Download Recognize the Impact of QOL Measurements on Oncology

Recognizing the Importance of QoL Measurements of
Oncology Trials — Executing / Informing:
The Building of Your Strategic Plan
Scott Megaffin
March 23, 2016
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9th
Annual Oncology Commercialization & Market Access CBI Conference
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Check us out:
www.churchillpharma.com
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Presentation Objectives
A well conducted QoL Deliverable will:
1. Meet evidence requirements for reimbursement and market access
2. Generate the HEOR evidence for labeling throughout product life cycle
3. Communicate full brand value to payers and clinicians
Hint: This is a test
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Executive Summary
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Background:
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Define your commercialization opportunity (Big Data)
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Understand the literature (The Oncology Maze)
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Determine strategic and tactical objectives
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Inform: 1. Health Economics 2. Outcomes Research
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Execute: QoL Strategy with data / validation
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Key commercialization milestones
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Year -2: Commercialization plan; know your literature; establish the QoL plan
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Year -1: Phase III trial data; submit NDA
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Launch year: Phase III trial data published - editorials, commentaries; opinion
leader perspective
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Launch +0/+1: Approval; brand as standard of care for indication
QoL strategy supports and informs commercialization timeline
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Case example: Rigosertib (ONTX)
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Second-line monotherapy for patients:
– Relapsed after hypomethylating agents (HMAs)
– Failed to respond to HMA
– Intolerant to HMA
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Uses novel mechanism of action in MDS
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Delays progression to acute myeloid leukemia (AML)
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Phase III ON 01910 Na. Trial In Myelodysplastic SyndromE
(ONTIME) trial (rigosertib vs. supportive care) ongoing
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Case example: Understanding the data
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Group of related cytopenias:
– Can include anemia, dysplastic changes
– Three risk classification schemes: French-American-British, World
Health Organization (WHO), International Prognostic Scoring System
(Bennett 1982, Vardiman 2002, Greenberg 2012)
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Incidence difficult to quantify:
– Estimates range from 20,000 to 80,000 new cases per year in US (Cogle
2011)
– Accuracy of estimate highly dependent upon data source (e.g, cancer
registry, claims data)
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Median age at diagnosis < 60 years (Vardiman 2002)
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Long term prognosis is poor: 3 to 6 months, depending upon risk
Understanding data means understanding
the impact of QoL
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Case example: Understanding disease treatment
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Largely incurable (Nimer 2008)
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Best supportive care (BSC) includes:
– Blood transfusions
– Iron chelation therapy, especially if transfusion-dependent
– Anemia management (NCCN 2013)
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After diagnosis, most patients receive BSC only, due to:
– Advanced patient age
– Toxicities of current medications (Greenberg 2010)
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Antineoplastic treatments
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Only curative therapy is hematopoietic stem cell transplantation;
few are candidates
Treatment options limited,
QoL becomes mixed with quantity
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Case example: Defining - QoL, in population
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Little may be known about quality of life (QoL)
– Small studies cited fatigue, transfusion dependence and management of
iron overload as factors contributing to low QoL (Steensma 2008, Thomas 2012, Payne
2008)
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Value to patients of being “transfusion independent” is high
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No studies specifically measured QoL in second-line MDS
QoL for MDS was not well defined, no studies in
2nd Line MDS treatment
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Case example: Knowledge Gap - Cost of care
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Cost of BSC and treatment $50,000 per year (Greenberg 2008, Wang 2012)
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Few studies examined cost effectiveness of HMAs
– Those that had suggested treating MDS as cost effective
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Cost estimation hampered by same issues as incidence estimation
(e.g., incomplete data, wide variation in estimates)
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No studies specifically measure cost in second-line MDS
No studies compared cost effectiveness for
second-line MDS
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HEOR: Aligning the tactics
Goal: Improve acceptance of YOUR COMPOUND in YOUR Malignancy treatment
1. Claims analysis to improve incidence estimates
2. Conceptual model to understand treatment decision-making
3. Claims analysis to characterize burden of illness
4. Cost effectiveness analysis of current second-line treatment
5. Validation - Patient survey for quality of life
6. Cost effectiveness analysis of treatment your compound
7. Decision model, either: progression – survival (?)
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Validated Tools
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Presentation Summary
The successful QoL Deliverable will:
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Meet evidence requirements for reimbursement and market access
•
Generate the HEOR evidence for labeling throughout product life cycle
•
Communicate full brand value to payers and clinicians
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Thank you . . . and
Rock Chalk!!
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References
Bennett JM, Catovsky D, Daniel MT, et al. Proposals for the classification of the myelodysplastic syndromes. Br J Haematol. 1982;51:189-199.
Cogle CR, Craig BM, Rollison DE, List AF. Incidence of the myelodysplastic syndromes using a novel claims-based algorithm: high number of uncaptured
cases by cancer registries. Blood. 2011;117:7121-7125.
Greenberg PL, Tuechler H, Schanz J, et al. Revised international prognostic scoring system for myelodysplastic syndromes. Blood. 2012;120:2454-2465.
Greenberg PL. Current therapeutic approaches for patients with myelodysplastic syndromes. Br J Haematol. 2010;150:131-143.
Greenberg PL, Cosler LE, Ferro SA, Lyman GH. The costs of drugs used to treat myelodysplastic syndromes following National Comprehensive Cancer
Network Guidelines. J Natl Compr Canc Netw. 2008;6:942-953.
National Comprehensive Cancer Network (NCCN). NCCN clinical practice guidelines in oncology: myelodysplastic syndromes, version 2.2013.
http://www.nccn.org/professionals/physician_gls/pdf/mds.pdf. Accessed February 11, 2013.
Nimer SD. Myelodysplastic syndromes. Blood. 2008;111:4841-4851.
Payne KA, Rofail D, Baladi JF, et al. Iron chelation therapy: clinical effectiveness, economic burden and quality of life in patients with iron overload. Adv
Ther. 2008;25:725-742.
Prébet T, Gore SD, Esterni B, et al. Outcome of high-risk myelodysplastic syndrome after azacitidine treatment failure. J Clin Oncol. 2011;29:3322-3327.
Steensma DP, Heptinstall KV, Johnson VM, et al. Common troublesome symptoms and their impact on quality of life in patients with myelodysplastic
syndromes (MDS): results of a large internet-based survey. Leuk Res. 2008;32:691-698.
Thomas ML, Crisp N, Campbell K. The importance of quality of life for patients living with myelodysplastic syndromes. Clin J Oncol Nurs. 2012;16
(Suppl):47-57.
Vardiman JW, Harris NL, Brunning RD. The World Health Organization (WHO) classification of the myeloid neoplasms. Blood. 2002;100:2292-2302.
Wang R, Gross CP, Frick K, et al. The impact of hypomethylating agents on the cost of care and survival of elderly patients with myelodysplastic
syndromes. Leuk Res. 2012;36:1370-1375.
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