st marys hospital ingrid v. bassett, md, mph massachusetts general hospital harvard medical school...
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St Mary’s Hospital
Ingrid V. Bassett, MD, MPHMassachusetts General Hospital
Harvard Medical SchoolMay 25, 2010
Who Starts ART in Durban, South Africa?…Not Everyone Who
Should
Conflict of Interest Disclosure Ingrid V. Bassett, MD, MPH
Has no real or apparent
conflicts of interest to report
Overview 2.9 million on ART in sub-Saharan Africa, but
6.7 million need it How much of this gap is due to failure to link to
care after a new HIV diagnosis? What can be done to improve linkage?
WHO, 2009
Road Map Retention versus Linkage Linkage in resource-limited settings Durban, South Africa study Strategies to improve Linkage
Poor retention well-documented
Systematic review sub-Saharan Africa of adult patient retention in ART programs
Non-research ART programs, 2000-2007 33 patient cohorts (>74,000 patients) Very high rates of loss ~40% not in care at 2 years:
Loss to follow-up 56% Death 40%
Rosen, PLos Medicine, 2007
Background: Poor retention substantial during scale-up Updated systematic review 2007-2009 >226,000 patients, 39 cohorts, 80% in Afr ~25% lost at 2 years, ~35% lost at 3 years Slightly better than before, but still
substantial losses after ART initiation Routine M+E and PEPFAR reporting focus
on ART patients
Fox, Trop Med & Intl Health, 2010
Retention
On ART
Linkage
What is known about rates of linkage to HIV care after a new HIV diagnosis?
What are risk factors for failing to enter care? Do these differ by setting?
HIV Test CD4 count Training 1,2,3 On ARTPsychosocialAssessment
Determinants of mortality and non-death losses: Cape Town
Community-based ART program, 2002-2005
1235 enrolled in ART program 121 died (46% pre-tx; 40% early tx) Risk: symptomatic disease and CD4 <100 After first year of ART, low mortality rate <1%/year
High risk of pre-ART and early ART deaths
Lawn, AIDS, 2006
What is rate of mortality and retention pre-ART in Uganda? TASO ART Clinic, Jinja, rural Uganda Focus on 4-8 week pre-ART screening period 26% of ART-eligibles did not finish screening
Risk: lower median CD4, male gender Increased over time with clinic expansion
Home visits to ascertain status 30% on ART with different provider 25% alive and not on ART (44% due to transport) 28% died 17% LTFU
High rate of pre-ART mortality
Amuron, BMC Public Health, 2009
Why failing to link in Malawi? Cross-sectional study Rural Malawi (MSF), 2004-2007 Defaulters missed appointment by >1 mo 874 adults pre-ART traced, 71% found:
51% dead, most within 3 months of last visit Reasons for defaulting: stigma, dissatisfaction with
care/staff, perceived improved health, transport costs
McGuire, Trop Med & Intl Health, 2010
From HIV test through ART start in Mozambique: a retrospective study Routine care data from 2 HIV care networks HIV tested 2004-2005, first year after free ART in
public sector 7005 with HIV
Only 56% enrolled ART clinic within 30d 1506 ART-eligible
Only 31% start ART within 90d of CD4
Micek, JAIDS, 2009
Failure to Link: Open questions What proportion of newly identified HIV-
infected don’t start ART? What are the risk factors for failing to link to care?
Few prospective data about losses and mortality before HIV clinic entry
Valuable to design interventions to improve linkage to HIV care
Who Starts ART in Durban, South Africa?
…Not Everyone Who Should Ingrid V. Bassett, MD, MPH
Susan Regan, PhDSenica Chetty, MSc
Janet Giddy, MBChB, MFamMedLauren M. Uhler, BA
Helga Holst, MD, MBADouglas Ross, MBChB, MBA
Rochelle P. Walensky, MD, MPHKenneth A. Freedberg, MD, MSc
Elena Losina, PhD St Mary’s Hospital
Background: HIV in South Africa > 5 million people HIV-infected Largest ART program in the world Only ~40% of HIV-infected who need ART
are receiving it Few data why HIV-infected fail to link to care
WHO 2009; PEPFAR 2008; Lawn, AIDS, 2008
Objectives To evaluate rates of ART initiation within 12
months of a positive HIV test in Durban, South Africa
To identify baseline factors that predict failure to be on ART at 1 year
Methods: Two Study Sites
Prospective, observational cohort Sites: Outpatient departments in Durban
McCord (urban) St. Mary’s Mariannhill (semi-rural)
Partially government subsidized Patients pay a fee for care PEPFAR-funded HIV clinics
Methods: Study population Adults (≥18y) English or Zulu speaking Enrolled prior to rapid HIV test Enrolled November 2006-October 2008 Follow-up through June 2009
Methods: Data collection Baseline enrollment interview 6, 12 month questionnaire Domains: demographic, geographic, clinical Electronic medical record review at
enrollment site: CD4, ART start
Methods: Two Outcomes1) Obtaining CD4 count within 90 days
2) ART initiation within 12 months for eligible patients CD4 ≤ 200/µl within 90 days of HIV test ART initiation at study site documented in medical record
Methods: Data analysis Predictors of failing to initiate ART evaluated
with multivariate logistic regression Kaplan-Meier curve of time to ART initiation Mortality pre- and post-ART initiation
Enrolled2,775
HIV-negative1,308
HIV-infected1,467
HIV Test
No test/result: 71Indeterminate: 6
54% HIV prevalence
Screened3,401
Results: Cohort enrollment
Bassett, AIDS, 2010
HIV-infected cohort characteristics
Female 54% Median age 34 yrs (IQR 28-
41) Median follow-up time 12 mos (IQR 8-
14) Follow up available 70%
Bassett, AIDS, 2010
HIV-infected1,467
CD4 countwithin 90 days
Yes607
No862
CD4<200/μl368
CD4≥200/μl237
59% no CD4within 90 days
Results: CD4 count within 90 days
61% CD4<200/µlART eligible at baseline
Unknown2
Bassett, AIDS, 2010
HIV Tested*
HIV+
CD4/results
Eligible for ART
Start ART
*Screened 11/06-10/08, enrolled in study and have known HIV status
368
How many start ART?
