BACKGROUND: Although overall 5-year survival rates for ovarian cancer are poor (10-30%), stage I/IIa patients have a 95% 5-year survival. New biomarkers that improve the diagnostic performance of existing tumor markers are critically needed. A previous study by Zhang et al. reported identification and validation of three biomarkers using proteomic profiling that together improved early-stage ovarian cancer detection. METHODS: To evaluate these markers in an independent study population, postdiagnostic/pretreatment serum samples were collected from women hospitalized at the Mayo Clinic from 1980 to 1989 as part of the National Cancer Institute Immunodiagnostic Serum Bank. Sera from 42 women with ovarian cancer, 65 with benign tumors, and 76 with digestive diseases were included in this study. Levels of various posttranslationally forms of transthyretin and apolipoprotein A1 were measured in addition to CA125. RESULTS: Mean levels of five of the six forms of transthyretin were significantly lower in cases than in controls. The specificity of a model including transthyretin and apolipoprotein A1 alone was high [96.5%; 95% confidence interval (95% CI), 91.9-98.8%] but sensitivity was low (52.4%; 95% CI, 36.4-68.0%). A class prediction algorithm using all seven markers, CA125, and age maintained high specificity (94.3%; 95% CI, 89.1-97.5%) but had higher sensitivity (78.6%; 95% CI, 63.2-89.7%). CONCLUSIONS: We were able to replicate the findings reported by Zhang et al. in an independently conducted blinded study. These results provide some evidence that including age of patient and these markers in a model may improve specificity, especially when CA125 levels are >/=35 units/mL. Influences of sample handling, subject characteristics, and other covariates on biomarker levels require further consideration in discovery and replication or validation studies.
BACKGROUND: Although overall 5-year survival rates for ovarian cancer are poor (10-30%), stage I/IIa patients have a 95% 5-year survival. New biomarkers that improve the diagnostic performance of existing tumor markers are critically needed. A previous study by Zhang et al. reported identification and validation of three biomarkers using proteomic profiling that together improved early-stage ovarian cancer detection. METHODS: To evaluate these markers in an independent study population, postdiagnostic/pretreatment serum samples were collected from women hospitalized at the Mayo Clinic from 1980 to 1989 as part of the National Cancer Institute Immunodiagnostic Serum Bank. Sera from 42 women with ovarian cancer, 65 with benign tumors, and 76 with digestive diseases were included in this study. Levels of various posttranslationally forms of transthyretin and apolipoprotein A1 were measured in addition to CA125. RESULTS: Mean levels of five of the six forms of transthyretin were significantly lower in cases than in controls. The specificity of a model including transthyretin and apolipoprotein A1 alone was high [96.5%; 95% confidence interval (95% CI), 91.9-98.8%] but sensitivity was low (52.4%; 95% CI, 36.4-68.0%). A class prediction algorithm using all seven markers, CA125, and age maintained high specificity (94.3%; 95% CI, 89.1-97.5%) but had higher sensitivity (78.6%; 95% CI, 63.2-89.7%). CONCLUSIONS: We were able to replicate the findings reported by Zhang et al. in an independently conducted blinded study. These results provide some evidence that including age of patient and these markers in a model may improve specificity, especially when CA125 levels are >/=35 units/mL. Influences of sample handling, subject characteristics, and other covariates on biomarker levels require further consideration in discovery and replication or validation studies.
Authors: Christopher C Silliman; Monika Dzieciatkowska; Ernest E Moore; Marguerite R Kelher; Anirban Banerjee; Xiayuan Liang; Kevin J Land; Kirk C Hansen Journal: Transfusion Date: 2011-08-31 Impact factor: 3.157
Authors: Charlotte H Clarke; Christine Yip; Donna Badgwell; Eric T Fung; Kevin R Coombes; Zhen Zhang; Karen H Lu; Robert C Bast Journal: Gynecol Oncol Date: 2011-06-25 Impact factor: 5.482
Authors: Zoya Yurkovetsky; Steven Skates; Aleksey Lomakin; Brian Nolen; Trenton Pulsipher; Francesmary Modugno; Jeffrey Marks; Andrew Godwin; Elieser Gorelik; Ian Jacobs; Usha Menon; Karen Lu; Donna Badgwell; Robert C Bast; Anna E Lokshin Journal: J Clin Oncol Date: 2010-04-05 Impact factor: 44.544
Authors: Feng Su; Jennifer Lang; Ashutosh Kumar; Carey Ng; Brian Hsieh; Marc A Suchard; Srinivasa T Reddy; Robin Farias-Eisner Journal: Biomark Insights Date: 2007-10-16
Authors: Byoung Kwon Kim; Jong Won Lee; Pil Je Park; Yong Sung Shin; Won Young Lee; Kyung Ae Lee; Sena Ye; Heesun Hyun; Kyung Nam Kang; Donghwa Yeo; Youngdai Kim; Sung Yup Ohn; Dong Young Noh; Chul Woo Kim Journal: Breast Cancer Res Date: 2009-04-28 Impact factor: 6.466