Clinical Care: 2010

Institute of Medicine Committee on HIV Screening and Access to Care

Michael Saag, MD, FIDSAUniversity of Alabama, BirminghamDirector, Center for AIDS Research

Chair, HIV Medicine Association (HIVMA)

Survival Data – Years After AIDS Diagnosis

MMWR Weekly June 2, 2006 / 55(21);589-592

How Did We Get Here?

Sequential exposure to effective “monotherapy” in a population of largely adherent, aggressively treated patients created a cohort of individuals with highly-resistant HIV

1996 1997 1998 19992000

ZDV NVP 3TC EFV LPV

ddI SQV RTV ABC TDF

d4T IDV NFV

New HAART Era

After years of sequential “monotherapy” many patients with MDR are now entering a period where more than one new medication may be readily available

2004 2005 2006 2007 2008 2009

T20 TPV DRV Maraviroc, Raltegravir Etravirine

Improved Life Expectancy with Modern ARV Therapy

Hogg, et al. Lancet, 2008

Updated from Chen, et al, 8th CROI, 2001

8 Year Survival in HAART Era8 Year Survival in HAART Era

CD4 Count at HAART InitiationCD4 Count at HAART Initiation

Median Median CD4CD4

% CD4 % CD4 < 200< 200

19961996 115 62.8%

19971997 180 53.8%

19981998 221 47.8%

19991999 212 49.3%

20002000 197 50.1%

20012001 277 39.5%

20022002 210 48.8%

20032003 220 47.2%

20042004 207 49.1%

Median Median CD4CD4

% CD4 % CD4 < 200< 200

20052005 278 39.6%

20062006 300 35.4%

20072007 296 35.2%

20082008 310 29.4%

Key Point:

Many (? Most) HIV infected patients in the US don’t know they are infected

• Universal, opt-out testing is needed

Slide 9

When To Start Treatment? – Summary of Current Guidelines

Guidelines symptoms or

CD4 <200

CD4 200-350

CD4 >350

IAS-USA:JAMA 2008

<www.iasusa.org>

treat treat Therapy should be considered and decision individualized

DHHS:<www.aidsinfo.

nih.gov>

treat treat treat*

* Split opinion > 500

symptoms

Slide 10

Cohort Study Results (NA-ACCORD / ART-CC)

Consequences of unchecked viral replication (Inflammation / Harm)

Improved tolerability / convenience of newer ARV regimens

Treatment reduces transmission of HIV Cost Savings

Reasons for Earlier Initiation of Therapy

Slide 11Inverse Probability Weighted Cox Regression Multivariate Analysis

*Stratified by Cohort and Year

Relative Hazard (RH)*

95% Confidence

IntervalP-value

Deferral of HAART at 351-500 1.7 1.4, 2.1 <0.001

Female Sex 1.1 0.9, 1.5 0.290

Older Age (per 10 years) 1.6 1.5, 1.8 <0.001

Baseline CD4 count (per 100 cells/mm3) 0.9 0.7, 1.0 0.083

• Results were similar when restricting the analysis to the 77% of participants with baseline HIV RNA data• Adjusted RH for deferral vs. immediate treatment was also 1.7 95% C.I. 1.4, 2.2; p <0.0001• HIV RNA was not an independent predictor of mortality

Slide 12

Relative Time on Treatment…

30 35 40 45 50 55 60 65 70AGE (years)

CD4 650/ul

CD4 500/ul

40 years on Rx

35 years on Rx

5 years

Slide 13

Relative Time on Treatment…

30 35 40 45 50 55 60 65 70AGE (years)

CD4 650/ul

CD4 500/ul

40 years on Rx

35 years on Rx

5 years

HARM?

Slide 14

Most New Infections Transmitted by Persons who Do Not Know Their Status

~25% Unaware

of Infection

~75% Aware

of Infection

account for…

~54% New

Infections

~46% of New

Infections

Source: G. Marks et al. AIDS 2006

Slide 15

0

5

10

15

20

25

30

Viral load (HIV-1 RNA copies/mL) and HIV transmission

Tra

nsm

issi

on

rat

e p

er 1

00 P

erso

n-Y

ears

<40

0

400

-349

9

350

0-99

99

10 0

00-4

9 99

9

>50

000

Quinn TC, et al. NEJM 2000; also Fideli U, et al. AIDS Res Hum Retrovir 2001

<40

0

400

-349

9

350

0-99

99

10 0

00-4

9 99

9

>50

000

<40

0

400

-349

9

350

0-99

99

10 0

00-4

9 99

9

>50

000

All subjectsMale-to-FemaleTransmission

Female-to-MaleTransmission

TNT: Based on the association of viral load and HIV transmission risk

Slide 16

Prevention of Transmission

TEST and TREAT – Testing and Linkage to Care (TLC+)

