Objectives: The diagnostic accuracy of faecal calprotectin (FC) concentration for paediatric inflammatory bowel disease (IBD) is well described at the population level, but not at the individual level. We reassessed the diagnostic accuracy of FC in children with suspected IBD and developed an individual risk prediction rule using individual patient data.
Methods: MEDLINE, EMBASE, DARE, and MEDION databases were searched to identify cohort studies evaluating the diagnostic performance of FC in paediatric patients suspected of having IBD. A standard study-level meta-analysis was performed. In an individual patient data meta-analysis, we reanalysed the diagnostic accuracy on a merged patient dataset. Using logistic regression analysis we investigated whether and how the FC value and patient characteristics influence the diagnostic precision. A prediction rule was derived for use in clinical practice and implemented in a spreadsheet calculator.
Results: According to the study-level meta-analysis (9 studies, describing 853 patients), FC has a high overall sensitivity of 0.97 (95% confidence interval [CI] 0.92-0.99) and a specificity of 0.70 (0.59-0.79) for diagnosing IBD. In the patient-level pooled analysis of 742 patients from 8 diagnostic accuracy studies, we calculated that at an FC cutoff level of 50 μg/g there would be 17% (95% CI 15-20) false-positive and 2% (1-3) false-negative results. The final logistic regression model was based on individual data of 545 patients and included both FC level and age. The area under the receiver operating characteristic curve of this derived prediction model was 0.92 (95% CI 0.89-0.94).
Conclusions: In high-prevalence circumstances, FC can be used as a noninvasive biomarker of paediatric IBD with only a small risk of missing cases. To quantify the individual patients' risk, we developed a simple prediction model based on FC concentration and age. Although the derived prediction rule cannot substitute the clinical diagnostic process, it can help in selecting patients for endoscopic evaluation.