Flynn, Kathryn E.

11025 Background: Adjuvant endocrine therapy (AET) improves outcomes in HR+ breast cancer. Nonadherence to AET is common, but manual screening for nonadherence is fraught. High-specificity structured cancer electronic health record (EHR) data, particularly if it includes key variables like stage, could streamline these steps for both clinical care and research purposes. We conducted an analysis of approaches to identifying patients as eligible for a multi-site AET adherence study to understand how variation in structured data informatics-supported screening impacts coordinator time. Methods: Mayo Clinic implemented a two-step identification: (1) EHR structured data (diagnosis date, stage, ER/PR/HER2 positivity, medication script) to prescreen for eligibility; (2) SureScripts fills to flag nonadherence using proportion of days covered < 80% across early fills. Medical College of Wisconsin (MCW) implemented a more manual screening process for Step 1 using only medication scripts. Coordinators at both sites then conducted a medical record review to assess if the resulting list of patients had a plan to continue AET for at least two additional years. Opt-out clinician permission preceded patient contact; pharmacists delivered a patient reported outcome (PRO)-guided intervention and documented encounters. Results: At Mayo, 829 patients were prescreened for study eligibility through informatics workflow; 120 (14.5%) met eligibility criteria. At MCW, 1,763 patients were prescreened; 168 (9.5%) were eligible. EHR filters included non–breast cancer encounters (50% at MCW) and ineligible based on time since cancer (36% at Mayo; 26% at MCW). At Mayo, screening required 5.6 minutes/patient for experienced coordinators. At MCW, experienced coordinators averaged 6.67 minutes/patient and inexperienced coordinators averaged 9.33 minutes/patient. Conclusions: Structured EHR data, pharmacy-fill information, and standardized workflows allowed consistent prescreening, intervention and recruitment processes across sites. Higher-specificity informatics-supported screening reduced the percentage of patients requiring manual review and reduced coordinator screening time. It also supported timely provider-permission steps and patient outreach. These workflows were feasible to implement at both institutions, and study enrollment is ongoing. Clinical trial information: NCT06765707 .

Background: First-line therapies for chronic-phase (CP) CML include the tyrosine kinase inhibitors(TKIs) dasatinib, nilotinib, bosutinib or imatinib, while ponatinib and asciminib are indicated only in later lines. There are typically high response rates to first-line therapy in CP-CML, with responses to second- and third-line therapy lower and highly dependent on the specific TKI. Our goal in this study is to evaluate the role of ponatinib in the treatment of patients with CML using data from routine clinical practice. Study design and methods: Data will come from the H. Jean Khoury Cure CML Consortium (HJKC3) CML registry, a North American multi-site research database. Participating sites include the HJKC3 members (curecml.org). Patient inclusion criteria include a diagnosis CML in chronic phase, receiving second line therapy after initial therapy with a second generation TKI (dasatinib, nilotinib, or bosutinib) or receiving third or later line TKI therapy for CML. Participating patients provide consent to collect their data both retrospectively and prospectively for 1 year. Clinical data, including toxicities and complications of TKI therapy, are abstracted from the electronic health record. Participating patients are invited to complete a questionnaire to assess health-related quality of life. Data are managed using REDCap, a secure web application. Study Objectives: The primary objective is to compare the outcome of patients treated with ponatinib vs. other TKIs as second or later line therapy. Secondary objectives are to evaluate patient-reported outcomes (PRO) for CML treated with second or later line therapy and to determine if there are any patient or disease characteristics that can predict outcomes. Statistical plan for clinical outcomes: Descriptive statistics will be used to compare baseline demographic characteristics. Categorical variables will be compared using the Chi-square test. Continuous variables will be compared using ANOVA. Overall survival will be calculated from the time of diagnosis to death from any cause and patients will be censored if they were alive at the last follow-up. Survival probabilities will be computed using the Kaplan-Meier method and compared with the log-ranktest. Cox regression analyses will be used to determine significant factors that influence survival, and hazard ratios with 95% confidence intervals will be presented. Event free survival (EFS) and transformation free survival (TFS) will be calculated for patients. For EFS, loss of complete hematologic remission, loss of major cytogenetic response, progression to accelerated or blast phase, or death from any cause at any time will be considered an event. For TFS, transformation to accelerated or blast phase while on therapy or death on study will be considered an event. Statistical plan for PRO: Different PRO domains will be analyzed separately (for example, depression separate from fatigue, etc.). Descriptive statistics for each PRO measure will be reported and compared to previously published studies. Differences by treatment type will be evaluated.

