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Transcript
HIV?
CHOLHUA , March 2015
Jean-Marc Fix, FSA, MAAA, VP, R&D
Why not?
The End
2
Is a segment of the
HIV-infected
population insurable?
CHOLHUA , March 2015
Jean-Marc Fix, FSA, MAAA, VP, R&D
Agenda
•
•
•
•
•
•
•
What is HIV infection?
Evolution of HIV infection mortality
Evolution of HIV infection treatment
Segmentation of HIV-infected population
Mortality of the better segments
Underwriting skills
Unknowns and risk mitigation strategies
4
Face of a killer
5
Face of a killer
6
Face of a killer
7
Face of a killer
8
Face of a killer
9
A Close-up
10
Video- Infection
• https://www.youtube.com/watch?v=RO8
MP3wMvqg
• 4’08”
11
Infectious pathway
•
•
•
•
•
Men having sex with men
Heterosexual
Intravenous drug user
Blood product (transfusion, hemophilia)
Occupational
12
Infectious pathway -Men
Other and
not reported
19%
Blood
transfusion
0%
High risk sex
7%
Hemophilia
0%
MSM+IDU
5%
IDU
8%
Male to
male(MSM)
61%
Source: HIV AIDS Surveillance vol 19 CDC
13
Infectious pathway Women
IDU
14%
Other and
not reported
39%
Blood
transfusion
0%
Source: HIV AIDS Surveillance vol 19 CDC
Hemophilia
0%
High risk sex
47%
14
What kills?
•
•
•
•
•
•
•
•
Depletion of CD4+ T helper cells
Loss of immune protection
AIDS defining diseases ~50% (1)
Liver disease (hepatitis co-infection)
Infection (non AIDS defining)
Cancer (non AIDS defining)
Cardiovascular
Drug overdose, accident, suicide
Source: Gill et al, Clin Infect Dis 2010
15
What we remember
AIDS Is Top Cause of Death for Young Adults
in U.S. Disturbing report by federal agency
San Francisco Chronicle 2/1/95
1985
Together in Life
and Death
2001
San Ramon pair die of
AIDS 2 days apart… Ray,
58, and Peggy, 54, of San
Ramon, died earlier this
month after battling the
disease for five years.
They were buried Monday
in the same grave. SFC
2/1/95
Hunting for the
Hidden Killers: AIDS
Time Magazine 7/4/83
1992
16
Número estimado de adultos y niños que vivían con el VIH
en 2008
América del Norte
Europa oriental y
Europa occidental Asia central
y central
1,5 millones
850 000
[1,4 – 1,7 millones]
1,4 millones
[710 000 – 970 000]
[1,2 – 1,6 millones]
África del Norte y
Oriente Medio
Caribe
240 000
[220 000 – 260 000]
América Latina
2,0 millones
[1,8 – 2,2 millones]
310 000
[250 000 – 380 000]
África subsahariana
22,4 millones
[20,8 – 24,1 millones]
Asia oriental
850 000
[700 000 – 1,0 millones]
Asia meridional y
sudoriental
3,8 millones
[3,4 – 4,3 millones]
Oceanía
59 000
[51 000 – 68 000]
Total: 33,4 millones (31,1 – 35,8
millones)
HIV mortality
18
HIV deaths
19
What we should be hearing
Managing HIV as a
Chronic Disease
South Afr j of HIV
Med 2004
HIV: Now a Manageable
Chronic Disease
Pharmacy Times 2007
When AIDS became a
chronic disease
West J Med 2000
Comprehensive Clinical
Care: Managing HIV as a
Chronic Illness
AIDS Clinical Care Journalwatch retrieved July 2010
20
HIV mortality
21
Trends in Annual Age-Adjusted* Rate of Death
Due to HIV Infection, United States, 1987−2010
Note: For comparison with data for 1999 and later years, data for 1987−1998 were modified to account
for ICD-10 rules instead of ICD-9 rules.
*Standard: age distribution of 2000 US population
Advances in treatment
Source: Pallella et al, J Acq Immune Def Syndr 2006
23
HAART
• Highly Active Antiretroviral Treatment
• Latest is triple cocktail, for ART naïve patients:
– NNRTI + 2 NRTI: Atripla and Complera
– Ritonavir boosted PI + 2 NRTI
– INSTI + 2 NRTI
NRTI = nuclesos(t)ide reverse transcriptase inhibitor
NNRTI = non-nucleoside reverse trans. inhib.
