I am doing an audit looking at survival for a particular cancer. I have done a univariate analyses and Kaplan-Meier curves using Prism Graphpad looking at prognostic factors which may affect survival. I now want to enter the significant factors into a multivariate analysis.
I shall be using SPSS version 21.
My question is that one of my factors, histology showed a trend for significance and I would like to include that. But there are 5 options for different histologies, and there is no reference category for that.
I have managed to do some of my other multivariate Cox regression on SPSS, via Analyze, Survival, Cox regression. Is it possible to do it the same way? Is this a matter of using a specific coding of categorical variables?
Best Answer
You should be able simply to specify one of the levels of the histology factor as the reference. For example, choose as reference the level that is expected to have the best outcome based on clinical expectations. I don't use SPSS but I expect, like in the R survival package that I use, that won't pose a problem, with hazard ratios for the other levels of the histology factor then expressed with respect to your reference level.
Before you do this, though, think hard about what you're trying to accomplish with the multivariate analysis. In my experience with similar analyses, many clinical variables having significant univariate relations to outcome are highly correlated with each other (like tumor size or spread to lymph nodes and the patient's disease stage, which is based on tumor size and spread to nodes). Even your histology subtypes may be correlated with other clinical variables. The particular variables that you find "significantly" related to outcome in the multivariate analysis then may be highly idiosyncratic to your particular data set, and not very useful for generalization to other data sets. And you have to resist the temptation to include too many variables in the multivariate analyis, lest you overfit the data. Some early consultation with a statistician experienced in survival analysis may save you a lot of trouble down the road if you want to publish your results.