Background and significance: There are typically high response rates to first line TKI therapies in chronic phase chronic myeloid leukemia (CP-CML). However, responses in later lines (second line and beyond) are diminished and highly dependent on the specific tyrosine kinase inhibitors (TKIs) used. Asciminib received FDA approval in October 2021 for the treatment of adult patients with Philadelphia chromosome-positive (Ph+) CML-CP who were previously treated with two or more TKIs, and in patients with Ph+ CML-CP with the T315I mutation. Our goal in this study is to evaluate the role of asciminib therapy for patients with CML beyond clinical studies, in routine clinical practice. Study Design and methods: Data for this study will be abstracted from the HJKC3 (H. Jean Khoury Cure CML Consortium) CML registry project (HJKC3-0005); the HJKC3 CML Registry is a collaborative academic multi-site registry. Patients will be consented to allow collection of both retrospective and prospective data for the HJKC3 CML Registry. The data forms and surveys will be built and managed through the Research Electronic Data Capture (REDCap), a secure web application managed by the Clinical & Translational Science Institute. Participating sites include members of the HJKC3 (curecml.org). This study will be an opportunity to evaluate asciminib usage in ‘real-world’ academic practices across the United States. This observational study will include cohorts of patients diagnosed with CP-CML previously treated with two or more tyrosine kinase inhibitors and/or receiving asciminib and/or those with a T315I mutation, not currently enrolled in a randomized controlled trial. The HJKC3 CML Registry intends to collect clinical and patient reported outcome (PRO) data. After obtaining patient consent, patients will be invited to complete PRO assessments. The study will attempt to collect PRO data regardless of disease or treatment status. PRO assessments will be primarily administered online, though study staff will offer alternatives (e.g., phone) for participants without internet access. Study subjects will be emailed a link to access a secure platform hosted by one of the study sites, Medical College of Wisconsin (MCW), using the REDCap platform. Study Objectives: The primary objective of the study is to describe characteristics of patients who were previously treated with two or more TKIs and treated with asciminib or with any other TKIs. The secondary objectives are to describe the clinical outcomes and PRO of those patients. Exploratory objectives include description of characteristics, treatment outcome and PRO for patients with T315I mutation. Statistical plan: The sample size of approximately 225 participants during the 5-year recruitment period is based on the available clinical expertise and ongoing recruitment data in the HJKC3 CML registry in lieu of statistical power analysis. We estimate that 150 patients in the HJKC3 CML registry will be treated with other TKI and 75 treated with asciminib. Among a total of 225 patients, we estimate that 75 patients with the T315I mutation will be enrolled in the registry. No formal statistical inference will be drawn to compare the outcomes between these two groups. Bayesian predictive probability (PP) will be utilized for the exploratory analysis of Major Molecular Response (MMR). Survival probabilities will be computed using the Kaplan-Meier method, and the p-values from the log-rank test will be provided. Different PRO domains of the patient's symptoms and functioning will be analyzed separately (e.g., depression separate from fatigue, separate from GI symptoms, etc.) since combining them into a summary score may dilute the effects of the individual (and not necessarily related) components and mask actual change. The main objective for the analyses of PRO data from the registry is to describe any differences by treatment type in patients treated with asciminib and other TKIs.

Abstract Background Light chain (AL) amyloidosis is a plasma cell neoplasm associated with high early mortality and severe morbidity that can cause severe disability. We explored the impact of AL amyloidosis on symptoms and well-being from the perspectives of patients and health care providers who regularly care for AL patients. We intended to develop a conceptual understanding of patient-reported outcomes in AL amyloidosis to identify the context of use and concept of interest for a clinical outcome assessments tool in this disease.Method Twenty patients and 10 professionals were interviewed. Patient interviews captured the spectrum of amyloidosis experience including time from diagnosis, type of organ involvement, and presence and type of treatment received. Interviews with professionals included physicians, advanced practice providers, registered nurse, and a patient advocate; these interviews covered similar topics. Results The impact of AL amyloidosis on patients’ life was multidimensional, with highly subjective perceptions of normality and meaning. Four major themes from patients and experts included diagnosis of AL amyloidosis, living with AL amyloidosis, symptom burden, and social roles. Barriers to patient-reported outcomes data collection in patients were additionally explored from experts. The themes provide a comprehensive understanding of the important experiences of symptom burden and its impact on daily life from AL amyloidosis patients’ and from the perspectives of professionals who care for patients with AL amyloidosis. Conclusion These findings further the conceptual understanding and identification of a preliminary model of concept of interest for development of a clinical outcome assessments tool for AL amyloidosis.

