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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 UPDATES

Cancer Oncology Practice Clinicians Settings Health System, Community, Patients/ and Society Family

Mobile App Development

Trial and Data Collection

Preliminary Analyses FOCUS GROUPS

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) chemotherapy Brain 26 (14.4) Breast 26 (14.4) medication in past week. Other 36 (19.9) Phase 2: Baseline Symptoms

Symptom %

Fatigue 88.7 Symptoms reported on Drowsy 76.8 baseline MD Anderson Disturbed Sleep 68.8 Symptom Inventory Memory Problems 63.4 (MDASI) Distressed/Upset 61.7 Dry Mouth 51.1 Feeling Sad 48.6 Numbness/Tingling 47.9 Pain 44.6 Appetite Problems 43.0 Shortness of Breath 38.7 Nausea 37.6 Vomiting 13.4 Phase 2: RCT Results

Outcomes by Study Group in Overall Sample Outcome Measure Usual Care Mobile App P- % or M (SE) % or M (SE) value Self-Report Adherence (MMAS) 76.7% 86.2% .19

Pill Bottle/Cap Adherence (MEMS) 79.2% 81.5% .57

Change in Symptom Severity (MDASI) 0.08 (0.15) -0.30 (0.15) .60

Change in Quality of Life (FACT-G) -1.93 (1.13) 0.49 (1.19) .14 Physical Wellbeing 0.11 (0.23) 0.81 (0.48) .29 Social Wellbeing -2.22 (0.50) -0.55 (0.53) .03 Emotional Wellbeing 0.53 (0.40) 0.04 (0.41) .39 Functional Wellbeing -0.40 (0.41) 0.35 (0.43) .22 Change in Satisfaction with Care (FACIT-TS) Explanations -0.34 (0.19) 0.04 (0.20) .17 Interpersonal -0.29 (0.13) 0.07 (0.13) .06 Comprehensiveness -0.89 (0.49) 0.08 (0.52) .18 Trust -0.24 (0.12) -0.24 (0.13) .97 Phase 2: RCT Results

MEMS Adherence Moderated by Baseline Self- Reported Adherence Phase 2: RCT Results

Outcomes by Study Group in Patients with Poor Self- Reported Adherence at Baseline (N=35)

Outcome Measure Usual Care Mobile App P- % or M (SE) N (%) or M (SE) value Pill Bottle/Cap Adherence (MEMS) 63.9% 86.2% .03

Change in Symptom Severity (MDASI) 0.05 (0.29) -0.04 (0.34) .84

Change in Quality of Life (FACT-G) -2.70 (2.48) 1.36 (3.04) .31 Physical Wellbeing -0.85 (0.97) 1.46 (1.18) .14 Social Wellbeing -1.69 (0.90) -0.53 (1.11) .42 Emotional Wellbeing 0.14 (0.74) -0.001 (0.90) .90 Functional Wellbeing -0.30 (0.81) 0.43 (0.99) .57 Change in Satisfaction with Care (FACIT-TS) Explanations -0.76 (0.45) 0.93 (0.56) .03 Interpersonal -0.29 (0.14) -0.001 (0.18) .22 Comprehensiveness -1.46 (1.01) 1.15 (1.24) .11 Trust -0.43 (0.25) -0.14 (0.31) .48 Phase 2: RCT Results

MEMS Adherence Moderated by Baseline Self- Reported Anxiety Symptoms (HADS-Anxiety>7) Phase 2: RCT Results

Outcomes by Group in Patients with Anxiety (N=46) Outcome Measure Usual Care Mobile App P- % or M (SE) % or M (SR) value Self-Report Adherence (MMAS) 68.0% 95.7% .047

Pill Bottle/Cap Adherence (MEMS) 69.4% 85.5% .044

Change in Symptom Severity (MDASI) 0.02 (0.33) -0.30 (0.36) .52

Change in Quality of Life (FACT-G) -4.56 (2.37) 2.28 (2.60) .06 Physical Wellbeing -0.27 (0.82) 1.92 (0.90) .09 Social Wellbeing -4.07 (1.07) -1.36 (1.18) .10 Emotional Wellbeing 0.63 (0.81) 0.62 (0.89) .99 Functional Wellbeing -0.85 (0.84) 1.10 (0.92) .13 Change in Satisfaction with Care (FACIT-TS) Explanations -0.35 (0.34) 0.20 (0.37) .29 Interpersonal -0.52 (0.23) 0.24 (0.24) .028 Comprehensiveness -1.53 (0.85) 1.10 (0.93) .047 Trust -0.32 (0.28) -0.39 (0.30) .89 Conclusions

• Patients prescribed oral chemotherapy experience concerning problems with adherence.

• A variety of psychosocial and treatment factors are associated with adherence.

• Despite the advantages of oral chemotherapy, symptoms and side effects occur at high rates, especially fatigue, drowsiness and sleep disturbance. Conclusions

• Through a multi-step process involving numerous stakeholders, we successfully developed a smartphone mobile app to support patients prescribed oral chemotherapy.

• In the overall sample, the mobile app was generally not associated with outcomes but lead to improvements in self- reported social wellbeing compared to usual care and marginally significant improvement in satisfaction with interpersonal treatment with clinicians.

