Elena Stoffel

Cascade testing, the site‐specific genetic testing of relatives within families with an inherited condition, is underutilized. Long wait times for appointments in specialty genetics clinics are a known barrier to genetic testing access. In our cancer genetics, New Patient Clinic (NPC), the long wait time for an appointment (on average 5 months for routine referrals), was identified by both providers and patients as a barrier to uptake of cascade testing. Timely testing of at‐risk relatives is essential to maximize the benefits of cascade testing and reduce cancer morbidity and mortality. Our objective was to improve access via implementation of a different clinical model that designated appointments for patients seeking cascade testing. A secondary goal was to improve use of genetic counselor time. We implemented a dedicated Cascade Testing Clinic (CTC) with an expedited triaging and unique scheduling model to decrease patient wait time to appointment and optimize clinician time. We report on the process and outcomes here. Between October 2016 and February 2020, the average wait time between referral date and first scheduled appointment date was 46 days for the CTC compared to 144 days for the NPC ( p < 0.0001). No‐show/cancelation/rescheduling rate was 11.7% in the CTC compared to 29.7% in the NPC ( p < 0.0001). Genetic counselors saw approximately twice as many patients per half‐day clinic in the CTC compared to the NPC ( p < 0.00001). Modifications to clinic staffing and appointment times were made based on provider feedback. Implementation of a dedicated clinic specifically for patients seeking cascade testing significantly shortened wait times for this population, reduced patient drop‐off, and improved clinician efficiency. The relatively straightforward indications and generally uncomplicated medical histories made this an ideal population for expedited appointments.

Background: Racial segregation is linked to poorer neighborhood quality and adverse health conditions among minorities, including worse cancer outcomes. We evaluated relationships between race, neighborhood social disadvantage, and cancer survival. Methods: We calculated overall and cancer-specific survival for 11,367 non-Hispanic Black (NHB) and 29,481 non-Hispanic White (NHW) individuals with breast, colorectal, lung, or prostate cancer using data from the Metropolitan Detroit Cancer Surveillance System. The area deprivation index (ADI) was used to measure social disadvantage at the census block group level, where higher ADI is associated with poorer neighborhood factors. Associations between ADI and survival were estimated using Cox proportional hazards mixed-effects models accounting for geographic grouping and adjusting for demographic and clinical factors. Results: Increasing ADI quintile was associated with increased overall mortality for all four cancer sites in multivariable-adjusted models. Stratified by race, these associations remained among breast (NHW: HR = 1.16, P < 0.0001; NHB: HR = 1.20, P < 0.0001), colorectal (NHW: HR = 1.11, P < 0.0001; NHB: HR = 1.09, P = 0.00378), prostate (NHW: HR = 1.18, P < 0.0001; NHB: HR = 1.18, P < 0.0001), and lung cancers (NHW: HR = 1.06, P < 0.0001; NHB: HR = 1.07, P = 0.00177). Cancer-specific mortality estimates were similar to overall mortality. Adjustment for ADI substantially attenuated the effects of race on mortality for breast [overall proportion attenuated (OPA) = 47%, P < 0.0001; cancer-specific proportion attenuated (CSPA) = 37%, P < 0.0001] prostate cancer (OPA = 51%, P < 0.0001; CSPA = 56%, P < 0.0001), and colorectal cancer (OPA = 69%, P = 0.032; CSPA = 36%, P = 0.018). Conclusions: Area-level socioeconomic disadvantage is related to cancer mortality in a racially diverse population, impacting racial differences in cancer mortality. Impact: Understanding the role of neighborhood quality in cancer survivorship could improve community-based intervention practices.