Predictors of germline genetic testing referral and completion in ovarian cancer patients at a Comprehensive Cancer Center.

OBJECTIVES: To identify predictors of referral and completion of germline genetic testing among newly diagnosed ovarian cancer patients, with a focus on geographic social deprivation, oncologist-level practices, and time between diagnosis and completion of testing. METHODS: Clinical and sociodemographic data were abstracted from medical records of patients newly diagnosed with ovarian cancer between 2014 and 2019 in the University of North Carolina Health System. Factors associated with referral for genetic counseling, completion of germline testing, and time between diagnosis and test results were identified using multivariable regression. RESULTS: 307/459 (67%) patients were referred for genetic counseling and 285/459 (62%) completed testing. The predicted probability of test completion was 0.83 (95% CI: 0.77-0.88) for patients with a referral compared to 0.27 (95% CI: 0.18-0.35) for patients without a referral. The predicted probability of referral was 0.75 (95% CI: 0.69-0.82) for patients at the 25th percentile of ZIP code-level Social Deprivation Index (SDI) and 0.67 (0.60-0.74) for patients at the 75th percentile of SDI. Referral varied by oncologist, with predicted probabilities ranging from 0.47 (95% CI: 0.32-0.62) to 0.93 (95% CI: 0.85-1.00) across oncologists. The median time between diagnosis and test results was 137 days (IQR: 55-248 days). This interval decreased by a predicted 24.46 days per year (95% CI: 37.75-11.16). CONCLUSIONS: We report relatively high germline testing and a promising trend in time from diagnosis to results, with variation by oncologist and patient factors. Automated referral, remote genetic counseling and sample collection, reduced out-of-pocket costs, and educational interventions should be explored.

Degradation of acetalated dextran can be broadly tuned based on cyclic acetal coverage and molecular weight.

Microparticles (MPs) derived from acid-sensitive biopolymers enable rapid degradation and cargo release under acidic conditions, such as at tumor microenvironments, within lysosomal/phagosomal compartments inside phagocytic cells, or at sites of inflammation. One such acid-sensitive biopolymer, acetalated dextran (Ace-DEX), has tunable degradation rates and pH-neutral degradation byproducts consisting of dextran, acetone, and ethanol. By studying the degradation profiles of Ace-DEX MPs with varying cyclic acetal coverage (CAC) and dextran molecular weight (MW), we concluded that MPs composed of low CAC or high MW polymer degraded the fastest at both pH 7.4 and 5.0. To further understand the properties of this unique polymer, we encapsulated a model drug resiquimod, which is a toll-like receptor (TLR) 7/8 agonist, into Ace-DEX MPs of different polymer CAC and dextran MW. It was observed that resiquimod was released faster from MPs of lower CAC or higher MW. By evaluating the activation of RAW macrophages cultured with different types of resiquimod-loaded Ace-DEX MPs, we found that MPs of lower CAC or higher MW promoted greater nitrite production and resulted in more robust cell activation. Our results indicate we can precisely control the degradation profile, release kinetics, and bioactivity of encapsulated cargos by altering CAC and MW, furthering Ace-DEX MPs' novelty as a drug carrier.