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Risk factor analysis and nomogram development for steatorrhea in idiopathic chronic pancreatitis
Yu Liu1,2, Xiao Yi Yin3, Dan Wang2
1Department of Gastroenterology and Hepatology, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu Province, China.
Journal of Digestive Diseases
|June 15, 2022
Summary
This study identified male sex, diabetes, and young age as key predictors for steatorrhea in idiopathic chronic pancreatitis (ICP). A predictive nomogram was developed to aid early diagnosis and management of pancreatic exocrine insufficiency (PEI).
Area of Science:
- Gastroenterology
- Clinical Prediction Modeling
- Pancreatic Diseases
Background:
- Steatorrhea is a significant indicator of pancreatic exocrine insufficiency (PEI), often linked to pancreatitis complications.
- Idiopathic chronic pancreatitis (ICP) presents challenges in predicting steatorrhea development.
- Early identification of steatorrhea risk is crucial for timely intervention.
Purpose of the Study:
- To identify predictors of steatorrhea in patients with idiopathic chronic pancreatitis (ICP).
- To develop and validate a nomogram for predicting steatorrhea risk in ICP patients.
- To facilitate early diagnosis and management of PEI.
Main Methods:
- A retrospective-prospective cohort study involving 1633 ICP patients.
- Patients were randomly assigned to training and validation cohorts.
- Cox proportional hazard regression model used to identify predictors and construct the nomogram.
Main Results:
- 20.8% of ICP patients developed steatorrhea over a median follow-up of 9.8 years.
- Key predictors identified: male sex (HR 2.479), diabetes mellitus at/before ICP diagnosis (HR 2.274), and age < 18 years at ICP onset (HR 0.095).
- The developed nomogram demonstrated good concordance for predicting steatorrhea.
Conclusions:
- Predictors for steatorrhea in ICP were identified, enabling the creation of a predictive nomogram.
- The nomogram can assist in identifying high-risk populations for closer follow-up.
- Early detection and treatment of PEI may be improved through the use of this predictive tool.
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