I am not familiar with terms like PFS and OS, so I do not understand the question. However, it sounds like you want to use the CDF("Weibull") function to compute probabilities and maybe the difference between probabilities. The CDF gives the probability less than some value. If you want the probability greater than some value, use the SDF function, where SDF9x) = 1 - CDF(x). See Functions for continuous probability distributions in SAS - The DO Loop
You need to use a consistent scale to estimate the parameter and probabilities. You gave example parameters, but I do not know if those correspond to units of years, months, weeks, or days. When you estimate the probabilities, make sure you use the same scale for the length of time. In the following program, I used 10 (for years), but you might need to use 12*10 if the data are in months.
I doubt whether the following is actually what you need, but perhaps it will point you in the correct direction, or someone else who understands your question better might be able to modify the program. Best wishes.
data Transition_Probabilities;
/* Weibull parameters for PFS and OS */
shape_pfs = 0.77; /* shape for PFS */
scale_pfs = 0.31; /* scale for PFS */
shape_os = 1.56; /* shape for OS */
scale_os = 0.19; /* scale for OS */
length = 10; /* 10 years */
/* Calculate survival probabilities using the Weibull survival function.
The SDF is 1 - CDF.
I AM NOT SURE WHAT DEFINITIONS TO USE! */
/* calculate transition probabilities */
/* PFS to Progressed Disease */
trans_prob_pfs_prog = sdf("weibull", length, shape_pfs, scale_pfs);
/* Progressed Disease to Death */
trans_prob_prog_deats = sdf("weibul", length, shape_os, scale_os);
/* PFS to Death */
trans_prob_pfs_death = cdf("weibull", length, shape_pfs, scale_pfs) -
cdf("weibul", length, shape_os, scale_os);
run;
proc print data=Transition_Probabilities;
run;
... View more
