In cancer research, parametric models are used in several areas:
1. Survival Analysis: In survival analysis, parametric models like the Weibull, Exponential, and Log-Normal distributions are used to model survival times of cancer patients. These models help in estimating the likelihood of survival over a period and can be used to compare the effectiveness of different treatments.
2. Tumor Growth Modeling: Parametric models can describe the growth kinetics of tumors. For instance, the Gompertz model is often used to characterize the growth of solid tumors. These models help researchers understand how tumors grow and respond to treatments over time.
3. Risk Prediction: Parametric models are employed to predict the risk of cancer recurrence or the development of secondary cancers. The Cox Proportional Hazards model, though semi-parametric, can be extended to parametric forms to predict these risks more accurately.
4. Dose-Response Relationships: In pharmacokinetics, parametric models are used to understand how different doses of chemotherapy or radiotherapy influence tumor reduction and patient side effects.
