1 racial/ethnic and gender disparities in aids clinical trials: a multi-method evaluation of a...

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Racial/ethnic and Gender Disparities in AIDS Clinical Trials: A Multi-method Evaluation of a Behavioral Intervention

Marya Viorst Gwadz, Ph.D.Center for Drug Use and HIV Research (CDUHR),Institute for AIDS ResearchNational Development and Research Institutes, Inc. (NDRI)New York, NY9/25/2008

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Overview

• Causes of disparities in ACTs

• Efficacy of a brief behavioral intervention

• Barriers to screening, eligibility, enrollment

• Experiences of ACT screening among PLHAs

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Collaborators

• Beth Israel Medical Center (D. Mildvan, MD)• Housing Works (K. Cylar, CSW)• NDRI (M. Gwadz, Ph.D.)

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Types of AIDS Clinical Trials

• Treatments for HIV/AIDS• Opportunistic infections• Co-occurring conditions (HCV)• Cancers associated with AIDS• Reconstitute immune systems • Observational• Varying levels of commitment and risk

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Background – HIV/AIDS disparities• Racial/ethnic minorities are 33% of population • Racial/ethnic minorities 70% of AIDS cases • > 80% of women with HIV/AIDS are minorities

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Implications of HIV/AIDS disparities

• Greater morbidity

• Greater mortality, early mortality

• Treatment delays, sub-optimal treatment

• Disparities are increasing

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ACT disparities• African-American men and women • 28.8% (n=2,218) of AACTG participants are

African-American (2003)

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Why are ACT disparities problematic?

• Individual PLHA– Denies access to treatments, knowledge– Denies high level of attention and care– Denies chance to contribute to community

• Research– Likely limits generalizability of research findings– May reduce treatment efficacy

• Ethics– Perpetuates long-standing barriers

• Likely contributes to HIV/AIDS disparities

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ACT disparities are complex

Individual

Social Network

Organizations & providers(health care, social service)

Clinical trials units

Clinical trials inclusion/exclusion criteria

History, mistreatment , fear, mistrust, misinformation

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Individual

Social Network





Norms, misinformation

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Individual

Social Network






Low #s referrals

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Individual

Social Network






Low #s referrals

Low outreach, intervention

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Individual

Social Network






Low #s referrals

Low outreach, intervention

Mismatch??

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The ACT1 Project

• Exploratory• Brief intervention with PLHA• Pre-test, post-test design• Multi-level qualitative research

– PLHA– Case managers – Medical providers– Clinical trials staff

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Steps toward ACT enrollment

Why promote screening among POC/women?

• Base rates of screening are negligible• Screening is very low risk/no risk• Knowledge • Allays concerns and fears• Altruistic• Builds relationships between PLHA and CTU• Information to stakeholders• Enrollment

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ACT1 intervention key characteristics

• Social Action Theory • Motivational Interviewing • Three contacts

• Two group sessions • Brief individual phone Health Education

Contact (10 – 20 minutes)• Manualized• Lead by clinician and peer

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Intervention core elements

ACTION STATE

BACKGROUNDAge

GenderSocioeconomic Status

Race/ethnicityChildren

CONTEXUTAL INFLUENCES

Living SituationHealth StatusSocial SupportSubstance Use

BACKGROUND FACTORS

INTERVENTION

KNOWLEDGE

ATTITUDESBeliefs, Fears

Mistrust

MOTIVATIONWillingness Readiness

SOCIAL CONTEXTNorms

Social SupportProviders

SKILLSProblem Solving

Decisional Balance

CHANGE MECHANISMS

OUTCOME

Screening for ACTs

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Primary target of intervention

Individual

Social Network




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ACT1 Project recruitment, retention

(N=580)

Recruited AIDS Service Org (ASO) 64%

Recruited CBO 5%

Recruited snowball/outreach 31%

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Demographic characteristics(N=580)

Age (M, SD) 44.72 (7.76)

Female 39%

Race/ethnicity

African-American 56%

Latino/Hispanic 32%

Other 8%

High school diploma/equivalent 65%

Living with child/children 13%

Stable housing 71%

Medicaid-eligible 96%

Employed 5%

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Health and substance use(N=580)

HIV dx > 5 years ago 79%

Receiving anti-retrovirals 68%

HCV-infected 40%

SF12 physical health < median 64%

SF12 mental health < median 70%

Any alcohol use past 2 months 34%

Any drug use past 2 months 38%

Substance use - daily 6%

Current MMTP program 13%

Lifetime IDU 34%

Recent IDU 5%

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Knowledge of ACTs

Total Male Female p

Knowledge score (range 0. – 1.0)

0.53 (0.18) 0.54 (0.18) 0.51 (0.19) n.s.