• Intervention effects on outcomes were stronger in patients who reported poor adherence and high anxiety at baseline. Acknowledgments

Stakeholder Partners Funding Source: Co-Investigators: PCORI (IHS-1306-03616), PI: Greer • Steven Safren, Ph.D. • William Pirl, M.D. • Jennifer Temel, M.D. • Inga Lennes, M.D. • Joanne Buzaglo, Ph.D. • Kamal Jethwani, M.D. Research Coordinators: • Jamie Jacobs, Ph.D. • Nicole Amoyal, Ph.D. • Lauren Nisotel, B.S. • Joel Fishbein, B.A. • James MacDonald, B.A. • Charn Xin C. Fuh, B.S. • Molly Ream, B.A. Disclaimer

Funding Source: PCORI (IHS-1306-03616) The data and statements reported in this presentation are solely the responsibility of the author(s) and do not necessarily represent the views of the Patient- Centered Outcomes Research Institute (PCORI), its Board of Governors or Methodology Committee. Oral Anticancer Agents: Utilization, Adherence, and Health Care Delivery

Wendy Nelson, PhD Behavioral Research Program Division of Cancer Control and Population Sciences

LRF October 19, 2017 The views expressed here are those of the presenter and do not represent any official position of the National Cancer Institute or National Institutes of Health.

LRF October 19, 2017 Motivation

§ Targeted oral anticancer (OAC) medications have transformed cancer care

§ OAC medications offer many potential advantages over traditional IV chemotherapy − Superior effectiveness − Convenient home-based treatment − A sense of control over treatment − Avoid IV infusions, trips to hospital

§ Potential downsides of OAC medications − Complex treatment regimens, often in addition to other medication regimens − OAC medications require strict adherence to be effective − Patients/caregivers are responsible for symptom management − Financial burden − Difficulties acquiring OAC medication

42 Adherence to OAC Medication is Critical for Achieving a Therapeutic Response

§ Many oral agents are cytostatic § Optimal adherence: correct drug, correct dose, correct time, correct conditions § Imatinib adherence in CML <80% → no molecular response § Imatinib adherence in GIST → 2-year progression free survival 80% in continuous group vs. 16% in interrupted group § Full dose ibrutinib adherence in CLL → improved PFS in patients missing < 8 days of treatment compared to patients missing > 8 consecutive days of treatment § Suboptimal adherence → toxicity, more physician visits, higher hospitalization rates, unnecessary treatment changes, breakdown in the patient-provider relationship, increased health care expenditures, biased response rates in clinical trials § OAC medication adherence estimates vary widely: 20% - 100%

43 Treatment Schedules Are Complex

Sun Mon Tues Wed Thurs Fri Sat

Lenolidomide Lenolidomide Ixazomib Lenolidomide Lenolidomide Lenolidomide Lenolidomide Week 1 Lenolidomide Dexamethasone Week 2 Lenolidomide Lenolidomide Dexamethasone Rest Rest Rest Rest

Rest Rest Ixazomib Lenolidomide Lenolidomide Lenolidomide Lenolidomide Week 3 Lenolidomide Dexamethasone

• Regimens are complex and often in addition to other medications • Adherence is inversely related to dosing complexity • “…clinicians must realize that lack of adherence typically reflects the complexity of the regimen rather than willful or manipulative behavior from the patient.” (2008 National Comprehensive Cancer Network Task Force Report on Oral Chemotherapy)

44 Polypharmacy

Characteristics of Medicare Part D Beneficiaries by Type of Oral Cancer Medication Used

Characteristics Imatinib Erlotinib Anastrozole Letrozole (N=123) (N=96) (N=2,397) (N=1,078) Mean [SD] Mean [SD] Mean [SD] Mean [SD]

Age 75.3 [6.39] 76.61 [6.55] 75.33 [7.08] 74.76 [7.07]

Number of 1.93 [1.93] 3.13 [2.53] 2.04 [1.93] 1.99 [1.97] comorbidities Number of 9.75 [6.63] 13.24 [6.00] 7.71 [4.87] 8.03 [4.99] noncancer drugs

Kaisaeng et al. Journal of Managed Care & Specialty Pharmacy 2014; 20:669-675. 45 Polypharmacy

§ Underappreciated barrier to OAC medication adherence

§ Potential risks of polypharmacy

− Drug-drug interactions (e.g., gefitinib/anticoagulants; imatinib/rifampin; lapatinib/fentanyl)

− Drug-food interactions (e.g., ibrutinib/grapefruit, Seville oranges; lapatinib/grapefruit)

− Prescribing cascade

− Unnecessary treatment change

− Increased health care costs (physician visits; hospitalizations)

§ Why do interventions to improve adherence to OAC medication focus only on the OAC medication?

46 Pharmacists

Pharmacists are uniquely positioned to:

§ Evaluate a patient’s medications for potential drug-drug and drug-food interactions

§ Provide medication counseling and information about safe handling of medication

§ Provide medication reconciliation

§ Contact the prescribing physician

§ Assist in procuring the OAC medication in a timely fashion

§ Help patients obtain financial assistance so they can afford their medication

47 Why do we need this funding opportunity announcement?

§ Utilization − Little information is available on the adoption of newly approved targeted oral agents − Little information is available on off-label use of oral agents − Are targeted oral agents being prescribed appropriately?

§ Adherence − Strict adherence is critical to achieving an optimal clinical outcome − Suboptimal adherence may lead to relapse, side-effects, unnecessary treatment changes, increased use of health care resources

§ Health Care Delivery − Health care systems need to establish new roles, responsibilities, safety standards, patient education strategies for targeted oral therapies − Home-based treatment with targeted oral therapy requires new models of care coordination

48 Purpose

§ Assess and describe the current state of oral anticancer medication utilization, adherence, and delivery

§ Identify the structural, systemic, and psychosocial barriers to adherence

§ Develop models and strategies to improve safe and effective delivery of oral anticancer agents so that clinical outcomes are optimized

49 Utilization Challenges

§ Understand how OAC medications are being prescribed, used, and monitored

− Disparities in access (e.g., rural and underserved populations, insurance)

− Off-label use

§ Potential research questions:

− What are the patient and provider characteristics associated with prescribing and use of OAC agents?

