Method:
1). Patient: This retrospective study included 321 children diagnosed
with acute lymphoblastic leukemia (ALL) at Beijing Children’s Hospital
between November 2016 and May 2023. All patients were identified from
the hospital’s case management system. ALL diagnosis was confirmed
through bone marrow morphology. Acute pancreatitis was defined based on
the presence of at least two out of three criteria: acute
gastrointestinal symptoms, serum lipase or amylase levels at least three
times the upper limit of normal, and characteristic imaging findings.
Patients were excluded if they had pre-existing organ failure, a history
of pancreatic surgery, prior pancreatitis, liver cirrhosis, hepatitis,
or incomplete information in the case management system. The control
group consisted of patients without pancreatitis. The study was deemed
minimal risk by the ethics committee, and therefore informed consent was
waived.
2). Data collection: demographic and other characteristics of the
patients were collected, including age, gender, weight,
Immunophenotyping, risk classification, chemotherapy phase, cumulative
dose of asparaginase administered (usually Pegaspargase in our center),
MRD level after induction therapy, presence of infection prior to
chemotherapy, presence of pancreatic morphologic abnormalities as
indicated by ultrasound, liver and kidney function, lipids, bilirubin,
pancreatin, C-reactive protein, etc.
3). Statistical analysis: To build the predictive model, variables with
over 20% missing data were excluded. The remaining missing data were
addressed using multiple imputation with the “mice” package in R
software. Patients were randomly divided into training (80%) and
validation (20%) cohorts. The predictive model was developed using the
training data and then evaluated for accuracy using the validation data.
Descriptive statistics for continuous variables included mean and
standard deviation or median and interquartile range, while categorical
variables were presented as percentages. Chi-square or Fisher’s exact
test was used to compare categorical variables between groups, while
t-tests were employed for continuous variables.
Independent risk factors for pancreatitis were screened by lasso
regression which were further output for the construction of nomogram
model. To prepare the independent variables for analysis, disordered
categorical variables were converted into dummy variables. Continuous
variables underwent standardization before being included in the
regression analysis. The predictive model’s performance was evaluated
using the area under the receiver operating characteristic curve (AUC).
An AUC exceeding 0.7 indicated a useful model, while an AUC between 0.8
and 0.9 suggested high diagnostic accuracy.[9, 10] To assess the
calibration of the prediction model, a calibration curve was generated.
[11]
Statistical significance was defined as a p-value less than 0.05, and
all analyses were performed using R version 4.0.3.
The local ethics committee of Beijing Children’s Hospital approved this
study.