Related Experiment Video
Updated: Nov 19, 2025

Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform
Published on: April 12, 2021
Multicenter study of risk factors of unplanned 30-day readmissions in pediatric oncology
Kamila Hoenk1,2, Lilibeth Torno1, William Feaster1
1Children's Hospital of Orange County, Orange, California, USA.
Insights
Unplanned 30-day readmissions in pediatric oncology are influenced by specific cancer types, chemotherapy, and infections. Oncology-specific models can improve risk prediction for these high-risk patients.
Area of Science:
- Oncology
- Health Services Research
- Biostatistics
Background:
- Pediatric oncology patients experience high hospital readmission rates.
- Research into risk factors for unplanned 30-day readmissions in this population is limited.
Purpose of the Study:
- To develop a statistical model identifying risk factors for unplanned 30-day readmissions in pediatric oncology patients.
- To provide insights into factors influencing readmission risk within this specific patient group.
Main Methods:
- A mixed-effects statistical model was developed using data from 32,667 encounters of 10,418 pediatric patients with neoplastic conditions.
- Data were sourced from the Cerner Health Facts Database across 16 hospitals.
- The model was trained on 75% of the data and validated on an independent test dataset.
Main Results:
- Specific cancers (acute lymphoid leukemia in relapse, neuroblastoma, rhabdomyosarcoma, bone/cartilage cancer) increased readmission odds.
- Number of cancer medications and chemotherapy administration were associated with higher readmission odds for all cancer types.
- Interactions between Wilms Tumor and chemotherapy, and between recent chemotherapy and infections, significantly increased readmission risk. The model achieved an AUC of 0.714 on the test dataset.
Conclusions:
- Readmission risk in pediatric oncology is significantly influenced by cancer type, chemotherapy exposure, and healthcare utilization.
- Oncology-specific predictive models are crucial for effective decision support, outperforming models developed for mixed populations.
Background:
Pediatric oncology patients have high rates of hospital readmission but there is a dearth of research into risk factors for unplanned 30-day readmissions among this high-risk population.
Aim:
In this study, we built a statistical model to provide insight into risk factors of unplanned readmissions in this pediatric oncology.
Methods:
We retrieved 32 667 encounters from 10 418 pediatric patients with a neoplastic condition from 16 hospitals in the Cerner Health Facts Database and built a mixed-effects model with patients nested within hospitals for inference on 75% of the data and reserved the remaining as an independent test dataset.
Results:
The mixed-effects model indicated that patients with acute lymphoid leukemia (in relapse), neuroblastoma, rhabdomyosarcoma, or bone/cartilage cancer have increased odds of readmission. The number of cancer medications taken by the patient and the administration of chemotherapy were associated with increased odds of readmission for all cancer types. Wilms Tumor had a significant interaction with administration of chemotherapy, indicating that the risk due to chemotherapy is exacerbated in patients with Wilms Tumor. A second two-way interaction between recent history of chemotherapy treatment and infections was associated with increased odds of readmission. The area under the receiver operator characteristic curve (and corresponding 95% confidence interval) of the mixed-effects model was 0.714 (0.702, 0.725) on the independent test dataset.
Conclusion:
Readmission risk in oncology is modified by the specific type of cancer, current and past administration of chemotherapy, and increased health care utilization. Oncology-specific models can provide decision support where model built on other or mixed population has failed.
More Related Videos
08:31Murine Model of Leukemia Relapse to Induction Chemotherapy for Acute Lymphoblastic Leukemia
Published on: October 17, 2025
05:16Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure
Published on: June 10, 2025
Related Concept Videos
Pharmacokinetics in Pediatric Patients: Drug Excretion
Pharmacokinetics in Pediatric Patients: Overview and Drug Absorption
Pharmacokinetics in Pediatric Patients: Drug Metabolism
Pharmacokinetics in Pediatric Patients: Drug Distribution
Cancer Survival Analysis
Kidney Transplant III: Nursing Management