− Do genetic testing requirements and health insurance coverage affect the utilization of OAC agents?

− What are current trends in utilization of newly approved OAC therapies?

− What are the patterns of off-label use of OAC medications?

50 Adherence Challenges

§ Understand how cognitive, affective, and motivational processes influence adherence behavior − Beliefs about the safety and effectiveness of a “pill” − Expectations about side effects, treatment outcome − Depression, anxiety

§ Understand the adherence needs of patients with cognitive, visual, physical, or health literacy limitations

§ Potential research questions:

− How do patients perceive the risks associated with oral therapy, and how do these risk perceptions influence adherence?

− Are there major differences in patterns of adherence depending on the duration or complexity of the treatment regimen?

− How do financial considerations (e.g., out-of-pocket costs) influence adherence?

51 Health Care Delivery Challenges

§ Understand how health care delivery systems are adapting to meet safety standards and the educational needs of patients and caregivers − Symptom management − Coordination of care

§ Potential research questions:

− What system, health care team, provider, and patient-level factors are associated with the safe administration of oral agents?

− How can pharmacy care models facilitate coordination of care for patients and health care teams?

− What features of health care delivery systems lead to improved safety and adherence?

− What models of care help to enhance symptom self-management?

52 Considerations

§ Studies may be observational/descriptive or include interventions; observational studies should emphasize modifiable factors for future interventions

§ Studies may focus on utilization, adherence, or health care delivery issues related to oral anticancer agents (no need to study everything)

§ Consult your Program Director if you have questions

53 Research Priorities

§ Cross-disciplinary collaborations (e.g., clinical pharmacists, research nurses, social workers, financial navigators)

§ Studies focused on newer targeted OAC agents

§ Primary data collection is encouraged

54 Grant Mechanisms – R01 and R21

NIH Research Project Grant NIH Exploratory/Developmental Grant (R01) (R21) PA-17-060 PA-17-061

§ Supports discrete, specified, circumscribed § Supports exploratory/developmental research research projects projects § Most commonly used grant mechanism § May be used for pilot or feasibility studies § No specific dollar limit § Preliminary data not required − Advance permission required for >$500K § Direct costs for the two-year project period direct costs in any year may not exceed $275K § 3-5 years of funding § 2 years of funding § Standard receipt dates § Standard receipt dates

For more information: grants.nih.gov/grants/funding/funding_program.htm#RSeries 55 Read the funding opportunity announcements carefully

§PA-17-060 (R01) https://grants.nih.gov/grants/guide/pa-files/PA-17-060.html

§PA-17-061 (R21) https://grants.nih.gov/grants/guide/pa-files/PA-17-061.html

§ Upcoming R01 application due dates: February 5, 2018; June 5, 2018

§ Upcoming R21 application due dates: February 16, 2018; June 16, 2018

§ Start the process early! Allow time for registration in Grants.gov and NIH eRA Commons

§ Verify successful submission by checking the eRA Commons

56 Program Contacts Wendy Nelson, PhD [email protected] 240-276-6971 Adherence

Kate Castro, RN, MS, AOCN [email protected] 240-276-6834 Health Care Delivery

Kelly Filipski, PhD [email protected] 240-276-6841 Utilization

57 U.S. Department of Health & Human Services National Institutes of Health / National Cancer Institute

cancercontrol.cancer.gov

1-800-4-CANCER

58 Adherence in the Tyrosine Kinase Inhibitor Era, or How to Run the CML Marathon

Michael J. Mauro, MD Leader, Myeloproliferative Neoplasms Program Memorial Sloan Kettering Cancer Center, New York, NY Background the success story of ABL kinase inhibitors in CML The history of CML is long, the kinase inhibitor era short

1845 1865 1879 1903 1953 1965 1968 1983 2001 2006 2012 2016

First description of CML Fowlers’s solution -1% arsenic trioxide Staining methods for blood Radiotherapy

Busulfan 1998: After seminal preclinical work first Hydroxyurea clinical trials commence with STI571 (imatinib); 1999, target inhibition BMT validated, resistance identified (T315I) Interferon 1845: John Hughes Bennett reported a Imatinib “Case of Hypertrophy of the Dasatinib Spleen and Liver in 1960: 1973: which Death Took Nowell & Hungerford Nilotinib Janet Rowley Place from describe the Suppuration of the describes the Philadelphia Bosutinib Blood” in the 9:22 translocation Edinburgh Medical Chromosome 1983: Nora Heisterkamp Ponatinib Journal; Virchow in and John Groffen, with Germany wrote up a others, describe the BCR- Generic Imatinib similar observation ABL fusion gene product CML is an increasingly prevalent and survivable cancer

lifespan

prevalence

200000

180000

160000

140000 10x greater steady state number 120000 of CML patients in US by 2050 100000 • Incidence 4700 per year

Number of Cases of Number 80000 • Age-matched mortality ratio vs normal population = 1.50 60000 • Accounts for increased US 40000

20000 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Huang et al, Cancer 118:3123-3127, 2012. Year Bower H et al, J Clin Oncol 34:2851-57, 2016. CML IV Study: Comorbidity effect on CML TKI response, transformation

As measured by the Charleson Comorbidity Index (CCI)

Saußele S et al. Blood 2015;126:42-49 CML IV Study: Comorbidity effect on survival, irrespective of age

Charlson Comorbidity Index (CCI) calculated including age Comorbidites trump CML response!

