Pachman, Deirdre R.

1543 Background: Treatment toxicity may limit the ability of cancer patients to receive all recommended cycles of therapy. Four to six cycles of docetaxel plus cyclophosphamide (TC) is a common adjuvant chemotherapy regimen for early-stage breast cancer. We assessed the impact of routine collection of patient-reported outcomes (PROs), coupled with a collaborative care model-based symptom management intervention, on the number of cycles of TC received by patients with breast cancer. Methods: The Enhanced, EHR-facilitated Cancer Symptom Control (E2C2) trial was a cluster-randomized, pragmatic clinical trial, conducted between March 2019 and January 2023 at Mayo Clinic Rochester and within the Mayo Clinic Health System in Minnesota and Wisconsin. Patients regularly reported the severity of 6 SPPADE symptoms (Sleep deficit, Pain, Physical function impairment, Anxiety, Depression, and Energy deficit/fatigue) on 11-point numerical rating scales. Each symptom score was interpreted as none to mild (0-3), moderate (4-6), or severe (7-10). The E2C2 intervention included symptom management education modules, clinician decision support aids, and the option to discuss severe symptoms with a nurse, physical therapist, or social worker. Patients with breast cancer who received at least one cycle of TC were included in this analysis. We compared the number of cycles of docetaxel and cyclophosphamide completed by patients in the control condition versus those in the intervention condition. Results: We identified 198 patients with breast cancer who received TC during the control condition and 128 who received TC during the intervention condition. Median age was 61.3 years in the control group and 60.3 years in the intervention group, and 94% and 95% were white, respectively. Those receiving treatment during the control condition, on average, completed 3.53 cycles of docetaxel, while those receiving TC during the intervention condition completed 3.77 cycles ( p = 0.014). Seventy-eight percent in the control group completed at least 4 cycles of docetaxel, compared to 84% in the intervention group. Those receiving TC during the control condition completed an average of 3.71 cycles of cyclophosphamide, compared to 3.78 cycles in the intervention condition (p = 0.231). Eighty-four percent of patients in the control group and 86% in the intervention group completed at least 4 cycles of cyclophosphamide. Conclusions: Routine PRO surveillance, coupled with guideline-based collaborative care interventions, was associated with completion of a greater number of cycles of docetaxel. These findings suggest that routine symptom surveillance and management may enhance the docetaxel tolerance profile and improve treatment adherence in patients with early-stage breast cancer, allowing for delivery of an optimized treatment course.

The objective of this manuscript is to present the protocol of a study aiming to test the effects of Accelerated Resolution Therapy® (ART) on pre-loss grief and prolonged grief among older adult family caregivers. This study also aims to better understand predictors of response to ART®, and cognitive processes that occur among grieving individuals following ART®. Design: The study is a double-blinded, randomized clinical trial. Setting: This study takes place at both inpatient and outpatient palliative care and hospice programs at two Mayo Clinic sites. Participants: Participants include older adult ( ≥ 60 years) immediate family members who are primary caregivers of someone with an advanced illness and life expectancy of less than 12 months. Intervention: Participants are randomized to either the ART® intervention group or the attention control group. In the ART® intervention, caregivers engage in imaginal exposure, lateral eye movements, and imagery rescripting via 4 sessions lasting 1-1.5 hours each. The attention control group receives a standard social work intervention, including education, resources, and active listening, which is matched for time and attention. Both interventions will longitudinally follow caregivers from active caregiving into bereavement. Outcomes Measured: The primary outcomes of pre-loss grief and prolonged grief will be measured with the Pre-Loss Grief 12 item (PG-12-R) before the care recipient’s death, and with the Prolonged Grief-13 (PG-13-R) afterwards.

