Dynamic Risk Prediction of Response to Ursodeoxycholic Acid Among Patients with Primary Biliary Cholangitis in the USA.

BACKGROUND

Ursodeoxycholic acid (UDCA) remains the first-line therapy for primary biliary cholangitis (PBC); however, inadequate treatment response (ITR) is common. The UK-PBC Consortium developed the modified UDCA Response Score (m-URS) to predict ITR (using alkaline phosphatase [ALP] > 1.67 times the upper limit of normal [*ULN]) at 12 months post-UDCA initiation). Using data from the US-based Fibrotic Liver Disease Consortium, we assessed the m-URS in our multi-racial cohort. We then used a dynamic modeling approach to improve prediction accuracy.

METHODS

Using data collected at the time of UDCA initiation, we assessed the m-URS using the original formula; then, by calibrating coefficients to our data, we also assessed whether it remained accurate when using Paris II criteria for ITR. Next, we developed and validated a dynamic risk prediction model that included post-UDCA initiation laboratory data.

RESULTS

Among 1578 patients (13% men; 8% African American, 9% Asian American/American Indian/Pacific Islander; 25% Hispanic), the rate of ITR was 27% using ALP > 1.67*ULN and 45% using Paris II criteria. M-URS accuracy was "very good" (AUROC = 0.87, sensitivity = 0.62, and specificity = 0.82) for ALP > 1.67*ULN and "moderate" (AUROC = 0.74, sensitivity = 0.57, and specificity = 0.70) for Paris II. Our dynamic model significantly improved accuracy for both definitions of ITR (ALP > 1.67*ULN: AUROC = 0.91; Paris II: AUROC = 0.81); specificity approached 100%. Roughly 9% of patients in our cohort were at the highest risk of ITR.

CONCLUSIONS

Early identification of patients who will not respond to UDCA treatment using a dynamic prediction model based on longitudinal, repeated risk factor measurements may facilitate earlier introduction of adjuvant treatment.