Grant Number:	5R01CA243188-06 Interpret this number
Primary Investigator:	Doherty, Jennifer
Organization:	University Of Utah
Project Title:	Identifying Multilevel Drivers of Differences in Ovarian Cancer Treatment and Survival: an Integrative Approach
Fiscal Year:	2025

Epithelial ovarian cancer (EOC) is the fifth leading cause of cancer deaths in women, but survival varies widely. This could be due to some women being less likely to receive standard-of-care therapy, and more likely to have chemotherapy dose reduction, even within an equal-access healthcare system. However, these factors do not completely explain observed survival differences, and furthermore, little is known about other factors that might be associated with worse survival. We propose to conduct the first integrative, cells-to-society evaluation of the interplay among multilevel factors on differences in EOC treatment and survival outcomes. We will assemble a cohort of over 6,000 EOC cases diagnosed at Kaiser Permanente Northern California (KPNC) between 2000 and 2022. KPNC has longstanding electronic clinical databases, complete pathology specimen storage, long-term retention of members, and substantial variability in sociodemographic, clinical, and area-based characteristics. We will perform centralized pathology review to classify histotypes by the recent gold standard WHO criteria, and will conduct chart review to capture data that are not available electronically. We will examine multilevel drivers of differences in treatment received, recurrence, and survival (overall and EOC-specific), including geographic accessibility, area-based, healthcare system, and patient-level factors. In 800 women with high grade serous EOC, we will also determine gene expression subtypes and characterize their associations with receipt of treatment and survival. Our comprehensive integrative approach to examine the interplay among patient (e.g., age, obesity, comorbidities) clinical (e.g., tumor stage, histotype, treatments received), health system (e.g., provider volume), geographic (e.g., distance to care, poverty) and biological (e.g., molecular characteristics) factors will provide unique insights into multilevel drivers of persistent poor survival for EOC patients. The KPNC setting provides the opportunity to examine these factors while minimizing confounding by the known contribution of insurance status, leveraging rich clinical databases to investigate and control for detailed prognostic variables. For EOC, this proposed study is unprecedented in its transdisciplinary nature and large sample size, and will serve as a unique resource for future research related to multilevel factors to improve EOC treatment and survival.




BuDDI: Bulk Deconvolution with Domain Invariance to predict cell-type-specific perturbations from bulk.
Authors: Davidson N.R. , Greene C.S. .
Source: Biorxiv : The Preprint Server For Biology, 2023-10-05 00:00:00.0; , .
EPub date: 2023-10-05 00:00:00.0.
PMID: 37503097
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