AbstractObjectivesTo report lessons from integrating the methods and perspectives of clinical informatics (CI) and implementation science (IS) in the context of Improving the Management of symPtoms during and following Cancer Treatment (IMPACT) Consortium pragmatic trials.Materials and MethodsIMPACT informaticists, trialists, and implementation scientists met to identify challenges and solutions by examining robust case examples from 3 Research Centers that are deploying systematic symptom assessment and management interventions via electronic health records (EHRs). Investigators discussed data collection and CI challenges, implementation strategies, and lessons learned.ResultsCI implementation strategies and EHRs systems were utilized to collect and act upon symptoms and impairments in functioning via electronic patient-reported outcomes (ePRO) captured in ambulatory oncology settings. Limited EHR functionality and data collection capabilities constrained the ability to address IS questions. Collecting ePRO data required significant planning and organizational champions adept at navigating ambiguity.DiscussionBringing together CI and IS perspectives offers critical opportunities for monitoring and managing cancer symptoms via ePROs. Discussions between CI and IS researchers identified and addressed gaps between applied informatics implementation and theory-based IS trial and evaluation methods. The use of common terminology may foster shared mental models between CI and IS communities to enhance EHR design to more effectively facilitate ePRO implementation and clinical responses.ConclusionImplementation of ePROs in ambulatory oncology clinics benefits from common understanding of the concepts, lexicon, and incentives between CI implementers and IS researchers to facilitate and measure the results of implementation efforts.

PURPOSE The enhanced, electronic health record (EHR)–facilitated cancer symptom control (E2C2) trial is a cohort cluster-randomized, stepped-wedge, hybrid type II trial that leverages EHR systems to facilitate a collaborative care model (CCM) approach with the goal of improving cancer symptom management. Understanding factors that influence care team adoption of EHR systems remains a critical understudied area of research. This study examines how oncology care teams' perceptions regarding the feasibility, acceptability, and appropriateness of E2C2 EHR systems preimplementation were associated with adoption 3 months after implementation and characterizes differences in adoption by individual- and system-level factors. METHODS Care team members completed an electronic survey before and 3 months after implementation of E2C2 for their respective sequence. Adoption was defined as frequency of use to statements aligned with care team–directed EHR systems designed to facilitate CCM approaches. Chi-square tests assessed differences in adoption while logistic regression models estimated associations between baseline mean scores of acceptability, feasibility, and appropriateness on care team adoption at 3 months. RESULTS Results from 94 care team members (37.2% oncologists, 72.6% female, 55.3% in their role for 6+ years) found that adoption rates ranged from 48.9% to 71.7%, with significant differences observed by location (community-based health care systems v tertiary medical center) and professional role. Adjusting for professional role, care team members reporting higher levels of perceived acceptability and appropriateness at baseline had greater odds of adopting EHR systems at 3 months. CONCLUSION EHR systems perceived as acceptable and appropriate are more likely to be adopted by oncology care teams in our sample. Future implementation efforts should consider tailored strategies to facilitate adoption of EHR systems designed to promote CCM-based approaches to improve cancer symptom management.

12079 Background: Many troublesome symptoms experienced by men with prostate cancer are not specific to a particular disease state or treatment modality. As such, these issues' scope is neither fully appreciated nor characterized in the reporting of clinical trial data. A modern accounting of poorly controlled symptoms is needed to better inform survivorship and supportive care efforts. Methods: Data are drawn from the Enhanced, EHR-facilitated Cancer Symptom Control (E2C2) study, a cluster-randomized stepped wedge trial examining the effectiveness of routine symptom assessment and management on patient-centered outcomes and healthcare utilization (NCT03892967). This is a population-level study supporting patients with cancer, who are cared for in medical oncology clinics across the Midwest United States. The trial utilizes an automated symptom monitoring system with EHR-enabled algorithms for symptom triage and intervention. The current analysis focuses on pre-intervention surveys. The cohort includes E2C2 participants with prostate cancer (as determined by the Mayo Clinic Cancer Registry) receiving curative or palliative-intent therapies, along with prostate cancer survivors who previously completed their treatment. The prevalence of SPPADE symptoms (sleep disturbance, pain, impaired physical function, anxiety, depression, fatigue [low energy]) was assessed using 0 to 10 numerical rating scales (NRS), with scores of 4-6 indicating moderate symptoms and 7-10 indicating severe symptoms. Results: A total of 1,388 men with prostate cancer completed a pre-intervention survey between March 2019 and January 2023. The median age at completion of first survey was 74 years. The cohort includes patients living in diverse settings, including urban (n=718, 52%), micropolitan (n=250, 18%), small town (n=218, 16%), and rural (n=200, 14%) environments. The proportion of patients experiencing moderate-to-severe symptoms (NRS score ≥4) was 47% for fatigue, 40% for impaired physical function, 32% for sleep disturbance, 27% for pain, 22% for anxiety, and 20% for depression/emotional distress. The three domains with the highest prevalence of severe symptoms (NRS score ≥7) were fatigue (17%), impaired physical function (12%), and sleep disturbance (10%). Conclusions: Proactive symptom monitoring identifies a high overall burden of moderate-to-severe symptoms, particularly fatigue and impaired physical function, among prostate cancer patients and survivors. Collaborative care approaches and symptom control trials are needed to mitigate and manage these burdensome symptoms. Clinical trial information: NCT03892967 . [Table: see text]

