Transcript Early Warning Indications for Virological Failurex

Early Warning Indicators for
Virological Failure in the
Southern African Context
Vincent Marconi, MD
Professor of Medicine
Emory University School of Medicine
Rollins School of Public Health
Disclosure
At the time this presentation was given I had no real or perceived
vested interests that related to this presentation nor did I have any
relationships with pharmaceutical companies, biomedical device
manufacturers, and/or other corporations whose products or
services are related to pertinent therapeutic areas. However, I have
received research funding from ViiV, Gilead and Bayer.
Vincent Marconi
It’s a busy Monday in ART
Since 1995, antiretroviral
therapy has averted
7.6 million deaths globally,
Initiation
Clinic…
including 4.8 million deaths in sub-Saharan Africa.
Together, these life-saving medicines have gained approximately 40.2
million life-years since the epidemic started.
2013 UNAIDS Gap Report
“Perseverance is the foundation of all actions”
Colors
• Mr. N,
49 up
M the fight!”
“Don’t
give
• Recently diagnosed with TB/HIV
• Fevers, cough and weight loss
• CD4 110
• Receiving TB Tx
• Starting Regimen 1a
6th Century BC Lao Tzu
MSF
• Ms. S, 34 F
• Known HIV for 1 yr
•1973
Diarrhea
Bob Marley
• CD4 210
• Received PMTCT, Breastfeeding
• Starting Regimen 1b
Do you have any concerns??
1. Which gender is
at a higher risk of
VF
a) Male
b) Female
Do you have any concerns??
2. Which age group
is at higher risk of
VF?
a) Young
b) Old
Do you have any concerns??
3. Which clinical factors
increase risk of VF?
a)
b)
c)
d)
e)
f)
g)
Diarrhea
Low CD4
Weight loss
Breastfeeding
PMTCT
a and b
c and e
Demographic and Clinical
Factors
• Men – Drain 2013, Anude 2013
• Younger Age – Silverberg 2007,
Weintrob 2008
• Low CD4 – Badri 2008
• Concurrent OI’s – Marconi 2008
• D4t – PHIDISA 2010, McGrath 2012
• Diarrhea
• PMTCT*
Marconi AIDS Pt Care STD 2014
ART Need and Coverage
• 37.5 million people
living with HIV
– 25.8 M (69%) in SSA
– 6.8 M (18%) in SA
• 15 million people
receiving ART
(MDGI) in 3/15
– 10.7 M in SSA (43%)
– 2.9 M in SA (43%)
UNAIDS 2015
Kaiser 2015
“This
early-release guideline makes
Prevalence
available two key recommendations that
were developed during the revision
process in 2015. First, antiretroviral
therapy (ART) should be initiated in
everyone living with HIV at any CD4 cell
count. Second, the use of daily oral preexposure prophylaxis (PrEP) is
recommended as a prevention choice for
people at substantial risk of HIV infection
as part of combination prevention
approaches”
2010-2013 New ART
WHO Guidelines on
when to start ART and
on PreP
September 2015
Public Health Dilemma
• Increasing number of
individuals with HIV requiring
therapy
–
–
–
–
Increasing number of infections
Opt-out testing (HCT)
Earlier treatment (per WHO)*
Increasing coverage for
treatment (>40%)
– Decreasing mortality among
treated
• Limited capacity and resources
to manage existing patients on
therapy (funding declining)
*New Guidelines Sept 2015 for all people living with HIV
VF and HIV Drug Resistance:
No Small Problem
• Worldwide estimates of
11-47% virologic failure
within one year of first
ART (1.7 – 7M)*
Upward estimate of 1.3M with at least
• 40-95% individuals VF
1 1major
resistance mutation in SA
have >
major resistance
mutation
(if everyone was on ART it would be
• 4.4-44.7% of individuals
3M max estimate)
on ART will have drug
resistance within one year
(0.6 – 6.7M)*
• Over time triple class
failure will accumulate
* Calculated for 15M on ART (19% in SA)
GAP Report 2014
How can we prevent VF?