Charlson Comorbidity Index (CCI) calculated without age

Saußele S et al. Blood 2015;126:42-49 At present, five oral, small molecular kinase inhibitors approved in the US for Ph+ Leukemia: a ‘spoil of riches’; more on the way?

2001 1st Gen. TKI Novartis (1st line) Imatinib (STI571)

2007/2010 2007/2010 nd BMS Novartis 2 Gen. TKIs st nd (1st, 2nd line) (1 , 2 line) Dasatinib (BMS354825) Nilotinib (AMN107)

2012/2015 2012 South Korea IL-YANG: Pfizer only (1st, 2nd line) (2nd/3rd line) Radotinib (IY5511) Bosutinib (SKI606) (1st/2nd/3rd line 2018?)

rd 3 Gen. TKI 2012 4th Gen. TKI (allosteric): Ariad (2nd?/3rd line) ABL001 Ponatinib (AP24534) Know Your Tools: Comparing TKI Toxicity in CML

Issue Imatinib Nilotinib Dasatinib Bosutinib Ponatinib Dosing QD/BID, with BID, without QD, w/ or QD, with QD, w/ or food food (2h) w/o food food w/o food Long term Most Extensive; Extensive; Extensive, More limited but safety extensive Emerging Emerging No emerging increasing; toxicity toxicity toxicity Emerging toxicity Heme intermediate least Most severe; ~dasatinb in éthrombocytopenia toxicity ASA-like 2nd, 3rd line; ASA-like effect effect; ~nilotinib in lymphocytosis 1st line Non- Edema, GI élipase, ébili, Pleural / Diarrhea; élipase, pancreatitis; Heme effects, échol, églu pericardial transaminitis rash; hypertension; toxicity êPhos Black box: QT effusions Black box: vascular prolongation; occlusion, heart failure, screening req’d and hepatotoxicity Emerging early Vascular PAH ? Mild renal Vascular toxicities question re: events (pulmonary effects events (ICVE, IHD, CHF; ?late (ICVE, IHD, arterial PAD, VTE) renal effects PAD) hypertension) Printed by Jerald Radich on 8/21/2017 10:48:02 AM. For personal use only. Not approved for distribution. Copyright © 2017 National Comprehensive Cancer Network, Inc., All Rights Reserved.

NCCN Guidelines Version 1.2018 NCCN Guidelines Index Table of Contents Chronic Myeloid Leukemia Green/Yellow/Red LightsDiscussion

RESPONSE MILESTONESc,e

BCR-ABL1 (IS) 3 months 6 months 12 months >12 months

>10%f YELLOW RED

>1%–10% GREEN YELLOW RED

0.1%–1% GREEN YELLOW

<0.1% GREEN

CLINICAL CONSIDERATIONS SECOND-LINE AND SUBSEQUENT TREATMENT OPTIONS RED • Evaluate patient compliance and drug interactions Switch to alternate TKI (CML-5) • Mutational analysis and Evaluate for HCT (CML-6) YELLOW • Evaluate patient compliance and drug interactions Switch to alternate TKI (CML-5) • Mutational analysis or Continue same TKI (CML-F)g or Dose escalation of imatinib (to a max of 800 mg) and Evaluate for HCT (CML-6)

GREEN • Monitor response (CML-F) and side efects Continue same TKI (CML-F)h

cSee Monitoring Response to TKI Therapy and Mutational Analysis (CML-C). eSee Criteria for Hematologic, Cytogenetic, and Molecular Response and Relapse (CML-D). fPatients with BCR-ABL1 only slightly >10% at 3 months and/or with a steep decline from baseline, may achieve <10% at 6 months and have generally favorable outcomes. Therefore, it is important to interpret the value at 3 months in this context, before making drastic changes to the treatment strategy. gAchievement of response milestones must be interpreted within the clinical context. Patients with more than 50% reduction compared to baseline or minimally above the 10% cutof can continue the same dose of dasatinib or nilotinib for another 3 months. hDiscontinuation of TKI with careful monitoring is feasible in selected patients. See Discontinuation of TKI Therapy (CML-E).

Note: All recommendations are category 2A unless otherwise indicated. Clinical Trials: NCCN believes that the best management of any patient with cancer is in a clinical trial. Participation in clinical trials is especially encouraged. CML-3 Version 1.2018, 07/26/17 © National Comprehensive Cancer Network, Inc. 2017, All rights reserved. The NCCN Guidelines® and this illustration may not be reproduced in any form without the express written permission of NCCN®. Shrinking International Standard the iceberg: (IS) qPCR Early Molecular Response: <10% or 1-log (10x) drop from 10% starting level Early Molecular Response Early Molecular Response Complete Cytogenetic Response: 1% <1% or 2-log (100x) drop Complete Cytogenetic Response Complete Cytogenetic Response Major Molecular Response: 0.1% <0.1% or 3-log (1000x) drop Major Molecular Response Major Molecular Response 4-log drop (<0.01%) 0.01% MR4 MR4 4.5 log drop, ‘MR4.5’, 0.0032% MR4.5 MR4.5 Complete Molecular Remission: ‘CMR’ ‘CMR’ <0.0032%; below the level of eligible for detection for standard labs Response MR5-6? ‘treatment free remission’ trials Expectations

