A Validated Risk Prediction Model for Bone Fragility in Children With Acute Lymphoblastic Leukemia.

Area of Science:

• Pediatric Endocrinology
• Pediatric Oncology
• Bone Metabolism

Background:

• Bone fragility can be present at diagnosis in pediatric acute lymphoblastic leukemia (ALL).
• Routine dual-energy X-ray absorptiometry (DXA) is not always feasible for all children with ALL.
• Low lumbar spine bone mineral density (LS BMD Z-score ≤ -2.0) is an indicator of fracture risk and potential BMD worsening during treatment.

Purpose of the Study:

• To develop and validate a risk prediction model for low LS BMD at diagnosis in pediatric ALL patients.
• To assess the association between low LS BMD at diagnosis and symptomatic fractures.
• To identify children at risk for bone fragility early in their ALL diagnosis.

Main Methods:

• Utilized multivariable logistic regression to develop a prediction model using data from the DCOG-ALL9 cohort (n=249).
• Validated the model in the Canadian Steroid-Associated Osteoporosis in the Pediatric Population (STOPP) cohort (n=99).
• Assessed model performance using the area under the receiver operating characteristic curve (AUC).

Main Results:

• The prediction model, incorporating weight and age, achieved an AUC of 0.71 in the development cohort and 0.74 in the validation cohort.
• The model correctly identified 71% of patients with low LS BMD at diagnosis.
• Low LS BMD at diagnosis was associated with LS BMD at treatment cessation (OR 5.9) and symptomatic fractures (OR 1.7) within 12 months post-treatment.

Conclusions:

• A prediction model for low LS BMD at diagnosis in pediatric ALL patients has been successfully developed and validated.
• This model can aid in the early identification of bone fragility in pediatric ALL patients.
• Early identification facilitates timely intervention to mitigate fracture risk and manage bone health during and after cancer treatment.