HIV, TB and ART: the CD4 enigma

Brian Williams

Treatment as Prevention in Africa 1 May 2014, Gaborone, Botswana

Williams (2012) http://arxiv.org/pdf/1211.2798v2.pdf

HIV drives TB Nunn et al. Nature Reviews of Immunology. 2005; 5: 819-26

Delay ~ 5 years

IRR ~ 15

Kisumu, Kenya

9.4

1.11.11.0

5.9

2.2

0

2

4

6

8

10

1991-1994 1995-1997 1998-1999

Ann

ual i

ncid

ence

(%)

. HIV- HIV+

TB incidence among gold miners in SACorbett et al. J Infect Dis. 2003;188: 1156-63.

HIV- HIV+

1.02.2

1.1

5.9

1.1

9.4

1991-1994 1995-1997 1998-1999TB in South African Gold Miners

10

8

6

4

2

0

Inci

denc

e (%

p.a

.)9.4

1.11.11.0

5.9

2.2

0

2

4

6

8

10

1991-1994 1995-1997 1998-1999

Ann

ual i

ncid

ence

(%)

. HIV- HIV+

TB incidence among gold miners in SACorbett et al. J Infect Dis. 2003;188: 1156-63.

HIV- HIV+

1.02.2

1.1

5.9

1.1

9.4

1991-1994 1995-1997 1998-1999TB in South African Gold Miners

10

8

6

4

2

0

Inci

denc

e (%

p.a

.) IRR ~ 10

IRR ~ 2 No change

But not in HIV-negative people

Gold Miners in South Africa

Corbett et al. Journal of Infectious Diseases 2003; 188: 1156-63

0

100

200

300

400

500

600

700

1980 1985 1990 1995 2000 2005 2010

TB

inci

denc

e/10

0k/y

rTB

inci

denc

e/10

0k/y

r

0

100

200

300

400

500

600

700

1980 1985 1990 1995 2000 2005 2010

TB

inci

denc

e/10

0k/y

rTB

inci

denc

e/10

0k/y

r

0.00

0.05

0.10

0.15

0.20

0.25

0.30

1980 1985 1990 1995 2000 2005 2010

HIV

pre

vale

nce

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

1980 1985 1990 1995 2000 2005 2010

HIV

pre

vale

nce

0

100

200

300

400

500

1980 1985 1990 1995 2000 2005 2010

TB in

cide

nce/

100k

/yr

IRR ~ 34 IRR ~ 7.4

11x 2.7x

Zimbabwe Botswana

Williams et al. Proc Nat Acad Sc USA. 2010; 107: 17853-4.

Tube

rcul

osis

H

IV

Impact depends on the setting

The only two things that are known to be predictive of TB are CD4 cell counts in

HIV-positive people and BMI.

Lonnroth et al. Int J Epidemiol. 2010; 39: 149-55.

If CD4 falls by 100 cells/mL TB increases by 36% (19%−42%)

CD4 cells/mL

Ann

ual i

ncid

ence

of T

B

Antonucci et al. JAMA. 1995; 274: 143-8; Badri et al. Lancet. 2002; 359: 2059-64.

I µ e - 0.0036 C

1500

1000

500

0

Ethio

pia

Guine

aBi

ssau

Nige

riaS.

Afric

aTa

nzan

ia

Ugan

da

Zamb

ia

Ugan

da

CD4/µL

Williams et al. J Inf. Dis. 2006; 194: 1450-8; Bussman et al. Clin. and Diag. Lab. Immunology 2004

1,200

600

1,276

233

Mean (95%) Range (95%)

CD4 highly variable in HIV-negative people

Botsw

ana

0

200

400

600

800

1000

0 1 2 3 4 5 6 7

Time spent on ART/years

Incr

ease

in C

D4

cell

coun

t But not when you recover under ART

Gras et al. J Acquir Immune Defic Syndr. 2007; 45: 183-92.

So putting all of this together: What can modelling tell us?

Williams et al. PNAS 2005; 102: 9619-24.

Fit the trend in HIV prevalence

HIV in Botswana

Putting lots of people on ART

HIV in Botswana

Leaving fewer people not on ART

HIV in Botswana

Reduces infectiousness and hence incidence

HIV in Botswana

But has a much greater impact on mortality

HIV in Botswana

TB in Botswana

HIV-negative

On ART Off ART

Total

What do we know?

• HIV drives TB with a delay of about 5 years and an IRR of ~ 5 to 40. • TB in HIV+ people does not increase TB in HIV- people • ART reduces the risk of TB by about 60% at all CD4 cell counts.

What do we think we understand?

• The short disease duration in HIV-positive people limits the impact on TB in HIV-negative people.

• CD4 may be the key link between HIV and TB. • CD4 recovery is independent of when we start ART; the increase

due to ART is independent of starting CD4. • ART restores some, but not all, CD4 function reducing AIDS-

related TB by about 60%

What do we still not understand? •  If CD4 is so variable why is it so important? • Why is HIV-survival independent of the initial CD4 cell count? •  If CD4 cell counts determine the risk of TB in HIV-positive people is

it also true for HIV-negative people? • Since CD4 is so variable on the way down; why is it so predictable

on the way up? • Why is the incidence rate ratio for TB with and without HIV in

Zimbabwe five times that in Botswana?