1Inferred from MR2.0; IRIS IM400 TIDEL I TIDEL II SPIRIT ENESTnd DASISION 2 MR4.0 rather than MR4.5 (IM400) ENEST/DA (IM600) (IM600) FRANCE (NIL) (DAS) SISION (IM600) >10%@3mo --- 33%/36% 24% 12% --- 9% 16% CCyR @12mo 69% 65%/73% 88% 87%1 65% 80% 85% MMR@12mo 40% 27%/28% 47% 64% 49% 55% 46% MMR@24mo 55% 44%/46% 73% 73% 53% 71% 64% MR4.5@12mo --- 4%/--- 18%2 19% 22%2 11% 5% MR4.5@24mo --- 9%/8% --- 34% 26%2 25% 17% OS@3y 92% 94%/93% --- 96% --- 95% 94% Criteria for consideration of treatment free remission (TKI cessation): the rules as noted by the NCCN Age ≥18 years. Chronic phase CML. No prior history of accelerated or blast phase CML. On approved TKI therapy (imatinib, dasatinib, nilotinib, bosutinib, or ponatinib) for at least three years. Prior evidence of quantifiable BCR-ABL1 transcript. Stable molecular response (MR4; ≤0.01% IS) for ≥2 years, as documented on at least four tests, performed at least three months apart. No history of resistance to any TKI. Access to a reliable QPCR test with a sensitivity of detection of ≥4.5 logs that reports results on the IS and provides results within 2 weeks. Monthly molecular monitoring for the first six months following discontinuation, bimonthly during months 7–24, and quarterly thereafter (indefinitely) for patients who remain in MMR (MR3; ≤0.1% IS). Consultation with a CML Specialty Center to review the appropriateness for TKI discontinuation and potential risks and benefits of treatment discontinuation, including TKI withdrawal syndrome. Prompt resumption of TKI, with a monthly molecular monitoring for the first six months following resumption of TKI and every 3 months thereafter is recommended indefinitely for patients with a loss of MMR. For those who fail to achieve MMR after six months of TKI resumption, BCR-ABL1 kinase domain mutation testing should be performed, and monthly molecular monitoring should be continued for another six months. Reporting of the following to a member of the NCCN CML panel is strongly encouraged: -Any significant adverse event believed to be related to treatment discontinuation. -Progression to accelerated or blast phase CML at any time. 100 EURO-SKI: Survival without loss of MMR fantastic therapy + n=200; MR4 or greater, >2y (inclusion) 80 Relapses, n=86 good monitoring= Relapses within 6 months , n=77 fantastic outcomes… 60 40 Relapsemol-free survival at 6 months : 61% (54-68)

‘treatment free remission’ Relapse free survival 20

Saussele S, et al. EHA. 2014: [abstract LB-6214] 0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Months from discontinuation of TKI Do Adverse Events Occur With TKI Withdrawal? N=200; 222 AEs in 98 patients were reported 57 AEs in 31 patients were related to treatment stop, no grade 4

Patients Patients AEs AEs All Grade Grade 3 All Grade Grade 3 (n) (n) (n) (n) Musculoskeletal pain, joint pain, 23 3 39 6 arthralgia Other (sweating, skin disorders, folliculitis, 8 0 18 3 depressive episodes, fatigue, urticaria, weight loss)

Musculoskeletal pain in CML patients after discontinuation of imatinib: a tyrosine kinase inhibitor withdrawal syndrome? J. Richter et al. J Clin Oncol. 2014 Sep 1;32(25):2821-3.

Tyrosine kinase inhibitor withdrawal syndrome: a matter of c-kit ? Response to Richter et al. Ph. Rousselot et al.

Mahon FX et al, Blood 2014 124:151 Summary I

• Highly treatable, functionally curable disease • New paradigm of chronic therapy x years or indefinitely; normal life span expected • Multiple choices of oral agents: • Overlapping and unique side effects • ‘dealer’s choice’ algorithm; careful monitoring, toxicity management, etc. navigation required • Momentum towards ‘treatment free remission’; realistic expectation for smaller minority @ present Adherence in CML What do we know Adherence to therapy is a critical factor for achieving deep molecular response linked to treatment free remission • MMR • adherence to imatinib therapy, RR=11.17 (p=0.001) • CMR • adherence to imatinib therapy, RR=19.35 (p=0.004)

Marin D, et al. J Clin Oncol 2010; 28(14): 2381–2388. “Drugs don’t work in patients who don’t take them” C Everett Koop, M.D. former U.S. Surgeon General

“The most likely cause of sudden molecular relapse is that the patient stopped therapy”

T Hughes, Adelade AUS Cartoon drawn by CML patient (OHSU, Portland, OR) Pharmacy Record Analysis of 4043 Patients Prescribed Imatinib • Patient adherence with imatinib therapy estimated at 75%. – Only 41% of patients were more than 90% adherent.

