Adherence and Oral Therapies in Lymphoma and CLL: A Lymphoma Research Foundation Workshop October 19, 2017 Welcome Meghan Gutierrez Chief Executive Officer Lymphoma Research Foundation Workshop Co-Chairs Jonathan Friedberg, MD, MMSc James P. Wilmot Cancer Institute, University of Rochester Michael Williams, MD, ScM University of Virginia Cancer Center Workshop Steering Committee Christopher Flowers, MD Winship Cancer Institute of Emory University Neil Kay, MD Mayo Clinic Rochester John P. Leonard, MD Weill Cornell Medicine and New York Presbyterian Sonali Smith, MD The University of Chicago Workshop Background • Oral Therapies in Lymphoma Workshop convened Fall 2015 in Washington, D.C. • First multi-stakeholder meeting to explore changing nature of lymphoma/CLL treatment, implications of oral therapies • Expert presentations and discussion outlined key issues, opportunities, and challenges facing the community Workshop Findings • Three core themes emerged from the 2015 workshop: • Impact of oral therapies on a heterogeneous disease like lymphoma is vast and therefore can serve as a case study for other cancers • Numerous challenges including adherence, monitoring, toxicity management, patient education, and cost • Research plays essential role in ensuring HCPs and patients have the information and treatment choices required to maximize outcomes and ensure quality of life Workshop Findings • Adherence focus areas: • Challenges related to adherence highly complex and difficult to quantify • Numerous barriers exist to accurately measure adherence • Existing methods of adherence assessment and emerging technologies could eventually play role in both measuring and supporting patient adherence • Little data exists on the clinical impact of adherence Program Goals • Review epidemiology/forms nonadherence, methods of adherence assessment, and barriers to accurately measuring adherence • Identify primary causes of nonadherence as well as related adherence interventions and tools • Discuss the design and implementation of studies focused on adherence in lymphoma/CLL Workshop Agenda 9:15 AM Patient Adherence and Oral Anticancer Treatment Joseph Greer, PhD, Massachusetts General Hospital 10:00 AM Utilization and Adherence of Oral Anticancer Agents: Perspectives and Opportunities from the National Cancer Institute (NCI) Wendy Nelson, PhD, MPH, Basic Biobehavioral and Psychological Sciences Branch, NCI 10:20 AM Adherence in the TKI Era, or How to Run the CML Marathon Michael J. Mauro, MD, Weill Cornell Medical College 10:45 AM Break 11:00 AM Oral Therapies and Adherence in Lymphoma Roundtable Moderated by Drs. Williams and Friedberg Christopher Flowers, MD, Winship Cancer Institute of Emory University John P. Leonard, MD, Weill Cornell Medical Center Sonali Smith, MD, The University of Chicago 12:15 PM Summary and Next Steps: Areas and priorities for future investigation 12:30 PM Lunch Patient Adherence & Oral Anticancer Treatment Joseph Greer, Ph.D. Program Director, Center for Psychiatric Oncology & Behavioral Sciences Associate Director, Cancer Outcomes Research Program Overview Review rates and correlates of adherence to oral chemotherapy Discuss development of a mobile app intervention to improve symptom monitoring and adherence to oral chemotherapy Describe results of an randomized controlled trial of the mobile app intervention Background The increased use of oral chemotherapy has revolutionized cancer care through improved: • Disease outcomes and patient survival • Convenience of treatment administration • Quality of life by avoiding problems with IV infusion However, patients generally receive less supervision and support for adherence and monitoring of side effects as opposed to directly- observed infusion chemotherapy. Background • Documentation of oral versus IV chemotherapy plans in 175 patients with metastatic NSCLC • ASCO Quality Oncology Practice Initiative Greer et al. J Oncol Pract, 2014 Background Rates of adherence to oral cancer therapies range from 16% to 100% A variety of patient, clinician, treatment, and system factors are associated with non-adherence Ruddy et al. CA: A Cancer Journal for Clinicians, 2009 Greer et al. The Oncologist, 2016 Background 51 studies on rates and/or correlates of adherence (ranging from 46% to 100%) • Methods of adherence assessment included: -plasma level (n=1) -medical chart review (n=3) -electronic monitoring (n=7) -pill count (n=5) -pharmacy/insurance records (n=32) -self report by patient (n=25), physician (n=7), family (n=3) Greer et al. The Oncologist, 2016 Background Pilot study of 90 patients Percentage of Patients with Greater than with CML, metastatic 90% Adherent to Oral Chemotherapy NSCLC, RCC, BC 90 80 • Adherence per MEMS 70 – Mean = 89.3% 60 50 – Less than 