I am struggling a bit to model the following problem. Basically, I would like to model tumor mutation burden (mutations per megabase, a continuous) as a function of treatment (categorical). The following is an example of how data looks like
patient-id therapy-1 therapy-2 therapy-3 cancer-type TMB PID-1 1 NA 1 CT-1 1.3 PID-2 0 0 1 CT-1 0.14 PID-3 NA 0 1 CT-2 5 PID-4 1. 1 NA CT-3 2.3 PID-5 1 1 NA CT-3 10 ... ...
1 - treated; 0 - not treated; NA - No information
I was trying multiple linear regression, but in most cases one patient got multiple therapies. This is where I am confused on how to interpret the results of linear regression. So far, I haven't included the
cancer-type information into the model. However, IMO, including cancer-type into model will yield specific treatment effects in specific cancer type? Or is it over-expectation of what we can achieve from linear model?
Also, is there a better way to address the problem to get reasonable associations between treatment and TMB in this case?
Thank you for the help. Stay safe!