Politics and polypill

1. Politics and Polypills: Strategies for
Improving Global Cardiovascular Health
Mark Huffman, MD, MPH
Northwestern University Feinberg School of Medicine
16 November 2012
1

2. Outline
• Political economy of NCDs
• WHO “25 by 25”
• Polypills
• Kerala ACS Registry and ACS QUIK
2

3. POLITICAL ECONOMY
OF NCDs
3

4. Are NCDs neglected?
Fuster V, Voute J. Lancet 2005; 366:1512
Horton R. Lancet 2005; 366:1514

5. “Calls to action” published
in medical journals: 1966–2007
Ebrahim S. Int. J. Epidemiol. 2008;37:225-230

6. Potential reasons why NCDs
might be neglected
1. Apathy
NCDs are difficult/complex to tackle
Aren’t NCDs part of normal aging?
Myth that risk factors only account for 50% of deaths
2. Inadequate funding
Development aid for health (DAH) has risen from
$5.6B (1990) to $22B (2007), but how much for NCDs?
3. NCDs are invisible
“Scandal of ignorance” as described by Setel et al.
(lack of vital registration systems)
Stuckler D, et al. in Sick Societies. Eds. Stuckler and Siegel. Oxford, 2011.

7. Who’s “in charge” of NCDs?
World Health Organization
United Nations development agencies
International financial institutions (World Bank, IMF)
National development agencies
Ministries of health
Academic institutions
Private donors (for-profit and not-for-profit groups)
Stuckler D, et al. in Sick Societies. Eds. Stuckler and Siegel. Oxford, 2011.

8. Who’s “in charge” of NCDs?
World Health Organization
United Nations development agencies
International financial institutions (World Bank, IMF)
National development agencies
Ministries of health
Academic institutions
Private donors (for-profit and not-for-profit groups)
3 indicators to assess the power/influence of these institutions:
1) Where does the money come from? How much? Where does it go?
2) Who sits on the board and whose interests do they serve?
3) Who wins conflicts?
Stuckler D, et al. in Sick Societies. Eds. Stuckler and Siegel. Oxford, 2011.

9. Where does the money come from?
DAH commitments (2007): $22B
PRIVATE
MONEY
Ravishankar N, et al. Lancet 2009; 363:2113.

10. Where does the money come from?
DAH commitments (2007): $22B
…but only ~2/3 ($15B) can be accounted for
(and do not represent disbursements)
Ravishankar N, et al. Lancet 2009; 363:2113.

11. But little funding for NCDs ($ millions)
25000
20000
Chronic diseases
15000
Infectious diseases
10000 (HIV, TB, malaria)
Total health aid
5000
0
2001 2002 2003 2004 2005 2006 2007
11
Nugent R, Feigl A. Center for Global Development WP 228, 2011.

12. But little funding for NCDs ($ millions)
25000
20000
Chronic diseases
15000
Infectious diseases
10000 (HIV, TB, malaria)
Total health aid
5000
0
2001 2002 2003 2004 2005 2006 2007NCDs: $0.78/DALY
ID: $23.9/DALY
Total: $16.4/DALY
12
Nugent R, Feigl A. Center for Global Development WP 228, 2011.

13. Who are the NCD funders?
Funder Purpose 5 year total (2004-2008)
WHO (incl. PAHO) General NCDs $873M
Wellcome Trust General NCDs $458M
Bloomberg + Gates Tobacco, cervical cancer $250M
World Bank General NCDs $183M
Novo Nordisk Diabetes $58M
GE Foundation General NCDs $41M
NIH Tobacco, cancer, CVD $27M
InterAmerican Development Bank General NCDs $21M
International Diabetes Federation Diabetes $18M
Hilton Foundation Sense organ diseases $12M
Nugent R, Feigl A. Center for Global Development WP 228, 2011.

