10/13/2009

1

Ellen M. Tedaldi, M.D. , FACPProfessor of Medicine

Director, Temple HIV ProgramTemple University School of Medicine

Philadelphia, PA

�Review determinants of ethnic and

gender differences

�Provide overview of toxicity in clinical

trials related to race/gender

�Discuss future research

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2

ARV ToxicityPharmacokinetics

Genetics

Gender

CD4

Race

Drug-Drug

Co-Morbidity

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� Immediate-short term• Host immune response

• ARV related

�Long Term• ARV related

• Co-factors

• Host genetics

•Demographics in

randomized trials

•Context of health

care disparities and

environment

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4

1987

• ACTG 019

• ZDV

• 92% male

1996

• ACTG 175

• Dual v. mono

• 80% male

• 70% white

2005

• 2 NN• NVP v. EFV

• >30% female

• Multi-Geography

2006

• FIRST

• CPCRA 058)

• 21% female

• 72% Black or Hispanic

2008

• GRACE

• DRV

• 69% female

• 84% Black or Hispanic overall

�Feminization of HIV• Poverty

• Depression

• Neurohumoral

�Co-Morbidities: Hepatitis C and B• Drug/alcohol use

�Co-Morbidities: cardiovascular, renal• ? Inflammation

�Concomitant OI’s = late presentation to

care

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� One of the first ARV

toxicities reported in

greater frequency

among blacks

Furth, NEJM 1987

Don, Ann Int Med, 1990

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� Pharmacogenomics

� Immunogentic

• Host immune response

and genetics

� Pharmacogenetic

• Drug Disposition

� Absorption

� Distribution

� Metabolism

� Elimination

• Drug targets

Becker S, HIV Update 2005 CCO

Becker S, HIV Update CCO, 2005

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�Occurs about 5% of exposures overall

�HLA-B 5701 haplotype • Found in 78% Western Australians with HSR

• In US, 46% with HSR

� Blacks 4%

� Whites 5%

� Hispanics 6%

Additional alleles contribute as well

Mallal S, Lancet 2002

Hughes , Pharmacogenomics, 2004

�Combination of Genetics and Immune

status and gender

Martin A, AIDS 2005

Women CD4 > 250 cells3 increase risk

Men CD4 > 400 cells3

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�Drug disposition and genetics• Drug Transporters e. g P-glycoprotein in the

MDR1 gene (Protease inhibitors)

• Drug metabolizing enzymes

� Genetic variation in single nucleotide polymorphisms

(SNP’s) e.g. CYP3A5 increased clearance of IDV, SQV

� UGT1A1—Atazanavir and jaundice

� Metabolized by CYP2B6 in the

P450B6

� Marked inter-individual and

inter-racial variation in CNS

and other side effects

� Higher efavirenz plasma

concentrations, longer

elimination half-life observed

in individuals with 516TT

polymorphism in cytochrome

P450 2B6 gene

� (Blacks , Hispanics >whites)

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MeasureAll Subjects (N = 152)

RaceP Value*

White Black Hispanic

Median estimated efavirenz half-life, hrs (IQR)

26 (19-39) 22 (18-29) 31 (23-51) 38 (24-45) < .001

Median duration with plasma efavirenz > 46.7 ng/mL† after last efavirenz dose, days (IQR)

6.7 (4.7-9.2) 5.5 (4.4-7.5) 8.1 (6.0-13.7) 8.7 (6.0-12.5) < .001

Plasma efavirenz > 46.7 ng/mL† for > 21 days, %

3.5 14.5 6.7

IQR, interquartile range; *Difference between groups; †IC95 for wild-type HIV-1

� Time to efavirenz elimination significantly longer in black, Hispanic subjects

Ribaudo, Clin Inf Dis 2006

MeasureAll Subjects (N = 152)

CYP2B6 GenotypeP Value*

516GG 516GT 516TT

Median estimated efavirenz half-life, hrs (IQR)

26 (19-39) 23 (18-35) 27 (19-31) 48 (39-77) < .001

Median duration with plasma efavirenz > 46.7 ng/mL† after last efavirenz dose, days (IQR)

6.7 (4.7-9.2)5.8 (4.4-

8.3)7.0 (5.0-

8.0)14.0 (11.1-

21.2)< .001

Predicted plasma efavirenz > 46.7 ng/mL† for > 21 days, %

5 5 29

Median predicted duration with plasma efavirenz 46.7-2486 ng/mL,‡ days (IQR)

5.6 (4.3-7.4)

6.4 (4.5-7.3)

11.4 (8.7-17.1)

< .001

IQR, interquartile range; *Difference between groups; †IC95 for wild-type HIV-1; ‡Concentration range at which

maximum pressure for resistance selection expected.

