No abstract

Successful proband‐mediated family communication and subsequent cascade genetic testing uptake requires interventions that present information clearly, in sufficient detail, and with medical authority. To facilitate family communication for patients receiving clinically actionable results via the MyCode® Community Health Initiative, a Family Sharing Tool (FST) and a cascade chatbot were developed. FST is an electronic mechanism allowing patients to share genetic test results with relatives via chatbot. The cascade chatbot describes the proband's result, associated disease risks, and recommended management and captures whether the user is a blood relative or caregiver, sex, and relationship to the proband. FST and cascade chatbot uptake among MyCode® probands and relatives was tracked from August 2018 through February 2020. Cascade genetic testing uptake was collected from testing laboratories as number of cascades per proband. Fifty‐eight percent (316/543) of probands consented to FST; 42% (227/543) declined. Receipt preferences were patient electronic health record (EHR) portal (52%), email (29%), and text (19%). Patient EHR portal users (p < 0.001) and younger patients were more likely to consent (p < 0.001). FST was deployed to 308 probands. Fifty‐nine percent (183/308) opened; of those, 56% (102/183) used FST to send a cascade chatbot to relatives. These 102 probands shared a cascade chatbot with 377 relatives. Sixty‐two percent (235/377) of relatives opened; of these, 69% (161/235) started, and of these, 57% (92/161) completed the cascade chatbot. Cascade genetic testing uptake was significantly greater among relatives of probands who consented to the FST (M = 2.34 cascades, SD = 2.10) than relatives of probands who declined (M = 1.40 cascades, SD = 0.82, p < 0.001). Proband age was not a significant predictor of cascade genetic testing uptake. Further work is needed to better understand factors impacting proband use of FST and relative use of cascade chatbots.

Background Medicare cancer expenditures in the last month of life have increased. Aggressive cancer care at the end-of-life (ACEOL) is considered poor quality care. We used Geisinger Health Plan (GHP) last month’s costs for cancer patients who died in 2018 and 2019 to determine the costs of and influence of Palliative Care (PC) on ACEOL. Method Patients with GHP ages 18-99 who died in 2018 and 2019 were included. Demographic, clinical characteristics, and Charlson Comorbid Index were compared across care groups defined as no ACEOL indicator, 1 or more than 1 indicator. Differences between groups were compared with Kruskal-Wallis tests and one-way ANOVA for 3 groups. Median two-sample tests and independent t-tests compared groups of 2. A P-value </= .05 indicated statistical significance. Results Of 608 eligible patients; 261 had no indicator, 133 had 1 and 214 > 1. There were incremental cost increases with each additional ACEOL indicator (p = < .0001). Palliative Care <90 days before death was associated with increased costs while consultations >90 days before death lowered cost (P < .0001) due to reduced chemotherapy in the last month. Completed ADs reduced cost by $4000. Discussion ACEOL indicators multiply costs during the last month of life. Palliative care instituted >90 days before death reduces chemotherapy in the last month of life and AD reduces health care costs. Conclusion Cancer health care costs increase with indicators of ACEOL. Palliative care consultations >90 days before death; ADs reduce cancer health care costs.

Background Predicting poor survival outcomes early in palliative chemotherapy is important to the timing of palliative care. Weight loss during chemotherapy if prognostic would lead to early palliative care. Method We collected demographics, stage, chemotherapy, chemotherapy cycles, weight, healthcare utilization, comorbidities (Charleson Comorbid Index), tumor markers, and weight changes over 60 days. We defined 3 groups of patients: 1. Weight gain to <.5% weight loss, 2. Weight loss< 2% and 3. Weight loss of >2%. A Chi-square test assessed differences in weight during treatment. Time-to-event analysis was expressed in a Kaplan Meier curve. Results 93 individuals died of pancreatic cancer in 2018 and 2019. The median age was 71.2 years. Forty-three had stage I and II, 40 stages III and IV cancers, and 10 had unknown stages. Most received FOLFIRINOX and gemcitabine/nab-paclitaxel chemotherapy. Thirty-six gained to lost < .5% during chemotherapy,8 lost < 2% and 49 patients lost > 2% of their weight. Mortality was available in 55 of 93 patients. Median survival was 16.6 months in those with weight gain to < .5% weight loss, 17.28 months for those with < 2% weight loss, and 20.5 months for those with > 2% weight loss ( P = .42). Discussion Weight loss over 60 days did not predict a poor prognosis in this small retrospective study; larger prospective studies may clarify the prognostic importance of weight loss during chemotherapy. Conclusion In this small retrospective study, weight loss over 60 days did not predict poor survival.

BackgroundEarly palliative care improves patient quality of life and in uences cancer care. The time frame of early has not been established. Eight quality measures re ect aggressive care at the end of life. We retrospectively reviewed patients who died with cancer between January 1, 2018 through December 31, 2019, and compared the timing of palliative care consultation, advance directives (AD), and home palliative care with aggressive care at the end of life (ACEOL). MethodsPatients without ACEOL indicators were compared to patients with one or more than one indicator of ACEOL. The proportion of patients who received palliative care, completed AD, and the timing of palliative care and AD (less than 30 days, 60-90 days, and greater than 90 days prior to death) was compared for patients who had ACEOL versus those who did not. Chi-square analysis was used for categorical data, one-way ANOVA for continuous variables, and odds ratio (OR) with con dence intervals (CI) was reported as a measure of effect size. A p-value 90 days (OR 0.46,95% CI 0.38-0.57).The most common indicator of ACEOL was new chemotherapy within 30 days of death, in 571 of 888 (64%) of patients experiencing ACEOL. DiscussionAD reduce ACEOL and often re ect goals of care and end-of-life discussions in the transition of care away from tumor directed therapy. Palliative care paradoxically in our experience is associated with greater ACEOL in the rst 90 days since consultation occurs late in the course of illness and the focus is on crisis management in patients who are frequently utilizing the health care system. If palliative care consultation occurs greater than 90 days before death, there is the opportunity for both aggressive symptom management and end of life discussions which may in uence aggressive care at the end of life.