3,500 2,921 2,913 2,908 2,883 2,742 3,000 2,617 2,448 2,269 2,500 2,126 1,997 1,866 2,000 Dramatic decline in persistency 1,671 1,368 1,500 –

Patients Month 4: near 100% – Month 5: 94% 1,000 685 – Month 14: 23% 500

0 0-1 1-2 2-3 3-4 4-5 5-6 6-7 7-8 8-9 9-10 10-11 11-12 12-13 13+ Months

Tsang, J-P, Rudychev I, Pescatore SL. J Clin Onc. 2006; 24:330s. Abs 6119. Long term adherence to imatinib

50 40.2% 40

30 25.3% Proportion of patients (%) 20 13.8% 12.6% 10 8% 0 <80% 80–90% 90–95% 95–99% ≥100% Percentage of intended dose Marin D, et al. J Clin Oncol 2010; 28(14): 2381–2388. We’ve got issues: Doctor and Patient

• Challenging for busy oncologists to • Increasing attention needed to be up to date on fine points of optimize early tolerability and managing a relatively rare cancer monitor late effects for ‘endurance’ such as CML (very diffuse CML care during chronic therapy in US) • Ongoing side effects may tempt • TKI side effects not as dramatic as patients to secretly quit meds; not those form traditional chemo and being taken seriously re: side effects thus may be discounted may frustrate patients • Appointment/MD time short; • Financial burden, inadequate extenders (PAs, etc.) involved and insurance coverage, government nursing time limited/absent to costs, generics versus copies, etc. counsel patients re: oral meds • Medical system and society more • “Of course they are taking their oriented to time-limited treatment, meds, it is cancer…” not living life fully with cancer as a chronic disease: paradox of having • New paradigm in CML: chronic cancer and still on treatment with maintenance therapy, ?indefinitely no outward change in appearance or at least x several years, unique Why is toxicity management so important?

Adherence to therapy Adherence to therapy, very likely to suffer in given the chronicity of the case of poorly therapy still necessary managed or under- for patients with CML managed side effects: (advice ranges from 3+, ‘self-management’… 5+ to 8-10 yrs+) is one of the strongest predictors of outcome… 6-year probability of MMR according to the measured adherence rate

p<0.001

Marin D, et al. J Clin Oncol 2010; 28(14): 2381–2388. 6-year probability of CMR according to the measured adherence rate

p=0.002

Marin D, et al. J Clin Oncol 2010; 28(14): 2381–2388. Imatinib plasma levels, viewed in the setting of an adherence study, were not an independent predictor of molecular response

Total population Adherent patients

Marin D, et al. J Clin Oncol 2010; 28(14): 2381–2388. Adherence is critical after dose escalation

• In 32 patients who failed to achieve MMR at 18 months the dose of imatinib was increased to 600 mg od

• The adherence rate in these 32 patients was 86%, which is significantly lower that that observed in the 55 subjects who remained on 400 mg (98.8%, p=0.02)

1.0 1.0 Adherence >90%, n= 18 0.9 p =0.0002 0.9 p =0.01

0.8 0.8

0.7 0.7

0.6 0.6

0.5 0.5 Adherence >90%, n= 18 0.4 0.4

Probability of MMR Probability 0.3 0.3

0.2 Adherence ≤90%, n= 14 log reduction of 4 Probability 0.2

0.1 0.1 Adherence ≤90%, n= 14 0.0 0.0 0 6 12 18 24 30 36 42 48 54 60 66 72 0 6 12 18 24 30 36 42 48 54 60 66 72

Months from start of imatinib therapy Months from start of imatinib therapy Marin D, et al. J Clin Oncol 2010; 28(14): 2381–2388. Marin D,Marin et al. J Cumulate incidence of loss of CCyR 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Poor adherent patients have a higher of probability 0 Clin Adherencerate Adherencerate >85%, n=69 Oncol 6 Monthsfrom enrolment 2010; 28(14): 2381 28(14): 2010; losing the ≤ 85%, n=1885%, 12 – 2388. 18 CCyR p<0.0001 24

Probability of imatinib failure and a EFS lower 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0 p<0.0001 Adherencerate >85%, n=69 Adherencerate 6 Monthsfrom enrolment ≤ 85%, n=18 85%, 12 18 24 ADAGIO: About One Third of CML Patients Report Poor Adherence to Imatinib

• 169 CML patients treated with imatinib prospectively followed for 90 days 100 Baseline Follow-up 80 67% 64%

(%) 60 Wks 40

Past 4 22% 25% 20 16% 13% Patients Who Reported Whoin Reported Patients 3% 2% 1% 2% 0 Adherent Dose Not Consecutive Dose Dose Taken Doses Not Taken Reduced Taken > 2-Hr Delay Overall adherence and nonadherence by behavior, self-reported Noens L, et al. Blood. 2009;13:5401-5411. Microelectronic Monitoring System (MEMS 6 Trackcap) CML Study

• Records the time of opening the container

• Most reliable method of measuring adherence

• Marin study: patients told that adherence was measured by pill counts, not told about bottle cap electronic chip

Marin D, et al. J Clin Oncol 2010; 28(14): 2381–2388. The Ideal: 100% adherence as recorded by MEMS

Marin D, et al. J Clin Oncol 2010; 28(14): 2381–2388. The Reality: ‘Catching up’ to empty the bottle, as recorded by MEMS

Marin D, et al. J Clin Oncol 2010; 28(14): 2381–2388. The Reality: Poor adherence due to drug holiday, as recorded by MEMS

Marin D, et al. J Clin Oncol 2010; 28(14): 2381–2388. The Reality: Poor adherence and Human Nature, as recorded by MEMS

Marin D, et al. J Clin Oncol 2010; 28(14): 2381–2388. The dosing of medication may be very erratic as well

Marin D, et al. J Clin Oncol 2010; 28(14): 2381–2388. Achievement of a molecular response is related to the adherence to imatinib therapy

6-year probability of response Adherence rate n MMR (%) 4-log (%) CMR (%) p=0.01 p=0.02 p=0.02 100% 36 91.1 79.9 46.7 <99% 51 58.6 38.6 22.7 p<0.001 p<0.001 p=0.002 >95% 57 94.5 77.2 45.2 <95% 30 29.3 15.0 8.2 p<0.001 p<0.001 p=0.002 >90% 64 93.7 76.0 43.8 <90% 23 13.9 4.3 0 p<0.001 p=0.001 p=0.007 >85% 69 85.8 69.2 40.8 <85% 18 11.8 5.6 0 p=0.001 p=0.005 p=0.04 >80% 75 81.2 63.8 37.1 <80% 12 0 0 0

