Dear Svend,
Thanks a lot for Your Kind and prompt answer: as usual, You made the point.
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.
Your answer and hints are really helpful (I am an health economist - more
economist than health - I will take a look to Your very interesting book on
epidemiology for Statalisters).
Thanks a lot again for Your Kindness and for Your Time.
Kind Regards,
Carlo
-----Messaggio originale-----
Da: [email protected]
[mailto:[email protected]] Per conto di Svend Juul
Inviato: mercoled� 27 giugno 2007 21.58
A: [email protected]
Oggetto: Re: st: within stage of disease differences
Carlo asked:
I beg Your pardon for the possible trivialism of what follows. I am intended
to compare two different health care programmes (A and B) which perform the
same in terms of overall average per patient survival (13 years each) but
give different results in terms of years patients (50,000 patients enrolled
in programme A and 50,000 in programme B) spend throughout different stages
(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 knowledge
(and -findit-'s knowledge) no official or unoffical procedures deal with
that.
Now, you ask about checking for statistical significance within each stage.
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)
Svend
________________________________________________________
Svend Juul
Institut for Folkesundhed, Afdeling for Epidemiologi
(Institute of Public Health, Department of Epidemiology)
Vennelyst Boulevard 6
DK-8000 Aarhus C, Denmark
Phone, work: +45 8942 6090
Phone, home: +45 8693 7796
Fax: +45 8613 1580
E-mail: [email protected]
_________________________________________________________
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