# Correlation of a clinical activity index in comparison to frequently measured laboratory values in inflammatory bowel disease

## TL;DR

This study finds that a symptom-based index correlates with lab tests in IBD patients, helping identify those needing closer monitoring.

## Contribution

The study demonstrates that a clinical activity index correlates with lab values in IBD, offering a tool for personalized monitoring.

## Key findings

- Fecal calprotectin, hemoglobin, and CRP significantly correlate with the clinical activity index in both UC and CD.
- Ferritin shows no significant correlation with the activity index in IBD patients.
- The activity index helps identify active disease and may improve early detection of flares.

## Abstract

Several laboratory tests are used to monitor disease activity and possible complications in patients with inflammatory bowel disease (IBD). Due to limited resources, it is important to identify patients who benefit the most from tight laboratory testing and follow-up. We sought to assess the correlation between a symptom-based clinical activity index and commonly monitored laboratory tests in a large patient population.

The Finnish IBD registry records a validated IBD symptom index questionnaire (IBD-SI) that measures disease activity and the influence of IBD on daily life in patients with ulcerative colitis (UC) and Crohn’s disease (CD). The activity index was compared with the commonly measured laboratory values of fecal calprotectin (FC), hemoglobin (Hb), ferritin, and C-reactive protein (CRP).

A total of 5044 IBD patients with 171,967 activity index measurement pairs were included. FC, Hb, and CRP correlated significantly with the activity index in both UC (Spearman’s r 0.383, −0.212, 0.175; p < 0.001) and CD (Spearman’s r 0.156, −0.176, 0.152; p < 0.001). No correlation between the activity index and ferritin (Spearman’s r 0.038 [UC], 0.005 [CD]; p = 0.020, p = 0.825) was found.

The activity index is a useful tool in the assessment of IBD activity. Active or inactive disease can be identified better, which may be beneficial in planning more personalized follow-up strategies. Tight monitoring of disease can be better targeted to the correct patient population, and the onset of disease flare may be caught at an earlier stage.