� Those homozygous for 516TT demonstrated longer time to efavirenz elimination after efavirenz cessation

Ribaudo, Clin Inf Dis 2006

10/13/2009

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� Peripheral

Neuropathy and NRTI

� Metabolic:

hyperlipidemia

� Tenofovir Renal

Proximal Tubulopathy

� Mitochondrial

haplotypes

� APOC3

� May have

ethnic/racial

differences

� ABCC2

polymorphisms with

gene for MRP2

transporterTozzi, HIV Curr Res, 2008

� Genetic variations

are complex

� Generalizability to

diverse populations

� Discordance between

genotype and

phenotypic

expression

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� Multifactorial

• Body weight/fat

• Hormonal influences

• Pharmacogemonics

• Slower gastric

emptying

(bioavailability)

• Drug distribution e.g.

pregnancy and plasma

volume

Gandhi M et al, Ann Rev Pharmacol Toxicol, 2004

Dependent Variables AOR P-value Confidence

interval 95%

CD4 nadir, per 50 cells

0.8

0.305 (0.6-1.2)

Age, per 10 yr.

1.6

0.117 (0.9-2.9)

Female

23.4

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�Women: decreased clearance of

Indinavir, ritonavir, amprenavir

�Blacks: lower α-1 acid-glycoprotein

(AAG)for lopinavir, ritonavir, amprenavir

• But… percentages of women and non-whites

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Clinical Trial HIV-1 RNA < 50 copies/mL

Adverse Events

MO5-730[1] (N = 664): LPV/RTV QD vs LPV/RTV BID

Arms Combined Women: 72%Men: 78%

� Nonsignificant trend toward ↑ diarrhea in men vs women: 17.1% vs 11.1% (P = .093)

� Triglyceride ↑ significantly greater in men vs women:36.3 vs 58.7 mg/dL (P = .026)

� HDL ↑ significantly greater in women vs men: 9.05 vs6.90 mg/dL (P = .041)

CASTLE[2] (N = 883): ATV/RTV vs LPV/RTV

ATV/RTV armWomen: 76% Men: 79%

LPV/RTV armWomen: 73% Men: 78%

� Women on LPV/RTV experienced more nausea vsmen (14% vs 5%), but less diarrhea (9% vs 12%)

� Triglyceride ↑ on LPV/RTV greater in men vs women: 34 vs 64 mg/dL

ARTEMIS[3] (N = 343): DRV/RTV vs LPV/RTV

DRV/RTV armWomen: 84% Men: 84%

� Women experienced more vomiting vs men (11% vs4%), but less diarrhea (26% vs 37%)

1. da Silva B, et al. IAC 2008. Abstract TUPE0069. 2. Absalon J, et al. IAC 2008. Abstract TUPE0062. 3. Andrade-Villanueva J, et al. IAC 2008. Abstract TUPE0064.

ADRs possibly treatment related determined by the investigators;

Laboratory abnormalities reported as ADRs are not shown; ADRs, adverse drug reactions

� There were no meaningful differences in incidence of serious ADRs or

rate of treatment discontinuation due to ADRs between women and

men

Rash

Headache

Anorexia

Vomiting

Nausea

Flatulence

Diarrhea

Abdominal pain

Female, n=104

Male, n=239

0 5 10 15 20

Adverse Drug Reactions, %

Fourie J, et al. 5th IAS 2009. Poster CDB072

TTCA0137-9203-82UN

10/13/2009

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Study criteria

• ≥18 years of age

• Viral load ≥1,000

copies/mL

• Previous therapy

consisting of a PI- or

NNRTI-based HAART

regimen of ≥12 weeksa

• No prior use of

PREZISTA/r,

INTELENCE, ENF, or TPV

N = 420

(70% women,

30% men)

PREZISTA/r 600/100mg bid

+ investigator-selected OBRb

48 Weeks4-Week

follow-up

Target

Enrollment

aPatients were allowed to enter the study on treatment interruption of ≥4 weeks; bInvestigator-

selected NRTIs and NNRTIs were allowed; ENF, TPV or agents from novel classes were not

allowed; PI, protease inhibitor; NNRTI, non-nucleoside reverse transcriptase inhibitor; OBR,

optimized background therapy; ENF, enfuvirtide; TPV, tipranavir

• Open-label, single-arm, Phase IIIb study conducted at 65 sites across the US, Puerto

Rico and Canada for 48 weeks

• The primary endpoint was virologic response (HIV-1 RNA

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The least-squares mean difference between sexes in the observed and ITT–LOCF analyses, adjusted for baseline viral

load and CD4+ count, was 34 cells/mm3 (95% confidence interval [CI]: 0.4, 68; P=.047) and 11 cells/mm3 (95% CI: –18,

39; P≥.05), respectively; ITT, intent-to-treat; LOCF, last observation carried forward

• Median change from baseline to Week 48 in the observed CD4+ count was

higher in women than men

• Median change from baseline to Week 48 in CD4+ count for the ITT–LOCF

analysis was similar in women and men

Squires, K et al. 5th IAS 2009. Poster MOPEB042

TTCA0137-9203-11UN

Grade 3–4 laboratory abnormalities, n (%) Women (n=287) Men (n=142)

Total cholesterol (grade 3 only) 10 (4.6) 5 (4.2)

Triglycerides 1 (0.5) 11 (9.2)

Aspartate aminotransferase 8 (3.0) 7 (5.1)

Alanine aminotransferase 6 (2.2) 4 (2.9)

Hyperglycemia 6 (2.2) 4 (2.9)

