Ovarian cancer is the leading cause of death from gynecologic malignancies in the United States. Because symptoms tend be nonspecific, early detection is difficult and most ovarian cancers are diagnosed at an advanced stage when the prognosis is poor. Nonetheless, there is clinical evidence that even given the same tumor characteristics, some cases experience much better survival than others. However, little is known about lifestyle factors affecting ovarian cancer survival. Obesity in particular may delay diagnosis, hinder optimal surgical and cytotoxic treatment, and cause postoperative complications. Kaiser Permanente Northern California (KPNC) offers a unique opportunity to evaluate the impact of obesity and weight changes on several aspects of ovarian cancer clinical management, including detection, treatment, and survival, as it comprises a large population with detailed laboratory, clinical, and treatment information. We propose to conduct a retrospective cohort study including approximately 1,900 invasive ovarian cancer cases diagnosed between 2000-2008 and follow-up information through 2010 among KPNC members. Our main objectives are to examine the role of body mass index (BMI) on ovarian cancer survival and on CA-125 levels, a tumor marker routinely used in the clinical management of ovarian cancer. Multivariate Cox Proportional Regression methods will be used to estimate hazard ratios and 95% confidence intervals. We will also use multivariate logistic regression to evaluate the association between BMI and elevated CA-125 (defined as >35 U/ml). Our findings may provide critical information to improve our understanding of ovarian cancer prognostic factors and to reduce disparities in the quality of cancer care in obese patients, with the ultimate goal of improving clinical management of ovarian cancer to reduce ovarian cancer deaths. This study represents the first step in the preparation of an R01 application to develop a prospective cohort study of ovarian cancer survivors among KPNC members to study genetic and lifestyle factors affecting survival. In addition to addressing significant issues, the study is designed to provide experience in cancer survivorship, as well as familiarity with KPNC files and procedures, and to generate preliminary data and publications to support the R01 proposal. The proposed plans for a K22 Award will complement the strong foundation provided by the candidate's K07 Award and afford her the additional protected time needed during her critical transition phase to become an independent investigator and a leading expert in the nutritional epidemiology of female hormonal cancers, spanning prevention and survival.

Public Health Relevance

We propose to evaluate the role of excess body mass and changes in weight on ovarian cancer prognosis using the unique opportunity provided by the Kaiser Permanente of Northern California system, which includes a large population with detailed laboratory and clinical information. Our study has the potential to provide critical information for the optimal management of ovarian cancer with the ultimate goal of reducing ovarian cancer deaths.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Career Transition Award (K22)
Project #
1K22CA138563-01A2
Application #
7988376
Study Section
Subcommittee G - Education (NCI)
Program Officer
Jakowlew, Sonia B
Project Start
2010-09-01
Project End
2013-08-31
Budget Start
2010-09-01
Budget End
2011-08-31
Support Year
1
Fiscal Year
2010
Total Cost
$203,040
Indirect Cost
Name
University of Medicine & Dentistry of NJ
Department
Surgery
Type
Schools of Medicine
DUNS #
617022384
City
Piscataway
State
NJ
Country
United States
Zip Code
08854
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Harris, Holly R; Babic, Ana; Webb, Penelope M et al. (2018) Polycystic Ovary Syndrome, Oligomenorrhea, and Risk of Ovarian Cancer Histotypes: Evidence from the Ovarian Cancer Association Consortium. Cancer Epidemiol Biomarkers Prev 27:174-182
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Praestegaard, Camilla; Jensen, Allan; Jensen, Signe M et al. (2017) Cigarette smoking is associated with adverse survival among women with ovarian cancer: Results from a pooled analysis of 19 studies. Int J Cancer 140:2422-2435
Reid, Brett M; Permuth, Jennifer B; Chen, Y Ann et al. (2017) Integration of Population-Level Genotype Data with Functional Annotation Reveals Over-Representation of Long Noncoding RNAs at Ovarian Cancer Susceptibility Loci. Cancer Epidemiol Biomarkers Prev 26:116-125

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