12065 Background: Incidence of cancer, including colorectal, breast, pancreas, kidney, and uterine cancer, is increasing in younger populations. Adolescents and young adults (AYA, defined as age 15-39) with cancer face unique challenges. This study aimed to characterize how symptom burden differs between AYA and non-AYA (aged 40+) patients with cancer. Methods: We performed a subgroup analysis of the E2C2 study, a cluster-randomized, pragmatic trial examining the effectiveness of routine symptom assessment and guideline-based management on patient-centered and healthcare utilization metrics during and following cancer treatment. Six symptoms [Sleep disturbance, Pain, Physical function impairment, Anxiety, Depression, and Energy deficit/fatigue (SPPADE)] were evaluated using 11-point numerical rating scales (NRS). Symptom severity was classified as mild (0-3), moderate (4-6), or severe (7-10). We conducted a subgroup analysis of symptom burden among AYA patients (defined as age 18-39 in this study), using their first-reported NRS scores. Results: The E2C2 cohort included 2,598 AYA patients and 38,061 non-AYA patients who completed >1 SPPADE NRS on at least one survey. AYA patients were more likely than non-AYA patients to report severe anxiety ( p<0.0001) and depression ( p<0.0001) (Table). Non-AYA patients were more likely to report severe pain ( p=0.02179), fatigue ( p=0.0022), and physical function limitations ( p<0.0001). Sociodemographic differences were also noted. A higher proportion of AYA patients held a bachelor’s degree or higher (38% vs 28%), were employed (73% vs 37%), and lived in an urban setting (67% vs 56%), compared to non-AYA patients. Non-AYA patients were more likely to have government insurance (63% vs 21%) and to be married (72% vs 59%). Conclusions: AYA patients with cancer were more likely to report severe depression and anxiety compared to their counterparts age 40 and above, underscoring the need for targeted and tailored psycho-oncology care for this population. [Table: see text]

