Good call, didn't know about that

When you say "has any influence", I'm assuming you mean causal influence, rather than just being correlated with a particular outcome. This puts us in the domain of causal inference. I suggest you go through a causal inference tutorial or two to get some domain knowledge. See https://causalinference.gitlab.io/kdd-tutorial/ and https://economics.mit.edu/sites/default/files/inline-files/causal_tutorial_1.pdf. Econometric modeling revolves heavily around this, so you're probably going to find more sources that are econometric rather than medical.

My personal approach: Train an xgboost model (or really any ML model) using the appropriate hazard function and bayesian optimization for hyperparameter tuning, then compare the log likelihood function of the parameter at its actual values vs counterfactual values. If the counterfactual values provide a similar fit, you're looking at something that is not likely causal.