Clinical and Emergent Biomarkers and Their Relationship to the Prognosis of Ovarian Cancer.

ABSTRACT:

Objective

Ovarian cancer is the most lethal gynecological malignancy, but information relevant to prognosis and outcomes remain unknown. Here, we used statistical methods to focus specifically on interactions between candidate prognostic variables.

Methods and results

Univariate, multivariate, and elastic net modeling of 42 variables were applied to a cohort of 542 ovarian cancer patients with 393 episodes of cancer recurrence/death. In univariate analyses, overexpression of TFF3, MDM2, and p53 were associated with improved recurrence-free survival. In multivariate analyses adjusted for age, histology, stage, grade, ascites, and residual disease, overexpression of PR appeared to provide a protective effect [hazard ratio for >50% of cells positive, 0.64 (95% confidence interv

SUBMITTER: Jatoi A 

PROVIDER: S-EPMC4764381 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature