Patient-Reported Outcomes Are a Practical Tool for Monitoring Crohn's Disease Activity in Real-World Care

Crohn's disease activity scores are used to "quantify" disease activity, for clinical care, and research. They can be impractical to use repeatedly in busy clinical settings. In a large real-world dataset, we therefore investigated how often each of indices, patient-reported outcomes 3 (PRO3), patient-reported outcomes 2 (PRO2), Crohn's Disease Activity Index (CDAI), and Harvey-Bradshaw Index (HBI), could be calculated and explored the correlation amongst them.

Crohn's Colitis Care is a cloud-based inflammatory bowel disease-specific electronic medical record used in Australasia. Data to generate disease activity indices are sought at each clinical assessment. Completion rates of, and agreement between PRO2 and PRO3 with CDAI and HBI were calculated. Statistical analysis was performed using the Pearson correlation coefficient and simple linear regression.

Of 26,230 clinical assessments for people with Crohn's disease, CDAI was available in 6509 (24.8%) of assessments, HBI in 7286 (27.8%), PRO3 in 21,234 (81.0%), and PRO2 in 21,416 (81.6%). There was 87.6% agreement in disease severity categorization between PRO2 and CDAI, Pearson coefficient 0.85, and Coefficient of Determination (R²) value = 0.73. There was 93.3% agreement in disease severity categorization between PRO2 and HBI, Pearson coefficient 0.94, and R² value = 0.89. Similarly, there was 86.8% agreement in disease severity categorization between PRO3 and CDAI, Pearson coefficient 0.95, and R² value = 0.90. There was 88.2% agreement in disease severity categorization between PRO3 and HBI, Pearson coefficient 0.93, and R² value = 0.86.

The markedly higher rate of available PRO2 and PRO3 scores compared to CDAI and HBIs makes it more pragmatic to use patient-reported outcome measures in data from real-world care. Moreover, the accuracy and reliability of patient-reported outcome measures reflected in its very strong correlation with both CDAI and HBI severity categories makes it a reliable clinical measure to adopt in clinical practice, making large scale analysis supported by digital medicine easier and thus enhancing real-world clinical research.