14. Who are the NCD funders?
Funder Purpose 5 year total (2004-2008)
WHO (incl. PAHO) General NCDs $873M
Wellcome Trust General NCDs $458M
Bloomberg + Gates Tobacco, cervical cancer $250M
World Bank General NCDs $183M
Novo Nordisk Diabetes $58M
GE Foundation General NCDs $41M
NIH Tobacco, cancer, CVD $27M
InterAmerican Development Bank General NCDs $21M
International Diabetes Federation Diabetes $18M
Hilton Foundation Sense organ diseases $12M
Nugent R, Feigl A. Center for Global Development WP 228, 2011.

15. Who are the NCD funders?
Funder Purpose 5 year total (2004-2008)
WHO (incl. PAHO) General NCDs $873M
Wellcome Trust General NCDs $458M
Bloomberg + Gates Tobacco, cervical cancer $250M
World Bank General NCDs $183M
Novo Nordisk Diabetes $58M
GE Foundation General NCDs $41M
NIH Tobacco, cancer, CVD $27M
InterAmerican Development Bank General NCDs $21M
International Diabetes Federation Diabetes $18M
Hilton Foundation Sense organ diseases $12M
Whose interests are being served? What ties to these organizations have to
food/beverage, agriculture, and pharmaceutical industries?
Nugent R, Feigl A. Center for Global Development WP 228, 2011.

16. MAPPER
16

17. BMGF Stock Portfolio
Holding Portfolio Rank $USD (B)
Berkshire Hathaway 1 $5.9B
McDonald’s 2 $0.6B
Coca-Cola 4 $0.5B
Waste Management 5 $0.5B
Walmart 7 $0.4B
Coca-Cola FEMSA 9 $0.4B
Costco 10 $0.3B
Monsanto >20 $0.02B
Total $11.9B
Stuckler D, et al. PLoS Med 2011; 8:e1001020.

18. BMGF Stock Portfolio
Holding Portfolio Rank $USD (B)
Berkshire Hathaway 1 $5.9B
McDonald’s 2 $0.6B
Coca-Cola 4 $0.5B
Waste Management 5 $0.5B
Walmart 7 $0.4B
Coca-Cola FEMSA 9 $0.4B
Costco 10 $0.3B
Monsanto >20 $0.02B
Total $11.9B
Stuckler D, et al. PLoS Med 2011; 8:e1001020.

19. WHO Budget, 2000-2013 projected
2007: ~12% of WHO budget directed to NCDs
Nugent R, Feigl A. Center for Global Development WP 228, 2011.

20. Where does the WHO get its money?
Nugent R, Feigl A. Center for Global Development WP 228, 2011.

21. Where does the WHO get its money?
Gates annual operating budget: $3.8B
Gates WHO contribution: $150M (14% of VC)
Nugent R, Feigl A. Center for Global Development WP 228, 2011.

22. Public/global health and politics
Research!America respondents GBD
Siegel KR, et al. Global Health Action 2011; 4:6339.

23. Public/global health and politics
5 types of political incentives:
1. Political: squeaky wheel
2. Economic: private companies seek to shift priorities
3. Organizational: sustaining (or growing) the status quo
4. Symbolic: MDGs
5. Scientific: technical arguments (weakest)
Political economy of NCDs will likely remain weak without
paying attention to these incentives
Stuckler D, et al. in Sick Societies. Eds. Stuckler and Siegel. Oxford, 2011.

24. WHO “25 BY 25”
24

25. 25
http://daccess-
ods.un.org/TMP/3950904.30974

26. 26
http://daccess-
ods.un.org/TMP/3950904.30974

27. 27
http://daccess-
ods.un.org/TMP/3950904.30974

28. 65th World Health Assembly:
May 26, 2012
28
who.int

29. WHO Draft Framework: Oct 31, 2012
Premature = <70 years
29
who.int

30. WHO Indicators/Targets Meeting:
Nov 5-7, 2012
119 Member States; 9 Voluntary Targets by 2025
25% reduction in mortality from CVD, cancer, DM, and chronic lung disease
10% reduction in harmful use of alcohol
10% reduction in insufficient physical activity
Halt the rise in diabetes and obesity
25% reduction in prevalence of raised blood pressure
30% reduction mean population sodium intake (<20000 mg sodium)
30% reduction in tobacco use
50% of eligible people receive drugs/counseling to prevent heart attacks, strokes
80% availability of affordable basic technologies and essential medicines, including
generics, required to treat major NCDs in both public and private facilitates
30
who.int

