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Aspects of tuberculosis and HIV diagnosis, care and treatment in Rwandan health facilities:operational studies
Kayigamba, R.F.
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Citation for published version (APA):Kayigamba, R. F. (2014). Aspects of tuberculosis and HIV diagnosis, care and treatment in Rwandan healthfacilities: operational studies.
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Download date: 12 Mar 2020
123
Chapter 8
Discordant treatment responses to combination antiretroviral therapy are common in Rwanda: a prospective cohort study
Felix R Kayigamba,1 Molly F Franke,2,3 Mirjam I Bakker,4 Emmanuel Bagiruwigize,1
Ferdinand WNM Wit, 5,6 Michael L Rich,2,3,7 Maarten F Schim van der Loeff 5,6,8
Affiliations: 1. INTERACT, CPCD, PO Box 2181, Kigali, Rwanda; 2. Department of Global
Health and Social Medicine, Harvard Medical School, Boston, MA, USA; 3. Partners In
Health/Inshuti Mu Buzima, Rwinkwavu, Rwanda; 4. Royal Tropical Institute, KIT Biomedical
Research, Amsterdam, the Netherlands; 5. Amsterdam Institute for Global Health and
Development (AIGHD), Amsterdam, the Netherlands; 6. Center for Infection and Immunity
Amsterdam (CINIMA), Academic Medical Center (AMC), Amsterdam, the Netherlands; 7. Division
of Global Health Equity, Brigham and Women’s Hospital, Boston, MA, USA; 8. Public Health
Service of Amsterdam (GGD), Amsterdam, the Netherlands.
Submitted
124
Abstract Background Some anti-retroviral therapy naïve patients starting combination anti-retroviral therapy
(cART) experience a limited CD4 count rise despite virological suppression, or vice
versa. We assessed the prevalence and determinants of discordant treatment responses in
a Rwandan cohort.
Methods A discordant immunological cART response was defined as an increase of <100 CD4
cells/mm3 at 12 months compared to baseline in spite of full virological suppression
(viral load <40 copies/mL). A discordant virological cART response was defined as
detectable viral load at 12 months in combination with an increase in CD4 count ≥100
cells/mm3. The prevalence of, and independent predictors for these two types of
discordant responses were analysed in two cohorts nested in a 12-month prospective
study of cART-naive HIV patients treated at nine rural health facilities in two regions in
Rwanda.
Results Among 382 patients with an undetectable viral load at 12 months, 112 (29%) had a CD4
rise of <100 cells/mm3. Age ≥35 years (P=0.002) and longer travel times to the clinic
(P=0.02) were independent determinants of an immunological discordant treatment
response, but sex, baseline CD4 count, BMI, and WHO stage were not. Among 326
patients with a CD4 rise of ≥100 cells/mm3, 56 (17%) had a detectable viral load at 12
months. Female sex was negatively associated with a virological discordant treatment
response (P=0.05), but age, baseline CD4 count, BMI, WHO stage, and travel time were
not.
Conclusions Discordant treatment responses were common in cART-naïve HIV patients in Rwanda.
In programs without viral load monitoring a limited increase in CD4 count after 12
months of therapy could be misinterpreted as a (virological) treatment failure and lead to
unnecessary treatment changes.
Key words: HIV; ART; cART; combination antiretroviral treatment; CD4 count;
adherence; viral load; discordant response; Africa; Rwanda.
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Background The aim of combination antiretroviral therapy (cART) is to suppress plasma viral load to
undetectable levels. The usual median time to achieve full viral suppression is about 100
days [1,2]. Most HIV patients, both in high-income and in resource-poor countries, also
display an immunological response to treatment, measured as an increase in the CD4
count [3-5]. In 14-25% of patients the CD4 count does not rise substantially in spite of
successful viral suppression [1,6-9]. This phenomenon has been named an
immunological discordant treatment response.
Studies have reported an increased incidence of AIDS events or death among those with
such discordant responses [1,6,8-11]. The mortality risk among immunological discordant
responders is between that of complete responders and that of complete non-responders
[6,8]. Therefore discordant treatment responses are regarded as suboptimal treatment
outcomes.
Older age and lower baseline viral load have consistently been shown to be associated
with discordant response [1,6,7,9]. A study conducted in Canada found that low
adherence and lamivudine or zidovudine containing regimens were associated with a
discordant response [6]. Studies examining the relationship between baseline CD4 cell
count and discordant response show conflicting results, with some reporting a positive
association between low CD4 count and a discordant treatment response [1,6,12], and
others showing a positive association between high CD4 cell count and discordant
treatment response.[7,9] Most studies on discordant responses have been done in cohorts
from high-income countries.
Another type of discordant treatment response is a good immunological response despite
incomplete suppression of viral replication. This type of response was found to be
associated with a history of injecting drug use, a very high baseline HIV viral load, and
with poor adherence [6]. Those with a discordant virological response have a higher
mortality risk [6,8,10,11], and also this response is regarded as a suboptimal treatment
response.
126
Rwanda is one of only three countries in sub-Saharan Africa with a generalised HIV
epidemic where over 90% of ART eligible HIV patients are on cART [13]. A dense
network of clinics and hospitals provide HIV care and treatment, free of cost [14]. We
studied the frequency of discordant treatment responses in a cohort of cART-naïve HIV
patients starting cART in Rwanda, and to assess which factors were determinants of a
discordant response in this setting.
Methods From a prospective study of 610 ART-naïve HIV infected patients starting cART at nine
health facilities in Rwanda [15] we identified two nested cohorts of patients in which we
could do analyses of two different types of discordant treatment response.
A detailed description of the study methods and of treatment outcomes of the full cohort
has been published [15]. In brief, patient enrollment started in June 2007 and ended in
August 2008. Inclusion criteria were: (1) documented HIV infection; (2) starting cART at
one of the nine selected Ministry of Health (MOH) centers in the two study regions; (3)
residence in one of the study regions for at least the past one year. Patients were excluded
if their CD4 count was above 350 cells/mm3 at the time of cART initiation, if they were
aged less than 21 years or if they had previously initiated cART. An exception to this
latter criterion was made for women who had received short term antiretrovirals to
prevent mother to child transmission of HIV in the past.
Standard of care for cART cART was provided free-of-charge to all individuals who met Rwanda MOH eligibility
criteria [16]. The first-line cART regimen for HIV-infected individuals consisted of either
stavudine or zidovudine, plus lamivudine and nevirapine. Efavirenz replaced nevirapine
in individuals who were receiving tuberculosis (TB) treatment. Co-trimoxazole was
routinely prescribed to individuals with CD4 cell counts <350 cells/mm3 or World
Health Organization (WHO) HIV disease stage 3 or 4 [17]. CD4 cell counts were
routinely measured prior to initiation of cART. All patients were urged to disclose their
HIV status to at least one family member or friend and also identify a “treatment buddy”
in order to facilitate treatment adherence. At five of the nine health centers, patients
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additionally received community-based social support from community health workers
(including directly observed treatment), nutritional support, transportation stipends, and
other support as needed [15].
Data collection A baseline clinical exam was done just before cART initiation for all patients enrolled
into the study. A trained health worker from the health facility completed a standardized
intake form. Data collected included age, sex, marital status, literacy, study site, patient
travel time to the clinic, weight and height, baseline CD4 cell count, WHO HIV disease
stage, cART start date, antiretroviral regimen, and whether patient was being treated for
TB at the time of initiation of cART. CD4 cell count measurements were done both at
baseline and after 12 months, using the FACS Count system (Becton Dickinson TM, La
Pont de Claix, France). Plasma viral load measurement was done only after 12 months of
cART, using the Cobas TaqMan 48 Analyzer (Roche, Geneva, Switzerland); the
threshold level for detection of VL was 40 copies/mL. During monthly clinic visits
patients were examined. When opportunistic infections were diagnosed, these were
treated. Treatment regimen changes were made where necessary e.g. in case of
pregnancy, treatment for TB, or adverse effects. Adherence was assessed 3 months and
12 months after the start of cART, using the validated Center for Adherence Support
Evaluation (CASE) adherence index. This index is a simple composite measure of self-
reported ART adherence, based on three adherence questions [18]. The theoretical score
range is from 3 to 16, however pilot data suggested that participants had difficulty
distinguishing between two response categories: missing a dose an average of “zero times
per week” and “less than once a week”. We therefore combined these response
categories for a total maximum score of 15. A CASE index score of 10 or less indicates
suboptimal adherence [18].
Selection of nested cohorts
Of the 610 patients included in the full cohort, 35 (6%) had died at the end of the 12-
month observation period, 13 (2%) had defaulted; 15 (3%) had been transferred to other
clinics, and 547 patients were retained in care at 12 months (Figure 1). From 17 (3%) of
these 547 no VL measurement was available; the baseline CD4 count was done more
than 7 days after start of cART in 3 patients (1%); from 22 (4%) no CD4 count was
available at the 12-month time point; and from 39 patients (7%) the dates of the end-of-
128
observation period CD4 count and VL measurement were more than 60 days apart.
Thus, of 466 patients still in care at 12 months essential measurements were available.
Nested Cohort 1 consisted of patients who had undetectable viral load at 12 months
(n=382). Nested Cohort 1 allowed us to study what we here refer to as “immunological
cART discordance”. An immunological discordant cART response was defined as an
increase of <100 CD4 cells/mm3 at 12 months compared to baseline in spite of full
virological suppression (VL<40 copies/mL).
Nested Cohort 2 consisted of patients enrolled in the prospective study who had
experienced an increase in CD4 count of 100 cells/mm3 or more at 12 months compared
to baseline (n=326). Nested Cohort 2 allowed us to examine a less common type of
discordant cART treatment response and what we refer here to as “virological cART
discordance”. A virological discordant response was defined as an increase of CD4 count
of 100 cells/mm3 or more in the first 12 months and incomplete viral suppression at
month 12.
Statistical analysis Univariable logistic regression analysis was done to identify factors that were associated
with discordant treatment responses. Subsequently, multivariable logistic regression (by
step-wise elimination of variables) was performed to identify independent determinants
of a discordant treatment response. The variables sex, age, CD4 count at baseline and
region were retained in the model irrespective of their associated P values. Other
variables were included into a starting model if they were associated with the outcome at
P<0.20 in univariable analysis. These variables were dropped one by one, based on a
criterion of P<0.05, using the likelihood ratio test, until a parsimonious model was
obtained.
In a secondary analysis, we examined whether adherence to cART, assessed 3 months
(+/- 1 month) after the start of cART, was predictive of discordant treatment responses,
in univariable and multivariable models.
129
All reported P values were two-sided. P values <0.05 were considered statistically
significant. All analyses were done using Stata software version 11 (StataCorp, College
Station, Texas, USA). Ethical approval The study protocol was approved by the Rwanda National Ethics Committee Kigali,
Rwanda and the Partners Human Research Committee, Boston, USA. All individual
patients recruited into the study signed consent forms before they were enrolled. Data
were double entered into an electronic medical record system (OpenMRS) that was
password protected and patient identification codes instead of patient names were used
during analysis to ensure the patients’ confidentiality.
Results Of the 466 were retained in care after 12 months and who had a 12-month viral load and
CD4 count measurement done 140 patients had a CD4 rise less than 100 cells/mm3
(Table 1). Of these, 112 had an undetectable viral load and 28 had a detectable viral load.
Only seven of those 28 had a viral load of 1,000 copies/mL or above. Thus, of patients
identified with a limited CD4 rise after 12 months, only 5% (7/140; 95%CI 2-10%) had
virological failure (here defined as viral load ≥1,000 copies/mL).
Analysis of immunological discordant treatment responses: nested cohort 1 Table 2 shows the baseline characteristics of nested cohort 1, alongside the
characteristics of the full cohort. The median age (interquartile range [IQR]) was 37 (32-
44) years and 64% of patients were female. About two-thirds were literate, and 59% were
married or cohabiting. The median (IQR) CD4 count at baseline was 240 (150-295)
cells/mm3. Forty-six percent (177/382) of patients were in WHO stage 3 or 4 at the start
of the treatment. The median time between baseline CD4 count and the date of start of
cART was 22 (9-41) days.
Table 3 shows the follow-up data of nested cohort 1, next to the data of the full cohort
for comparison. The median (IQR) CD4 count at 12 months was 390 (179-502)
cells/mm3 and the median increase between the baseline CD4 count and the 12-month
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CD4 count was 163 (87-259) cells/mm3. The median time between the start of cART
and the 12 month CD4 count was 364 days (IQR 357-373).
Of the 382 patients in nested cohort 1, 112 (29%) had a rise in CD4 cell count of less
than 100 cells/mm3 between baseline and 12-month measurements. In univariable
analysis, only older age was significantly associated with an immunological discordant
treatment response (Table 4). In multivariable analysis, older age (P=0.002), and having a
longer travel time to the clinic (P=0.02) were significantly associated with an
immunological discordant treatment response. Those from the Kayonza/Kirehe region
were less likely to have a discordant treatment response; this was close to statistical
significance (P=0.07). There was no association between baseline CD4 count and an
immunological discordant treatment response (P=0.9), and none of the other
demographic or health factors were associated with an immunological discordant
response (Table 4).
Of the 382 patients included in the analysis of an immunological discordant treatment
response, 326 (85%) had a 3-month adherence measurement. Adherence was assessed at
a median of 85 days (IQR 82-98) after the start of cART. In univariable analysis good
adherence was not significantly associated with a lower risk for a discordant treatment
response (OR=0.5, 95%CI 0.3-1.2). When adherence was added to the multivariable
model obtained in the primary analysis, good adherence was not significantly associated
with a lower odds of a discordant treatment response (aOR=0.5, 95%CI 0.2-1.1,
P=0.09). The effect size of all other variables in the model only changed marginally (data
not shown).
Analysis of virological discordant treatment responses: nested cohort 2 Table 2 shows the baseline characteristics of nested cohort 2, alongside the
characteristics of the full cohort and those of nested cohort 1. The median age
(interquartile range [IQR]) was 36 (31-44) years and 63% of patients were female. About
two-thirds were literate, and 59% were married or cohabiting. The median (IQR) CD4
count at baseline was 239 (155-294) cells/mm3. Forty-six percent (149/326) of patients
were in WHO stage 3 or 4 at the start of the treatment. The median time between
baseline CD4 count and the date of start of cART was 22 (9-42) days.
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Table 3 shows the follow-up data of nested cohort 2, next to the data of the full cohort
and of nested cohort 1 for comparison. The median (IQR) CD4 count at 12 months was
454 (362-541) cells/mm3 and the median increase between the baseline CD4 count and
the 12-month CD4 count was 206 (156-297) cells/mm3; by definition, all had an increase
in CD4 count of at least 100 cells/mm3. The median time between the start of cART and
the 12 month CD4 count was 364 days (IQR 356-373).
Of the 326 patients in nested cohort 2, 56 (17%) did not have a fully suppressed viral
load. In univariable analysis women had a significantly lower risk for a virological
discordant response (OR=0.5, 95%CI 0.3-1.0), but none of the other variables were
associated with a virological discordant response (Table 5). In multivariable analysis,
including (a priori) age, sex, baseline CD4 count and region, none of the variables, were
significantly associated with a discordant virological response (Table 5), although female
sex was of borderline significance (P=0.05).
Sixteen of the 326 patients in nested cohort 2 (5%) had a viral load of 1,000 copies/mL
or above. We also assessed determinants of a discordant treatment response defined in
this less strict way. No significant determinants of such a discordant treatment response
were identified, but power was limited.
An adherence measurement was available for 278 (85%). In univariable analysis good
adherence at 3 months was not associated with a virological discordant treatment
response (OR=0.7, 95%CI 0.3-2.1). When we added adherence to the previously
obtained multivariable model, good adherence was not a significant determinant of this
type of discordant treatment response (OR=0.6, 95%CI 0.2-2.0; P=0.5); the effect of the
other variables did not change substantially (data not shown).
Discussion
Among patients with a CD4 rise less than 100 cells/mm3, 20% had a detectable viral
load, but only 5% had virological failure defined as viral load>1,000 copies/mL.
Conversely, 17% of patients with a CD4 rise of 100 cells/mm3 or more, did not have a
fully suppressed viral load. Together, these results indicate the poor predictive value of a
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rise of the CD4 count for virological suppression. Discordant treatment responses (i.e.,
the absence of an adequate immunological response despite an undetectable viral load or
vice versa) were observed in 36% of cART-naïve HIV patients in Rwanda, 12 months
after start of cART. Older age and long travel distance to the clinic were associated with
an immunological discordant treatment response.
The frequency of immunological discordant treatment response in this study population
was higher than that observed in several other studies, where the proportion ranged
between 14% and 25% [1,6-9]. Immunological discordant treatment response remains an
unsolved challenge to physicians involved in long term HIV care and treatment. In
agreement with most other studies [1,6,7,9,11,12] we found that older age was a
significant risk factor for immunological discordant treatment responses. The degree of
immune restoration is dependent on the thymic function; as thymic function decreases
with age [11,19,20], this may explain why older people are at higher risk of incomplete
immune restoration. All our patients were on a regimen including a non-nucleoside
reverse transcriptase inhibitor (NNRTI; mostly nevirapine), which is known to be
associated with a lower CD4 increase after the start of cART [21].
Most studies found that low VL at start of cART was associated with immunological
discordant treatment responses [6,7,9,12], but as we did not have baseline VL available,
we could not assess this in our cohort. Regarding the effect of baseline or nadir CD4
count, studies have provided contradictory results. Some [1,6,12] found that a low
baseline or nadir CD4 count was predictive of immunological discordant treatment
responses, while others [7,9] found the reverse, and some studies found no association
between baseline CD4 count and immunological discordant treatment response [10,11].
In our cohort we did not observe any effect of baseline CD4 count on discordant
treatment responses. The remarkable finding from several studies that a higher baseline
CD4 count is a significant predictor of a discordant treatment response is probably due
to regression to the mean. Due to random variation in the measurement of CD4 counts
and due to individual variation of CD4 counts, those with the highest CD4 counts are
bound to have lower CD4 counts upon subsequent measurements even in the absence of
any intervention [8,22]. The median CD4 count in our study population was not very low
(231 cells/mm3), so one might have expected this phenomenon to occur in our study as
well, but this was not observed.
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We also found that an immunological discordant treatment response was more common
in patients who had to travel more than two hours to the clinic. This was not explained
by a lower adherence among them (data not shown). A possible explanation could be the
circadian rhythm of the CD4 counts: CD4 counts are lowest around noon and peak early
in the morning. If those who had to travel the longest had their blood drawn at noon,
that might lead to an observed lower CD4 count. However, we did not see such trends in
the baseline CD4 counts (data not shown).
The other type of discordant treatment response - incomplete suppression of viral
replication but a good immunological response - was observed in 15% of patients with a
CD4 rise of 100 cells/mm3 or more. We could not identify any independent determinants
of such discordant treatment response. The interpretation of these data is not
straightforward, as the viral load might have become detectable just because of a brief
interruption of therapy. Most of the patients with detectable viral load (71%; 40/56) had
VL <1,000 copies/ml . We only had a single viral load measurement, so we could not
distinguish between transient viremia or full-blown prolonged viremia associated with
poor adherence or resistance. Nevertheless, these data underscore that clinicians should
be equally careful not to switch cART too early because of transient viremia not
associated with resistance.
In many ART programs in Africa no VL monitoring is done. In such programs limited
CD4 count rises might be erroneously interpreted as treatment failure and patients may
subsequently be switched to second line regimens. In our study only 5% of patients with
a limited CD4 rise after 12 months had virological failure (VL ≥1,000 copies/mL). This
suggests that in most such cases the (costly) treatment change is unnecessary. Point-of-
care VL tests are needed to avoid this; in public health clinics such tests could
differentiate between ART failure and a (less threatening) discordant treatment response.
Nevertheless, both discordant treatment responses are associated with poorer outcomes
[6,8,10,11], and should, if diagnosed, be regarded as a danger sign to the clinician.
Limitations Our study has several limitations. We did not have baseline VL measurements and for
the definition of viral success we relied on a single VL determination at around 12
134
months after the start of cART. If that single VL determination was not representative of
the VL over time in a particular patient, misclassification might have occurred, regarding
some patients as virological responders who in fact were not having a complete
virological response to therapy and vice versa. Furthermore, a single viral load
measurement of more than 1,000 copies/mL does not infallibly identify the development
of viral resistance to the anti-retroviral therapy used. A high viral load can be caused by
temporary treatment interruptions, for instance by stock-outs, and the viral load is usually
quickly and fully re-suppressed after re-initiation of cART. Also, we relied on only one
CD4 count at around 12 months. Daily fluctuations in CD4 counts and fluctuations
induced by opportunistic infections are common, so this may have lead to another
misclassification, in two directions: regarding some persons unfairly as immunological
non-responders and others unfairly as immunological responders. So long as the
misclassification was not associated with the predictors under study, we would expect it
to lead to underestimations of the true associations. This misclassification might have
reduced power to detect significant associations with baseline variables.
Conclusion Immunological discordant treatment response (no adequate immunological response
despite a good virological response) was observed in 29% of ART-naïve HIV patients in
Rwanda, 12 months after start of cART. Older age was a predictor for immunological
discordance, but low baseline CD4 count was not. When viral load monitoring is not
done (as is the case in many ART programs in sub-Saharan African countries), a limited
increase of the CD4 count after 12 months could be misinterpreted as a (virological)
treatment failure and lead to unnecessary changes to more expensive second-line ART
regimens. Development and implementation of low-cost point of care VL tests should be
prioritized.
Acknowledgements We acknowledge and thank the Doris Duke Charitable Foundation for financial support
of this research. Technical support was provided by the Infectious Disease Network for
Treatment and Research in Africa (INTERACT), funded by the Netherlands
Organization for Scientific Research/Netherlands Foundation for the Advancement of
Tropical Research (NWO/WOTRO) and the European Union (SANTE/2006/105-316).
135
We are grateful to the study staff: Adrienne Socci, Massudi Hakizamungu, Wellars
Ndayambaje, Eline Uwitonze, Albertine Mukeshimana, Ernest Nyirinkindi, Jean
Damascene Uwamuhoro, Carine Dusenge, Claire Dusabe, and Jean Claude Nyiramana.
We also thank Cheryl Amoroso, Benjamin Akimana, Christian Allen, Darius Jazayeri,
Ellen Ball, the Rwanda-based PIH-EMR team, and Laboratory Management of the
Rwanda National Reference Laboratory. Thanks to Frank Cobelens for providing
feedback on a draft of this ms.
Competing interests The authors declare that they have no competing interests.
Authors' contributions Study design [FK; MF; AS; MR]; recruitment and follow-up [FK;MF; AS; MH; EB]; data
management [MF; EB]; data analysis [FK; MSVDL]; wrote the first draft [FK;MSVDL];
contributed to the manuscript & analysis [all authors]; saw and approved final version [all
authors].
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139
Tabl
e 1.
Viro
logi
cal a
nd im
mun
olog
ical
trea
tmen
t res
pons
es a
mon
g 46
6 pa
tient
s ret
aine
d in
car
e at
12
mon
ths a
nd w
ith fu
ll da
ta, R
wan
da, 2
007-
2008
Vi
ral L
oad
<4
0 co
pies
/mL
= N
este
d Co
hort
1
≥40
copi
es/m
L Al
l
CD4
incr
ease
<1
00 c
ells/
mm
3 11
2 28
14
0 ≥1
00 c
ells/
mm
3 =
Nes
ted
Coho
rt 2
27
0 56
32
6
All
382
84
466
140
Tabl
e 2:
Bas
elin
e ch
arac
teris
tics o
f nes
ted
coho
rts 1
and
2 a
nd o
f the
full
coho
rt o
f 610
HIV
infe
cted
pat
ient
s sta
rtin
g cA
RT, R
wan
da, 2
007-
2008
Fu
ll Co
hort
N
=610
Nes
ted
Coho
rt 1
(fo
r the
ana
lysi
s of
imm
unol
ogic
al d
isco
rdan
t cA
RT re
spon
se)
N=3
82
Nes
ted
Coho
rt 2
(fo
r the
ana
lysi
s of
viro
logi
cal d
isco
rdan
t cAR
T re
spon
se)
N=3
26
Age
M
edia
n ag
e (IQ
R) in
yea
rs
37 (3
1-45
) 37
(32-
44)
36 (3
1-44
) 20
-34
year
s 23
7 (3
8.9%
) 14
8 (3
8.7%
) 14
4 (4
4.2%
) 35
-44
year
s 22
0 (3
6.1%
) 13
9 (3
6.4%
) 11
0 (3
3.7%
) ≥4
5 ye
ars
153
(25.
1%)
95 (2
4.9%
) 72
(22.
1%)
Sex
M
ale
234
(38.
4%)
139
(36.
4%)
122
(37.
4%)
Fem
ale
376
(61.
6%)
243
(63.
6%)
204
(62.
6%)
Lite
racy
Una
ble
to re
ad
203
(33.
3%)
131
(34.
3%)
113
(34.
7%)
Able
to re
ad
407
(66.
7%)
251
(65.
7%)
213
(65.
3%)
Mar
ital s
tatu
s
S
ingl
e 28
(4.6
%)
16 (4
.2%
) 16
(4.9
%)
M
arrie
d/co
habi
ting
351
(57.
8%)
221
(58.
9%)
193
(59.
2%)
D
ivor
ced/
sepa
rate
d 60
(9.9
%)
38 (1
0.0%
) 33
(10.
1%)
W
idow
ed
168
(27.
7%)
107
(28.
0%)
84 (2
5.8%
)
Miss
ing
3 --
-- CD
4 co
unt a
t bas
elin
e
Med
ian
CD4
(IQR)
cel
ls/m
m3
231
(148
-289
) 24
0 (1
50-2
95)
239
(155
-294
) <1
00 c
ells/
mm
3 91
(14.
9%)
53 (1
3.9%
) 43
(13.
2%)
100-
199
cells
/mm
3 14
9 (2
4.4%
) 82
(21.
5%)
78 (2
3.9%
)
141
200-
350
cells
/mm
3 37
0 (6
0.7%
) 24
7 (6
4.7%
) 20
5 (6
2.9%
) M
edia
n tim
e (IQ
R) in
day
s CD4
cou
nt -
star
t cAR
T*
22 (9
-41)
22
(9-4
1)
23 (9
-42)
W
HO S
tage
at b
asel
ine
1
117
(19.
2%)
73 (1
9.2%
) 61
(18.
8%)
2 19
6 (3
2.2%
) 13
1 (3
4.4%
) 11
5 (3
5.4%
) 3
281
(46.
1%)
168
(44.
1%)
139
(42.
8%)
4 15
(2.5
%)
9 (2
.4%
) 10
(3.1
%)
Miss
ing
1
1 1
BMI a
t bas
elin
e in
kg/
m2
M
edia
n BM
I 20
.7 (1
8.6-
22.7
) 20
.7 (1
8.7-
22.7
) 20
.8 (1
8.8-
22.9
) <1
8.5
151
(25.
0%)
87 (2
2.9%
) 69
(21.
3%)
18.5
-24.
9 39
8 (6
5.8%
) 25
7 (6
7.6%
) 22
4 (6
9.1%
) ≥2
5 56
(9.3
%)
36 (9
.5%
) 31
(9.6
%)
Miss
ing
5
2 2
On
TB tr
eatm
ent a
t sta
rt o
f cAR
T
N
o 58
5 (9
6.2%
) 36
6 (9
6.1%
) 31
3 (9
6.3%
)
Yes
23
(3.8
%)
15 (3
.9%
) 12
(3.7
%)
M
issin
g 2
1 1
ARV
regi
men
A
ZT, 3
TC, N
VP
153
(25.
2%)
93 (2
4.4%
) 76
(23.
5%)
d
4T, 3
TC, N
VP
398
(65.
6%)
254
(66.
7%)
218
(67.
3%)
A
ZT, 3
TC, E
FV
38 (6
.3%
) 24
(6.3
%)
19 (5
.9%
)
d4T
, 3TC
, EFV
18
(3.0
%)
10 (2
.6%
) 11
(3.4
%)
M
issin
g 3
1 2
Trav
el ti
me
to c
linic
<30
min
utes
12
9 (2
1.4%
) 78
(20.
5%)
62 (1
9.1%
) Be
twee
n 30
& 6
0 m
inut
es
148
(24.
5%)
93 (2
4.4%
) 83
(25.
5%)
142
Betw
een
1 &
2 h
ours
18
6 (3
0.8%
) 12
4 (3
2.6%
) 11
3 (3
4.8%
) >
2 ho
urs
141
(23.
3%)
86 (2
2.6%
) 67
(20.
6%)
Miss
ing
6
1 1
Regi
on
Ru
heng
eri
306
(50.
2%)
197
(51.
6%)
163
(50.
0%)
Kayo
nza/
Kire
he
304
(49.
8%)
185
(48.
4%)
163
(50.
0%)
Nes
ted
Coho
rts 1
and
2 a
re n
ot m
utua
lly e
xclu
sive
coho
rts,
patie
nts m
ay b
e in
clud
ed in
bot
h. N
umbe
rs a
re n
(%) o
r Med
ian
(IQR)
unl
ess i
ndic
ated
ot
herw
ise. H
IV H
uman
imm
unod
efic
ienc
y vi
rus;
cAR
T Co
mbi
natio
n an
tiret
rovi
ral t
reat
men
t; BM
I Bod
y m
ass i
ndex
; IQ
R In
ter-
quar
tile
rang
e; W
HO W
orld
He
alth
Org
aniza
tion;
N N
umbe
r; AZ
T zid
ovud
ine;
3TC
lam
ivud
ine;
d4T
stav
udin
e; N
VP n
evira
pine
; EFV
efa
vire
nz. *
Med
ian
time
(IQR)
in d
ays b
etw
een
base
line
CD4
coun
t and
dat
e st
art o
f ART
.
143
Tabl
e 3:
Fol
low
-up
data
of 6
10 H
IV p
atie
nts o
n cA
RT, R
wan
da, 2
007-
2008
Full
coho
rt
N=6
10
Nes
ted
Coho
rt 1
N
=382
N
este
d Co
hort
2
N=3
26
CD4
coun
t at 1
2 m
onth
s
Med
ian
CD4
(IQR)
cel
ls/m
m3
392
(275
-507
) 39
0 (1
79-5
02)
454
(362
-541
) <1
00 c
ells/
mm
3 12
(2.3
%)
7 (1
.8%
) --
100-
199
cells
/mm
3 47
(9.0
%)
32 (8
.4%
) 12
(3.7
%)
200-
349
cells
/mm
3 14
5 (2
7.7%
) 11
0 (2
8.8%
) 57
(17.
5%)
350-
449
cells
/mm
3 18
2 (3
4.8%
) 13
4 (3
5.1%
) 14
1 (4
3.3%
) ≥5
00 c
ells/
mm
3 13
7 (2
6.2%
) 99
(25.
9%)
116
(35.
6%)
Miss
ing
87
--
Di
ffere
nce
in C
D4 c
ount
bet
wee
n ba
selin
e an
d 12
mon
ths
M
edia
n di
ffere
nce
(IQR)
cel
ls/m
m3
163
(84-
258)
16
3 (8
7-25
9)
206
(156
-297
) <0
cel
ls/m
m3
30 (5
.7%
) 20
(5.2
%)
-- 0-
99 c
ells/
mm
3 12
7 (2
4.3%
) 92
(24.
1%)
-- 10
0-19
9 ce
lls/m
m3
167
(31.
9%)
126
(33.
0%)
155
(47.
6%)
200-
299
cells
/mm
3 10
2 (1
9.5%
) 74
(19.
4%)
90 (2
7.6%
) ≥3
00 c
ells/
mm
3 97
(18.
6%)
70 (1
8.3%
) 81
(24.
9%)
Miss
ing
87
--
Vira
l loa
d af
ter 1
2 m
onth
s of t
reat
men
t
Med
ian
VL (I
QR)
cop
ies/
mL
39.9
(39.
9-39
.9)
39.9
(39.
9-39
.9)
39.9
(39.
9-39
.9)
<40
copi
es/m
L 43
0 (8
1.1%
) 38
2 (1
00.0
%)
270
(82.
8%)
40-9
99 c
opie
s/m
L 71
(13.
4%)
- 40
(12.
3%)
1,00
0-9,
999
copi
es/m
L 16
(3.0
%)
- 10
(3.1
%)
≥10,
000
copi
es/m
L 13
(2.5
%)
- 6
(1.8
%)
Miss
ing
vira
l loa
d
80
- --
Out
com
e at
12
mon
ths f
ollo
w-u
p
144
Died
35
(5.7
%)
-- --
Defa
ulte
d 13
(2.1
%)
-- --
Tran
sfer
red
out
15 (2
.5%
) --
-- Re
tain
ed in
car
e, u
ndet
ecta
ble
vira
l loa
d 43
0 (7
0.5%
) 38
2 (1
00.0
%)
270
(82.
8%)
Reta
ined
in c
are,
det
ecta
ble
vira
l loa
d 10
0 (1
6.4%
) --
56 (1
7.2%
) Re
tain
ed in
car
e bu
t no
vira
l loa
d m
easu
red
done
at 1
2 m
o 17
(2.8
%)
-- --
Med
ian
time
(IQR)
bet
wee
n ba
selin
e &
12
mo
CD4
coun
t in
days
38
6 (3
72-4
13)
386
(372
-412
) 39
1 (3
72-4
11)
Med
ian
time
(IQR)
bet
wee
n st
art o
f cAR
T &
12
mo
VL in
day
s 36
6 (3
61-3
74)
366
(361
-374
) 36
6 (3
61-3
74)
Med
ian
time
(IQR)
bet
wee
n st
art o
f cAR
T &
12
mo
CD4
coun
t in
days
36
4 (3
56-3
74)
364
(357
-373
) 36
4 (3
56-3
73)
Num
bers
in T
able
are
N (%
), un
less
men
tione
d ot
herw
ise. H
IV H
uman
imm
unod
efic
ienc
y vi
rus;
cAR
T co
mbi
natio
n an
tiret
rovi
ral t
reat
men
t; IQ
R In
ter-
quar
tile
rang
e; N
Num
ber;
mo
mon
th; V
L Vi
ral l
oad.
145
Tabl
e 4:
Ana
lysi
s of d
eter
min
ants
of i
mm
unol
ogic
al d
isco
rdan
t tre
atm
ent r
espo
nses
(CD4
cou
nt ri
se <
100
cells
/mm
3 des
pite
com
plet
e vi
rolo
gica
l su
ppre
ssio
n) in
Nes
ted
Coho
rt 1
, Rw
anda
, 200
7-20
08
Pa
tient
s with
di
scor
dant
re
spon
se
Biva
riate
an
alys
is M
ultiv
aria
ble
anal
ysis
OR
(95%
CI)
P va
lue
aO
R (9
5% C
I) P
valu
e
11
2/38
2 (2
9.3%
)
Ag
e-gr
oup
<0
.001
0.00
2 20
-34
year
s 28
/148
(18.
9%)
1
1
35-4
4 ye
ars
47/1
39 (3
3.8%
) 2.
2 (1
.3-3
.8)
2.
1 (1
.2-3
.7)
≥4
5 ye
ars
37/9
5 (3
9.0%
) 2.
7 (1
.5-4
.9)
2.
8 (1
.5-5
.2)
Se
x
0.32
0.44
M
ale
45/1
39 (3
2.4%
) 1
1
Fe
mal
e 67
/243
(27.
6%)
0.8
(0.5
-1.3
)
0.8
(0.5
-1.3
)
Mar
ital s
tatu
s
0.
56
S
ingl
e 3/
16 (1
8.8%
) 0.
6 (0
.2-2
.1)
Mar
ried/
coha
bitin
g 62
/221
(28.
1%)
1
D
ivor
ced/
sepa
rate
d 11
/38
(29.
0%)
1.0
(0.5
-2.2
)
W
idow
ed
36/1
07 (3
3.6%
) 1.
3 (0
.8-2
.1)
Li
tera
cy
0.54
U
nabl
e to
read
41
/131
(31.
3%)
1
Able
to re
ad
71/2
51 (2
8.3%
) 0.
9 (0
.5-1
.4)
CD
4 co
unt a
t bas
elin
e
0.
85
0.
89
<100
cel
ls/m
m3
16/5
3 (3
0.2%
) 1
1
10
0-19
9 ce
lls/m
m3
22/8
2 (2
6.8%
) 0.
8 (0
.4-1
.8)
1.
0 (0
.4-2
.1)
20
0-35
0 ce
lls/m
m3
74/2
47 (3
0.0%
) 1.
0 (0
.5-1
.9)
1.
1 (0
.6-2
.2)
W
HO S
tage
at b
asel
ine
0.66
146
1 an
d 2
58/2
04 (2
8.4%
) 1
3
and
4 54
/177
(30.
5%)
1.1
(0.7
-1.7
)
BMI a
t bas
elin
e in
kg/
m2
0.48
<1
8.5
30/8
7 (3
4.5%
) 1.
4 (0
.8-2
.3)
18
.5-2
4.9
71/2
57 (2
7.6%
) 1
≥2
5 11
/36
(30.
6%)
1.2
(0.5
-2.5
)
On
TB tr
eatm
ent a
t sta
rt c
ART
0.40
No
109/
366
(29.
8%)
1
Y
es
3/15
(20.
0%)
0.6
(0.2
-2.1
)
ARV
regi
men
0.
61
A
ZT, 3
TC, N
VP
32/9
3 (3
4.4%
) 1
d4T
, 3TC
, NVP
71
/254
(28.
0%)
0.7
(0.4
-1.2
)
A
ZT, 3
TC, E
FV
7/24
(29.
2%)
0.8
(0.3
-2.1
)
d
4T, 3
TC, E
FV
2/10
(20.
0%)
0.5
(0.1
-2.4
)
Trav
el ti
me
to c
linic
0.
07
0.
02
<30
min
utes
23
/78
(29.
5%)
1
1
Betw
een
30 &
60
min
utes
27
/93
(29.
0%)
1.0
(0.5
-1.9
)
1.0
(0.5
-1.9
)
Betw
een
1 &
2 h
ours
28
/124
(22.
6%)
0.7
(0.4
-1.3
)
0.8
(0.4
-1.5
)
> 2
hour
s 34
/86
(39.
5%)
1.6
(0.8
-3.0
)
2.2
(1.0
-4.9
)
Site
0.
61
0.
07
Ruhe
nger
i 60
/197
(30.
5%)
1
1
Kayo
nza/
Kire
he
52/1
85 (2
8.1%
) 0.
9 (0
.6-1
.4)
0.
6 (0
.3-1
.0)
HI
V hu
man
imm
unod
efic
ienc
y vi
rus;
cART
com
bina
tion
antir
etro
vira
l tre
atm
ent;
BMI b
ody
mas
s ind
ex; O
R O
dds r
atio
; aO
R ad
just
ed o
dds r
atio
; CI
Conf
iden
ce in
terv
al; T
B tu
berc
ulos
is; W
HO W
orld
Hea
lth O
rgan
izatio
n; A
ZT zi
dovu
dine
; 3TC
lam
ivud
ine;
d4T
stav
udin
e; N
VP n
evira
pine
; EFV
efa
vire
nz.
Com
plet
e vi
rolo
gica
l sup
pres
sion
= vi
ral l
oad
<40
copi
es/m
L af
ter 1
2 m
onth
s of c
ART.
147
Tabl
e 5:
Ana
lysi
s of v
irolo
gica
l disc
orda
nt tr
eatm
ent r
espo
nses
(CD4
cou
nt ri
se ≥
100
cells
/mm
3 but
inco
mpl
ete
viro
logi
cal s
uppr
essio
n, i.
e. V
L≥40
co
pies
/mL)
in N
este
d Co
hort
2, R
wan
da, 2
007-
2008
Patie
nts w
ith d
isco
rdan
t re
spon
se
n/N
(%)
Biva
riate
an
alys
is M
ultiv
aria
ble
anal
ysis
OR
(95%
CI)
P va
lue
aO
R (9
5% C
I) P
valu
e
Ove
rall
56/3
26 (1
7.2%
)
Ag
e-gr
oup
0.
85
0.
90
20-3
4 ye
ars
24/1
44 (1
6.7%
) 1
1
35
-44
year
s 18
/110
(16.
4%)
1.0
(0.5
-1.9
)
0.9
(0.4
-1.7
)
≥45
year
s 14
/72
(19.
4%)
1.2
(0.6
-2.5
)
1.0
(0.5
-2.2
)
Sex
0.
03
0.
05
Mal
e 28
/122
(23.
0%)
1
1
Fem
ale
28/2
04 (1
3.7%
) 0.
5 (0
.3-1
.0)
0.
5 (0
.3-1
.0 )
M
arita
l sta
tus
0.97
Sin
gle
3/16
(18.
8%)
1.1
(0.3
-4.0
)
M
arrie
d/co
habi
ting
34/1
93 (1
7.6%
) 1
Div
orce
d/se
para
ted
6/33
(18.
2%)
1.0
(0.4
-2.7
)
W
idow
ed
13/8
4 (1
5.5%
) 0.
9 (0
.4-1
.7)
Li
tera
cy
0.27
U
nabl
e to
read
23
/113
(20.
4%)
1
Able
to re
ad
33/2
13 (1
5.5%
) 0.
7 (0
.4-1
.3)
CD
4 co
unt a
t bas
elin
e
0.
29
0.
33
<100
cel
ls/m
m3
6/43
(14.
0%)
1
1
100-
199
cells
/mm
3 18
/78
(23.
1%)
1.9
(0.7
-5.1
)
1.9
(0.7
-5.3
)
200-
350
cells
/mm
3 32
/205
(15.
6%)
1.1
(0.4
-2.9
)
1.3
(0.5
-3.3
)
148
WHO
Sta
ge a
t bas
elin
e
0.
92
1 an
d 2
30/1
76 (1
7.1%
) 1
3
and
4 26
/149
(17.
5%)
1.0
(0.6
-1.8
)
BMI a
t bas
elin
e in
kg/
m2
0.95
<1
8.5
12/6
9 (1
7.4%
) 1.
0 (0
.5-2
.1)
18
.5-2
4.9
38/2
24 (1
7.0%
) 1
≥2
5 6/
31 (1
9.4%
) 1.
2 (0
.5-3
.1)
O
n TB
trea
tmen
t at s
tart
cAR
T
N
o 56
/313
(17.
9%)
N.A
.
Y
es
0/12
(0.0
%)
ARV
regi
men
0.
60
A
ZT, 3
TC, N
VP
15/7
6 (1
9.7%
) 1
d4T
, 3TC
, NVP
35
/218
(16.
1%)
0.8
(0.4
-1.5
)
A
ZT, 3
TC, E
FV
2/19
(10.
5%)
0.5
(0.1
-2.3
)
d
4T, 3
TC, E
FV
3/11
(27.
3%)
1.5
(0.4
-6.5
)
Trav
el ti
me
to c
linic
0.
28
<30
min
utes
7/
62 (1
1.3%
) 1
Be
twee
n 30
& 6
0 m
inut
es
17/8
3 (2
0.5%
) 2.
0 (0
.8-5
.2)
Be
twee
n 1
& 2
hou
rs
17/1
13 (1
5.0%
) 1.
4 (0
.5-3
.6)
>
2 ho
urs
15/6
7 (2
2.4%
) 2.
3 (0
.9-6
.0)
Si
te
0.56
0.71
Ru
heng
eri
26/1
63 (1
6.0%
) 1
1
Ka
yonz
a/Ki
rehe
30
/163
(18.
4%)
1.2
(0.7
-2.1
)
1.1
(0.6
-2.0
)
HIV
hum
an im
mun
odef
icie
ncy
viru
s; cA
RT c
ombi
natio
n An
tiret
rovi
ral t
reat
men
t; BM
I Bod
y m
ass i
ndex
; OR
Odd
s rat
io; a
OR
adju
sted
odd
s rat
io; C
I Co
nfid
ence
inte
rval
; TB
tube
rcul
osis;
WHO
Wor
ld H
ealth
Org
aniza
tion;
AZT
zido
vudi
ne; 3
TC la
miv
udin
e; d
4T st
avud
ine;
NVP
nev
irapi
ne; E
FV e
favi
renz
. in
com
plet
e vi
rolo
gica
l sup
pres
sion
= VL≥4
0 co
pies
/mL a
fter
12
mon
ths o
f cAR
T
149
Figure 1. Flow chart showing how nested cohort 1 and nested cohort 2 were selected from the full cohort, Rwanda, 2008-2009.