“Tailored Therapy”
“One Size Fits All”
Targeted Approach
Key Clinical/Programmatic
Questions
• Can we predict which patients are likely
to experience virologic failure?
– Before starting
– While on treatment
• Can we prevent these patients from
experiencing virologic failure?
Population-Level Early
Warning Indicators
HIVDR Early Warning Indicators (EWI)
Highpriority
element
• Indicators which speak to concerns about HIVDR
– Assess factors at individual clinics which are known to
create situations favourable to the emergence of
HIVDR
– EWIs provide an alert to clinic and ART programmes -thus providing an opportunity for corrective action
– Indicators exist for adults and children
Bennett DE et al., Antivir Ther 2008
WHO-recommended HIVDR EWIs
EWI
EWI Target
1. Prescribing practices
100%
2. Lost to follow-up at 12 months
≤ 20%
3. Retention on first-line ART at 12 months
≥ 70%
4. On-time drug pick up
≥ 90%
5. On-time appointment keeping
≥ 80%
6. Drug supply continuity
100%
8. Viral load <1000 copies/ml at 12 months
≥ 70%
Bennett DE et al., Antivir Ther 2008
Collated results provide a national level
At-a-glance assessment of site performance
National Level Reporting
Site
1
2
3
4
5
EWI 1: On-time EWI 2: Retention EWI 3: Pharmacy EWI 4: Dispensing EWI 5: Virological
Pill Pick-up in Care
Stock-outs
Practices
Suppression
95%
75%
100%
70%
70%
50%
100%
15%
100%
75%
75%
0%
95%
85%
100%
0%
78%
98%
95%
0%
50%
…
…
…
…
…
…
100
100%
100%
100%
0%
100%
Countries implementing at least one aspect of the Global
HIVDR Strategy and locations of HIVDR testing laboratories
As of 2011, 124 rounds of EWI monitoring in 58 countries in > 2000 clinics
ART Program Use of EWI Results
1.
Strengthened record keeping systems
•
•
•
•
•
2.
3.
4.
5.
Formation of clinic specific care optimizing committees1
Validation of existing electronic record keeping systems1, 2,3
Adjustments in pharmacy record keeping to permit on time pill pick up assessments 3
Pilot of enhanced defaulter tracing to identify patients missing drug pick-ups with the
goal of reengaging in care within 48 hours1
General strengthening of records4,5,6,7,8
Seek funding support from partners to scale-up EWI9
District teams to support adherence and trace patients LTFU1,10,11
Scale-up viral load testing5
Regular review of patient pill pick-up and establishment of formal
referral system to document transfers-in/out6
1Hong
et al. JAIDS 2010; 2 Anna Jonas, MoHSS Namibia, personal communication; 3Dawn Pereko, MSH Namibia,
personal communication; 4Jack N et al. CID (in press); 5Ye M et al. CID (in press); 6Daonie e et al. CID (in pres); 7Nhan DT
el al. CID (in press); Hedt BL et al., Anti Viral Ther 2008; 9Paula Mundari, Uganda National ART Programme, IAS 2010,
Vienna; 10Evelyne B, National ART Program, Burundi, personal communication; 11Anna Jonas, MoHSS Namibia,
personal communication.