MMR=major molecular response; CMR=complete molecular response. Marin D, et al. J Clin Oncol 2010; 28(14): 2381–2388. Marin D,Marin et al. J

Cumulate incidence of loss of CCyR 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0 Adherence and the achievement are MMR of the Clin CCyR,no MMR, AdherenceRate >85%,n=23 MMR, CCyR,no MMR, AdherenceRate Oncol 6 only only independent predictors for outcome n=53 Monthsfrom enrolment 2010; 28(14): 2381 28(14): 2010; Conclusion to theConclusion Marin Study: 12 p=0.0009 ≤ 85%, n=11 85%, 18 – 2388. p<0.0001 p<0.0001 24

Probability of imatinib failure 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0 p<0.0001 CCyR, no MMR, Adherence Rate >85%,CCyR, MMR,Adherence n=23 no MMR, n=53 CCyR, no MMR, Adherence Rate ≤85%,CCyR, MMR,Adherence n=11 no 6 Months from enrolment p=0.003 12 18 p<0.0001 24 Complexities, Actions, Algorithms CV toxicity, switching TKIs, management deficits SIMPLICITY Study Overview: Landmark Observational Study in CML

Strategic Objective: Determine effectiveness of available CP-CML treatments, understand impact of CML and treatment on QoL and evaluate HRU and associated cost burden in real-world setting Inform clinical practice clinical Inform Eligibility: Primary Research Objective Retrospective (imatinib) • Newly-diagnosed CP-CML N=252 • To better understand the use of dasatinib and patients Prospective (nilotinib) other TKIs in first-line CML in a real world setting • Receiving 1st line imatinib, N=408 dasatinib or nilotinib Secondary Research Objectives Prospective (imatinib) • ≥18 years at time of diagnosis N=416 • Evaluate patient benefit of CML treatment • Not participating in a CML Prospective (dasatinib) • Determine healthcare resource utilization clinical trial N=418

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 for outcomes Improve CP

Enrollment Enrollment End of patients - CML (Retrospective (Prospective study cohort) cohort) follow-up Data Collection

• Demographics • Clinical characteristics • Bone marrow aspirates • Hospitalizations • Vital signs • TKI treatment • Blood tests • QoL outcomes • Physical exam • Comorbidities • Molecular response • Treatment adherence • CV assessments • Spleen assessment • Cytogenetics • Discontinuation

3 SIMPLICITY: Lack of Adherence to Monitoring Guidelines in Clinical Practice

About 1 in every 5 patients are not tested for MR at 12 months and almost half are not tested for CyR

Patients not tested for CyR at 12 months1 Patients not tested for MR by 12 months1

Overall (N=862) 51% Overall (N=862) 17%

US 38% US (n=573) (n=573) 13%

Europe 58% Europe 19% (n=289) (n=289)

Age <65 years at initiation of first-line TKI, patients who had switched from first-line TKI and those seen in academic centres were more likely to be monitored by 12 months (p<0.05)2

1. Goldberg SL, Cortes J, Gambacorti-Passerini C, et al. Cytogenetic and molecular testing in patients with chronic myeloid leukemia (CML) in a prospective observational study (SIMPLICITY). J Clin Oncol. 2014;32:5s (suppl; abstr 7050). 2. Goldberg SL, Cortes J, Gambacorti-Passerini C, et al. Predictors of performing response monitoring in patients with chronic-phase chronic myeloid leukemia (CP-CML) in a prospective observational study (SIMPLICITY). J Clin Oncol. 2014;32:(suppl 30; abstr 116). SIMPLICITY: Patients Discontinuing First-Line TKI

Quarter of SIMPLICITY patients discontinue TKI treatment in first 12 months

862 pts with at least 12 months of follow-up

Imatinib 30% Pts who (n=400) discontinued index Tx:

Dasatinib 17% 24% (n=230)

(N=207) patients of Proportion Nilotinib 21% discontinuing treatment (%)* treatment discontinuing (n=232)

*P<0.001

Intolerance most common reason for TKI discontinuation in first 12 months

862 pts with at least 12 months of follow-up

Second-line TKI choices vary by region; in the US, DAS was most common second-line TKI, while in Eu, the second-line TKI choice was more equally distributed

862 pts with at least 12 months of follow-up

Imatinib Dasatinib Nilotinib FIRST-LINE (n=119) (n=40) (n=48)

SECOND-LINE DAS NIL IM NIL DAS IM All patients 45% 32% 40% 17% 33% 29%

SECOND-LINE DAS NIL IM NIL DAS IM Pts in Europe 36% 42% 33% 0% 25% 12%

SECOND-LINE DAS NIL IM NIL DAS IM Pts in US 58% 26% 41% 21% 35% 32%

Hehlmann R, Cortes J, Gambacorti-Passerini C et al. Tyrosine kinase inhibitor (TKI) switching experience from SIMPLICITY, a prospective observational study of chronic phase chronic myeloid leukemia (CP-CML) patients in clinical practice. 19th European Hematology Association (EHA) Annual Meeting; June 12–14, 2014, Milan, Italy: abstract P883 ENRICH STUDY: Changes in Toxicity and QoL in Patients Switched from Imatinib to Nilotinib - 45 / 52 patients had a total of 182 low-grade (grade 1/2), imatinib-related, nonhematologic AEs at baseline. - Of the 182 AEs, 130 were grade 1 and 52 were grade 2.

