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Algorithm Optimizes Value of CA125 II Screening for Ovarian Ca

Algorithm Optimizes Value of CA125 II Screening for Ovarian Ca

WASHINGTON--Applying a newly developed mathematical model to an
updated version of a familiar tumor marker may increase the chance
of finding ovarian cancers at an earlier stage, Robert C. Knapp,
MD, said at the American Cancer Society Conference on Gynecological
Cancers.

"If we could detect ovarian cancer early in asymptomatic
women," said Dr. Knapp, professor emeritus of gynecology,
Harvard Medical School, "it would make a significant difference
in reducing the horrible mortality from this disease."

Currently, three quarters of ovarian cancers are diagnosed at
late stages, when the 5-year survival rate is only 20%. Women
whose cancers are found at stage I, however, have a 90% chance
of surviving at least 5 years.

Evaluate Changes Over Time

Dr. Knapp said that by evaluating changes in several CA125 radioimmunoassays
taken over a period of time, using the updated CA125 II test (Centocor,
Malvern, Penn), the new algorithm has improved the assay's positive
predictive value (PPV) for the risk of ovarian cancer from approximately
2% to 16%.

The new CA125 II radioimmunoassay utilizes M11, a high-affinity
antibody, in combination with the OC125 antibody. Its standard
curve is stronger and sharper than the original CA125, enhancing
resolution and reducing fluctuations, Dr. Knapp said.

The algorithm looks at the initial level of the CA125 marker,
as well as the exponential slope of the line connecting the marker
readings. It also takes into account any assay variability that
might produce false readings in the short term, said biostatistician
Steven Skates, PhD, who developed the algorithm and was lead investigator
of the study reported at the meeting.

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