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Willingness to participate in ACTsTotal Male Female p

If a primary dr recommended it 88% 89% 88%

If trial took place at a CBO where already felt comfortable

84% 85% 82%

If current treatment seemed to be failing

74% 75% 72%

If trial was testing a new ARV medication

62% 70% 50% ***

If a friend or family member recommended it

69% 68% 69%

If testing a new combination of older ARV medications

56% 61% 46% ***

*** p < .001

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Willingness to participate in ACTs

Total Male Female

Willingness score (range 0-100; M, SD)

66.7 (20.3) 66.6 (19.6) 61.5 (20.9) **

** p < .01

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Intervention efficacy

N = 580 % (of total)

Attended intervention 539 93%

Made screening appt 272 47%

Attended screening 143 25%

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Intervention efficacy - enrollmentN = 580 % (of total)

Attended intervention 539 93%

Made screening appt 272 47%

Attended screening 143 25%

Completed screening 95 16%

Eligible 10 2% 11% of those who completed screening

Enrolled 6 1% 60% of those eligible

Context

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The “Leaky Pipe”Total sample

N = 580

Attended intervention93%, n=539

Made screening appt47%, n=272

Attended screening appt25%, n=143

Completed screening16%, n=95

Eligible2%, n=10

Enrolled1%, n=6

Lost at each step

129 (22%) made appt but did not attend

267 (46%) attended intervention but no screening appt

41 (7%) did not attend intervention

48 (8%) attended but did not complete screening

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Intervention dose responseNo

appointment (N=308)

Made appt, did not

start (N=129)

Started but did not finish

(N=48)

Screening complete

(N=95)

p

No. of group sessions (0-2)

1.44 (0.85) 1.77 (0.62) 1.69 (0.69) 1.75 (0.65) ***

Health Education contact

76% 87% 88% 91% **

Total dose (0-3) 2.20 (1.10) 2.64 (0.72) 2.56 (0.77) 2.65 (0.68) ***

** p < .01, *** p < .001

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Demographic predictors of screeningNo

appoint.Made

appt, did not start

Started but did

not finish

Screening complete

p

Age (M, SD) 43.89 (7.82)

45.05 (7.71)

46.56 (6.73)

46.04 (7.83)

**

Female 38% 44% 40% 37%

African-American 57% 50% 61% 57%

Latino/Hispanic 33% 33% 28% 30%

High school diploma/equivalent 66% 61% 62% 67%

Living with child/children 13% 16% 12% 8%

Stable housing 70% 72% 81% 69%

Medicaid-eligible 98% 95% 96% 93% +

Employed 7% 5% 2% 2%

+ p < .10, ** p < .01

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Health predictors of screening

No appoint-

ment (N=308)

Made appt, did not

start (N=129)

Started but did not

finish (N=48)

Screening complete

(N=95)

P

HIV dx > 5 years ago 79% 82% 77% 76%

Receiving anti-retrovirals 65% 68% 81% 73% +

HCV-infected 39% 43% 40% 40%

SF12 physical health T score 45.63 44.17 46.79 45.74

SF12 mental health T score 43.71 43.67 42.88 43.66

Any alcohol use past 2 mos 36% 30% 29% 36%

Any drug use past 2 mos 39% 35% 42% 35%

Current MMTP program 13% 16% 6% 12%

Substance use frequency (M) 9.42 7.72 8.48 8.29

+ p < .10

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Attitudinal predictors of screeningNo

appointment (N=308)

Made appt, did not start

(N=129)


(N=48)

Screening complete

(N=95)

p

ACT knowledge BL (0-100) 52.51 (19.16) 52.68 (15.18) 54.68 (16.54) 52.87 (19.77)

ACT knowledge FU-BL 5.42 (20.39) 9.38 (17.81) 11.65 (20.54) 6.36 (18.31) .12

ACT Mistrust BL (0-100) 51.77 (14.45) 49.81 (13.72) 51.80 (14.18) 48.53 (13.19)

ACT Mistrust FU-BL 0.38 (14.24) 0.61 (13.84) -0.94 (13.37) -0.15 (13.67)

ACT Altruism BL (0-100) 82.72 (18.84) 80.57 (20.50) 83.19 (21.73) 83.22 (17.64)

ACT Altruism FU-BL -1.45 (20.87) -0.61 (21.78) 1.14 (24.05) -0.70 (18.68)

ACT Willingness BL (0-100) 63.25 (21.12) 67.43 (16.84) 61.56 (22.75) 66.38 (20.24)

ACT Willingness FU-BL 0.59 (20.47) -2.68 (19.89) 8.20 (22.30) 4.76 (15.67) **

Ever thought about screening 31% 40% 58% 47% *

*p < .05, ** p<.01

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Social-level predictors of screening

No appointment (N=308)

Made appt, did not

start (N=129)


(N=48)

Screening complete

(N=95)

p

Family support 31% 38% 33% 27%

Case manager support

36% 34% 29% 34%

Physician support 33% 38% 44% 38%

Friends’ support 18% 24% 17% 27% .13

Partner support 29% 26% 31% 25%

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Structural-level predictors of screening

No appoint-

ment (N=308)

Made appt, did not

start (N=129)


(N=48)

Screening complete

(N=95)

p

Recruited at ASO 69% 62% 56% 56% +

Recruited at CBO 5% 4% 4% 11%

Recruited outreach/snowball

27% 34% 40% 34%

Miles from hospital zip code and home zip code

5.85 (3.44) 6.00 (3.24) 6.36 (3.75) 5.89 (3.27)

