Presentation is loading. Please wait.

Presentation is loading. Please wait.

CHOLHUA , March 2015 Jean-Marc Fix, FSA, MAAA, VP, R&D

Similar presentations


Presentation on theme: "CHOLHUA , March 2015 Jean-Marc Fix, FSA, MAAA, VP, R&D"— Presentation transcript:

1 CHOLHUA , March 2015 Jean-Marc Fix, FSA, MAAA, VP, R&D
HIV? CHOLHUA , March 2015 Jean-Marc Fix, FSA, MAAA, VP, R&D

2 Why not? The End

3 Is a segment of the HIV-infected population insurable?
CHOLHUA , March 2015 Jean-Marc Fix, FSA, MAAA, VP, R&D

4 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

5 Face of a killer

6 Face of a killer

7 Face of a killer

8 Face of a killer

9 Face of a killer

10 A Close-up

11 Video- Infection https://www.youtube.com/watch?v=RO8MP3wMvqg 4’08”

12 Infectious pathway Men having sex with men Heterosexual
Intravenous drug user Blood product (transfusion, hemophilia) Occupational

13 Infectious pathway -Men
Source: HIV AIDS Surveillance vol 19 CDC

14 Infectious pathway -Women
Source: HIV AIDS Surveillance vol 19 CDC

15 Source: Gill et al, Clin Infect Dis 2010
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

16 Together in Life and Death
What we remember 1985 AIDS Is Top Cause of Death for Young Adults in U.S. Disturbing report by federal agency San Francisco Chronicle 2/1/95 Together in Life and Death 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 2001 1992 Hunting for the Hidden Killers: AIDS Time Magazine 7/4/83

17 Total: 33,4 millones (31,1 – 35,8 millones)
Número estimado de adultos y niños que vivían con el VIH en 2008 Europa oriental y Asia central 1,5 millones [1,4 – 1,7 millones] Europa occidental y central [ – ] América del Norte 1,4 millones [1,2 – 1,6 millones] Asia oriental [ – 1,0 millones] África del Norte y Oriente Medio [ – ] Caribe [ – ] Asia meridional y sudoriental 3,8 millones [3,4 – 4,3 millones] África subsahariana 22,4 millones [20,8 – 24,1 millones] América Latina 2,0 millones [1,8 – 2,2 millones] Oceanía 59 000 [ – ] Total: 33,4 millones (31,1 – 35,8 millones)

18 HIV mortality

19 HIV deaths

20 What we should be hearing
Managing HIV as a Chronic Disease South Afr j of HIV Med 2004 When AIDS became a chronic disease West J Med 2000 HIV: Now a Manageable Chronic Disease Pharmacy Times 2007 Comprehensive Clinical Care: Managing HIV as a Chronic Illness AIDS Clinical Care Journalwatch retrieved July 2010

21 HIV mortality

22 Trends in Annual Age-Adjusted
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

23 Source: Pallella et al, J Acq Immune Def Syndr 2006
Advances in treatment Source: Pallella et al, J Acq Immune Def Syndr 2006

24 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

25 Video-Treatment https://www.youtube.com/watch?v=RO8MP3wMvqg 4’09”

26 Advances in treatment

27 Action path of treatment

28 Action path of treatment

29 (1): Marsden and Zack J Antimicrob Chemo 2009
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

30 Variables for mortality
Age Gender Smoking Income CD4+ cell count Viral load Time since infection Response to treatment Quality of follow-up Infection source

31 Source: Pallella et al NEJM 1998
Mortality by therapy When: 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

32 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

33 Source: Bashkaran et al, JAMA 2008
Mortality evolution When: 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

34 Source: Bashkaran et al, JAMA 2008
Mortality evolution Deaths Pre 1996 Expected 56 28 33 39 41 37 Observed 1332 481 231 212 188 127 Obs/Exp 24 17 7.0 5.5 4.6 3.4 Source: Bashkaran et al, JAMA 2008

35 Source: Bashkaran et al, JAMA 2008
Mortality evolution Source: Bashkaran et al, JAMA 2008

36 Source: Bashkaran et al, JAMA 2008
Mortality evolution Source: Bashkaran et al, JAMA 2008

37 Source: adapted from Table 4, Bashkaran et al, JAMA 2008
Mortality by age Ratio observed to expected mortality by age, 15 year after seroconversion Age at seroconversion 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

38 Source: Lewden et al, J Acq Immune Def Syndr 2007
Mortality by segment 7 year post cART France, first treated with PI 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

39 Source: Lewden et al, J Acq Immune Def Syndr 2007
Mortality by segment CD4+ count cells/mm3 SMR 500+ 2.5 3.5 5.6 <200 30.3 Source: Lewden et al, J Acq Immune Def Syndr 2007

40 Source: Lewden et al, J Acq Immune Def Syndr 2007
Mortality by segment Source: Lewden et al, J Acq Immune Def Syndr 2007

41 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

42 Source: Braithwaite et al, Am J of Med 2005
Modeling flowchart Source: Braithwaite et al, Am J of Med 2005

43 Source: from Braithwaite et al, Am J of Med 2005
Mortality Age 30 Age CD4+ (cells/mm^3) Viral load /ml Median survival Mort Mult (men) 30 800 10,000 31.30 400% 100,000 23.70 x 1,000,000 17.20 500 26.80 21.20 14.60 200 21.90 18.10 12.20 Source: from Braithwaite et al, Am J of Med 2005

44 Source: from Braithwaite et al, Am J of Med 2005
Mortality Age 40 Age CD4+ (cells/mm^3) Viral load /ml Median survival Mort Mult (men) 40 800 10,000 28.00 250% 100,000 22.60 425% 1,000,000 15.20 x 500 24.40 350% 18.90 14.00 200 19.70 15.50 10.90 Source: from Braithwaite et al, Am J of Med 2005

45 Source: from Braithwaite et al, Am J of Med 2005
Mortality Age 50 Age CD4+ (cells/mm^3) Viral load /ml Median survival Mort Mult (men) 50 800 10,000 22.30 200% 100,000 20.30 250% 1,000,000 14.30 x 500 21.10 225% 17.70 325% 12.90 200 16.50 375% 14.60 500% 10.20 Source: from Braithwaite et al, Am J of Med 2005

46 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

47 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

48 Data limitations- the bad news
Atherosclerotic cardiovascular conditions take a long time to manifest themselves

49 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

50 Coronary heart disease risk in HIV
% increase in risk HIV+ 1 HIV+ 2 HIV – (7) Age - per year 9% 6% 6-9% Sex – M vs F N/A 110% % Diabetes – Yes vs No 260% 90% % Smoking – Yes vs No 140% 290% 70-290% Hypertension –Yes vs No 30% 80% 80-90% Tot Chol - per 1mmol/L 26% 25-33% HDL chol. - per 1mmol/L -28% -52% Source: Schambelan et al, Circulation 2008

51 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

52 Unknowns and risk mitigation strategies
Full underwriting Shorter term or shorter term equivalent coverage? Limit the face amount Reinsure

53 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

54 Kill the Virus Immune response boosters: cytokines, interferon,
monoclonal antibodies, vaccine, gene therapy

55 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

56 Prevent Normal Virus Process
Viral decay accelerator Innate antiretroviral factor

57 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

58 Maybe one day Kill infected active cells Kill infected latent cells
Prevent CD4+ cell depletion Gene therapy Vaccine

59 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)

60 Questions?


Download ppt "CHOLHUA , March 2015 Jean-Marc Fix, FSA, MAAA, VP, R&D"

Similar presentations


Ads by Google