = {Gionata Fiorino and Silvio Danese and Laurent Peyrin‐biroulet and Miquel Sans and Fabrizio Bonelli and Mariella Calleri and Claudia Zierold and Roberta Pollastro and Fabio Moretti and Alberto Malesci},
journal = {United European Gastroenterology Journal},
year = {2026},
month = sep,
doi = {10.1002/ueg2.12268},
url = {https://hal.univ-lorraine.fr/hal-04168200v1},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - LIAISON ® Calprotectin for the prediction of relapse in quiescent ulcerative colitis: The EuReCa study
AU - Gionata Fiorino
AU - Silvio Danese
AU - Laurent Peyrin‐biroulet
AU - Miquel Sans
AU - Fabrizio Bonelli
AU - Mariella Calleri
AU - Claudia Zierold
AU - Roberta Pollastro
AU - Fabio Moretti
AU - Alberto Malesci
PY - 2026
DA - 2026/09/17
JO - United European Gastroenterology Journal
DO - 10.1002/ueg2.12268
UR - https://hal.univ-lorraine.fr/hal-04168200v1
AB - Introduction: Fecal calprotectin (FC) is established as a diagnostic marker to differentiate between inflammatory bowel diseases and non-inflammatory conditions. Furthermore, it may be effective in monitoring response to treatment, and to predict relapse during maintenance therapy. Design: This was a prospective longitudinal study carried out in Italy, France and Spain. The primary objective was to correlate the LIAISON® Calprotectin assay measurements to quiescent ulcerative colitis (UC) or relapse as assessed by clinical data. Patients were assessed every 3 months for 12 months, and at 18 months. Results: The last FC measured prior to relapse was the variable that predicted relapse in a statistically significant manner. With a 62.3 μg/g cut-off the area under the curve was 0.619, and the sensitivity was 62.9% (95% Confidence Interval [CI] 44.9%-78.5%) and specificity 63.0% (95% CI 53.1%-72.1%). Using machine learning methods, the last FC measurement was shown to have the largest impact in predicting relapse. An algorithm was developed that included other variables available following a clinician's visit, which resulted in an area under the curve of 0.754 for predicting relapse. Conclusion: In the present study FC measured by the LIAISON® Calprotectin assay on the visit before relapse is predictive of relapse in patients with quiescent UC. In a proof of concept, the accuracy of prediction can further be improved including other variables in an algorithm developed by machine learning. Trial registration: The trial is registered at clinicaltrials.gov with reference number NCT05168917.
SN - 2050-6406
SN - 2050-6414
ER -