Failure to obtain CD4Failure to
start ARTwhen eligible
Bassett, AIDS, 2010
154
605
2,775
1,467
Results: Long delay from HIV diagnosis to ART start
P<0.001
0.00
0.25
0.50
0.75
1.00
Pro
port
ion
Sta
rtin
g A
RT
0 90 180 270 360Days Since HIV Testing
Males: 40% started ARTby 6 months
Females:55% started ARTby 6 months
Bassett, AIDS, 2010 days
P<0.001
Results: Predictors of failure to start ART within 12 months
Male gender RR 1.5 (1.1-2.1) No HIV+ family/friend RR 5.1 (1.8-14.9)
Adjusting for: age, CD4 count, prior HIV test, work outside the home
Bassett, AIDS, 2010
Results: High rate of mortality 15% of HIV-infected cohort (216 deaths/1,467) 21% of ART eligible cohort (76 deaths/368)
051015202530
<50 50-99 100-149 150-199 >200
% deadHIV+cohortwith CD4
P<0.001CD4 (/µl) strataBassett, AIDS, 2010
High rate of mortality pre-ART Most patients died pre-ART or with unknown
ART status
051015202530
<50 50-99 100-149 150-199 >200P<0.001
CD4 (/µl) strata
Overall
Pre-ART
% deadHIV+cohortwith CD4
Bassett, AIDS, 2010
Limitations Sites may not be representative of public
sector hospitals in South Africa 30% of pre-ART patients were unreachable Likely underestimates mortality and ART
initiation that occurred at non-study sites
Bassett, AIDS, 2010
Study conclusions Substantial pre-ART loss along care path Men less likely to initiate ART Severe immune suppression at diagnosis Long delays to ART initiation High rates of pre-ART mortality
Bassett, AIDS, 2010
Implications Promote early HIV diagnosis and care Monitor mortality and losses pre-ART Improve access for men Interventions needed to improve linkage to
care/minimize delays Following new HIV diagnosis After ART eligibility determined
Learning from on-ART strategies: patient tracking
2 ART facilities Lilongwe, Malawi, 2006-09 Patients who missed clinic appt >3 weeks 2,653 patients identified, 85% traced by phone
and home visit 30% died
1,158 found alive, not transferred 74% returned to clinic (women, age >39 at ART start)
Tweya, Trop Med & Int Hlth, 2010
Learning from on-ART strategies
“Patient tracers” phone calls or home visits to ascertain vital status, help subjects return to care
Proactive adherence support, including home visits, community-based collaborations
Transportation vouchers Eliminate co-pays Reliable (electronic) monitoring
Geng, JAMA, 2008; Ochieng, IAS, 2007; Tweya, Trop Med & Intl Health, 2010; Rosen, Trop Med & Intl Health, 2010; Etienne, Trop Med & Intl Health, 2010; Forster, Bull WHO,2008
Learning from on-ART strategies: efficiency
Johannesburg 4-month pilot study of telephone tracing by social worker
Average $432/patient returned to care
Lessons learned from this and others: Maintain updated contact information Capacity to know about clinic transfers Capacity to access national death registry
Rosen, Trop Med & Intl Health, 2010 Bassett, JAIDS, 2009; Mwanaga, CROI, 2008;Tweya, Trop Med & Intl Health, 2010;
Learning from US linkage to care trial HIV-infected, recently diagnosed, multi-site US RCT case management vs standard of care Primary outcome in-care at 12 months A higher proportion in intervention arm visited
HIV clinician at least once within 6 months (78% versus 60%, p < 0.01) and at least twice within 12 months (64% versus 49%, p < 0.01)
No similar RCT has yet been performed in resource-limited settings
Gardner, AIDS, 2005
Upcoming NIMH-funded linkage to care trial Multi-site RCT in Durban starting in 2010 Assess clinical impact and cost-
effectiveness of a health system navigator assigned in the outpatient setting
Navigator in-person, SMS, phone contacts Evaluate linkage to HIV care and TB
treatment completion
AcknowledgementsDurban Team Janet Giddy Senica Chetty Douglas Ross Lindeni Sangweni Aletta Maphasa Success Mncwabe Yolisa Mgobhozi Bongiwe Mdadane Matilda Mazibuko Helga Holst
Study participants at McCord and St. Mary’s Hospitals, Durban
US Team and Funders Rochelle Walensky Ken Freedberg Elena Losina Susan Regan Sarah Bancroft Harv Univ Program on AIDS Harvard CFAR AI60354 NIAID K23 AI068458 Harvard Catalyst Grant Upcoming trial: NIMH R01
MH090326
St Mary’s Hospital