Adult with Viral load suppressed rate at
6 months
Target
FY 2014/15
FY 2011/12
FY 2012/13
Amajuba District Municipality
96.5
92.5
94.5
94.1
1,108
eThekwini Metropolitan Municipality
96.5
90.2
92.9
92.8
4,535
Harry Gwala District Municipality
96.5
74.4
78.9
83.5
1,577
iLembe District Municipality
96.5
90.3
91.7
0.0
0
Ugu District Municipality
96.5
92.1
93.2
91.3
3,941
uMgungundlovu District Municipality
96.5
80.2
80.9
84.5
915
Umkhanyakude District Municipality
96.5
92.5
90.5
91.3
1,884
Umzinyathi District Municipality
96.5
82.7
94.5
92.9
369
Uthukela District Municipality
96.5
87.6
89.7
93.1
1,676
Uthungulu District Municipality
96.5
67.5
78.2
83.9
4,250
Zululand District Municipality
96.5
83.3
87.1
92.6
718
KwaZulu-Natal
96.5
84.9
87.7
89.4
20,973
District
FY 2013/14 Progress Q3
VLS at 6m
FY 2013/14
Adult percentage lost to follow up after
6 months ART
Target
FY 2014/15
FY 2011/12
FY 2012/13
Amajuba District Municipality
10.7
13.6
12.7
18.1
942
eThekwini Metropolitan Municipality
10.7
12.4
14.3
23.2
5,412
Harry Gwala District Municipality
10.7
8.6
10.9
20.4
1,515
iLembe District Municipality
10.7
6.5
11.6
1.9
7
Ugu District Municipality
10.7
8.7
9.7
19.7
2,224
uMgungundlovu District Municipality
10.7
11.4
17.2
18.8
1,068
Umkhanyakude District Municipality
10.7
6.1
8.5
24.0
2,256
Umzinyathi District Municipality
10.7
4.8
8.4
18.4
514
Uthukela District Municipality
10.7
6.9
10.5
15.0
1,482
Uthungulu District Municipality
10.7
9.6
10.8
17.6
2,038
Zululand District Municipality
10.7
8.8
10.9
17.3
665
KwaZulu-Natal
10.7
9.6
11.9
20.0
18,123
District
FY 2013/14 Progress Q3
LTF at 6m
Q3 FY2013/14
Adult with Viral load completion rate at
6 months
NDoH Target
FY 2014/15
FY 2011/12
FY 2012/13
Amajuba District Municipality
80
54.0
47.9
48.4
11,678
eThekwini Metropolitan Municipality
80
64.6
64.4
67.4
4,872
Harry Gwala District Municipality
80
65.1
55.3
44.1
1,148
iLembe District Municipality
80
50.2
44.0
42.6
23,041
Ugu District Municipality
80
38.6
36.2
32.4
1,178
uMgungundlovu District Municipality
80
26.5
30.6
29.6
4,888
Umkhanyakude District Municipality
80
41.4
39.4
35.4
1,888
Umzinyathi District Municipality
80
33.0
43.8
0.0
0
Uthukela District Municipality
80
37.7
42.9
53.4
4,318
Uthungulu District Municipality
80
38.6
35.2
28.4
1,083
Zululand District Municipality
80
43.4
37.6
32.0
2,064
KwaZulu-Natal
80
17.4
15.4
19.3
397
District
FY 2013/14 Progress Q3
VLD at 6m
FY 2013/14
HIVDR Early Warning Indicators (EWI)
• Programmatic Level*
• Individual Level
– Prescribing practices
– Pharmacy Refill
Data/Clinic Visits
– LTFU 12 mos ART
– Pill Counts/Self– Retention on 1st Line
Reported Adherence
ART at 12 mos/VL UD
– Clinical Risk Factors
– Timely ARV pickup
– Baseline Minority
– ARV appointments
Drug Resistance
– ARV shortages
– Psychosocial Risk
– Adherence
Factors
– Baseline HIVDR
*WHO recommends (http://www.who.int/hiv/topics/drugresistance/indicators/en/index.html)
Determinants of ART Response
Increased Immune Activation
Immunologic Decline
Disease Progression
Increased Transmission
Poor QOL and High Mortality
Ongoing Viral Replication
Access to Potent cART
(Properly prescribed
Combinations)
Toxicity, Adverse
Effects, Tolerability
Treatment Fatigue
Acceptance
Adherence
and Uptake
Behavioral
Socioeconomic and
Cultural Factors
Viral Replication
Capacity, Virulence
and Resistance
Pharmacokinetics
Absorption
Metabolism
Drug Interactions
Systemic and
Intracellular
Concentration
Host Immune and
Intrinsic Factors
Inhibition of Viral Replication
Decreased Immune Activation
Immune Reconstitution
Arrested Disease Progression
Decreased Transmission
Improved QOL and Survival
Nachega/Marconi IDDT 2011
Socioeconomic, Cultural and Psychological
Determinants of Health
Patient
Adapted from
Munoz 1996
Social Ecological Model
Bronfenbrenner 1979
Behavior Paradigm
Ordonez JAR 2012
Barriers to Clinical Care
• Poverty/Economic
• Sociocultural
– Transportation
– Perceived stigmatization
– Food Insecurity
– Influence of charismatic
churches
– Disability Grants
– Traditional healers
– Poor social support
– Gender Inequalities
• Institutional
• Political
– Long wait times
– Migration
– Negative staff
experiences
– Controversy over
provision of HIV Tx
– Poor health literacy
– Unfavorable policies
– Limited substance abuse
treatment and mental
health facilities
Kagee J Health Pscyhol, Global
Public Health 2010
Western Cape
Barriers to Adherence
• Barriers to Care
• Symptoms/QOL
• Psychosocial
Tired of taking ARVs
Fear of taking ARVs in front of others
Difficulty swallowing
Remembering to take pills
Side effects
Cost of meds
Peltzer BMC Public Health 2010
Bhat Euro J Clin Microb ID 2010
Maqutu AIDS Beh 2010
Sarna Pub Health Rep 2010
Coetzee AIDS Beh 2013
What More Do You Want to
Know?
