Leveraging an Informatics Approach to Identify an Unmet Clinical Need for BRCA1/2 Testing Among Patients With Ovarian Cancer.

PURPOSE: Although BRCA1/2 testing in ovarian cancer improves outcomes, it is vastly underutilized. Scalable approaches are urgently needed to improve genomically guided care. METHODS: We developed a Natural Language Processing (NLP) pipeline to extract electronic medical record information to identify recipients of BRCA testing. We applied the NLP pipeline to assess testing status in 308 patients with ovarian cancer receiving care at a National Cancer Institute Comprehensive Cancer Center (main campus [MC] and five affiliated clinical network sites [CNS]) from 2017 to 2019. We compared characteristics between (1) patients who had/had not received testing and (2) testing utilization by site. RESULTS: We found high uptake of BRCA testing (approximately 78%) from 2017 to 2019 with no significant differences between the MC and CNS. We observed an increase in testing over time (67%-85%), higher uptake of testing among younger patients (mean age tested = 61 years v untested = 65 years, P = .01), and higher testing among Hispanic (84%) compared with White, Non-Hispanic (78%), and Asian (75%) patients (P = .006). Documentation of referral for an internal genetics consultation for BRCA pathogenic variant carriers was higher at the MC compared with the CNS (94% v 31%). CONCLUSION: We were able to successfully use a novel NLP pipeline to assess use of BRCA testing among patients with ovarian cancer. Despite relatively high levels of BRCA testing at our institution, 22% of patients had no documentation of genetic testing and documentation of referral to genetics among BRCA carriers in the CNS was low. Given success of the NLP pipeline, such an informatics-based approach holds promise as a scalable solution to identify gaps in genetic testing to ensure optimal treatment interventions in a timely manner.

Optimal Time to Ship Human Islets Post Tissue Culture to Maximize Islet.

Access to functional high-quality pancreatic human islets is critical to advance diabetes research. The Integrated Islet Distribution Program (IIDP), a major source for human islet distribution for over 15 years, conducted a study to evaluate the most advantageous times to ship islets postisolation to maximize islet recovery. For the evaluation, three experienced IIDP Islet Isolation Centers each provided samples from five human islet isolations, shipping 10,000 islet equivalents (IEQ) at four different time periods postislet isolation (no 37°C culture and shipped within 0 to 18 hours; or held in 37°C culture for 18 to 42, 48 to 96, or 144 to 192 hours). A central evaluation center compared samples for islet quantity, quality, and viability for each experimental condition preshipment and postshipment, as well as post 37°C culture 18 to 24 hours after shipment receipt. Additional evaluations included measures of functional potency by static glucose-stimulated insulin release (GSIR), represented as a stimulation index. Comparing the results of the four preshipment holding periods, the greatest IEQ loss postshipment occurred with the shortest preshipment times. Similar patterns emerged when comparing preshipment to postculture losses. In vitro islet function (GSIR) was not adversely impacted by increased tissue culture time. These data indicate that allowing time for islet recovery postisolation, prior to shipping, yields less islet loss during shipment without decreasing islet function.