Vomiting Prevention in Children With Cancer

The goal of this single arm trial is to learn if a machine learning (ML) model predicting the risk of vomiting within the next 96 hours will impact vomiting outcomes in inpatient cancer pediatric patients. The main questions it aims to answer are whether an ML model predicting the risk of vomiting within the next 96 hours will: Primary 1\. Reduce the proportion with any vomiting within the 96-hour window Secondary 1. Reduce the number of vomiting episodes 2. Increase the proportion receiving care pathway-consistent care 3. Impact on number of administrations and costs of antiemetic medications Newly admitted participants will have a ML model predict the risk of vomiting within the next 96 hours according to their medical admission information. The prediction will be made at 8:30 AM following admission. Pharmacists will be charged with bringing information about patients' vomiting risk to the attention of the medical team and implementing interventions.

NCT Number	NCT06886451
Lead Sponsor	The Hospital for Sick Children
Conditions	Chemotherapy Induced Nausea and Vomiting, Quality of Life (QOL), Pediatric Cancer
Enrollment	1,332 participants
Start Date	2025-03-18
Primary Completion	2027-03-18 (estimated)
Study Completion	2027-03-18 (estimated)
Updated on ClinicalTrials.gov	2026-03-05