Colors
•
•
•
•
Multiple partners
Lives alone
>60 min from clinic
Taxi driver
MSF
•
•
•
•
Spouse deceased
3 children
Lives <30 min from clinic
Domestic worker
Concerns??
4. Which
socioeconomic
factor increases risk
of VF?
a) Partner Status
b) Low Income
c) Long Distance to
Clinic
d) Type of Employment
Economic
Alsan
•
•
•
•
•
> 50% SA live in poverty (HSRC 2004)
– 10% living in informal settlements; 40% with extended family; Median household size 4.5 people
– Income decline associated with VF in Uganda (Alsan CROI 2011)
>40% food insecurity (Rose Pub Health Nutr 2002)
Unemployment 25-42% (Kingdon 2004); 80% high school only, 10% middle school
Individuals may trade health for disability grant (Ojikutu JID 2007)
72% of poor live in rural areas and need to travel long distances to district hospitals (ART rollout sites)
Masculinity vs. Dependency
• For men, automobile ownership
was a risk factor for VF
• For women, financial insecurity
was a risk factor for VF
– Unemployment
– Non-spouse family paying for care
(employer)
– Staying with family other than
spouse
Hare AIDS Beh 2014
Anna Hare, MD
Claudia Ordonez, MA
Neighborhood Impact
Daniella Coker, MPH
• Neighborhood SES effect independent of individual SES
• Implies contextual (not only compositional) effects such
as geography/transportation and culture
Institutional
•
Vella JAIDS 2010
–
–
–
–
–
•
•
•
•
•
Number of new patients per year
Staff training and time commitment
Patient to staff ratio (NS)
Secure area (early on)
Confidentiality
Available services - especially
substance abuse and social
(Ncama Int J Nurs Stud 2008)
Dedicated staff, outreach vehicles,
contact <30 d after missed visit
(Braitstein JIAS 2012)
Task shifting, Down referral,
Decentralized care*
Fast Tracking (Geng CROI 2011)
Adherence clubs (Luque CROI 2012)
*Sanne Lancet 2010, Brennan AIDS 2011, Long PLoS
Med 2011, Matovu JAIDS 2013, STRETCH NIM-ART
BMC 2013Kredo Cochrane 2013
Vella JAIDS 2010
Braitstein
Political
•
•
•
•
Beliefs about HIV/AIDS
Controversies over provision of HIV treatment
Migration (intra- and inter-national)
“Weak Rights” to the system - access basic services,
housing, health services and employment (Balbo
2005)
• Unequal distribution of healthcare expenditure 
infrastructural and personnel deficits in public sector
– Private (20% of popn) > public (80%) spending by
7x per capita (Goudge 1999)
– Lack of comprehensive and integrated care (Jack
JAIDS 2004)
Anything Else?
