# Childhood lymphadenopathy: ultrasonographic predictors of malignancy in a retrospective cohort of 500 patients

## TL;DR

This study identifies ultrasound features as strong predictors of malignancy in children with swollen lymph nodes, potentially reducing unnecessary biopsies.

## Contribution

The study demonstrates that ultrasonographic features are more reliable than traditional parameters like size or location for predicting malignancy in pediatric lymphadenopathy.

## Key findings

- Ultrasonographic assessment was the only independent predictor of malignancy, with suspicious nodes having ~56-fold higher odds of malignancy.
- The model showed excellent discrimination with an AUC of 0.92 for predicting malignancy.
- Traditional parameters like node size and region were not significant in multivariable analysis.

## Abstract

Pediatric lymphadenopathy is common and usually benign, yet selecting children who need biopsy remains challenging. We evaluated clinical and ultrasonographic (US) predictors of malignancy in a large pediatric cohort.

We retrospectively analyzed 500 children (0-18 years) evaluated for regional lymphadenopathy at a tertiary pediatric hematology-oncology clinic (June 2024-March 2025). Demographics, node location/size/count, US features, viral tests, and biopsy/bone-marrow results were extracted. Univariable tests and multivariable logistic regression identified independent predictors of malignancy. Model performance was assessed with Hosmer-Lemeshow and ROC AUC.

Median age was 6 years; cervical nodes predominated (92.2%), and multiple nodes were frequent (93.6%). Biopsy was performed in 47 children; malignancy was found in 23. Final diagnoses in the cohort were reactive (87.4%), infectious (6.8%), hematologic malignancy (4.4%), and solid tumor metastasis (1.4%). On univariable analysis, node size ≥2 cm, multiplicity, and region were associated with malignancy (p < 0.05). In multivariable analysis, only US assessment remained independently predictive: nodes categorized as suspicious on US had ∼56-fold higher odds of malignancy (adjusted OR ≈ 55.6; 95% CI 14.3-200; p < 0.001), whereas size and region were not significant. The model showed good calibration and excellent discrimination (AUC = 0.92; 95% CI 0.88-0.96).

US features outperformed traditional parameters (size/site) for predicting malignancy. Incorporating US-driven criteria into pathways may reduce unnecessary biopsies while preserving timely cancer detection.