Download Long-Term Survival in Cancer Patients

Long-Term Survival in
Cancer Patients –
Defining Novel Value Metrics
and Methodologies in an Era of
Immuno-Oncology Medicines
12 November 2014
Amsterdam, The Netherlands
Welcome and Introduction
Professor Bengt Jönsson
Stockholm School of Economics
Stockholm, Sweden
2
Immuno-Oncology (I-O) Therapies –
New Questions in Need of Answers
“How do we make
informed decisions for
patients in need when
long-term outcomes with
I-O therapies remain
uncertain?”
3
“If a significant proportion of
patients are expected to live
longer with cancer and/or after
cancer, what does this mean
for health technology
assessments (HTA)?”
The Aspirational Goal for I-O Therapies –
Reaching a New Normal
% Survival
Theoretical Survival with Various Cancer Treatments1,2
As cancer therapies evolve,
the cancer survival curve
continues to change
50
Clinicians: Benefit:Risk
HTAs: Effectiveness
and Value
Patients: Hope
Time
4
1. Chen TT. J Immunother Cancer. 2013;1:18. 2. Ribas A, et al. Clin Cancer Res. 2012;18:336-41.
Agenda
5
Introduction
Prof Bengt Jönsson
07:30
Immuno-Oncology Therapies: What, Why and How?
Dr David Chao
07:40
How Do We Fully Assess Value in I-O?
Prof Isabelle Durand-Zaleski
07:50
Long-Term Survival: The Need for Patient-Focused Metrics
Cilia Linssen
08:00
Q&A and Panel Discussion
08:10
Thank You and Close
08:30
Immuno-Oncology Therapies:
What, Why and How?
Dr David Chao
Royal Free Hospital
London, UK
6
Dr Chao has done consultancy work and/or been sponsored by
AstraZeneca, BMS, GSK, MSD, Novartis and Roche.
What Is Immuno-Oncology
• Our understanding of how cancers evade
the immune system continues to evolve1–3
• Cancer cells can evade the immune
system by shielding tumours from an
immune response5–8
• I-O offers an innovative approach to
fighting cancer, which involves harnessing
the body’s immune system to fight the
disease4, 5-10
7
1. Hanahan D, et al. Cell. 2011;144:646-674. 2. Gajewski TF, et al. Nat Immunol. 2013;14:1014-1022. 3. Poschke I, et al. Cancer Immunol Immunother. 2011;60:11611171. 4. Eggermont A, et al. Ann Oncol. 2012;23:viii5. 5. Pardoll DM. Nat Rev Cancer. 2012;12:252-264. 6. Shields JD, et al. Science. 2010;328:749-752. 7. Drake CG, et
al. Adv Immunol. 2006;90:51-81. 8. Baruah P, et al. Immunobiology. 2012;217:669-675. 9. NCI. NCI Dictionary of Cancer Terms Website. 10. Fox BA, et al. J Transl Med.
2011;9:214.
What Can We Expect From I-O in the Next Few Years?
Any setting with evidence of tumour-mediated inhibition of the immune system
is a potential candidate for immuno-oncology therapy
A. Infiltrating
immune cells
reported
B. Evidence of
tumourassociated
immunosuppres
sion
C. Tumour-immune
system
interactions
correlate with
clinical
prognosis
8
I-O Agents Across Tumour Types1,2
Oesophageal (A,B,C)
1. Ascierto PA, et al. J Translational Med. 2014;12:141-153. 2. BMS. Immuno-Oncology Website.
Leukaemia/
What Can We Expect from I-O in the Next Few Years?
