Grant Number:	1R01CA283207-01A1 Interpret this number
Primary Investigator:	Kurian, Allison
Organization:	Stanford University
Project Title:	Personalizing Genetic Test Results Management and Outcomes After Diagnosis of Cancer: the Georgia-California Seer Genelink Study
Fiscal Year:	2024

Abstract: The rapid diffusion of genetic testing across adult cancer diagnoses is a unique opportunity to personalize cancer treatment and prevention at the population level. Germline genetic testing guidelines have broadened to encompass nearly all patients with breast, ovarian and pancreatic cancer; all patients with advanced prostate cancer; and many patients with colorectal, endometrial, and other cancer types. The growing use of genetic testing is driving the development of precision oncology: a new paradigm for personalizing prevention and treatment based on genetic testing results in addition to or instead of traditionally- measured tumor features. Increasingly, an inherited pathogenic variant in a specific gene serves as an essential common thread that connects diverse cancer diagnoses and enables genetically-targeted cancer therapy. However, we know virtually nothing about how genetic test results are managed across cancer types. We pioneered the Georgia-California (GACA) Genetic Testing Linkage Initiative, linking industry-provided genetic testing data to SEER registry records for all adults diagnosed with cancer in Georgia and California from 2013-19. We found that genetic testing across cancer conditions has increased but rates are too low relative to clinical recommendations. Our foundational work underscores the urgent need for research about how well genetic testing results are broadly integrated into the management of cancer. We are now completing the next phase of the GACA Genetic Testing Linkage Initiative: merging SEER data for all adults diagnosed with cancer in Georgia or California from 2013-21 (N=1,826,000), with an update planned for cancers diagnosed in 2022-23 (N=456,000), to genetic results through 2025. We will use this unique, population-based data infrastructure to determine whether genetic testing results management is effectively personalized across common cancers with high testing rates. We will also examine cancer mortality by genetic testing results to inform communication about prognosis and personalized treatment. Our hypotheses are as follows: Extensiveness of surgery (e.g., organ preservation vs. removal) is well-personalized: it is strongly associated with clinical indications derived from tumor features, host factors and actionable genetic results, but not with non-actionable genetic results, socioeconomic or healthcare system factors. Receipt of chemotherapy and genetically targeted systemic therapies (immune checkpoint inhibitors and poly(ADP-ribose) polymerase inhibitors) is well-personalized: these treatments are strongly associated with clinical indications and actionable genetic results, but not with non-actionable genetic results, socioeconomic or healthcare system factors. Among cancer patients treated with systemic therapies, patients with PVs have lower cancer-specific mortality, controlling for tumor features, treatments, comorbidities, socioeconomic and healthcare system factors.





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