31. Questions about “25 by 25”
Buy-In
• Only 19 member states provided comments after posted to web, followed
by 22 member states when requested via email/web survey (?overlap) to
the initial set of targets, suggesting low buy-in.
Mechanisms for Monitoring
• Monitoring risk factors q5 years via WHO Steps
• Monitoring of policies: ?systematic review ; ?funding
• Reporting q5 year at the WHA and UN GA
Methodologic Factors
• Baseline mortality rates: unavailable for ~40% of WHO Member States
• Reference population standard has not been defined
(can influence comparisons)
• Younger countries with more premature deaths have more tougher climb
31
who.int

32. All “25 by 25” Targets Are Not Created Equal
NCD deaths under 70 25% reduction in
as % of all NCD deaths premature NCD deaths
(2008) (2025)
Country Male Female Male Female
Afghanistan 81 72.2 60.8 54.2
Brazil 52.3 42.2 39.2 31.7
China 43.9 32 32.9 24.0
India 61.8 55 46.4 41.3
Russian Federation 55 25.4 41.3 19.1
South Africa 69 53.7 51.8 40.3
United States of America 36.5 23.6 27.4 17.7
32
who.int

33. POLYPILLS
33
BMJ, 2003

34. POLYPILLS®
34
BMJ, 2003

35. Polypill® Possibilities and Problems?
35

36. Possibilities
80% reduction in CVD events (predicted)
Increased adherence
Less reliance on physicians
Lower cost
Problems
Primary vs. secondary prevention
Emphasis on pills > lifestyle > policies
Dose titration, side effects
Lower margins

37. Polypill®, or Fixed Dose Combination, Origins
Goals:
• 4 drugs in 1
(ASA, BB, ACE, statin)
• Improve adherence
• Lower cost
Richard Peto

38. Research Requirements for Polypill®
1) Stability testing
2) Bioavailability testing
3) Assessment of short-term effects on BP, LDL cholesterol,
and platelet aggregation
4) Assessment of safety and short-term symptomatic side
effects
5) Study of interactions and effects on combination of drugs
on physiologic mechanisms
6) Studies on adherence to treatment
Multiple polypills (at least 2 doses per drug) envisioned
WHO/Wellcome Trust were charged with partnering with
industry for testing, including cost-effectiveness via RCTs or
community demonstration projects (5-year timeline!)

39. Was 80% Risk
Reduction Realistic?
Reduction IHD event risk Stroke risk
Risk factor Agent in risk factor reduction (%) reduction (%)
LDL cholesterol Statin 70 mg/dl 61 (51 to 71) 17 (9 to 25)
3 classes of drug at 11 mmHg
Blood pressure 46 (39 to 53) 63 (55 to 70)
half standard dose (DBP)
Serum
Folic acid (0.8 mg/d) 3 μmol/L 16 (11 to 20) 24 (15 to 33)
homocysteine
Not
Platelet function Aspirin (75 mg/d) 32 (23 to 40) 16 (7 to 25)
quantified
Combined effect All 88 (84 to 90) 80 (71 to 87)
Wald and Law. BMJ, 2003.

40. Stability Testing and Costs:
Unanticipated Hurdles
theheart.org

41. The Indian Polycap Study (TIPS)
2,053 patients with 1 major risk factor included; 12 week trial in India (2007-2008)
Polycap: ASA 100 mg, simvastatin 20 mg, atenolol 50 mg, ramipril 5 mg, HCTZ 12.5 mg
Manufactured by Cadila Pharmaceuticals, Ltd.
Yusuf S, et al. Lancet, 2009;373:1341.

42. Polycap’s Short-Term Effects
Blood pressure= 5.7 mmHg fall Platelet aggregation
LDL = 31 mg/dl fall
Projected Risk Reduction
IHD Stroke
Wald/Law 88% 80%
Polycap 62% 48%
Yusuf S, et al. Lancet, 2009;373:1341.

