Early detection of ovarian cancer with proteomic patterns

Computer-assisted detection of proteomic patterns identifies types of ovarian cancer and could help screen high-risk populations.

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Over 80% of ovarian cancers are diagnosed when the disease is at a late stage, with a consequent 5-year survival rate of around only 35%. Therefore new technologies for the detection of early-stage ovarian cancer would be of great benefit. In February 8 online The Lancet, Emanuel Petricoin III and colleagues from the US Food and Drug Administration, Bethesda, show that computer-assisted detection of proteomic patterns could help screening for ovarian cancer.

Petricoin et al. analysed blood proteins of women with ovarian cancer using mass spectroscopy and a novel computer-searching algorithm. They found a discriminatory proteomic pattern that correctly identified all 50 ovarian cancer cases and 63 of the 66 non-cancer cases from a set of 116 masked serum samples (sensitivity 100%; specificity of 95%, and positive predictive value of 94%) (Lancet 2002, 359:572–577).

"These findings justify a prospective population-based assessment of proteomic pattern technology, as a screening tool for ...

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