PI = protease inhib.
INSTI = integrase strand transfer inhib.
Source: Guidelines for the use of antiretroviral agents in HIV-1 infected adults
and adolescents DHHS as of 3/15
24
Video-Treatment
• https://www.youtube.com/watch?v=RO8
MP3wMvqg
• 4’09”
25
Advances in treatment
26
Action path of treatment
27
Action path of treatment
28
HIV reservoirs
• CD4+ memory T-cell
• Can stay inactive and virus dormant for
many years
• Under current therapy: 60+ years to
clear the virus (1)
(1): Marsden and Zack J Antimicrob Chemo 2009
29
Variables for mortality
•
•
•
•
•
•
•
•
•
•
Age
Gender
Smoking
Income
CD4+ cell count
Viral load
Time since infection
Response to treatment
Quality of follow-up
Infection source
30
Mortality by therapy
• When: 1994-1997
• Where: 8 cities in US
• Who:12% IDU, 12% Females, MSM
decreasing to 65%
• Severity: All had CD4+ cell counts below
100/mm3
• Significant treatment change in 1996
Source: Pallella et al NEJM 1998
31
Mortality by therapy
• RR death or morbidity
None vs. Monotherapy
1.5
None vs. combo
2.9
None vs. combo with
protease inhibitor
4.5
Source: Pallella et al NEJM 1998
32
Mortality evolution
• When: 1981-2006
• Where: 23 cohorts in Europe, Australia,
Canada
• Who:18% IDU, 22% Females, MSM
57%
• Severity: Since seroconversion
• Follow-up: median 6.3 (range 1 day to
23.8 years)
Source: Bashkaran et al, JAMA 2008
33
Mortality evolution
Deaths
Pre
1996
199697
199899
200001
200203
200406
Expected
56
28
33
39
41
37
481
231
212
188
127
17
7.0
5.5
4.6
3.4
Observed 1332
Obs/Exp
24
Source: Bashkaran et al, JAMA 2008
34
Mortality evolution
Source: Bashkaran et al, JAMA 2008
35
Mortality evolution
Source: Bashkaran et al, JAMA 2008
36
Mortality by age
Ratio observed to expected mortality by age, 15 year after seroconversion
Age at
seroconversion
1996-1997
2004-2006
15-24
3720%
736%
25-34
2225%
375%
35-44
3728%
150%
45+
na
192%
Source: adapted from Table 4, Bashkaran et al, JAMA 2008
37
Mortality by segment
• 7 year post cART France, first treated with PI
1997-99
• Overall: SMR 7.0
– Men 4.8
– Women 13.0
• HCV status
– Positive: 13.9
– Negative: 4.4
• HIV transmission
– IV drugs 16.3
– Other 5.5
Source: Lewden et al, J Acq Immune Def Syndr 2007
38
Mortality by segment
CD4+ count
cells/mm3
SMR
500+
2.5
350-499
3.5
200-349
5.6
<200
30.3
Source: Lewden et al, J Acq Immune Def Syndr 2007
39
Mortality by segment
Source: Lewden et al, J Acq Immune Def Syndr 2007
40
Mortality by age, CD4+
count and viral load
• Monte Carlo simulation model
• Includes HIV resistance evolution with
treatment
• Calibrated from a US cohort (CHORUS,
less IDU, less non-white)
• Validated against VA study (more IDU,
more non-white)
Source: Braithwaite et al, Am J of Med 2005
41
Modeling flowchart
Source: Braithwaite et al, Am J of Med 2005
42
Mortality Age 30
Age
CD4+ (cells/mm^3)
30
800
500
200
Viral load /ml
Median survival
Mort Mult (men)
10,000
31.30
400%
100,000
23.70
x
1,000,000
17.20
x
10,000
26.80
x
100,000
21.20
x
1,000,000
14.60
x
10,000
21.90
x
100,000
18.10
x
1,000,000
12.20
x
Source: from Braithwaite et al, Am J of Med 2005
43
Mortality Age 40
Age
CD4+ (cells/mm^3)
40
800
500
200
Viral load /ml
Median survival
Mort Mult (men)
10,000
28.00
250%
100,000
22.60
425%
1,000,000
15.20
x
10,000
24.40
350%
100,000
18.90
x