Colors
•
•
•
•
•
Regular Unprotected Intercourse
Frequent alcohol use
Distrustful of healthcare
Feels stigmatized by friends
Sees TH for “low energy”
MSF
•
•
•
•
•
Experiences violence at home
No longer attends Church
Depressed
Had negative clinic experiences
Trouble concentrating
Concerns??
5. Which psychosocial
factor(s) increases risk
of VF?
a)
b)
c)
d)
e)
f)
g)
Unsafe sex
Intimate Partner Violence
Stigma
Depression
Dementia
Poor Clinic Experience
All of the above
Sociocultural
• Social marginalization leads to poor retention in care (Goudge
SAHARA J 2009)
• Ability to resist stigma and other barriers – impact of Social Capital
(Ware PLoS Med 2009, Young HPTN 043 JAIDS 2010, Achieng
CROI 2011)
– negative attitudes/beliefs about PLHIV (feelings of disgust, blame)
– negative perceptions about PLHIV (discrimination)
– perceptions of fair treatment for PLHIV (equity)
• Traditional Healers incorporated in ARV programs (Shuster J Comm
Health 2009)
Traditional African Medicine
•
•
•
•
•
•
WHO (2008) est 80% Africans use TAM
Babb (2007) 84% TAM use > 1x for HIV;
32% current use
Dahab & Reid (2008) adherence barrier,
under-reporting
Sutherlandia, St. John’s Wort, garlic, and
American ginseng CYP 450 interactions
(Mills 2005, Lee 2006, Izzo 2009)
Potential toxicities (Hsiao 2003)
SARCS and RFVF Study*
–
–
–
50-80% have prior to enrollment at SKT
5-20% have some TAM involvement after ART
initiation
No relationship to drug resistance, virologic failure
or clinical events
*
Marconi CID 2008
Murphy AIDS 2010
Sunpath AIDS 2012
Marconi AIDS Pt Care STDs 2013
Appelbaum GPH 2014
Psychosocial
• Number of people in social support network correlated with
adherence (Ncama Int J Nurses Stud 2008)
• Relationship factors and treatment supporters enhance
adherence (Nachega JAIDS 2006)
• Intimate Partner Violence/Abuse (Dunkle, Jewkes, Pronyk)
• Depression (Peltzer BMC Public Health 2010)
• Dementia (Joska AIDS Beh 2010) – 42.4% mild neurocognitive
disorder and 25.4% HIV-D in Cape Town starting ART
• Stigma/Disclosure (Lyimo BMC Pub Health 2012)
• Alcohol Misuse and a partner with HIV (Naidoo BMC
Public Health 2013)
PsychoSocial
Stigma, Faith and Depression
• For Men
– Having >1 HIV-positive partner or family
member (OR=2.44, 95% CI 1.01-5.90)
– Having >1 family member who died of
HIV (OR=2.98, 95% CI 1.29-6.91)
– Disclosing HIV status to friends
(OR=3.67, 95% CI 1.46-9.23)
Rachel Kearns, MPH
• For Women
– Not actively practicing their faith
(OR=1.75, 95% CI 1.00-3.06)
– Depression (OR=2.42, 95% CI 1.23-4.77)
Sally John, PhD
Risk Factors for Virological
Failure Study
Henry Sunpath, MD, MPH
Questions
•
•
•
•
Who
What
Why
How
− is at risk?
− are the barriers?
− do these barriers exist?
− can we reduce the risk?