Phase I
Phase II
Phase III
Ipilimumab
(multiple solid and haematological cancers)
(melanoma, prostate, lung, GBM)
Tremelimumab
(HCC, melanoma, mesothelioma)
Tremelimumab
(melanoma)
Ipilimumab
Post-approval
Ipilimumab
(melanoma)
Pidilizumab
(pancreatic, prostate, melanoma, lymphoma)
Nivolumab
(multiple solid and haematological cancers)
Nivolumab
(melanoma, RCC, NSCLC)
Nivolumab (Japan)
(melanoma)
Pembrolizumab
(brain, melanoma, NSCLC, renal, breast)
Pembrolizumab
(melanoma, NSCLC)
Pembrolizumab (USA)
(melanoma)
INCB 24360
(breast, melanoma, NSCLC, myelodysplatic syndromes, ovarian)
MPDL3280A
(kidney,
renal, bladder,
AMP-224
(Advanced
cancer)lymphoma, melanoma, NSCLC)
INCB 24360
BMS-936559
(breast, melanoma, NSCLC, myelodysplatic syndromes, ovarian)
(Melanoma, NHL, solid
Indoximod
tumours)
(Breast, prostate, glioma, melanoma, pancreatic, lung, pancreatic)
MGA 271 (Refractory cancers)IMP321
(Melanoma, breast, RCC, pancreatic)
9
1. NIH. ClinicalTrials.gov
MPDL3280A
(NSCLC)
HCC, hepatocellular carcinoma;
NSCLC, non-small cell lung cancer;
RCC, renal cell carcinoma; GBM,
glioblastoma multiforme;
What Do Outcomes Show?
Primary Analysis of Pooled OS Data (N=1861 Patients)
1.0
0.9
Median OS, months (95% CI): 11.4 (10.7–12.1)
Proportion Alive
0.8
0.7
0.6
3-year OS rate, % (95% CI): 22 (20–24)
0.5
0.4
0.3
0.2
0.1
Ipilimumab
CENSORED
0.0
0
12
24
36
48
60
72
84
96
108
120
120
26
15
5
0
Months
Patients at Risk
Ipilimumab
1861
10
839
370
254
192
170
1. Schadendorf D, et al. Pooled analysis of long-term survival data from phase II and phase III trials of ipilimumab in metastatic or locally
advanced, unresectable melanoma. Presented at: European Cancer Congress 2013 (ECCO-ESMO-ESTRO); 27- Sep–1 Oct, 2013; Amsterdam,
The Netherlands. Abstract 24.
What Do Falling Mortality Trends Mean for I-O Therapies?
Cancer mortality trends in the EU from 1970-1974 to 2005-2009
and predicted rates for 20141
Deaths per 100 000 Population
All Cancer EU
•
•
11
EU Male
EU Female
Men
Lung
Breast
Lung
Colorectum
Women
Colorectum
Pancreas
Uterus
Prostate
Pancreas
Stomach
Leukaemias
Stomach
Leukaemias
Reduced overall mortality rates and subsequent prolonged survival of cancer
patients may require a chronic disease approach when assessing novel therapies
Current metrics need to be reevaluated in the context of I-O therapies and how they
may be applied
1. Malvezzi M, et al. Ann Onc. 2014;25:1650-1656.
Why Do We Need to Think Differently About I-O?
Use of chemotherapy
principles and conventional
endpoints do not fully
capture the benefits
of I-O drugs1-3
I-O drug activity is
not standardised1,4
Need for new approach
and integrated knowledge
sharing to fully
demonstrate value of I-O
therapies
I-O drugs use new mechanisms to control tumour growth.
We need new tools (to complement our old tools) for assessing their value2
12
1. Hoos, et al. OncoImmunology. 2012;1:334-339. 2. Hoos A, et al. J Immunother.2007;30:1-15. 3. Hoos A, et al. JNCI.2010;102:1388-1397.
4. Wolchok JD, et al. Clin Cancer Res. 2009;15:7412-7420.
63-Year Old Gentleman….
•
•
•
13
Malignant melanoma of right
leg 1987
Local relapses in September
2010 and 2011
Increasing shortness of breath
summer 2012
63-Year Old Gentleman….
•
•
•
•
14
Formal pleurodesis and biopsy
confirmed relapse
BRAF mutation positive
Randomised on COMBI-V trial
to combination arm
Commenced 16 February 2013
Response to Dabrafenib and Trametinib at 9 Days
15
Response to Dabrafenib and Trametinib at 2 Months
16
Progression at 7 Months
•
•
•
Came off study
September 2013
Remained well
Started on trial with new I-O
agent (PD-1 inhibitor), October
2013
After 3 Months on I-O Agent…
•
•
18
Ongoing response
Interruption due to
autoimmune toxicities
In Summary…
•
•
•
•
19
Focus immune response onto the cancer
Define patients with best benefit risk profile for different
therapies
Optimise treatment, e.g. how long is long enough?