43. Adherence to Polycap at 12 Weeks
Overall Polycap
N=2,053 N=412
Drugs permanently stopped 303 (14.8%) 66 (16.0%)
Drug-specific reasons 77 (3.8%) 14 (3.4%)
Cough 9 (0.4%) 1 (0.2%)
Dizziness/hypotension 46 (2.2%) 10 (2.4%)
Gastritis/dyspepsia 15 (0.7%) 1 (0.2%)
Hyperkalemia 3 (0.1%) 1 (0.2%)
Bradycardia 4 (0.2%) 1 (0.2%)
Other reasons 69 (3.4%) 20 (4.9%)
Social reasons/refused treatment 201 (9.8%) 40 (9.7%)
Yusuf S, et al. Lancet, 2009;373:1341.

44. Low Secondary Prevention Rx Rate: PURE
CHD Stroke
153,996 participants across 628 urban/rural communities in 17 countries (2003-
2009)
Yusuf S, et al. Lancet, 2011; 378:1231.

45. Polypill: But For Whom?
45
theheart.org

46. (Potential) Limitations of Polypill
“How will I be able to evaluate my patients’ side effects
of the individual medications?”
• Possibly overstated given distinctions across drugs
-Bleeding vs. mylagias vs. orthostasis vs. cough
“I need to titrate the doses of my patients’ drugs.”
• Limited role dose escalation/de-escalation for most patients
-Low dose aspirin and high-dose statin preferred for 2o prev.
• Likely does not require cardiologist, nor even physician
“What about clopidogrel for my post-MI patients?”

47. Estimated Costs
of 5 Priority Interventions
Cost per person
Interventions per year
China India Russia
Tobacco FCTC 0.14 0.16 0.49
Mass-media, voluntary action
Dietary salt 0.05 0.06 0.16
by food industry
Mass-media, food taxes,
Obesity, unhealthy diet
subsidies, labeling and 0.43 0.35 1.18
and physical inactivity
marketing restriction
Tax, advertising bans,
Harmful alcohol intake 0.07 0.05 0.52
restricted access
Cardiovascular risk Combination of drugs,
1.02 0.9 1.73
reduction polypharmacy
Total cost per person 1.72 1.52 4.08
Beaglehole R, et al. Lancet 2011; 377:1438.

48. Cost-effectiveness of Polypill
for CVD in India (per 1M/10yrs)
> 35% > 25% > 15%
Costs and Effects No Polypill Risk Risk Risk
Total cost (millions) $23.5 $34.5 $51.4 $92.2
MI averted -- 10,200 14,400 21,300
Deaths from CHD
averted -- 10,500 13,500 19,600
Cost per DALY
averted
-- $300 $990 $1,500
Note: Each strategy is compared with no polypill.
Disease Control Priorities in Developing Countries, 2nd edition, 2006, Table 45.6

49. Polypill 2o Prevention Trials
Sample Primary
Title Manufacturer Sponsor Size Outcome
UMPIRE Dr. Reddy’s Lab European Comm. 2,000 Adherence
IMPACT Dr. Reddy’s Lab Health Research 600 Adherence
Council (NZ)
Kayini GAP Dr. Reddy’s Lab National Health and 1,000 Adherence
Research Council
(Australia)
SPACE Dr. Reddy’s Lab Hospital do 2,000 Adherence
Coracao
FOCUS* Ferrer CINI/Ferrer 4,000 Adherence
TIPS-K* Cadila Cadila 500 Adherence
*Only two “true” 2o prevention trials; others include high CV risk (>15% over 5 years)
49
Prabhakaran D, et al. Clin Invest 2012; in press.