+ p < .10

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Multivariate Continuation Ratio ModelAdjusted Odds

Ratio 95% Confidence

Interval df χ2

Number of group sessions (0-2) 1.450** 1.200 – 1.759 1 14.99**

Health Education Contact 1.931** 1.317 – 2.854 1 11.48**

Age 1.021* 1.004 – 1.039 1 5.85**

Medicaid Eligible 0.463* 0.225 – 0.914 1 4.95*

Receiving Antiretrovirals 1.206 0.904 – 1.609 1 1.62

Recruitment Location 2 15.42**

ASO 0.758+ 0.569 – 1.007 1

CBO 2.317** 1.256 – 4.407 1

Stage 2 9.66**

Attending at Least One Appt 1.088 0.806 – 1.469 1

Completing Screening 1.851** 1.251 – 2.763 1

+ p < .10, * p < .05, ** p < .01

LESSONS LEARNED

Integration of quantitative and qualitative findings

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Barriers to participation – PLHA

• Mistrust is potent– PLHA, families, social networks– “Don’t want to be a white man’s guinea pig”

• Willingness to participate is potent– Ambivalence contributes to inaction

• Lack of information, misinformation

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Barriers to participation – PLHA 2• Lack of outreach by clinical trials sites, others

– “We didn’t know they wanted us”• Substance use

– Assume will be excluded– Fear stigma

• “We don’t go to the doctor anyway”• Primary care provider relationship • Hard to separate screening & enrollment• Often did not know screening was incomplete

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Barriers– health care providers

• High support for and awareness of ACTs• Low #s of referrals for screening• Providers have concerns and biases

– Perfect adherence– Treatment of substance users– Loss of patients– Interference with primary care

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Barriers – social service providers

• Lack of information, misinformation • Similar mixed attitudes as PLHA

– Distrust– Interest, desire to know more about trials

• Uncomfortable discussing ACTs due to lower medical knowledge

• Do not commonly refer PLHA to ACTs

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• Outreach to populations insufficient• Outreach cannot address barriers• Most clinical trials sites differ from clinic

settings– Some perceived as not as accommodating – More formal, more structured– Unfamiliar setting or location

Barriers – clinical trials sites

Barriers – clinical trials (preliminary data)

• POC and women may be somewhat less likely to:– Complete screening– Be found eligible for

medical reasons

BI-ACTU2005

ACT1 Project 2004-05

Screening incomplete

25% 35%

Ineligible – medical reasons

37% 48%

Eligible (estimated)

14% 2%

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Main medical reasons for ineligibility

• Lack of provider pre-screening• Current/past VL, CD4, and ART mismatches

– E.g., “bad-good” patterns instead of “good-good”• E.g., high VL and high CD4 counts, vice versa

– Treatment naïve more likely to be eligible• Understanding medical mismatches can inform

future trials– Liberalize inclusion criteria?– New research questions?

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• PLHA generally had positive experiences – “The people there were very nice, comfortable,

respectable… Made you feel comfortable, you can trust in them. That's basically what you really want, especially doing the studies that's something like what I'm gonna be doing.”

• Reactions to ineligibility included– Mild to moderate disappointment– Relief– Optimism for future– Appreciated access to ACT system

In the context of low eligibility - experiences of screening

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Planning ACT2 – Address leaky pipe

• Not all ACT1 intervention components were active or necessary

• Retain combined group, individual format

• Enhance theoretical model – Understand ACT2 intervention’s mechanisms of action – Theory of Triadic Influence– Social-cognitive and Motivational Interviewing

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The ACT2 Project

• Randomized controlled trial design• Peer-driven intervention (PDI)

– More intensive (6 hrs total plus peer education)– Repetition, clarity, reduced complexity– Addresses structural barriers (S4)– Intervention thru screening & enrollment process

• Regular feedback to ACT stakeholders to inform future trials

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Theory of Triadic Influence Model

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Primary targets of intervention

Individual

Social Network




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ACT1 and ACT2 collaborators• Beth Israel Medical Center, Clinical Trials Unit • Housing Works, Inc.• AIDS Service Center• Betances Health Center• Institute for AIDS Research and the Center for Drug Use and HIV

Research (CDUHR), National Development and Research Institutes, Inc.

• ACT1: Funded by National Institutes of Health Grant # 1U01 46370 to Donna Mildvan, MD. (Marya Gwadz, Site PI at NDRI)

• ACT2: Funded by National Institutes of Health Grant (NIAID) #R01 AI070005 to Marya Gwadz, Ph.D.

• The ACT1 and ACT2 Projects are dedicated to the memory of Keith Cylar, Co-founder and Co-CEO of Housing Works (1958-2004), and former Housing Works PI, Project ACT

1 racial/ethnic and gender disparities in aids clinical trials: a multi-method evaluation of a...

Documents

act disparities problematic

overviewcauses of disparities

gender disparities

act enrollmentwhy

optimal treatment disparities

research institutes

aids cases

s referralslow outreach