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