What do we (tentatively) conclude?

• ART will reduce HIV-TB by up to 60% in the short term. • To eliminate HIV-related TB we must eliminate HIV.

The classic tuberculous granuloma, found in active disease and latent infection

Barry et al. Nat Rev Microbiol. 2009; 7: 845-55.

During the acute phase of HIV: CD4 cell counts drop by 25% (9%--41%)1

TB incidence rises 3.8 (1.6--15.2) times.2

1. Williams et al. J Infect Dis. 2006; 194: 1450-8; Williams et al. Proc Nat Acad Sc USA. 2010; 107: 17853-4; 2. Antonucci et al. JAMA. 1995; 274: 143-8; Badri et al. Lancet. 2002; 359: 2059-64.

Explains the early impact on gold mines

CD4 recovery is independent of when you start… In

crea

se in

CD

4 ce

ll co

unt

0

100

200

300

400

0 1 2 3 4 5 6 7

Rate of increase = 224 (192--261)/mL/yr

Asymptote = 371 (355 389)/mL

Time spent on ART/years

CD4 cells/mL

Ann

ual T

B in

cide

nce

…but (TB) recovery is never complete

HIV-

Gupta et al. PLoS One 2012; 7: e34156.

4x

0

100

200

300

400

500

600

700

1980 1985 1990 1995 2000 2005 2010

TB

inci

denc

e/10

0k/y

rTB

inci

denc

e/10

0k/y

r

0

100

200

300

400

500

1980 1985 1990 1995 2000 2005 2010

TB in

cide

nce/

100k

/yr

IRR ~ 34 IRR ~ 7.4

Zimbabwe Botswana

Williams et al. Proc Nat Acad Sc USA. 2010; 107: 17853-4.

Tube

rcul

osis

Impact depends on the setting

0

200

400

600

800

0 2 4 6 8 10 120

200

400

600

800

0 2 4 6 8 10 12

CD

4/m

L

CD

4

CD

4/m

L

High CD4: Low TB Fast decline: big increase

Low CD4: High TB Slow decline: small increase

TB in HIV positive people does not affect HIV-negative people

Prevalence = Incidence x Duration

HIV-positive people with TB progress about 15 times faster

than HIV negative people.

Corbett et al. Am J Respir Crit Care Med. 2004; 170: 673-9; Wood et al. Am J Respir Crit Care Med. 2007; 175: 87-93; Williams et al. Am J Respir Crit Care Med. 2007; 175: 6-8.

Time to death (years)

CD

4 ce

ll co

unts

ART drives CD4 back up

Falling epidemic

Rising epidemic

Probability density

Modelling CD4 progression

Williams JID 2006; CASCADE Lancet. 2000; Gras JID 2007

1

10

100

1000

15 20 25 30 35BMI (kg/m2)

TB in

cide

nce/

100k

/yea

r

Navy recruits, (USA, 2); Male smokers (Finland); Mass radiography (Norway); Pensioners (Hong Kong); NHANES (USA).

Lonnroth et al. Int J Epidemiol. 2010; 39: 149-55.

p = 10-51 13.8% (13.4%14.2%)/BMI unit

0

50

100

150

200

250

-50 0 50 100 150 200 250Change in CD4 cell counts/µl/yr

Rel

ativ

e fre

quen

cy .

Williams et al. arXiv 2009 http://arxiv.org/abs/0908.1556 Rodriguez et al. JAMA 2006; 296: 1498-506.

Predicted distribution of the rate of change of CD4 cell counts over time

“First do no harm”

Data: Hargrove AIDS 2010; Model: Williams JID 2006.

0.001

0.010

0.100

1.0000 500 1000 1500 2000

CD4+ cell count M

orta

lity

at o

ne y

ear

HIV-positive

HIV+ and HIV- post-partum women in Harare (1997-2000)

2.5x 3.9x 100x

HIV-negative

0.00

0.05

0.10

0.15

0.20

0 500 1000 1500

0.00

0.05

0.10

0.15

0.20

0 500 1000 1500 2000

Predicted distribution of the distribution of CD4 cell counts in HIV-positive people given the distribution

in HIV-negative people in South Africa Williams et al. J Infect Dis. 2006; 194: 1450-8.

ART treatment according to various guidelines

Per

cent

nee

ding

trea

tmen

t Young men, Orange Farm, 2002

Williams et al. arXiv 2012; http://arxiv.org/abs/1208.3434

IAS/DHHS WHO

Countries 20 5

40

3

3

1

Year Organiz. CD4/mL Viral load/mL Countries 1996 IAS 500 30k 1997 IAS 500 5k 2000 IAS 350 5k 2002 IAS 200 50k 2002 WHO 200 2003 WHO 200 2007 WHO 200 2009 WHO 350 2010 IAS 500 100k 2012 Practice Immediate 1

500 3 350-500 3 350 40 200-350 5 250 5 200 15