Timely Ordering of Pharmacogenetic Testing in Pediatric Oncology
试验速览
- 阶段
- 不适用
- 状态
- 进行中（未招募）
- 入组人数
- 275
- 试验地点
- 2
- 主要终点
- Proportion of Patients with Pharmacogenetic Testing
研究概览
简要总结
The goal of this trial is to learn if a machine learning (ML) model can help optimize drug therapy in the pediatric population. The main question[s] it aims to answer are whether a machine learning model predicting receipt of a targeted medication within the next three months:
- Increases the offering of pharmacogenetic testing prior to receipt of a targeted medication
- Increases the number of patients with pharmacogenetic results prior to receipt of a targeted medication
- Increases the number of patients who have alteration in medication choice or dose based on pharmacogenetic results
This trial only focuses on the prediction and provision of participants with a high-risk of receiving a medication with a pharmacogenetic indication in the next three months.
详细描述
This study aims to evaluate the effectiveness of a ML model in predicting patients at high risk of requiring a "targeted medication" within the next three months. A machine learning model will predict, the morning following admission to any inpatient service, whether there will be receipt of a targeted medication within the next three months. The research team will be notified regarding eligible patients each morning, and the research team or pharmacogenomics team will approach the patient's primary care team as applicable. By leveraging ML, this study seeks to enhance the identification of patients who would benefit from such medications in a timely and resource-efficient manner.
The study team identified specific medications as indications for pharmacogenetic testing based on prevalence and level of evidence for modifying prescribing practices. These pre-selected medications are referred to as "targeted medications" and are as follows: azathioprine, brivaracetam, clobazam, clopidogrel, flecainide, phenytoin, tacrolimus, voriconazole and warfarin. Only systemically administered (oral, subcutaneous, intramuscular or intravenous) medications or prescriptions (e.g. not topical, intrathecal or intravitreal) are included. Phenytoin was only considered if given orally (to exclude emergency administration without a plan for ongoing treatment).
Pharmacogenetic testing will be offered to participants and conducted as addressed in an associated pharmacogenetic testing protocol (REB# 1000053445 PI: Iris Cohn).
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Supportive Care
- 盲法
- None
入排标准
- 年龄范围
- 6 Months 至 18 Years（Child, Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Inpatient at The Hospital for Sick Children
- •Between 6 months to 18 years old
排除标准
- •Prior pharmacogenetic testing and/or prior receipt of a targeted medication
- •Current Intensive Care Unit (ICU) admission
- •Expected hospital discharge is prior to midnight on the day of admission
研究组 & 干预措施
ML model
Participants predicted by an ML model to receive a "targeted medication" within three months following admission.
干预措施: ML-based intervention (Other)
结局指标
主要结局
Proportion of Patients with Pharmacogenetic Testing
时间窗: Day 1 to 3 months
The primary outcome will be the proportion of patients with pharmacogenetic testing offered among those who receive a medication with a pharmacogenetic indication within three months of prediction time. Testing must be offered prior to receipt of the first targeted medication.
次要结局
- Number of patients with pharmacogenetic results available prior to receipt of targeted medication(Day 1)
- Number of patients who have alteration in medication choice or dose based on pharmacogenetic results(Day 1)
研究者
Lillian Sung
Chief Clinical Data Scientist, Paediatric Oncologist
The Hospital for Sick Children