Continue to improve education and outcomes of
managing autoimmune side effects
What Is Old Is New Again?
“Stimulate the Phagocytes!”
The Doctor’s Dilemma by George Bernard Shaw
20 November 1906
20
How Do We Fully Assess Value in
Immuno-Oncology?
Professor Isabelle Durand-Zaleski
URC Eco, Ile de France
Paris, France
21
Professor Durand-Zaleski has been a speaker and adviser for Abbvie, BMS,
Janssen, Medtronic, Pfizer and Sanofi.
The Need to Reassess Oncology Metrics for I-O Therapies
•
•
As the field of immuno-oncology evolves,
we need to reassess the value of new I-O
drugs from a unique I-O perspective, not
exclusively from an oncology viewpoint1,2
Traditional study designs and value
metrics:1,3
•
•
•
•
•
•
22
Overlook the diversity of cancer patient
populations
Fail to differentiate from the unique
characteristics of I-O therapies
Do not address the heterogeneity of
response to different cancer treatments
Are designed to assess short-term,
incremental, clinical benefits
Could underestimate treatment benefits
due to the presence of delayed clinical
effects and durable survival associated
with I-O therapy
Insufficiently capture the quality of life
impact in patients with durable survival
1. Chen TT. J Immunother Cancer. 2013;1:18. 2. Ribas A, et al. Clin Cancer Res. 2012;18:336-41. 3. Fox BA, et al. J Transl Med. 2011;9:214.
How Is Value Best Demonstrated in I-O?
Traditional metrics are effective, but insufficient for
understanding the full value of I-O drugs
•
•
•
•
•
Overall survival (OS),
median or mean
5-yr survival
Disease-free survival
(DFS)
Progression free
survival (PFS)
Objective response rate
(ORR)
Clinical benefit (ORR +
Stable Disease [SD])
Response duration
Biomarkers
•
•
•
23
•
Survival
Safety
•
Value
•
Response
Resource
Impact
•
•
Safety profile
(Adverse events
[AE], Grade 3/4
AEs,
discontinuation)
Quality of life
(QoL)
Incremental cost
effectiveness ratio
(ICER)
Budget impact
Efficiency frontier
1. EMA. Guidance on the evaluation of anticancer medicinal products in man. 2011. 2. FDA. Guidance for industry clinical trial endpoints for the approval of cancer
drugs and biologics. 2007. 3. Kogan AJ, et al. Biotechnology Healthcare. 2008;5:22-35. 4. Imai H, et al. Breast Cancer. 2007;14:81-87. 5. Kumar R. Med J Armed
Forces India. 2013;69:273-277. 6. Geynisman DM. Hum Vaccin Immunother. 2014;7. [Epub ahead of print] 7. Burudpakdee C, et al. ESMO 2012. Poster 337P.
Definition of Ultimate Goal with Traditional Metrics
Varies by Cancer Type
Type
Aspects Terminology
Varying
Molecular
Not
specific to
one cancer
type
Statistical
Statistical
24
BMS. Data on file.
Definitions
‘Cure’
Diverse range of definitions
Persistent
complete
remission
Long-term absence of cancerous cells
(e.g., detectable by RT-PCR)
Cure models
Models show the proportion of ‘cured’ patients, e.g.,
plateau in survival curve at particular probability
corresponding to the fraction cured
Statistical cure
Absence of excess mortality in cancer patients
Definition of Ultimate Goal with Traditional Metrics
Varies by Cancer Type (cont’d)
Type
Aspects Terminology
Clinical cure
Clinical
Breast
cancer
Following treatment, the patient eventually
dies from other causes
The primary tumour volume at which the patient would
Treatment cure
never die from his/her specific disease, if detected and
threshold
treated
Molecular
Definite cure
Complete pharmacological eradication of LSCs
Clinical
Functional cure
Long-term absence of relapse
Malignant
melanoma
Molecular
Myeloma
Clinical
25
No recurrence of cancer during a patient's lifetime
Personal cure
Surgical
Chronic
myeloid
leukaemia
Definitions
BMS. Data on file.
