I am analysing trends in survival. I was recommended to use the following package and parameterization.
I have a model as follows (done with rms package):
survobj12 = with(data, Surv(time_12months,status_12months)) model2 = cph(survobj12 ~ rcs(time_to_diagnosis_in_years, 4), data=data,x=TRUE , y=TRUE)
Cox Proportional Hazards Model cph(formula = survobj12 ~ rcs(time_to_diagnosis_in_years, 4), data = data, x = TRUE, y = TRUE) Model Tests Discrimination Indexes Obs 11491 LR chi2 0.56 R2 0.000 Events 3534 d.f. 3 Dxy 0.009 Center 0.0343 Pr(> chi2) 0.9048 g 0.013 Score chi2 0.56 gr 1.013 Pr(> chi2) 0.9053 Coef S.E. Wald Z Pr(>|Z|) time_to_diagnosis_in_years 0.0145 0.0330 0.44 0.6597 time_to_diagnosis_in_years' -0.0271 0.0946 -0.29 0.7741 time_to_diagnosis_ine_years'' 0.0741 0.2853 0.26 0.7952
This is the plotted result: #plot ggplot(Predict(model2), vnames = "names")+ xlab("Time from diagnosis in years")+
This seems really nice; however, how should I interpret the plot? Is relative hazard equal to hazard ratios? The interpretation of hazard ratios is quite simple: e.g. HR = 2 means that females have two times higher risk for dying than males during a certain time period. However, my plot does not have a reference category at all.
So, are these two estimates (Relative Hazard and Hazard Ratio) equal to each other and what is the reference on my plot/analysis?