[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]
R: st: within stage of disease differences
Thanks a lot for Your Kind and prompt answer.
Actually I have determined Quality-Adjusted Life Years (QALYs) for each one
of the disease stage and I have found a statistical significant difference
in favour of programme A; however, this difference is due to utilities (ie.,
should someone who read us not engaged in health economics, in general
terms, a measure of health-related quality of life used for weighting years
of life and translate them into QALYs) which worsen as the disease evolves
from stage I to stage IV. The next step I am intended to take will be to
better outline the role played, if any, by the number of years spent with a
given utility for patients enrolled in programmes A and B. So this was a
QALYs issue, but now is a "time spent for each disease stage" issue.
Your answer and hints are really helpful (I am an health economist - more
economist than health - I will take a look to Stephen Jenkins's website You
were so Kind to suggest).
Thanks a lot again for Your Kindness and for Your Time.
[mailto:email@example.com] Per conto di Austin Nichols
Inviato: mercoledý 27 giugno 2007 22.09
Oggetto: Re: st: within stage of disease differences
I agree with Svend. I would advise you to start by redefining
"failure" as movement from Stage 1 to Stage 2 instead of movement from
alive to dead. Then repeat for each other transition--what you want
to do is measure the effect of a program on duration of a Stage, and
-streg- is the place to start. You may find Stephen Jenkins's website
I don't think you need enter the QALY fray just yet, not until you
want to "value" the different durations.
On 6/27/07, Svend Juul <SJ@soci.au.dk> wrote:
> Carlo asked:
> I beg Your pardon for the possible trivialism of what follows. I am
> to compare two different health care programmes (A and B) which perform
> same in terms of overall average per patient survival (13 years each) but
> give different results in terms of years patients (50,000 patients
> in programme A and 50,000 in programme B) spend throughout different
> (I^ II^ III^ and IV^) of the disease. Particularly, I would kindly ask You
> about some hints to check for any statistical significance within each
> stage. I tried tabi, chi2 exact with Stata 9, but I am not sure this the
> right way to tackle this issue.
> This is far from trivial, and this type of question has lead health
> economists, philosophers, epidemiologists, and biostatisticians to go war
> against each other.
> It looks like a QALY (Quality Adjusted Life Years) problem. To my
> (and -findit-'s knowledge) no official or unoffical procedures deal with
> Now, you ask about checking for statistical significance within each
> This requires data at the individual level with number of terminating
events (stage shift, death) and time at risk. Look at survival analysis
> (-st...- commands; the [ST] manual) and incidence rate ratios
> (-ir-; also in [ST] under -epitab-).
> Hope this helps (a bit)
* For searches and help try:
* For searches and help try: