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Adherence to antiretroviral therapy (ART) in Rwanda: Preliminary results from a national public health evaluation ICAP Data Dissemination Meeting June 3, 2009 Batya Elul Harriet Nuwagaba-Biribonwoha Deb Horowitz Denis Nash. Presentation outline. Background and rationale - PowerPoint PPT Presentation
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Adherence to antiretroviral therapy (ART) in Rwanda: Preliminary results from a
national public health evaluation
ICAP Data Dissemination Meeting
June 3, 2009
Batya ElulHarriet Nuwagaba-Biribonwoha
Deb HorowitzDenis Nash
Presentation outline
• Background and rationale
• Study objectives and methods
• Preliminary results
• Preliminary conclusions, strengths, limitations, and next steps
Background and rationale
Why study ART adherence?
• Strict ART adherence (≥95%) required for:– better immunological, virologic, and survival outcomes
– reducing risk of developing drug resistance
• Critical to improve how we deliver services and support patients to achieve and maintain optimal ART adherence
ART adherence estimates in US and sub-Saharan Africa (Mills et al, JAMA 2006)
United States Sub-Saharan Africa
ART adherence
• Pooled adherence estimates from meta-analysis (Mills et al, JAMA 2006)
– N. America: 55% (95% CI, 49%-62%)– Sub-Saharan Africa: 77% (95% CI,68%-85%)
• Very early in scale-up experience• Mostly smaller, non-representative samples• Generally involving treatment-naïve patients
Barriers to ART adherence (Mills et al, PLOS Medicine 2006)
• Consistent barriers to adherence across resource-rich and -limited settings– Fear of disclosure– Forgetfulness– Lack of understanding of treatment benefits– Complicated regimens– Being away from medications
• Barriers found more commonly in resource-limited settings– Access– Financial constraints
Rwandan context• ~150,000 HIV-positive adults and children including 49,000 on ART at 165
facilities (UNAIDS, Dec 07)
• Demeester et al (2005) : Cross-sectional study– ESTHER program at largest teaching hospital (CHUK)– 95 adults who initiated ART within 2-5 months of interview– 87% of patients reported taking all doses in previous month– 85-93% had therapeutic levels of NNRTI in serum
• Au et al (2006): Cross-sectional study – Project San Francisco research clinic in Kigali– 71 adults who initiated ART within 2 weeks of interview– Obstacles to ART adherence included:
• Fear medication would increase appetite (76%)• Interruption in daily schedule due to work (29%)• Not accepting HIV as life-threatening disease (28%)
Measuring ART adherence• No gold standard exists for measuring ART adherence• Commonly used measures
– Self-report (questionnaire and/or visual analogue scale)– Pharmacy refill records– Pill counts– MEMS (medication event monitoring systems)– Therapeutic drug monitoring– Clinician observation
• Few studies have validated self-report/pill count in resource-constrained settings
• CD4 count and viral load often used as objective indirect measures of ART adherence
Study objectives and methods
Study objectives
Among adults on ART for 6, 12, and 18 months as of September 2008-April 2009:
• Assess current ART adherence;
• Identify patient-level factors that are associated with current sub-optimal ART adherence;
• Identify site-level and contextual factors that are associated with current ART adherence, after adjusting for patient-level factors; and
• Compare current self-reported ART adherence, pill counts and pharmacy dispensing data as measures of ART adherence against CD4 cell count and viral load
Study design: Cross-sectional study of persons on ART with retrospective data collection
Data
Collection
6 month cohort
started ART
12 month cohort started
ART
18 month cohort
started ART
Sep 08-Apr 09-6
months
-12
months
-18
monthsTime on ART relative to data collection
Multistage sampling• Site sampling
– 113 public and faith-based clinics providing ART for >18 months in national ART program
• 20 sites randomly selected stratified by sector
– 14 public and 6 faith-based
• 7 private sites excluded
• Patient sampling
– 9,693 patients on ART for 6, 12, and 18 months at the 113 public and faith-based clinics
• 1,951 adult patients on ART for 6, 12, and 18 months at selected sites
• 1,798 randomly selected to participate in study
• Age ≥18 years
• Initiated 1st line ART at study site 6, 12 or 18 months prior to study start (+/- 2 months)
• Still receiving ART at initiating site
• Willing to provide informed consent
Patient eligibility criteria
Data collection
• Sept 08 – April 09
• 15 interviewers, 3 research coordinators
• 4 study assessments
– Patient interview
– Data abstraction
– Non-routine blood draw for viral load (~50% of sample)
– Site characteristics questionnaire
Patient questionnaire – 9 sections
• Socio-demographic information• Self-reported adherence• Side effects• Knowledge of and attitudes towards HIV/ART• Quality of life• Satisfaction and utilization of services• Psychosocial factors (e.g. disclosure, support)• Herbal, traditional and other medicine• Risky behaviors
Data abstraction – 6 sections• Demographic information
• Treatment information (regimen(s) and start dates)
• Medication pick-up (number of pills prescribed at last pick-up)
• Clinic visits (dates, WHO stage, weight and type of visit)
• Immunologic outcomes (CD4 counts)
• Patient status (alive and attending clinic, transferred out, died, LFU)
Viral load assessments• Done for ~50% of sample• Five cc blood drawn • Depending on distance of site from NRL:
– ≤4 hours: Samples transported directly to NRL in cool box– >4 hours: Centrifuged at site or nearby hospital and
transported on ice in cool box within 18 hours• Centrifuged samples aliquoted and stored at -70
degrees Celsius• Processed using real-time PCR
– Cobas TaqMan 48 with detection limit of 40 RNA copies / ML
Site assessment – 2 sections• Based on ICAP PFACTS tool
• Site and contextual characteristics– Location– Type of facility– HIV prevalence
• Facility characteristics – Funder– Care and treatment enrollment figures– Hours, facilities and staffing configuration– Availability and type of supportive services (e.g. food, adherence, peer
educators, outreach, home visits)
Measure Description Optimal adherence cut-off
Patient 3-day recall (self-reported)
• Abbreviated ACTG questions• For each medication, respondent indicated whether they took required pills during each of 3 days preceding interview
100% vs. ≤ 99% adherence
Patient 30-day recall(self-reported)
• Visual analogue scale (VAS) based on validated anchor line and ICAP-MZ pictorial scale• Patients presented with a line anchored using cups at 0 (empty cup) and 10 (full cup), provided with examples of what 0, 50 and 100% adherence would represent and asked to assess their own adherence for all ART medications over the past 30 days
100% vs. ≤ 99% adherence
Viral load Amount of plasma viral load copies at time of interview
≤ 40 vs. >40 copies/ML
Primary outcome measures
3-day self-reported adherence: Modified ACTG questions
Step One—Identification of antiretroviral medicationsIt looks like you’re supposed to take (read the names, color and shape of all of the antiretroviral drugs the patient is
supposed to take from Columns A, C and D). Is this correct? If not, ask the patient to show you their medication and complete the drug names in the table below.
Step Two—Self-reported adherence behavior for specific time periodsStarting with the drug in Row 1 and using the information in Columns A-E, say the following to complete cells B01-B04:
Now for (read drug name and describe the color and shape from Columns A, C and D), it looks like (read the number of pills per day in column E) pills of this medicine need to be taken each day.
Now think about yesterday. Of the (read the number of pills in column E) prescribed pills, how many did you miss
yesterday? Record this number in Column F. Now think about the day before that. That would have been (say the day of the week). Of the (read the number of
pills in column E) prescribed pills, how many did you miss on (say the day of the week)? Record this number in Column G.
Go back just one more day. That would have been (say the day of the week). Of the (read the number of pills in
column E) prescribed pills, how many did you miss? Record this number in Column H.
30-day self reported adherence: VAS
Additional outcome measures
• Self-reported treatment interruptions
– Number of times ever missed all pills for ≥3 consecutive days
• Drug possession ratio
– Data cleaning ongoing
– Only ~1/3 of sample brought pills to interview
• CD4 response
– Data cleaning ongoing
Preliminary Results
18 month cohort
N=495 (27.3%)
6 month cohort
N=701 (38.9%)
12 month cohort
N=602 (33.5%)
Started ART 6, 12 or 18 months prior to study start at selected sites, N=1951
Randomly selected for participation in study, N=1798
Determined to be ineligible, N=305
Confirmed to be eligible for study, N=1493 (100.0%)
Declined to participate, N=18 (1.2%) Not located by study team, N=37 (2.5%)
Enrolled in study, N=1438 (96.3%)
*The 1427 patients included in the analysis represent 95.5% of all patients confirmed to be eligible
Site characteristics, N=20 Characteristic N
Type of health facility Primary 13
Secondary 6
Tertiary 1
Location Urban 9
Rural 11
Sector Public 14
Faith-based 6
Funding partner PEPFAR 15
Global Fund 5
Payment / Fees Scheduled visits 0
Unscheduled visits 2
Lab tests 2
Patient socio-demographic characteristics
6 month N=577
12 month N=494
18 month N=356
Total N=1427 p-value
Female (%) 64.5 65.6 64.0 64.8 0.883 Mean age in years 37.5 37.5 37.1 37.4 0.774 Mean years of education 5.46 5.24 5.80 5.47 0.176 Religion (%) No religion 1.7 4.7 2.0 2.8 <0.001 Catholic 41.2 37.7 50.8 42.4 Other Christian 50.1 50.8 43.8 48.8 Muslim 6.9 6.9 3.4 6.0 Marital status (%) Married/living with partner 53.8 55.9 53.5 54.5 0.481 Separated/divorced 14.1 11.3 14.9 13.3 Widowed/not living with partner 22.0 25.1 22.5 23.2 Never married 10.1 7.7 9.0 9.0 Working (%) 33.4 30.8 35.7 33.1 0.317 Mean number of children ever born
3.5 3.64 3.62 3.59 0.961
Median CD4 count at ART initiation
12 months 18 months6 months
N=444N=497 N=326
Current ART regimens
N=575 N=355N=491
Self-reported 100% adherence: 3-day recall
12 months 18 months6 monthsN=493N=576 N=356
Timing of missed pills among patients reporting ≤100% adherence in 3 days preceding interview
N=38 N=23N=37
Followed dietary and timing instructions for taking ART in previous 3 days
6 months 18 months 12 months N=493N=576 N=356
Self-reported adherence: 30-day recall
0%
20%
40%
60%
80%
100%
6 months 12 months 18 months
≤80% adherent
90% adherent
100% adherent
N=575 N=489 N=352
30-day recall: Distribution of VAS responses
0
100
200
300
400
500
0 1 2 3 4 5 6 7 8 9 10
Num
ber o
f pati
ents
VASPoor adherence Good adherence
0
100
200
300
400
0 1 2 3 4 5 6 7 8 9 10
Num
ber o
f pati
ents
VASPoor adherence Good adherence
0
100
200
300
400
0 1 2 3 4 5 6 7 8 9 10
Num
ber o
f pati
ents
VASPoor adherence Good adherence
6 months, N=577 12 months, N=494
18 months, N=356
N=335 N=285 N=222
Current viral load
Association between self-reported 3-day adherence and viral load
0%
20%
40%
60%
80%
100%
6 months 12 months 18 months
% w
ith
un
det
ecta
ble
vir
al l
oad
100% adherent
<100% adherent
N=335 N=285 N=222
P<0.05
Association between self-reported 30-day adherence and viral load
0%
20%
40%
60%
80%
100%
6 months 12 months 18 months
% w
ith
un
de
tec
tab
le v
ira
l lo
ad
100% adherent
90% adherence
80% adherence
<80% adherent
N=335 N=285 N=222
P<0.05
Treatment interruptions among patients who ever missed ART
N=212 N=198 N=154
Most common reasons for ever missing ART
Least common reasons for ever missing ART
Most common side effects
Side effects considered “most bothersome”
Least common side effects
Side effects considered “least bothersome”
Attitudes towards ART6 month (N=577)
12 month (N=494)
18 month (N=356)
Total (N=1427) *
% agreeing with statement
ART can help people live longer 99.3 99.6 99.2 99.4
If people follow instructions about how to take ART, they will be healthier
99.0 100.0 98.9 99.3
If people stop taking ART, their illness will worsen
97.2 98.3 98.3 97.9
% disagreeing with statement HIV/AIDS is not a serious illness because PLWHA can take ART
57.1 61.4 62.9 60.0
ART is not worth taking because it has a lot of side effects
97.2 98.4 97.7 97.7
ART does not work as well as doctors and nurses say it will
96.5 96.9 97.5 96.9
People taking ART need to hide it from others
81.1 82.8 80.2 81.5
ART can cure HIV 56.7 55.0 55.2 55.7
* No significant differences between cohorts
Preliminary conclusions, strengths, limitations, and next steps
Preliminary conclusions• Self-reported adherence to ART is high among Rwandans remaining on ART
6, 12 and 18 months after ART initiation
• >80% of patients on ART have undetectable viral load
• Self-reported adherence and viral suppression do not vary by time on ART
• Some correlation between self-reported adherence (3 day and 30 day recall) and viral load
• High prevalence of non-specific side effects
– Well-tolerated in many instances
– Can’t directly attribute to ART (background prevalence unknown)
• Patients on ART have « positive » knowledge and attitudes about ART but also a few misconceptions
Study strengths• First nationally representative ART adherence study in Africa (worldwide?)
– Availability of virologic data on random subset of patients
• Obtained rapid estimates of adherence and risk factors at different time points after ART initiation (6, 12, 18 months) among patients currently on ART
• Multiple direct and indirect ART adherence measures used
• Varied patient-level predictors of adherence assessed, including include clinical, socio-demographic, psycho-social and behavioral factors
• Multi-site (n=20) nature allows assessment of association of site-level factors with adherence measures
• Provides rich dataset on other important outcomes related to ART scale-up, e.g. risky behaviors, quality of life, etc.
• Multi-institutional collaboration with capacity building (e.g., GCP and analysis training)
Study limitations• Limited to adults
• Did not include private clinics (n=7)
• Only one time point measured per patient
– Could not examine adherence as a predictor of death or LTF
– i.e., could not estimate within individual variation in adherence over time (reliability)
• Did not include provider perspective
• Pill count could not be done for ~2/3 of patients
• Definition of adherence not predicated on patient taking pills at right time or in right way
• Different questions used for 3-day and 30-day recall (ACTG vs. VAS)
Next steps• Analysis, analysis, analysis!!!
– Triangulation and correlation of different direct and indirect adherence measurements
– Examine patient- and provider-level predictors of ART adherence– Conduct other analyses, e.g. changing characteristics of patients on ART,
determinants of
• Broader input from ICAP community on interpretation of results and policy implications
• Develop program and policy recommendations– Interventions and target populations, strategies for routine measurement of ART
adherence
• In-country dissemination– Complete study report – Hold national dissemination meeting
AcknowledgementsPrincipal Investigators
Batya Elul (ICAP)Anita Asiimwe (CNLS)
Co-Investigators Paulin Basinga (RW SPH), Jules Mugabo (TRACPlus), Harriet Nuwagaba-Biribonwoha (ICAP), Deb Horowitz (ICAP), Veronicah Mugisha (ICAP), Etienne Rugigana (RW SPH), Stephania Koblavi-Deme (ICAP), Richard Nkunda (NRL), Eugenie Kayirangwa (CDC-RW), Denis Nash (ICAP)
Research Coordinators
Celestine Nyagatare (ICAP), Parfait Uwaliraye (RW SPH), Vincent Mutabazi (TRACPlus)
Data team Thierry Rusingiza (ICAP), Interviewers, Interviewer Supervisors, Data Entry Clerks
Logistics Njeri Micheu (ICAP), Jean d’Amour Habagusenga (RW SPH), ICAP and RW SPH admin and finance staff
Policy and program guidance
Ruben Sahabo (ICAP), Peter Twyman (ICAP)
Assistance with analysis and slide preparation
Suzue Saito, Amanda Farr