Upload
jubal
View
22
Download
0
Tags:
Embed Size (px)
DESCRIPTION
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 Research National Development and Research Institutes, Inc. (NDRI) New York, NY - PowerPoint PPT Presentation
Citation preview
1
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
2
Overview
• Causes of disparities in ACTs
• Efficacy of a brief behavioral intervention
• Barriers to screening, eligibility, enrollment
• Experiences of ACT screening among PLHAs
3
Collaborators
• Beth Israel Medical Center (D. Mildvan, MD)• Housing Works (K. Cylar, CSW)• NDRI (M. Gwadz, Ph.D.)
4
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
5
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
6
Implications of HIV/AIDS disparities
• Greater morbidity
• Greater mortality, early mortality
• Treatment delays, sub-optimal treatment
• Disparities are increasing
7
ACT disparities• African-American men and women • 28.8% (n=2,218) of AACTG participants are
African-American (2003)
8
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
9
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
10
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
Norms, misinformation
11
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
Norms, misinformation
Low #s referrals
12
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
Norms, misinformation
Low #s referrals
Low outreach, intervention
13
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
Norms, misinformation
Low #s referrals
Low outreach, intervention
Mismatch??
14
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
15
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
16
17
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
18
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
19
Primary target of intervention
Individual
Social Network
Organizations & providers(health care, social service)
Clinical trials units
Clinical trials inclusion/exclusion criteria
20
ACT1 Project recruitment, retention
(N=580)
Recruited AIDS Service Org (ASO) 64%
Recruited CBO 5%
Recruited snowball/outreach 31%
21
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%
22
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%
23
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.
24
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
25
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
26
Intervention efficacy
N = 580 % (of total)
Attended intervention 539 93%
Made screening appt 272 47%
Attended screening 143 25%
27
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
28
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
29
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
30
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
31
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
32
Attitudinal predictors of screeningNo
appointment (N=308)
Made appt, did not start
(N=129)
Started but did not finish
(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
33
Social-level predictors of screening
No appointment (N=308)
Made appt, did not
start (N=129)
Started but did not finish
(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%
34
Structural-level 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
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
35
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
37
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
38
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
39
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
40
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
41
• 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%
43
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?
44
• 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
45
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
46
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
47
Theory of Triadic Influence Model
48
Primary targets of intervention
Individual
Social Network
Organizations & providers(health care, social service)
Clinical trials units
Clinical trials inclusion/exclusion criteria
49
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