LBA12006 Background: Symptom burden and functional decline are prevalent, inconsistently treated, and associated with adverse health outcomes in patients with cancer. Symptom monitoring with electronic patient-reported outcome measures (ePROMs) has yielded mixed results due, in part, to care teams’ variable bandwidth and resourcing for symptom management. The collaborative care model (CCM) offers a validated means to address these issues and potentially improve clinical and health services outcomes. Capturing ePROMS through the electronic health record (EHR) for use in CCM delivery provides a potentially scalable approach to manage symptoms at the population level. Methods: E2C2 is a cluster-randomized, population-level, stepped wedge pragmatic trial that compares a bundled, EHR-facilitated, CCM-based intervention to improve control of SPPADE symptoms (Sleep interference, Pain, impaired Physical function, Anxiety, Depression, and Energy deficit/fatigue) with usual care. All patients, regardless of cancer type or stage, treated in the medical oncology clinics of a multi-state health system, were assigned to one of fifteen clusters. Control and intervention conditions monitored SPPADE symptoms with Epic EHR administered 11-point numerical rating scales (NRSs). Moderate and severe symptoms were defined as 4-6/10 and >7/10, respectively. The intervention added EHR clinician decision support; automated delivery of symptom self-management information; and options to address severe symptoms with a dedicated symptom care manager. The primary outcome was post-baseline SPPADE scores assessed using multivariate regression of six cluster-period mean SPPADE symptom scores against E2C2 exposure, fixed cluster and secular time effects. Results: From March 2019 to January 2023, 50,559 patients were assigned to E2C2 clusters and 40,295 completed at least one ePROM. At first assessment, participants’ mean age was 63.3 years; 58% were female; 26% were rural, and the prevalences of moderate or worse symptoms were fatigue 42%, impaired function 34%, sleep disturbance 34%, anxiety 27%, pain 26%, and depression 23%. The intervention significantly reduced mean composite SPPADE symptom scores, p <0.001, among all patients, as well as those with >1 moderate or worse symptom. All mean symptom scores were lower in the intervention group, with the largest effects detected among patients with fatigue -0.2 (-0.4, -0.07), anxiety -0.14 (-0.2, -0.03), and depression -0.1 (-0.2, -0.002). Conclusions: In this large cluster-randomized trial, an EHR-facilitated, bundled intervention that scaled CCM-based surveillance and management of SPPADE symptoms significantly reduced population-level symptom burden, particularly for fatigue, anxiety, and depression. This study provides real world evidence and the foundation for future national efforts aimed at controlling symptoms in patients with cancer. Clinical trial information: NCT03892967 .

1559 Background: Timely access to specialty Palliative Care (SPC) services provides significant benefits to hospitalized patients with cancer, including improvements in quality of life. However, many patients with cancer who could benefit from SPC suffer from lack of timely referral or do not receive SPC services. A previously published trial of an artificial intelligence/machine learning (AI/ML) model to predict need for SPC at Mayo Clinic increased timely SPC consultation of hospitalized patients overall. We sought to review the performance of this algorithm in patients with cancer across an expanded hospitalized population. Methods: The study population consisted of all patients admitted into a Mayo Clinic hospital in Minnesota, Wisconsin, Arizona and Florida between January 2020 and September 2023. Due to the size of the cohort a case-control sample of three controls for every case was created. Patients were considered to be a patient with cancer if they had at least one billing diagnosis up to 1 year prior to their index hospitalization from any of the 5 HCC categories denoting cancer: Metastatic Cancer and Acute Leukemia (HCC 8); Lung and Other Severe Cancers (HCC 9); Lymphoma and Other Cancers (HCC 10); Colorectal, Bladder, and Other Cancers (HCC 11); and Breast, Prostate, and Other Cancers and Tumors (HCC 12). The training data set consisted of 107,076 patient encounters with a total of 8,355,090 time periods of constant risk. An AI/ML model using gradient boosting methods which contained 269 variables (both static and time-varying) of various classes with SPC consultation treated as a time-to-event outcome was trained. Results: Due to the longitudinal nature of the prediction, performance was assessed using the max score AUC (using the max score a patient received during a given encounter prior to an event or discharge) to produce the AUC. The model had an overall AUC of 0.932 (0.929, 0.935 – 95% CI). We saw a decrease in performance of the AI/ML model in the Oncology population with an overall performance of 0.818 (0.806, 0.83). Some of the most influential variables were previous SPC visit, age, metastatic disease, acute leukemia diagnosis, and pain scores. Conclusions: An AI/ML model can effectively predict the need for an inpatient PC consult in a population of hospitalized patients with cancer. [Table: see text]