CD19-targeted chimeric antigen receptor (CAR)-T cell therapy is a novel treatment with promising results for patients with relapsed/refractory lymphoid malignancies. CAR-T cell therapy has known early toxicities of cytokine release syndrome (CRS) and neurotoxicity, but little is known about long-term neuropsychiatric adverse effects. We have utilized patient-reported outcomes (PROs), including PROMIS®measures, to assess outcomes of patients with relapse/refractory chronic lymphocytic leukemia (CLL), non-Hodgkin lymphoma (NHL), and acute lymphoblastic leukemia (ALL) who were treated with CD19-targeted CAR-T cells on a clinical trial in our institution (NCT01865617) and survived at least one year after treatment. Between October 2018 to February 2019, 52 patients (at their 1-5 year anniversary after CAR-T cell therapy) were sent a questionnaire. The questionnaire included the PROMIS Scale v1.2-Global Health and the PROMIS-29 Profile v2.1, as well as 30 additional questions, including questions pertaining to cognitive function. As of February 28, 2019, 40 questionnaires were returned (76.9% response rate) and were included in the analysis. Patients' characteristics are summarized in Table 1. Cognitive function was assessed by asking if patients had experienced difficulties with concentration, finding words, memory, or solving problems since their CAR-T cell therapy; answer "yes" to each of the questions received "1" point to determine the total cognitive difficulty score (0-4). PROMIS measures are standardized to a T-score metric, with a score of 50 representing the general US population mean. Clinically meaningful differences were defined as a 5-point difference in scores (1/2 standard deviation). The cohort's self-reported cognitive difficulties and PROMIS mean T scores are shown in Table 2. Mean T scores of PROMIS domains of Global Mental health, Global Physical Health, Social Function, anxiety, depression, fatigue, pain and sleep disturbance were not clinically meaningfully different from the mean in the general US population. However, 19 participants (47.5%) reported at least one cognitive difficulty and/or clinically meaningful depression and/or anxiety (Figure 1), and 7 participants (17.5%) scored ≤ 40 in Global Mental Health, indicating at least one standard deviation worse than the general population mean. On risk factor analysis, younger age was found to be associated with worse Global Mental Health (p=0.02), anxiety (p=0.01) and depression (p=0.01). Anxiety prior to CAR-T cell therapy was associated with increased likelihood of anxiety after CAR-T cell therapy (p=0.001). Multivariate analysis confirmed association between age and PROMIS Global Mental Health score (p=0.03). 15 participants (37.5%) reported cognitive difficulties post CAR-T cell therapy. On multivariate analysis, depression prior to CAR-T cell therapy was statistically significantly associated with higher likelihood of self-reported cognitive difficulties after CAR-T therapy (p=0.02) and there was a trend for association between acute neurotoxicity after CAR-T cell infusion and self-reported long-term cognitive difficulties (p=0.08). Having more cognitive difficulties was associated with worse Global Mental Health (p=0.0001) and worse Global Physical Health (p= 0.01). Similarly, worse scores for pain interference, sleep disturbance, fatigue, depression, anxiety, physical function, and social function were associated with more long-term self-reported cognitive difficulties (p=0.007,p=0.0003, p=0.00006, p=0.01, p=0.0007, p=0.003, p=0.0004 respectively). Our study demonstrates overall good neuropsychiatric outcomes in 40 long-term survivors after CAR-T cell therapy. However, despite good overall mean scores, nearly 50% of patients in the cohort reported at least one negative neuropsychiatric outcome (anxiety, depression or cognitive difficulty), and almost 20% scored at least one standard deviation lower than the general US population mean in Global Mental Health, indicating that there is a significant number of patients who would likely benefit from mental health services following CAR-T cell therapy. Younger age, anxiety and depression pre-CAR-T cell therapy, and acute neurotoxicity after CAR-T cell infusion may be risk factors for long-term neuropsychiatric problems in this patient population. Larger studies are needed to confirm these findings. Disclosures Shaw: Therakos: Other: Speaker Engagement. Lee:AstraZeneca: Research Funding; Incyte: Research Funding; Syndax: Research Funding; Amgen: Research Funding; Novartis: Research Funding; Takeda: Research Funding; Kadmon: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding. Turtle:T-CURX: Membership on an entity's Board of Directors or advisory committees; Kite/Gilead: Other: Ad hoc advisory board member; Caribou Biosciences: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Allogene: Other: Ad hoc advisory board member; Humanigen: Other: Ad hoc advisory board member; Juno Therapeutics: Patents & Royalties: Co-inventor with staff from Juno Therapeutics; pending, Research Funding; Nektar Therapeutics: Other: Ad hoc advisory board member, Research Funding; Precision Biosciences: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Eureka Therapeutics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Novartis: Other: Ad hoc advisory board member. Maloney:Juno Therapeutics: Honoraria, Patents & Royalties: patients pending , Research Funding; A2 Biotherapeutics: Honoraria, Other: Stock options ; Celgene,Kite Pharma: Honoraria, Research Funding; BioLine RX, Gilead,Genentech,Novartis: Honoraria.