71.4%

ASH 2012 ENRICH: Change in Severity of Most Frequently Reported Imatinib-Related Nonhematologic AEs*

Cortes J, et al. Blood. 2012;120(21):[abstract 3782]. ENRICH: Change from Baseline in QoL by Cycle

Cortes J, et al. Blood. 2012;120(21):[abstract 3782]. TKI General AE profile

Colors represent the frequency of side effect: green 0–1%; light green 2–5%; yellow 6–15%; orange 16–29%; red ≥ 30%

Patel, et al. Exp Rev Hematol. 2017;10:659–74 The most significant ‘late effects’: BCR-ABL1 TKI Associated Cardiovascular Adverse Effects

Cerebrovascular Disease Cardiomyopathy Congestive Heart Failure Endothelial Dysfunction? Atherosclerosis? Cardiomyocyte Injury?

Pulmonary Arterial Hypertension Coronary Heart Disease Myocardial Infarction Endothelial Dysfunction?

Endothelial Dysfunction? Atherosclerosis? Venous Thrombosis Peripheral Arterial Disease Platelet dysfunction? Endothelial Dysfunction? Prothrombotic state? Atherosclerosis? • Fatigue Other: • Musculoskeletal Sx / Cramping • Exercise-Induced Symptoms

è Morbidity and mortality; ? Effect on OS observations in front-line studies 105 è ? Delay/deferral of advantageous therapy both in front-line and salvage Kantarjian, et al. Blood. 2012;119:1981-1987. Front-line nilotinib in CML: CVEs over time (5y data- ENESTnd)

Larson RA, et al. J Clin Oncol. 2014;32:5s (suppl; abstr 7073). Summary of VOEs: ponatinib phase I and phase II (PACE) trials Treatment-Emergent Treatment-Emergent Adverse Events Serious Adverse Events Treatment- Treatment- All, All, Related, Related, n/N (%) n/N (%) n /N (%) n/N (%) Phase I 37/81 (46) 7/81 (9) 16/81 (20) 5/81 (6) All patients (N=81) Phase I CML and Ph+ ALL 31/65 (48) 7/65 (11) 14/65 (22) 5/65 (8) (N=65) Phase II (PACE) 109/449 (24) 45/449 (10) 67/449 (15) 27/449 (6) All patients (N=449)

27% Dec 2013 USPI

Phase I Data as of 26 Sep 2013; PACE Data as of 03 Sept 2013 Meta-analysis of VOEs: Imatinib versus subsequent generation TKIs

CI, confidence interval; CML, chronic myeloid leukemia; OR, odds ratio; Ph, Philadelphia chromosome; TKI, tyrosine kinase inhibitor; VOE, vascular occlusive event. Douxfils et al. JAMA Oncol. 2016 Feb 4. doi: 10.1001/jamaoncol.2015.5932. Meta-analysis: Arterial and Venous Occlusive Events

Favors imatinib Favors imatinib

Haguet et al. Expert Opin Drug Saf. 2016 MI ‘Complete Molecular CVA Remission’ PAD

Dyslipidemia ‘Treatment Free DM/Glu Intol Remission’

= Recommended Imatinib Bosutinib Dasatinib Nilotinib Ponatinib Guidelines in active = As clinically indicated development for CML Baseline Assessment Cardiovascular assessment patients and CV risk Blood pressure check Fasting glucose Fasting lipid panel ‘ABCDE’ Step Approach to CV Intervention * Echocardiogram A: Awareness of cardiovascular disease signs and symptoms Electrocardiogram A: Aspirin (in select patients) Ankle-brachial index 1-month follow up A: Ankle-brachial index measurement at baseline and follow- Cardiovascular assessment up to document peripheral arterial disease Blood pressure check B: Blood pressure control 3- to 6-month follow-up C: Cigarette/tobacco cessation Cardiovascular assessment C: Cholesterol (regular monitoring and treatment if indicated) Blood pressure check D: Diabetes mellitus (regular monitoring, dose of Fasting glucose radiation/chemotherapy, and treatment if indicated) Fasting lipid panel * D: Diet and weight management Echocardiogram E: Exercise (echocardiogram) Electrocardiogram Ankle-brachial index *Patients treated with dasatinib should be considered for echocardiogram if cardiopulmonary Barber M, Mauro M and Moslehi J, in press symptoms are present. Summary II

• Adherence has significant impact on response • Landmark responses key to avoid progression (MMR) • Landmark response key to consider TFR (MR4, CMR)

• Multiple liabilities: • chronicity of therapy with oral therapy, uncertain end date • Minimal disease symptoms, rapid/deep response (many “NED”) • Low grade adverse events common • More significant late effects under investigation, surveillance and risk assessment tools needed

• Under-monitoring and lack of expertise are risks on the provider side • Monitoring basic landmarks of response lacking • Switch of therapy common Take-aways • CML has opened the door to ‘cure’ with oral, low risk therapy (prior to imatinib, hormonal therapy for breast cancer and trastuzumab were only ‘targeted’ therapies) • All the challenges of chronic oral therapy exist and are magnified by impact on response and outcome • ‘Good problems: many drug choices; rapid response; lack or reinforcement of disease presence; common to be managing disease detected at minute levels or ‘NED’ • Uncertainty about length of therapy and treatment free remission leaves the ‘end game’ nebulous… Many TKIs = Long, Response Happy, Remission Healthy Life! Cure? Thank you for your attention! +212-639-3107 [email protected]