Predictive models help us understand how different tumors might behave and how patients might do over time. They can be pretty accurate, but their success isn’t the same for everyone. Here are some important points to think about:
Survival Rates: These models usually look at past data to make predictions. However, they can’t consider everything about each patient. Every person’s situation is different.
Biomarkers: Adding biomarkers to these models can make them better. Biomarkers give us more clues about how a tumor might act.
Limitations: Things like a patient’s age, background, and other health issues can make predictions tricky.
So, while these models are helpful, we should remember there is always some uncertainty!
Predictive models help us understand how different tumors might behave and how patients might do over time. They can be pretty accurate, but their success isn’t the same for everyone. Here are some important points to think about:
Survival Rates: These models usually look at past data to make predictions. However, they can’t consider everything about each patient. Every person’s situation is different.
Biomarkers: Adding biomarkers to these models can make them better. Biomarkers give us more clues about how a tumor might act.
Limitations: Things like a patient’s age, background, and other health issues can make predictions tricky.
So, while these models are helpful, we should remember there is always some uncertainty!