Lipase 5 (1.9) 5 (3.7)

Pancreatic amylase 4 (1.5) 6 (4.4)

Hyperuricemia 0 4 (2.9)

Plasma prothrombin time 0 4 (4.4)

� Grade 3-4 laboratory abnormalities were generally comparable

between sexesSquires, K et al. 5th IAS 2009. Poster MOPEB042

TTCA0137-9203-14UN

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aOccurring in ≥2% of patients in either group; bExcluding laboratory abnormalities reported

as AEs; SAE, serious adverse event

Adverse events, n (%) Women (n=287) Men (n=142)

Patients with ≥1 AE 259 (90.2) 118 (83.1)

Patients with ≥1 SAE 47 (16.4) 33 (23.2)

Patients with ≥1 AE at least possibly

related to PREZISTA/r 134 (46.7) 61 (43.0)

Patients with ≥1 grade 2–4 AE at least

possibly related to PREZISTA/ra,b 80 (27.9) 38 (26.8)

Diarrhea 13 (4.5) 7 (4.9)

Nausea 15 (5.2) 4 (2.8)

Rash 6 (2.1) 4 (2.8)

Weight increase 5 (1.7) 3 (2.1)

Vomiting 4 (1.4) 3 (2.1)

� Treatment with PREZISTA/r was similarly tolerated between women and men, with no

unexpected AEs, based on results from previous trials

� Four deaths were reported; all were considered unrelated to PREZISTA/r by the

investigator

Squires, K et al. 5th IAS 2009. Poster MOPEB042

TTCA0137-9203-13UN

� Factors associated with

nonadherence

• Depression

• Active substance use

• Active alcohol use

• Lack of trust in provider

• Lack of self-esteem

• Lack of support

� Potential contributors to non-

adherence in women

• Partner or family unaware

of patient’s HIV status

• Economic

status/dependence

• Care giving role in family

• Stigma

• Domestic violence

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� 17,826 women in 38

randomized clinical

trials with 14 ARV

� Stratified by treatment

naïve, experienced

� Efficacy analyses by

drug class also

� NO clinical or

statistical difference

in 48 week efficacy

outcomes

Struble et al,CROI 2009 Abs. 987b

� Both host and

environmental factors

important

� Further research into

gender specific trials

that include

adherence/retention

focus + evaluation of

gender specific

immunology

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�Higher rates of co-morbid conditions e.g.

cardiovascular, renal

�Psychosocial and economic factors

�? Stress, inflammation

Adjusted Hazard Ratio (95% Confidence Intervals)a

Femaleb Latinoc Blackc

Cardiovascular 1.49 (0.67-3.35) 0.62 (0.12-3.16) 2.64 (1.04-6.67)

Renal 0.47 (0.15-1.49) 0.42 (0.05-3.84) 3.83 (1.28-11.5)

Psychiatric 0.36 (0.13-0.99)d 1.08 (0.35-3.32) 2.45 (1.13-5.29)

Hepatic 0.80 (0.40-1.57) 1.05 (0.53-2.08) 0.98 (0.57-1.68)

Anemia 2.34 (1.09-4.99) 1.43 (0.45-4.58) 1.79 (0.72-4.50)

Death 1.33 (0.89-2.00) 1.04 (0.62-1.76) 1.31 (0.89-1.95)

Discontinuation due to

toxicity 1.13 (0.87-1.47) 0.97 (0.74-1.26) 0.82 (0.66-1.01)

Grade 4 adverse event, death

or discontinuation 1.06 (0.86-1.31) 0.89 (0.71-1.13) 0.96 (0.80-1.14)

Tedaldi, JAIDS 2008

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� According to multivariate analysis, several baseline factors correlated with death,

including black race, female sex, older age, IDU as a risk factor for infection, and

indicators of more advanced HIV infection (high HIV-1 RNA, low CD4+ cell count,

previous AIDS diagnosis)

Factor

Multivariate Analysis Including Factors

at Enrollment

Multivariate Analysis Including %

Time on HAART

HR (95% CI) P Value HR (95% CI) P Value

Female sex 1.53 (1.13-2.08) .007 1.62 (1.19-2.21) .002

Black race 1.33 (1.01-1.74) .04 1.00 (0.76-1.32) .99

IDU as a risk factor for infection 1.61 (1.12-2.31) .009 1.37 (0.95-1.97) .09

Baseline CD4+ cell count < .001 < .001

� 200 vs. 350 cells/mm3 0.59 (0.47-0.73) 0.50 (0.39-0.64)

� 200 vs. 500 cells/mm3 0.45 (0.31-0.64) 0.34 (0.23-0.49)

Baseline HIV-1 RNA log10 copies/mL 1.35 (1.15-1.57) < .001 1.29 (1.10-1.51) .002

Percentage of time in care while

receiving HAART (per 10%

increase)

-- -- 0.80 (0.77-0.83) < .001

Lemly DC, et al. J Infect Dis. 2009;199:991-998.

� Future research in

pharmacogenomics

in diverse population

� Strategy trials that

include health

disparities issues

� Enrollment of HIV

persons

representative of

epidemic

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They both matter-