New Method May Detect Ovarian Cancer Earlier
New Method May Detect Ovarian Cancer Earlier
In the past, using CA125 to predict the risk of ovarian cancer was questioned, because it often led to test results that incorrectly pointed to cancer.
In this study, though, researchers found cancer in women that would have been missed using the old methods.
The new method picked up 86% of the women with cancer. The conventional tests picked up only 41% to 66% , depending on the test, Menon says.
In all, 640 women had surgery for suspected ovarian cancer based on their risk level, and 133 were found to have invasive cancer. Another 22 were diagnosed with ovarian cancer within a year of their last yearly screen, she says.
"It's definitely exciting, it's promising,'' says Debbie Saslow, PhD, director of cancer control intervention for the American Cancer Society. Experts have been waiting for the results of this study for years, she says.
But, she says, information on whether it saves lives is crucial. Complicating the issue, she says, is that experts aren't certain about how all ovarian cancers will develop over time. Some get worse than others, she says.
In the study, just 133 of the 640 women who had surgery actually ended up having ovarian cancer, she points out.
If the research shows that the new method not only finds more cancers, but saves lives by doing so, Menon says the test could be used routinely in all women from age 50 on, when risk for the cancer rises.
Researchers should know more about that by the end of the year, she says, when a final breakdown of the results from this study is expected.
Experts would need to look at all the data, including the information on the method's ability to save lives from ovarian cancer, and make recommendations, Saslow says.
Her prediction, if research continues to bear out? "It's highly likely to be used clinically for high-risk women, probably for women with symptoms, and there's a big question mark for women who are not at high risk and don't have symptoms."
New Method May Spot Ovarian Cancer Earlier
Benefits of the Method continued...
In the past, using CA125 to predict the risk of ovarian cancer was questioned, because it often led to test results that incorrectly pointed to cancer.
In this study, though, researchers found cancer in women that would have been missed using the old methods.
The new method picked up 86% of the women with cancer. The conventional tests picked up only 41% to 66% , depending on the test, Menon says.
In all, 640 women had surgery for suspected ovarian cancer based on their risk level, and 133 were found to have invasive cancer. Another 22 were diagnosed with ovarian cancer within a year of their last yearly screen, she says.
Second Opinion on the New Approach
"It's definitely exciting, it's promising,'' says Debbie Saslow, PhD, director of cancer control intervention for the American Cancer Society. Experts have been waiting for the results of this study for years, she says.
But, she says, information on whether it saves lives is crucial. Complicating the issue, she says, is that experts aren't certain about how all ovarian cancers will develop over time. Some get worse than others, she says.
In the study, just 133 of the 640 women who had surgery actually ended up having ovarian cancer, she points out.
What's Next?
If the research shows that the new method not only finds more cancers, but saves lives by doing so, Menon says the test could be used routinely in all women from age 50 on, when risk for the cancer rises.
Researchers should know more about that by the end of the year, she says, when a final breakdown of the results from this study is expected.
Experts would need to look at all the data, including the information on the method's ability to save lives from ovarian cancer, and make recommendations, Saslow says.
Her prediction, if research continues to bear out? "It's highly likely to be used clinically for high-risk women, probably for women with symptoms, and there's a big question mark for women who are not at high risk and don't have symptoms."
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