11108 Background: Advances in cancer treatment have led to a growing population of patients living with metastatic cancer. Symptom burden for these patients is understudied. Our objective is to report the prevalence and severity of SPPADE symptoms (sleep disturbance, pain, physical function impairment, anxiety, depression, and low energy /fatigue) in a large cohort of patients with metastatic cancer. Methods: These data are drawn from the Enhanced, EHR-facilitated Cancer Symptom Control (E2C2) stepped wedge pragmatic trial evaluating a symptom management intervention for cancer patients (NCT03892967). This analysis was limited to those identified with metastatic disease using ICD- codes and a natural language processing algorithm prior to or within 30 days of their baseline symptom survey. Symptom severity was measured on a 0-10 scale with scores of 1-3 categorized as “mild”, 4-6 as “moderate”, and ≥7 as “severe.” A SPPADE composite score was calculated by summing six individual symptom scores and is an indicator of total symptom burden. We report descriptive statistics for each symptom by severity category. We also test for differences in SPPADE composite score by race, disability status, employment status, education and cancer type using Kruskal-Wallis tests. Results: 12,824 patients with metastatic disease completed a survey between March 2019 and January 2023. Discretized score distributions for the SPPADE symptoms are reported in the Table. The SPPADE composite mean score for the cohort was 17.6 (SD +/- 12.0). Significant differences were found in total symptom burden by sociodemographic and clinical characteristics ( p<0.01): Higher total symptom burden (Mean [SD])was experienced by individuals who were American Indian/Alaska Native (AI/AN) (23.8[13.5]) or African American (AA) (20.5[14.7]), disabled (24.0[12.8]) or unemployed (21.1[13.0]), and had a high school education (20.0[13.3]) or less than high school education (18.5[12.4]). There were also statistically significant differences ( p<0.01) in symptom burden across cancer types, with patients with metastatic lung cancer reporting the highest symptom burden (20.0[12.2]) and those with metastatic melanoma reporting the lowest (14.7[11.4]). Conclusions: SPPADE symptoms are common in patients with metastatic cancer, especially fatigue, sleep disturbance, and physical function impairment. Symptom burden is especially high in AI/AN, AA, disabled/unemployed, and less educated patients. Further research is needed to tailor symptom interventions among those living with metastatic disease. [Table: see text]

Abstract Background: SPPADE symptoms (Sleep disturbance, Pain, Physical function impairment, Anxiety, Depression/distress, and Energy deficits/fatigue) may result from cancer and its treatment. The aim of this analysis was to characterize SPPADE symptoms in patients with breast cancer. Methods. SPPADE data were drawn from the Enhanced, EHR-facilitated Cancer Symptom Control (E2C2) study, a stepped-wedge pragmatic cluster-randomized trial designed to evaluate a symptom management intervention in routine practice (NCT03892967). Symptom severity was measured on a 0-10 scale via a survey administered by patient portal, in-clinic tablet, or interactive voice response system (by phone) prior to, during, or soon after an outpatient oncology encounter. Scores of 4-6 were categorized as “moderate” and ≥7 as “severe.” In this analysis, only the data from each patient’s initial survey were included. Results. A total of 9,651 patients with breast cancer completed an initial E2C2 survey between March 2019 and January 2023. The proportion of patients with moderate or severe SPPADE symptoms were as follows: 22% moderate and 10% severe for insomnia; 18% moderate and 7% severe for pain; 17% moderate and 7% severe for anxiety; 15% moderate and 5% severe for emotional distress; 25% moderate and 12% severe for fatigue; and 22% moderate and 8% severe for impaired physical function. Table 1 presents score means and standard deviations by demographic subgroup. Conclusions. SPPADE symptoms are common in patients with breast cancer. These observations warrant routine implementation of symptom surveillance and management in breast oncology. Funding acknowledgement: The Improving the Management of symPtoms during And following Cancer Treatment (IMPACT) Consortium is a Cancer Moonshot Research Initiative under the authorization of the 2016 United States 21st Century Cures Act. This research was supported by the National Cancer Institute of the NIH, UM1CA233033 (Mayo Clinic, Rochester, MN). Insomnia, Pain, Anxiety, Distress, Fatigue, and Functional Impairment in Patients with Breast Cancer Citation Format: Kathryn Ruddy, Veronica Grzegorczyk, Deirdre Pachman, Sandra Mitchell, Bolun Liu, Deanne Smith, Ciara O'Sullivan, Shawna Ehlers, Jeph Herrin, Parvez Rahman, Andrea Cheville. Insomnia, Pain, Anxiety, Distress, Fatigue, and Functional Impairment in Patients with Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-12-09.