Minimal residual Low level of Langerhans cells that is still detectable
(by RT-PCR) following treatment
disease
Operational cure
Prolonged disease control with intensive therapy
LSC, leukaemic stem cells
Return to Normality – Is It All About Survival?
•
Five-year survival rate = the percentage of people alive five years after
their diagnosis or the start of treatment1
•
•
•
Stakeholders are questioning the value of available clinical endpoints for
reflecting “cure”
•
•
26
Many cancers are considered ‘cured’ when the patient is alive and no
remission occurs five years after diagnosis
Recurrence after five years remains a possibility
14% of assessed journal articles reject the idea that OS and/or relapse-free
(RFS) definitively measure ‘cure’
• ‘Reversion to general
‘While 5-year survival is a
useful indicator, it does
not provide direct
information on the main
aim of cancer treatment,
the cure of the patient’
–Francisci (2009)2
•
‘Five-year and ten-year
relapse-free survival is
not equivalent to cure’
–Hortobagyi (2003)3
mortality rates implies that
any patient surviving beyond
five years of second-line
systemic treatment is
effectively completely cured
of their metastatic disease.
No evidence has been
submitted to support such a
strong claim’
–NICE (2012)4
1. NCI. NCI Dictionary of Cancer Terms Website. 2. Francisci S, et al. Eur J Cancer. 2009;45: 1067-1079. 3. Hortobagyi GN. Eur J Cancer
Suppl. 2003;1: 24-34. 4. NICE. Final appraisal determination – Ipilimumab for previously treated advanced (unresectable or metastatic)
melanoma. 2012.
Potential Value Metrics for Assessing I-O Therapies
AUC and
restricted
mean
Potential
highest value
Survival rates
by year
Increasing
value with
increasing
survival times
27
QoL
These metrics are not designed to
replace existing metrics. Rather,
they:
• Account for long-term survival
• Demonstrate added value
• Provide more information on
safety and QoL
• Revisit currently available
metrics from a different
perspective
Potential New Value Metrics –
Area Under the Curve (AUC) and Restricted Mean
Treatment group
Restricted mean
estimate of
survival
difference
Control group
Median survival difference
Survival difference at maximum follow up
Survival Probability
Restricted mean survival difference
Final
observation
point at
5 years
(control and
treatment)
28
Estimated further survival difference
Survival after 5 years
is ignored by
traditional metrics
50% of patients alive
(control and treatment)
1. Davies A, et al. Health Outcomes Res Med. 2012;3:e25-e36.
Expected values
How Can We Measure What Matters to Stakeholders?
Survival
QoL
Simplified
care pathways
Required values
Patient identification
Successful treatment
Care
continuity
Keeping
patients at home
Use of innovative
therapy
Access to
expertise
Efficient use
of specialty resources
Well-defined role
In care pathway
No out of
pocket cost
Patients
Carers
Oncologists
Primary Care
Increased
Involvement
in patient care
Equal
access
Appropriate
treatment
Medical
29
Help with
compliance
Social
Economic
1. Adapted from Jean et al, 2012 Rapport Efficience de la télémédecine état des lieux de la littérature internationale et cadre
d’évaluation.
Conclusion
•
•
•
•
•
•
30
I-O therapies have the potential to transform cancer therapy and could become the
standard of care for many patients1,2
Efficacy and safety profiles for I-O therapies differ from previously characterised
chemotherapy and pathway-specific agents3
Current outcome measures as indicators of value do not fully assess new I-O
therapies4-6
Novel approaches (eg, AUC and restricted mean) that repurpose available tools need
to be explored7,8
May be particularly useful to assess outcomes and long-term survival in terms of
quality of life, durability and sustainability of treatment outcomes, clinical and societal
benefits
The evolving healthcare environment provides an opportunity to assess by
stakeholder how to improve access to innovative cancer treatments8,9
1. Wolchok J. Ann Oncol. 2012;23 (Suppl 8):viii15-viii21. 2. Hoos A, et al. JNCI. 2010;102:1388-1397. 3. Chen TT. J Immunother Cancer. 2013;1:18. 4. Hoos A, et al.
