CME 
JOBS 
OUTBREAKS 
PEER-TO-PEER 
QUIZZES & QUESTIONS 
MEDTECH The model was built based on retrospective patient data from 27 practices within The US Oncology Network.
Machine learning models are revolutionizing cancer treatment with their ability to accurately predict the likelihood of patients initiating IV therapy within 90 days of diagnosis, according to recent findings shared at the 2023 meeting of the American Society of Clinical Oncology.
Key Points:
- Machine learning models can predict which cancer patients are likely to initiate IV therapy within 90 days of diagnosis.
- The model includes data on insurance type, income level, stage of cancer diagnosis, and who initiated IV therapy.
- Regardless of insurance type, patients began IV therapy at the same rate.
Additional Points:
- Stage IV patients were more likely to start intravenous treatment than stage I patients, indicating treatment decisions are based on clinical severity.
- Younger patients were more likely to begin IV therapy than older patients, suggesting a need for outreach to older patients about the benefits of IV therapy.
- The model can be used to provide extra support to new patients who may need IV treatment recommended by their clinician.
Conclusion:
- Machine learning models are an effective tool for predicting the likelihood of cancer patients initiating IV therapy, and could be used to tailor support and treatment recommendations for individual patients.
Medical Oncology Latest Posts
- Study Shows AI Improves Accuracy of Skin Cancer Diagnoses
- Dostarlimab for Primary Advanced or Recurrent Endometrial Cancer
- Lung Cancer: 22 Early Signs and Symptoms
- Long-Term Use of Popular Heartburn Drugs Increases Risk of Stomach Cancer: Review
“Now that we have the model, when a new patient comes into our network, we can predict who may need extra support to consider IV treatment that is recommended by their clinician.”
Ping Ye, PhD
Senior Data Scientist
The US Oncology Network
The Woodlands, Texas