50. UMPIRE 1o Results
Fixed-dose
combination Usual care Treatment effect
Outcome (n=1002) (n=1002) (95% CI)
1.33
Adherence (%) 86 65
(1.26 to 1.41)
Systolic blood -2.6
129.2 131.7
pressure (mm Hg) (-4.0 to -1.1)
LDL cholesterol, -0.11
2.18 (84.3) 2.29 (88.5)
mmol/L (mg/dL) (-0.17 to -0.05)
"If we could address the shortfall in adherence, we would
do more [for CVD prevention] than generating another
blockbuster drug for a single risk factor.”
-Simon Thom, November 6, 2012
50
theheart.org

51. September December January March April
8-month timeline of events
51

52. Kerala ACS Registry/ACS QUIK
52

53. Kerala ACS Registry
25,748 ACS Admissions
2007-2009
Mohanan P, et al. Eur Heart J 2012; Sept 7 [Epub ahead of print]

54. Kerala ACS Registry:
Baseline Characteristics
STEMI Non-STEMI Unstable Angina
N (%) 9,5969 (37) 7,857 (31) 8,322 (32)
Demographics
Male, N (%) 7,400 (77.3) 5,932 (75.5) 6,591 (79.2)
Age, years (SD) 60.4 (12.1) 60.5 (11.9) 60.5 (12.1)
No education, N (%) 1,187 (22.5) 1,015 (25.9) 579 (11.8)
Key risk factors
History of diabetes, N (%) 3,314 (34.6) 2,981 (37.9) 3,388 (40.7)
History of hypertension, N (%) 5,315 (55.5) 3,788 (48.2) 3,365 (40.4)
History of smoking, N (%) 3,376 (35.3) 2,980 (37.9) 2,511 (30.2)
History of MI, N (%) 1,257 (13.1) 1,212 (15.4) 1,186 (14.3)
History of stroke, N (%) 212 (2.2) 170 (2.2) 264 (3.2)
History of PCI/CABG, N (%) 8 (0.1) 10 (0.1) 55 (0.7)
54
Mohanan P, et al. Eur Heart J 2012; Sept 7 [Epub ahead of print]

55. Kerala ACS Registry:
Baseline Characteristics
STEMI Non-STEMI Unstable Angina
N (%) 9,5969 (37) 7,857 (31) 8,322 (32)
Clinical features on presentation
Symptom to presentation >6 hrs, N
3,915 (41.2) 2,809 (36.1) 3,213 (39.0)
(%)
Door-to-needle <30 min, N (%) 5,209 (68.3) -- --
Heart rate, mean (SD) 79.5 (19.9) 80.4 (20.0) 80.5 (18.5)
SBP (mmHg), mean (SD) 138.9 (30.0) 141.3 (29.2) 142.7 (30.7)
Body mass index (kg/m2) 23.1 (3.6) 23.2 (3.6) 23.0 (3.6)
Killip class > 1, N (%) 1,048 (20.8) 828 (19.1) 1,120 (25.5)
Fasting blood glucose, mg/dl (IQR) 115 (94, 156) 112 (91, 152) 116 (93, 158)
55
Mohanan P, et al. Eur Heart J 2012; Sept 7 [Epub ahead of print]

56. In-hospital Diagnostics/Treatments
STEMI
Non-STEMI
100 Unstable Angina
80
% 60
40
20
0
56
Mohanan P, et al. Eur Heart J 2012; Sept 7 [Epub ahead of print]

57. In-hospital Event Rates
(p<0.01 for all)
12
Total
10 STEMI
8 Non-STEMI
Unstable Angina
%6
4
2
0
Death (%) Reinfarction (%) Stroke (%) ardiogenic shock (%)
Death, reinfarction, stroke, heart failure, or
C
57
Mohanan P, et al. Eur Heart J 2012; Sept 7 [Epub ahead of print]

58. Evaluation of Patient Characteristics
and In-Hospital Outcomes
In-hospital death In-hospital MACE
OR (95% CI) OR (95% CI)
Adjusted for age, sex, socioeconomic position (education), modified GRACE risk score
variables**, and within-hospital clustering (random effects model)
2.65 2.24
STEMI vs. unstable angina (ref)
(1.49, 4.69) (1.43, 3.52)
0.94 1.10
NSTEMI vs. unstable angina (ref)
(0.50, 1.78) (0.67, 1.81)
2.31 1.94
Symptom to door >6 hrs vs. <6 hrs (ref)
(1.75, 3.05) (1.55, 2.44)
1.81 1.75
Door-to-needle >30 min vs. <30min (ref)
(1.38, 2.38) (1.38, 2.21)
1.78 2.69
Inappropriate thrombolysis*
(1.08, 29.2) (1.88, 3.87)
*Non-STEMI and unstable angina only
**GRACE risk score variables include: age, heart rate, systolic blood pressure, serum creatinine, Killip class,
58
cardiac enzyme, and ST segment deviation. Cardiac arrest at presentation excluded (not available).

