Calculate the predicted risk score for each patient

[leonadoan]

Hi, first of all, thank you very much for developing such a useful package. It helps me a lot in my survival analysis.

I have a question regarding the prediction of the neural network. I applied COXPH for my model and .predict_surv_df() to predict my test set. The prediction would return the survival function for each patient. I would like to classify patients in the test set to high-risk and low-risk groups based on their risk scores. Is there any way to calculate the risk score for each patient based on the predicted survival function from the COXPH?

[havakv]

Hi, and thank you for the kind words.

Could you maybe provide a definition of the risk score? If you just want a to create a risk score, you could for instance use the survival prediction at a fixed point in time or just the model.predict(x) (essentially represents the log-partial hazard https://lifelines.readthedocs.io/en/latest/Survival%20Regression.html#cox-s-proportional-hazard-model). You can use these because CoxPH is a proportional hazard model, meaning the relative risk between two individuals are constant as a function of time (survival function will never cross).
Does this answer your question?

[leonadoan]

That's awesome, and absolutely what I'm looking for. Thank you very much for your help.