Methods
• Patients had to be >18 yo and on >5 months of their first
ART regimen (substitutions allowed for toxicity)
• Unmatched case-control study
– 158 Cases: VL > 1000 cpm
– 300 Controls: (2:1) virologic suppression (VL < 1000 cpm)
• McCord Hospital
• Eligible patients were enrolled between October 2010
and June 2012
Marconi AIDS Pt Care STDs 2014
Methods
• Data Collection:
– Semi-structured interview in preferred language,
coordinator blinded to case/control status
• Questionnaire – demographic, socioeconomic (including a
wealth index, employment, education and cohabitants),
psychological (including substance abuse, food insecurity,
traditional medicine use, safe sex practices, faith, stigma and
intimate partner violence), modified ACTG adherence
questionnaire, and clinic satisfaction indices
• Kessler 10
• Neurocognitive assessment and Pill count
– Study physician history/physical
• Symptom screen
• Karnofsky score
• Clinical information, pharmacy refills and laboratory data from
the chart
Marconi AIDS Pt Care STDs 2014
Methods
• Statistical Analysis:
– Access was calculated using the medication
possession ratio (MPR)
– Adherence was calculated using unannounced pill
counts and expected pill count from the pharm refills
– Multivariate model selection was performed by domain;
significant variables were carried over to final models
• Model 1 – Baseline variables
• Model 2 – Complete model without Adherence or Access
• Model 3 – Complete model with Adherence and Access
Marconi AIDS Pt Care STDs 2014
Participant Characteristics
Characteristic
Age at enrollment (mean)
Gender (%female)
Tuberculosis (%yes)
Lipodystrophy (%yes)
Recent CD4 count in cells/µL (median)
Recent CD4 count (%>350 cells/µL)
Mean ART Duration (months)
Current ART regimen contains
Stavudine (d4T)
Zidovudine (ZDV)
Other (tenofovir, didanosine, abacavir)
Fluconazole use in the past 6 months (%yes)
TS use in the past 6 months (%yes)
INH or RIF use in the past 6 months (%yes)
ETB use in the past 6 months (%yes)
Control
(300)
40.9
71.0
54.7
37.0
359.0
52.0
33.0
Case
(158)
37.1
52.5
55.1
15.2
206.0
22.8
24.7
P value
17.3
24.7
58.0
1.0
44.7
9.3
1.3
27.8
15.2
57.0
8.9
63.9
21.5
5.7
0.0077
<0.0001
0.0001
1.00
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
0.0001
0.0005
0.014
Marconi AIDS Pt Care STDs 2014
Employment Status
Employed Full Time
Employed Part Time
Working at Home
Unemployed Seeking
Work
Unemployed Not
Seeking Work
80% report having some source of income
30% receive some income from family members
Median number of individuals supported by patient’s income: 3.5
Symptoms in the past 4 weeks
30%
25%
20%
15%
10%
5%
0%
10% Feel symptoms are ARV related
20% Feel symptoms are a barrier to taking ARVs
0.1
Probability
of VF by Access or Adherence
0.0
obability of Virologic Failure
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.0
PCAR and MPR
Probability of VF
0.9
MPR
group
0.8
PCAR
0.7
0.6
0.5
Peng Wu, MPH
0.4
0.3
0.2
0.1
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
PCAR and MPR
MPR
PCAR
group (PCAR)
Pill Count Adherence
or Medication
Possession Ratio (MPR)
Wu CHIVR 2014
Brent Johnson, PhD
1
Domain/Risk Factor
Demographic
Age (per 5 year increase)
Gender (male)
Model 1
Model 2
Model 3
0.837†
2.262**
0.860
2.416**
1.112
1.789
1.108
2.034
1.722†
5.500***
0.593†
1.910
0.448*
3.136***
1.802*
5.023**
0.500*
1.783
0.509*
3.021**
2.532**
2.555*
1.720†
2.470**
2.079
1.409
1.992*
-----
0.428*
0.079***
0.608
0.078***
0.995
1.001
1.008
0.424*
0.446*
0.879*
0.503†
0.350†
---
0.311*
0.376*
0.760*
0.440†
0.266*
0.397*
0.855*
0.370
0.416
0.378
0.419
0.649†
0.455†
3.519**
0.624
2.636
2.800
-----
0.691†
0.435†
3.681**
0.956**
1.995**
Socioeconomic
Education (per 1 year)
Transportation (personal)