59. NEWS FLASH!
Optimal Care is Better than Non-Optimal Care
Non optimal in- Optimal in-
hospital hospital
medical therapy medical Adjusted OR*
(ref) therapy (95%CI)
*Adjusted for modified GRACE risk score variables: age, HR, SBP, SCr, Killip class, cardiac enzyme, and ST
segment deviation and within-hospital clustering. Cardiac arrest at presentation excluded (N/A).
N (%) N=15,411 (60) N=10,307 (40)
0.93
Death 632 (4.1) 366 (3.6)
(0.71, 1.22)
Death, reinfarction, 0.79
938 (6.1) 532 (5.2)
stroke, HF, or shock (0.63, 0.99)
Prabhakaran D, et al. AHA 2012 Scientific Sessions.

60. Optimal in-hospital Optimal discharge
medical therapy medical therapy
OR (95% CI) OR (95% CI)
Adjusted for modified GRACE risk score variables: age, HR, SBP, SCr, Killip class, cardiac enzyme (positive vs. negative), and ST
segment deviation and within-hospital clustering. Cardiac arrest at presentation excluded (N/A).
1.00 1.00
Age
(1.00, 1.01 (0.99, 1.00)
1.00 1.00
Women vs. men (ref)
(0.90, 1.12) (0.89, 1.13)
1.01 1.00
Heart rate (per bpm)
(1.00, 1.01) (1.00, 1.00)
1.00 1.00
Systolic blood pressure (per mmHg)
(1.00, 1.00) (1.00, 1.00)
0.56 0.67
Killip >1 vs. 1 (ref)
(0.50, 0.63) (0.59, 0.75)
1.17 1.71
NSTEMI vs. unstable angina (ref)
(0.95, 1.45) (1.35, 2.16)
0.51 1.39
STEMI vs. unstable angina (ref)
(0.42, 0.62) (1.15, 1.68)
2.14 0.74
Enzyme positive vs. negative (ref)
(1.75, 2.62) (0.60, 0.90)
1.03 0.97
Creatinine (per mg/dl)
(0.97, 1.10) (0.90, 1.04)
Optimal in-hospital medical therapy vs. 10.48
60 --
non optimal (ref) (9.37, 11.72)

61. ACS Quality Improvement in Kerala
(ACS QUIK): 2012-2017
• Cluster-randomized, stepped wedge clinical trial
• Aim to develop, implement, and evaluate quality
improvement toolkit on 30 day MACE (9.3%7.3%)
• Focus group discussions (Nov 2012) with help from Drs.
David Victorson and Shifalika Goenka to build toolkits
• Audit/feedback, standardized clinical pathways,
checklists (likely including Polycap or other avail. FDC)
• 2o outcomes: process of care, hrQOL, microeconomic
impact
61

62. Take Home Points
Politics
Evidence is necessary but insufficient for political change;
private forces dominate NCD landscape of weak political econ.
WHO 25 by 25
“Premature” focus on individuals <70 years; questions on buy-
in, monitoring, and methodology
Polypills®
More difficult/expensive than anticipated; 33% increased
adherence; 50-60% risk reduction; not just for LMICs
ACS QUIK
Hospital-based QI may be future source of frugal innovations

63. Politics and Polypills®: Strategies for
Improving Global Cardiovascular Health
Mark Huffman, MD, MPH
Northwestern University Feinberg School of Medicine
16 November 2012
63

64. Fixed dose combination therapy in HTN
64
Bangalore S, Am J Med 2007; 120:713.