Novel nomogram for differential diagnosis of UGT1A1 gene mutation-associated unconjugated hyperbilirubinemia with hemolytic diseases

Abstract

BACKGROUND

Chronic unconjugated hyperbilirubinemia requires careful differentiation between disorders caused by uridine diphosphate glucuronosyltransferase 1A1 (UGT1A1) gene mutation (Gilbert’s and Crigler-Najjar’s syndromes) and those caused by hemolytic diseases, as treatment goals and prognoses vary significantly. Due to the clinical overlap and the complexity of current specialized testing, accurately distinguishing these two etiologies presents a major clinical challenge.

AIM

To establish a convenient nomogram model to distinguish chronic unconjugated hyperbilirubinemia associated with UGT1A1 gene mutation from hemolytic diseases.

METHODS

In this retrospective study, patients diagnosed with chronic unconjugated hyperbilirubinemia at Beijing YouAn Hospital from January 2022 to May 2025 were enrolled and categorized into the UGT1A1 mutation-associated group and the hemolytic disease-associated group. To create a nomogram, least absolute shrinkage and selection operator regression and multivariate logistic regression were used to screen for differential diagnosis factors. The performance of the nomogram was evaluated by the receiver operating characteristic curve, precision-recall curve, calibration curve, and decision curve analysis.

RESULTS

A total of 429 patients (357 with UGT1A1 mutation-associated group, 72 with hemolytic disease-associated group) were enrolled. Patients diagnosed from January 2022 to December 2024 were randomly divided into training (n = 265) and internal validation (n = 114) cohorts. Patients diagnosed from January 2025 to May 2025 (n = 50) were used for external validation. Four key variables - abnormality of peripheral blood smear, hematocrit, red cell distribution width standard deviation, and reticulocyte percentage - were selected to construct the nomogram. External validation yielded an area under the receiver operating characteristic curve of 0.986, sensitivity of 100%, specificity of 90%, area under the precision-recall curve of 0.938, and F1-score of 0.833. Calibration curves showed good agreement between predicted and actual outcomes. Decision curve analysis confirmed the clinical utility of this nomogram.

CONCLUSION

We developed an effective nomogram model for the differential diagnosis of UGT1A1 gene mutation-associated and hemolytic disease-associated unconjugated hyperbilirubinemia, which improves clinical preliminary screening.

Keywords: Hyperbilirubinemia; Gilbert’s syndrome; Hemolysis; Diagnosis; Nomogram

Core Tip: Clinical characteristic overlap and the need for complex specialized testing make it challenging to distinguish uridine diphosphate glucuronosyltransferase 1A1 mutations from hemolytic diseases in patients with chronic unconjugated hyperbilirubinemia. In a genetically confirmed cohort, we applied least absolute shrinkage and selection operator and logistic regression to identify four variables for differential diagnosis: Abnormal peripheral blood smear, hematocrit, red cell distribution width standard deviation, and reticulocyte percentage. These variables were used to establish a nomogram model, which achieved an area under the receiver operating characteristic curve of 0.986 and an area under precision-recall curve of 0.938. This model provides a simple, interpretable, and cost-effective tool for early screening and triage, potentially reducing the need for complex testing.