Pay for care (family/spouse)
1.771†
1.517
Psychosocial
Faith activity (none)
Practice safe sex (<always)
Family HIV+ (none)
Treatment supporter (yes)
Clinic feel pleased (yes)
Depression (12+)
Symptoms and Exam
1.634*
--0.620*
1.991*
-------
Fatigue
Diarrhea
Sadness
Skin lesions
Medical History
Lipodystrophy (yes)
Log CD4 (per 1.0 increase)
Medications
ARV duration (per 1 month)
Recommend HIV clinic
Friend vs Family
Other vs Family
Provider vs Family
First Clinic (SKT)
ARV training sessions (3+)
Adherence counseling
2-4 vs 0-1
5+ vs 0-1
Current Regimen
ZDV vs d4T
Other vs d4T
Recall ARVs (TV/radio)
Trimethoprim/Sulfa (yes)
Fluconazole (yes)
Ethambutol (yes)
Access (0.1)
Adherence (0.1)
0.619*
0.489*
--1.625†
4.973*
2.729
-----
3.006
3.025
0.763*
ROC Curves for Each MV Model
1
2
AUC = 0.7824
AUC = 0.8867
3
AUC = 0.8881
Marconi AIDS Pt Care STDs 2014
Proposed Individual-Level EWI
Baseline (While Initiating
or Suppressed on ART)
Age
On ART Without
Access/Adherence
Measures*
Depression
On ART With
Access/Adherence
Measures*
Depression
Gender
Unsafe sex practices
Unsafe sex practices
Faith
Clinic Experience
Clinic Experience
Family Member HIV+
Fatigue
Fatigue
Treatment Supporter
Diarrhea
Rash
Clinic Recommendation
Lipodystrophy
Current CD4 count
Current Regimen
Current CD4 count
ARV Reminders
Fluconazole Use
ARV Reminders
Adherence
*These factors do not include those that were identified as baseline risk factors.
Marconi AIDS Pt Care STDs 2014
“I miss appointments
because the clinic is
crowded”
“I feel too tired to go to
the clinic”
“The lines are too long”
Institutional, Community and
Societal Factors
Access
“I miss appointments
because the clinic is too
far to travel”
VL
Adherence
“My pastor says I
should not take
ARVs”
“I do not like to take my
pills as they make me feel
sick”
“I forget to take my pills”
“I do not take my pills if I
have to take it in front of
others”
Marconi AIDS Pt Care STDs 2014
Future Directions
• Validate these measures in peri-urban and
rural settings
• Determine role of minority resistance
• Identify impact of drug concentrations
• Create a risk calculator
KZN HIV Drug Resistance Surveillance Study
R01 AI098558
Summary
• VF and HIVDR are growing global concerns
• Population-level EWI are useful for program evaluation but
lack specificity and timeliness for individual patient care
• Individual-level EWI at initiation and follow-up assists
patient risk stratification as well as enable targeted and
tailored interventions to VF
be employed
IS AN
• Consider all aspects of
the treatment paradigm with a key
EMERGENCY
focus on those impacting W/
adherence
OR W/O
• Pharmacy refills and pill RESISTANCE
counts are insufficient to predict VF
• Important to focus on both structural (institutional and
economic) as well as psychosocial factors when designing
interventions for patients
• Need to externally validate model in other settings (rural
and peri-urban) and include pharmacokinetics
Acknowledgments
McCord Hospital
• Sabelo Dladla
• Jane Hampton
• Helga Holst
• Sally John
• Roma Maharaj
• Phacia Ngubane
• Claudia Ordonez
• Melisha Pertab
• Sifiso Shange
• Henry Sunpath
UKZN/DDMRI/RKK/Bethesda
• Jaysingh Brijkumar
• Kelly Gate
• Michelle Gordon
• Yunus Moosa
• Selvan Pillay
Support
NIH/NIAID R01 AI098558
Emory University CFAR
Harvard University CFAR
Bayer Diagnostics
Gilead Pharmaceuticals
Emory University
• Hannah Appelbaum
• Daniella Coker
• Jonathan Colasanti
• Carlos del Rio
• Anna Hare
• Monique Hennink
• Rachel Kearns
• Baohua Wu
• Peng Wu
Harvard/URMSF/JHU
• Brent Johnson
• Daniel Kuritzkes
• Zhigang Lu
• Richard Murphy
• Jean Nachega
Special Thanks to the staff and patients of
Sinikithemba and iThemba Clinics…
…and my family for forbearance.