National AIDS Strategy…

ARV Receipt

Retention in Care

Outcomes

HIV DxLinkage to Care

ARV Adherence

Adapted from: Giordano et al. Curr HIV/AIDS Rep 2005;2:177-183, Samet et al. AIDS 2001;15:77-85, Eldred & Malitz. AIDS Pt Care STDs 2007;21:S1-2; Tobias et al. AIDS Pt Care STDs 2007;21:S3-8

Blueprint for HIV Treatment Blueprint for HIV Treatment SuccessSuccess

Adherence research has traditionally focused on ARV medications

Growing interest in expanding HIV adherence to include linkage & retention in care

ARV Receipt

Retention in Care

Outcomes

HIV DxLinkage to Care

ARV Adherence

Expanding the spectrum of Expanding the spectrum of adherenceadherence

25% of HIV-infected individuals in the U.S.

are undiagnosed

20-40% of newly diagnosed pts. fail to

establish care w/in 6 mos.

One-third of pts. w/ known HIV infection are not

engaged in care

Glynn & Rhodes. National HIV Prevention Conference 2005, Abstract 595, Gardner et al. AIDS 2005;19:423-431, Mugavero et al. Clin Infect Dis 2007;45:127-130, Fleming et al. 9th CROI 2002, abstract 11

Mean Annual Total Patient Costs by CD4 Count (cells/ul)

Mean Annual Total Patient Costs by Component

CD4 strata (cells/L)

Total ARV Non-ARV

Hospital Other Outpt.

Physician/clinic

< 50 $36,532 $10,885 $14,882 $8,353 $1,909 $533

50-199 $23,864 $11,862 $6,685 $3,369 $1,416 $532

200-349 $18,274 $11,935 $3,452 $1,186 $1,365 $336

> 350 $13,885 $9,407 $1,855 $1,408 $930 $285

All $18,640 $10,500 $4,240 $2,342 $1,199 $359

Patients with CD4 counts < 50 expend 2.6 times more health care dollars than those with CD4 counts > 350

(P<0.001)

Overall expenditures

Change in clinical status

$0

$5,000

$10,000

$15,000

$20,000

$25,000

$30,000

$35,000

$40,000

$45,000

CD4 <50 CD4 50-199 CD4 200-349 CD4 >=350

CD4 Category (cells/ul)

Mea

n A

nn

ual

Co

st

CD4 DeclinedCD4 UnchangedCD4 Improved*

*

*

* P=0.003

Major Focus of Appropriations:Provision of medications

• The majority of the new dollars in the current iteration of the RW appropriation of the President’s budget is targeted for Part B

• Over the last 8 years most increases in the RW Care Act have gone to ADAP

Policy implications

• Provision of antiretroviral and other essential medications Funding for ADAPs

Reality Check

• Operating budget of our clinic: $4.2 M / yr

(1800 active pts)

• Third party payment ~ $ 800,000/yr

• RW Title III $495,000/yr– Flat Funded for > 10 years– 2.5% cut in 2006– Despite 120% increase in patient volume over

last 8 years

• Part B funds ~ $1.0 M since 2007

• Annual Deficit ~ $1.8 M per year

Key Points

• Mortality is much higher when patients are diagnosed late in the course of infection (CD4 < 200 /ul)

• The majority (> 50%) of newly diagnosed patients are diagnosed late (except preg Women)

• Many (? Most) HIV infected patients in the US don’t know they are infected

• Universal, opt-out testing is needed

With more universal testing, a 25 -50% increase in patient volume will occur

Who will take care of these patients?

Policy implications

• Provision of antiretroviral and other essential medications– Funding for ADAPs

• Need dramatic increase in funding to increase clinic capacity Increase Part C funding Provide incentives for younger MDs to

go into HIV Medicine

Provision of medications

• “Every American who needs HIV treatment and care should have access to it”

• “People who are HIV-positive need essential medications”

• “Without the drugs, providing care is difficult to impossible”

PACHA. Achieving and HIV-Free Generation; IDSAnews 2006;16(1):7

Provision of HIV CARE

• “Every American who needs HIV treatment and care should have access to it”

• “People who are HIV-positive need essential medications”

• “Without the drugs, providing care is difficult to impossible”

• “Without qualified HIV care providers and clinics, HIV drugs mean nothing”

PACHA. Achieving and HIV-Free Generation; IDSAnews 2006;16(1):7

EDITORIAL COMMENTARY

Which Policy to ADAP-T:

Waiting Lists or Waiting Lines?

Michael S. Saag

University of Alabama at Birmingham Center for AIDS Research

Clinical Infectious Diseases    2006;43:1365-1367© 2006 by the Infectious Diseases Society of America. All rights reserved.

Thanks

UAB 1917 Clinic Cohort supported by UAB CFAR (grant P30-AI27767), CNICS (grant 1 R24-AI067039-1), and the Mary Fisher CARE Fund