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Risk of an Abnormal Suspicious False Positive Screening Exam for Ovarian Cancer in the PLCO Cancer Screening Trial.

Principal Investigator
Name
Sarah Nyante
Institution
NCI, DCEG, HREB
Email
About this CDAS Project
Study
PLCO (Learn more about this study)
Project ID
2009-0059
Initial CDAS Request Approval
Jul 10, 2009
Title
Risk of an Abnormal Suspicious False Positive Screening Exam for Ovarian Cancer in the PLCO Cancer Screening Trial.
Summary
Ovarian cancer remains a leading cause of gynecological cancer death. It has not yet been established if early detection of these cancers reduces ovarian cancer specific mortality. Previous reports from PLCO have indicated that TVU and CA-125 demonstrate poor performance characteristics as screening tools. Specificity is particularly important for ovarian cancer screening because the prevalence of disease is low, translating into an unacceptably low positive predictive value (PPV) (too many false positive tests) unless testing achieves high specificity. Given that false positive tests may eventuate in patient anxiety, cost and surgery with attendant morbidity, minimizing the number of false positive screens is a critical goal towards developing a clinically useful screening test. This project will represent an initial step in understanding the causes of false positive screens.
Aims

Objective: Establish a cohort of all women in the intervention arm of PLCO who underwent at least one screening exam for ovarian cancer (TVU and/or CA125) to address the following aims: Investigate potential risk factors associated with having a positive ovarian cancer screening exam (to include age, demographics, BMI, smoking, medical conditions, gynecologic history, reproductive history, menstrual history, exogenous hormone use, other cancer diagnosis and prior surgery) a. Assess characteristics of abnormal TVU findings (e.g. ovarian volume, morphology and histopathology), level of CA 125 and repeat measures for CA 125 related to all false positive screens to b. Characterize abnormal suspicious findings and identify risk factors associated with proceeding to surgery Develop a multivariate model for predicting risk of false positive TVUs or CA 125 tests and compare the factors in the model to established risk factors for ovarian cancer. Examine various thresholds for a risk model based on predicting false positive screens to identify optimal cut points.

Collaborators

Bruce Kessel (Hawaii)
Robert Greenlee (Marshfield)
Aimee Kreimer (NCI)
Sarah Nyante (DCP, NCI)
Paul Pinsky (NCI)
Doug Reding (Marshfield)
Mark Sherman (NCI)