ABSTRACT
Background: Patients with relapsed/refractory acute myeloid leukemia (AML) have poor outcomes and high levels of healthcare utilization at end of life. Palliative care remains underused in this population despite the high symptom burden. Questions remain regarding how best to integrate palliative care for high risk hematology patients. Prior implementation of standardized palliative care consultation triggers on an inpatient solid tumor service led to increased palliative care consultations and decreased healthcare utilization (Adelson et al, JOP 2017). We conducted a prospective cohort study evaluating standardized palliative care consultation triggers for patients admitted to a tertiary academic center with advanced AML. Method: Trigger criteria were developed for hospitalized patients with hematologic malignancies on the inpatient hematology floors at Smilow Cancer Hospital and included: 1) persistent disease after ≥ 2 lines of therapy, 2) length of stay (LOS) >7 days for symptom management, 3) Eastern Cooperative Oncology Group (ECOG) performance status > 2, and 4) refractory graft versus host disease (GVHD) after ≥ 3 lines of therapy. Patients with relapsed/refractory AML were included if they met criteria #1. A palliative care nurse coordinator performed chart review of admitted patients 1-2 times per week from June to December 2020 and contacted the primary team when a patient met eligibility. Patient characteristics and healthcare outcomes were compared with patients with AML meeting criteria #1 admitted pre-intervention (June to December 2019) using Fisher t-tests. Results: A total of 110 admitted patients with advanced AML met eligibility criteria #1 (64 pre-intervention and 46 post-intervention). Baseline patient and disease characteristics were similar, including mean age at admission (60.4 vs 60.9 years, p=0.848), gender (64% vs 59% male, p=0.691), prior transplant (56% vs 52%, p=0.702), and AML risk stratification (67% vs 78% adverse risk, p=0.283). In the post-intervention group, 61% of eligible patients were screened. Of the screened patients, 54% received a palliative care consult, 18% were declined by the primary team, 14% were marked as not eligible, and 14% did not have a palliative care consult with reason unspecified. Within the same admission, there was a significant increase in advance care planning and/or advanced directive documentation post-intervention (13% vs 28%, p=0.049). There was no differences in pre- and post-intervention groups in time to palliative care consult from admission (7.2 vs 4.9 days, p=0.245), LOS (12.13 vs 12.33 days, p=0.941), 30-day readmissions (52% vs 39%, p=0.246), critical/intermediate care escalation (22% vs 13%, p=0.318) during the same admission. By July 2021, 92% of the pre-intervention patients and 57% of the post-intervention patients were deceased. Of the deceased patients, there was no differences in pre- and post-intervention groups in blood transfusions (100% vs 96%, p=0.306) or hospice enrollment (46% vs 62%, p=0.157) within 14 days of death. There was also no significant differences in pre- and post-intervention groups in non-palliative anti-neoplastic therapy use (37% vs 38%, p=0.999), hospital admissions (95% vs 88% p=0.364), or critical/intermediate care escalation (51% vs 38%, p=0.350) within 30 days of death. Conclusion: A trigger-based palliative care referral intervention is feasible and doubled palliative care use in patients with relapsed/refractory AML. Our intervention was associated with increased advance care planning documentation during the admission. There were directional changes in other healthcare measures, including decreased time to palliative care consult and escalation of care, as well as increased hospice enrollment. These differences, however, were not statistically significant due to the small sample size. The significant healthcare use likely reflected high symptom burden at end of life, associated with transfusions and admissions for infection and symptom management. More research is needed to determine how best to sup ort these patients at end of life. Of note, our intervention period occurred during the COVID-19 pandemic, which may have impacted threshold for inpatient admissions and the inpatient census. Disclosures: Adelson: Carrum Health: Other: Stock;Abbvie: Consultancy;Roche/Genentech: Consultancy, Honoraria, Patents & Royalties, Research Funding;Heron: Consultancy;Celgene: Consultancy. Prebet: BMS: Research Funding;BMS, Curios, Daichi: Consultancy.
ABSTRACT
Background: Patient-trial matching is a critical step in clinical research recruitment that requires extensive review of clinical data and trial requirements. Prescreening, defined as identifying potentially eligible patients using select eligibility criteria, may streamline the process and increase study enrollment. We describe the real-world experience of implementing a standardized, universal clinical research prescreening protocol within a VA cancer center and its impact on research enrollment. Methods: An IRB approved prescreening protocol was implemented at the VACT Cancer Center in March 2017. All patients with a suspected or confirmed diagnosis of cancer are identified through tumor boards, oncology consults, and clinic lists. Research coordinators perform chart review and manually enter patient demographics, cancer type and stage, and treatment history into a REDCap (Research Electronic Data Capture) database. All clinical trials and their eligibility criteria are also entered into REDCap and updated regularly. REDCap generates real time lists of potential research studies for each patient based on his/her recorded data. The primary oncologist is alerted to a patient's potential eligibility prior to upcoming clinic visits and thus can plan to discuss clinical research enrollment as appropriate. Results: From March 2017 to December 2020, a total of 2548 unique patients were prescreened into REDCAP. The mean age was 71.5 years, 97.5% were male, and 15.5% were African American. 32.57 % patients had genitourinary cancer, 17.15% had lung cancer, and 46.15% were undergoing malignancy workup. 1412 patients were potentially eligible after prescreening and 556 patients were ultimately enrolled in studies. The number of patients enrolled on therapeutic clinical trials increased after the implementation of the prescreening protocol (35 in 2017, 64 in 2018, 78 in 2019, and 55 in 2020 despite the COVID19 pandemic). Biorepository study enrollment increased from 8 in 2019 to 15 in 2020. The prescreening protocol also enabled 200 patients to be enrolled onto a lung nodule liquid biopsy study from 2017 to 2019. Our prescreening process captured 98.57% of lung cancer patients entered into the cancer registry during the same time period. Conclusions: Universal prescreening streamlined research recruitment operations and was associated with yearly increases in clinical research enrollment at a VA cancer center. Our protocol identified most new lung cancer patients, suggesting that, at least for this malignancy, potential study patients were not missed. The protocol was integral in our program becoming the top accruing VA site for NCI's National Clinical Trial Network (NCTN) studies since 2019.