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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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