Title：A nomogram for acute pancreatitis in patients with acute lymphoblastic leukemia under CCLG-ALL regimen

Author: Mengjia Liu¹, Peijing Qi, Ying Wu¹, Wei Lin¹, Yuanyuan Zhang¹, Jiaole Yu¹, Jia Fan¹, Ruidong Zhang²

1. Department of leukemia, Beijing Children’s Hospital, Capital Medical University, Beijing 100045, China.

2. National Key Discipline of Pediatrics; Beijing Children’s Hospital, Capital Medical University, Beijing 100045, China. E-mail:zhangruidong@vip.sina.com.

Conflicts of interest:

The authors of this study declare that they have no conflicts of interest.

Acknowledgement:

This study was funded by the Capital’s Funds for Health Improvement and Research [No.2024-2-2094].

Ethical approval statement:

The ethics committee of Beijing Children’s Hospital reviewed and approved this study.

Data availability statement: data in this study will be available after publication.

Abstract：

Introduction: Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. While treatment outcomes have improved, chemotherapy complications remain a significant challenge for clinicians. Pancreatitis, a serious side effect of asparaginase, a crucial drug in ALL treatment, can impact chemotherapy tolerance and patient prognosis. This study aims to develop a clinical model that predicts pancreatitis risk in children with ALL undergoing chemotherapy, using clinical data.

Method: This study used clinical data from ALL patients enrolled in the CCLG-ALL trial. Lasso regression was employed to identify potential risk factors for pancreatitis. The patients were randomly divided into training and validation sets (80% and 20%, respectively). A predictive model was developed using the training set, and its performance was evaluated based on the area under the receiver operating characteristic curve (AUC) and calibration curve. The model’s predictive ability was then externally validated using the validation set.

Results: This study included 321 ALL patients, with 58 experiencing pancreatitis and 263 serving as controls. Elevated total bilirubin, direct bilirubin, and induction chemotherapy were identified as risk factors for pancreatitis. The model’s performance, evaluated using the training set, yielded a C-statistic of 0.862 and an AUC of 0.86. The model’s predictive ability was confirmed in the validation set, with an AUC of 0.95.

Conclusion: This study developed a predictive model for pancreatitis in children with ALL undergoing chemotherapy, demonstrating strong predictive ability. A nomogram was created based on this model, identifying elevated total bilirubin and direct bilirubin, as well as induction chemotherapy, as significant risk factors. These findings suggest a possible link between pancreatitis and biliary obstruction (due to elevated bilirubin levels), and a potential predisposition to pancreatitis during induction chemotherapy. Further research is warranted to explore these associations in greater depth.

Key word: leukemia, pancreatitis, nomogram, prediction model