Presence of comorbid conditions at diagnosis has prognostic value for a variety of cancers
Information on comorbid conditions present
at time of diagnosis has prognostic value for a wide variety of
cancers, according to an article in the May 26th issue of the Journal
of the American Medical Association.
The present system of cancer classification by stage does not consider
patient-based prognostic factors such as general health defined
as the number and severity of coexisting diseases, illnesses, or
conditions.
In the current research, Jay F. Piccirillo, MD, and his American
colleagues assessed whether comorbidity information obtained by
cancer registrars during their usual chart abstraction process could
provide important prognostic information.
Comorbidity data were collected by trained hospital-based cancer
registrars using the Adult Comorbidity Evaluation 27, a validated
chart-based comorbidity instrument. The study included a total of
17,712 patients receiving care between January 1, 1995 and January
31, 2001 for the primary diagnosis of new cancer of the prostate,
lung (non-small cell), breast, digestive system, gynecological,
urinary system, or head and neck.
"Our results demonstrate that hospital-based cancer registrars
can collect comorbidity information, which provides important prognostic
information," the authors wrote. "Comorbidity information
was prognostically relevant in all cancer sites while the exact
contribution varied from site to site. Comorbidity information was
more important among the cancers with longer mean survival (prostate
and breast) and prognostically least informative in the cancers
with the worst survival (lung). In addition, we showed that comorbidity
and extent of tumor spread or stage are prognostically complementary."
"Comorbidity information can be added to staging systems or
incorporated into decision making programs to aid in patient consultation
and improve patient decision making. Improved descriptions of the
patient with cancer results in improved prognostic stratification,
which will allow for more accurate estimates of treatment effectiveness
when conducting outcomes research and analyzing results from observational
hospital-based tumor registries," the researchers concluded.
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