90% = 25.6% 40 30 • Predictors of better 20 adherence: 10 – Improved symptom distress, 0 mood, QOL, satisfaction with CML NSCLC RCC BC providers and treatment, and perceived burden to others Jacobs et al. J Oncol Pract, 2017 Specific Aims To develop a patient-centered, smartphone mobile app for individuals with cancer prescribed oral chemotherapy To test the effect of the mobile app on the following: • Adherence to oral chemotherapy • Symptoms and treatment side effects • Quality of life • Satisfaction with cancer care Research Design & Methods Two phase study: • Mobile app development (year 1) • Randomized controlled trial (years 2 and 3) Multidisciplinary team of medical oncologists, psychologists, psychiatrist, and health technology eXperts Stakeholder engagement throughout the study Stakeholder Engagement: FOCUS GROUPS BIANNUAL UPDATESBIANNUAL GROUPS FOCUS Cancer Oncology Practice Clinicians Settings Health System, Community, Patients/ and Society Family Mobile App Development Trial and Data Collection Preliminary Analyses FOCUS GROUPS FOCUS Patients/ Health System, Family Oncology Cancer Community, Clinicians Practice and Society Settings Complete Analyses Prepare Dissemination Research Design & Methods Patient Eligibility Criteria: • Adult (age 18 or older) • Diagnosis of cancer with current prescription for oral chemotherapy • Receiving cancer care at MGH or community affiliate • Possess mobile smartphone (iOS or Android) Research Design & Methods Study Outcomes • Medication adherence (Self-Report & MEMS) • Symptoms and treatment side effects (MDASI) • Quality of Life (FACT-G) • Satisfaction with cancer care (FACIT-TS) Phase 1: Mobile App Development Multistep Process • Initial interviews with patients and clinicians Theory • Software development Design & • User-testing Development • Roll-out User Testing/ • Ongoing upgrades Quality Assurance Deployment/ Maintenance Phase 1: Mobile App Development Group Feedback Implementation Patients and Families “Connect patients with the Feature: Education Library Module - Resources and Social same disease type for social Networking support.” App includes a list of reputable, disease-specific resources for patients looking to connect with others. Healthcare “Provide patients with Feature: Symptom Reporting Module Representatives anchors and definitions of When a patient reports a symptom, app asks several questions symptoms so they can appropriately determine the about the frequency and duration before providing tailored feedback. severity and urgency of their symptoms.” Oncology Clinicians “The weekly symptom Feature: Symptom Reporting Trends Module reports that are sent to Weekly Symptom Reports provide a list of symptoms reported clinicians should be concise and easy to understand.” by the patient, as well as a color and numeric value (1-10) denoting severity. Practice Administrators “Provide resources and Feature: Symptom Reporting Module –“Touch to call clinical contact information for team” feature patients to use when they miss a dose of their Patients are provided with the study team contact information at baseline. Embedded in the symptom reporting feature is a medication.” “touch to call” button for their specific clinic. Phase 1: Mobile App Development App Components: • Chemo treatment plan • Weekly symptom and adherence reporting • Education library • Results feedback to oncology clinicians • Energy Tracking • Healthy Recipes • Social Networking Sites Phase 1: Mobile App Development Phase 2: RCT Study Design Baseline Data Collection R A Smartphone Mobile Post assessment 181 adult N App Intervention at approximately patients D (n=91) 12 weeks prescribed O oral M chemotherapy I Post assessment with access to Z Usual Care Control at approximately a Smartphone E Group (n=90) 12 weeks D Phase 2: RCT Results Approached (n=500) No Smartphone (n=178) Declined (n=110) Enrolled (n=212) Dropped out (n=28) Lost to follow-up (n=3) Baseline Assessment (n=181) Mobile App (n=91) Usual Care (n=90) Post Assessment (n=80) Post Assessment (n=89) • Withdrew (n=7) •Deceased (n=1) • Deceased (n=3) • Lost to follow-up (n=1) MEMS Cap Collected (n=85) •Did not return (n=4) MEMS Cap Collected (n=84) •Data lost (n=1) • Did not return (n=6) • Lost in mail (n=1) Phase 2: RCT Results Sample Demographics Mean (SD) or From 2/13/15 - 12/31/16, N (%) Age Mean (SD) 53.5 (12.9) we enrolled and Female 94 (53.6) randomized 181 patients Race in a trial comparing oral Caucasian 159 (87.8) chemotherapy mobile Asian 10 (5.5) African American 5 (2.8) app to usual care. Hispanic/Latino/a 4 (2.2) Multiracial 2 (1.1) • At baseline, 22% of Other 1 (0.6) patients reported either Ethnicity forgetting or having Hispanic 4 (2.2) problems remembering Cancer Type Hematologic 60 (33.1) to take oral Lung 33 (18.2)