Oncoimmunology. 2012;1:334-339. 5. Kudrin A. Hum Vaccin Immunother. 2012;8:1326-1334. 6. Ribas A, et al. Clin Cancer Res. 2012;18:336-341. 7. Ascierto PA, et
al. J Transl Med. 2014;12:141. 8. Wolchok JD et al. Clin Cancer Res. 2009;15:7412-7420. 9. Van Cutsem E, et al. Eur J Cancer. 2013;49:2476-2485.
Long-Term Survival: The Need for
Patient-Focused Metrics
Cilia Linssen
Lung Cancer Information Centre and
Lung Cancer Europe
31
Unmet Need Exists in Lung Cancer
Lung cancer is the most common cancer in the world and is the most
common cause of death from cancer worldwide1
1.825 million
Total cases per year worldwide
1.590 million
Total number of deaths per year worldwide
1.893 million Number of people alive after 5 years
24.483 million Healthy years of life lost
32
1. WHO Cancer Fact Sheet (No. 597), updated February 2014.
What Matters to Patients?
Domains of Lung Cancer
Survivor Needs1
Education/
Counselling
SocioEconomic
Support
Counseling and
Complementary
Diet, exercise
treatment for
and
alternative
and weight
How
do
we
measure
depression andwhat matters
medicine
control
anxiety
Financial
patients?
support
Information
33
Supportive
Care
1. Yun YH, et al. Ann Oncol. 2013;24:1552-159.
to
What Matters to Patients?
Lung cancer patients’ unmet needs/wants*
1.
2.
3.
4.
5.
6.
7.
8.
9.
34
Lack of energy/tiredness
Uncertainty about the future
Work around the home
Not being able to do the things they used to do
Anxiety
Worry that results of treatment are beyond their control
Learning to feel in control of the situation
Feelings of sadness
Making the most of their time
*In order of most frequently reported
1. Sanders SL, et al. Psycho-oncology. 2010;19:480-9.
What Matters to Caregivers?
Partners and cancer patient caregivers’ unmet
needs/wants*
1.
2.
3.
4.
5.
5.
6.
7.
8.
9.
10.
35
Managing concerns about cancer coming back
Reducing stress in the person with cancer’s life
Understanding the experience of the person with cancer
Accessible hospital parking
Information about benefits and side effects of treatments
Balancing needs of the person with cancer and yours
Obtaining best medical care
Addressing fears about person with cancer’s deterioration
Adjusting to changes in the person with cancer’s body
Addressing problems with sex life
Accessing information – prognosis
*In order of highest unmet need
1. Girgis A, et al. Psycho-oncology. 2013;22:1557-1564.
The ‘Sure Bet’ vs the ‘Hopeful Gamble’
Patients were asked which therapy they preferred, assuming same
out-of-pocket cost to the patient:
‘Sure Bet’
• Average survival = 24
months
• 100% certainty of death
at 24 months for ALL
patients
36
1. Lakdawalla DN, et al. Health Affairs. 2012;31:676-682.
‘Hopeful Gamble’
• Average survival = 24
months
• 50% of all patients live
10 months or less
• 30% of patients live
more than 10 months
but less 4.5 years
• 20% of patients live
more than 4.5 years
What Is the Value of Hope?
77%
Cancer patients prefer a ‘hopeful gamble’
to the ‘sure bet’
Patients may value treatments differently at different ages, in
different family circumstances, or from other perspectives
‘sure bet’
37
1. Lakdawalla DN, et al. Health Affairs. 2012;31:676-682.
‘hopeful gamble’
Align Values with Patients’ Views and Beliefs
Patients
Physicians
38
Payers
Concluding Remarks
39
Q&A and Panel Discussion
40
Thank You
41