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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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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.