1,000,000
14.00
x
10,000
19.70
x
100,000
15.50
x
1,000,000
10.90
x
Source: from Braithwaite et al, Am J of Med 2005
44
Mortality Age 50
Age
CD4+ (cells/mm^3)
50
800
500
200
Viral load /ml
Median survival
Mort Mult (men)
10,000
22.30
200%
100,000
20.30
250%
1,000,000
14.30
x
10,000
21.10
225%
100,000
17.70
325%
1,000,000
12.90
x
10,000
16.50
375%
100,000
14.60
500%
1,000,000
10.20
x
Source: from Braithwaite et al, Am J of Med 2005
45
HAART treatment consequences
•
•
•
•
Dyslipidemia
Insulin resistance/diabetes
Endothelial dysfunction
Altered fat distribution
• More AMI in HIV +
Source: Triant et al, J Clin Endocrinol Metab 2007
46
HAART treatment consequences
HIV +
HIV -
Ratio
Heart Attack Rates per 1000 PY
18-34
4.65
0.88
528%
35-44
10.13
3.34
303%
45-54
18.74
7.56
248%
55-64
33.39
14.78
226%
65-74
77.68
24.47
317%
75-84
43.63
36.47
120%
Source: Triant et al, J Clin Endocrinol Metab 2007
47
Data limitations- the bad news
• Atherosclerotic cardiovascular
conditions take a long time to manifest
themselves
48
Underwriting skill-the good news
• Cardiovascular risk: our best skill set
and treating physician are now well
aware of the risk
• Hepatitis co-infection (Hep. B &C)
• IDU
• We CAN identify the best risks
49
Coronary heart disease risk in HIV
% increase in risk
HIV+ 1 HIV+ 2 HIV – (7)
Age - per year
Sex – M vs F
Diabetes – Yes vs No
Smoking – Yes vs No
Hypertension –Yes vs No
9%
N/A
260%
140%
30%
6%
6-9%
110% 110-160%
90% 140-252%
290% 70-290%
80% 80-90%
Tot Chol - per 1mmol/L
N/A
26%
25-33%
HDL chol. - per 1mmol/L
N/A
-28%
-52%
Source: Schambelan et al, Circulation 2008
50
The best
•
•
•
•
Age: older is better
Behavior: no drugs, how HIV acquired
Income: higher is better
HIV characteristics: CD4+ cell count and
viral load
• Treatment: timing, quality, response,
follow-up, adherence
• Documentation: available and plentiful
51
Unknowns and risk mitigation
strategies
• Full underwriting
• Shorter term or shorter term equivalent
coverage?
• Limit the face amount
• Reinsure
52
Potential Treatment Venues
•
•
•
•
•
•
•
•
Don’t get infected
Kill the virus
Prevent entry of the virus in the cell
Prevent normal virus intracellular processes
Prevent viability of cell produced virus
Kill infected active cells
Kill infected latent cells
Prevent CD4+ cell depletion
53
Kill the Virus
• Immune response boosters:
– cytokines,
– interferon,
– monoclonal antibodies,
– vaccine,
– gene therapy
54
Prevent Virus Entry
• Prevent entry of the virus
– Block access on T cell
• CD4
• CCR5
• CXCR4
– Block connectors from virus
– Block fusion
– Cleave connectors: abzyme
55
Prevent Normal Virus Process
Viral decay
accelerator
Innate
antiretroviral
factor
56
Prevent viability of cell
produced virus
• Maturation inhibitors
– Env targeted cytotoxin (Berger 6/10)
– Gag cleavage (Adamson, 8/09)
– CA-CA interaction (ibid.)
• Zinc finger inhibitors
57
Maybe one day
•
•
•
•
•
Kill infected active cells
Kill infected latent cells
Prevent CD4+ cell depletion
Gene therapy
Vaccine
58
Updates
• Better understanding of CD4 cell death
due to HIV infection of nearby cells and
drug blocking that death and an existing
drug blocking that effect (Doitsh, Nature 2013)
• In monkeys, gene therapy ups the
natural defenses against HIV (Gardner, Nature
2015)
59
Questions?
60