AS121 - Hyperinsulinemia and Ovarian Cancer

This page provides study documentation for AS121. For description of the specimen results, see Specimen Results Description (open to public). Data sets of the specimen results are included in the existing WHI datasets located on the WHI Data on this site (sign in and a completed Data Distribution Agreement are required; see details on the Data site).

Investigator Names and Contact Information

Francesmary Modugno, PhD, MPH, Department of Epidemiology, University of Pittsburgh

Introduction/Intent

Although ovarian cancer is the leading cause of death from gynecologic cancer, the etiology remains elusive. There is intriguing evidence that insulin may play a role in the development of ovarian cancer. It is well known that insulin resistance is associated with diabetes, mellitus, and cardiovascular disease. Recent epidemiologic studies, however, have identified biological determinants of hyperinsulinemia as risk factors for ovarian cancer. Insulin is an important growth factor and it may promote ovarian cancer by acting directly on ovarian tissue or by modifying hormone activity levels, most importantly androgens. To date no studies have evaluated the role of hyperinsulinemia and insulin resistance on the risk of developing ovarian cancer. We propose the first study to look systematically at these factors. The primary aims and related hypotheses of this study are to:

1.   Determine if the following biological markers associated with insulin resistance differ between women who develop ovarian cancer and women who do not.

a) fasting glucose and insulin levels, insulin/glucose ratio

b) body size and body fat distribution (body mass index, waist-to-hip ratio)

2.   Determine the serum levels of IGF-I, IGFBP-I, and IGFBP-3 among women who develop ovarian cancer and controls.

Results/Findings

For a complete, up-to-date list of WHI papers related to this ancillary study, please use the searchable Bibliography section of this website. To search for papers by study number, access the Simple Search, and enter the study number in the “Related Studies” field.