Infection DOI 10.1007/s15010-013-0572-2
CLINICAL AND EPIDEMIOLOGICAL STUDY
Treatment outcomes of multidrug-resistant tuberculosis patients in Gauteng, South Africa E. Marais • C. K. Mlambo • J. J. Lewis • N. Rastogi • T. Zozio • M. P. Grobusch • A. Duse • T. Victor • R. W. Warren
Received: 8 September 2013 / Accepted: 10 December 2013 Ó Springer-Verlag Berlin Heidelberg 2013
Abstract Purpose Multidrug-resistant tuberculosis (MDR-TB) is associated with lengthy treatment, expensive and potentially toxic regimens, and high rates of treatment failure and death. This study describes the outcomes of 351 MDRTB patients who started treatment between 2004 and 2007 at the provincial MDR-TB referral hospital in Johannesburg, South Africa, and investigates risk factors associated with death. Methods The study involved the assessment of factors associated with treatment outcomes using a retrospective
E. Marais (&) C. K. Mlambo M. P. Grobusch A. Duse Department of Clinical Microbiology and Infectious Diseases, School of Pathology, University of the Witwatersrand and National Health Laboratory Service, Johannesburg, South Africa e-mail: [email protected] J. J. Lewis MRC Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine, London, UK
review of patient records, drug-susceptibility data and spoligotyping of isolates. Results Treatment success (completion/cure) was recorded in 158 (48.8 %) patients, while 65 (20 %) died, 93 (28.7 %) defaulted, 8 (2.5 %) failed treatment, 11(3.1 %) were transferred out to other health facilities and 16 (4.6 %) had no recorded final outcome. The proportion of successful treatment increased significantly over time. Univariable and multivariable analysis (P = 0.05) identified the year of MDR-TB diagnosis and spoligotypedefined families as factors associated with treatment outcome. No associations were found between treatment outcome and human immunodeficiency virus (HIV) status, previous TB and additional MDR resistance to streptomycin or ethambutol. Molecular typing of the strains revealed a diverse group of spoligotypes, with Beijing, LAM4 and H3 making up the largest groups. Conclusions This is the first published study to investigate treatment outcomes at this facility and to find a link between genotype and treatment outcome, suggesting that genotype determination could potentially serve as a prognostic factor.
N. Rastogi T. Zozio WHO Supranational TB Reference Laboratory, TB Mycobacteria Unit, Institut Pasteur de la Guadeloupe, Abymes, France
Keywords Multidrug-resistant tuberculosis Treatment outcome South Africa
M. P. Grobusch Department of Infectious Diseases, Center of Tropical Medicine and Travel Medicine, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
Introduction
T. Victor R. W. Warren Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Faculty of Health Sciences, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, US/MRC Centre for Molecular and Cellular Biology, Stellenbosch University, Tygerberg, South Africa
South Africa is faced with the dual epidemics of human immunodeficiency virus (HIV) (a prevalence of 10.6 % in 2011 [1] and tuberculosis (TB) (768 cases per 100,000 population in 2011 [2]), as well as resource and medical care limitations, making it a potential incubator for drugresistant Mycobacterium tuberculosis. This is evidenced by the country having a high burden of multidrug-resistant
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tuberculosis (MDR-TB) and numerous cases of extensively drug-resistant TB (XDR-TB) [2]. MDR-TB is characterised by difficulties in treatment as compared to drug-susceptible TB, since MDR-TB strains are resistant to the two most efficient anti-tuberculosis drugs, rifampicin and isoniazid [3]. MDR-TB treatment is frequently associated with high rates of treatment failure, which is more marked in countries with less developed TB programmes [4, 5]. It is also much more costly to treat an MDR-TB patient than a drugsusceptible patient, putting further pressure on health care systems in resource-constrained countries [6]. Knowledge of risk factors associated with poor outcomes for MDR-TB treatment is crucial for developing effective solutions. Several studies have been performed in developed countries to evaluate the treatment outcomes of MDR-TB patients and also to identify predictors of poor outcomes [7, 8]. Risk factors in developed and developing countries often include prior treatment with anti-TB drugs, resistance to TB drugs, HIV infection, age, male sex, hypertension, extra-pulmonary TB and the use of less effective drugs [9, 10]. There are less data on the outcomes of MDR-TB patients and factors associated with poor outcomes in high TB/HIV prevalence regions such as sub-Saharan Africa. Studies from the province of KwaZulu-Natal (KZN) highlight the magnitude of TB drug resistance as well as the negative effects of HIV infection, prior history of TB, year of diagnosis, male sex and low weight on poor treatment outcomes [11, 12]. However, these studies were performed before the roll-out of anti-retroviral treatment (ART). More recent work shows that HIV infection is not the primary factor influencing treatment outcome when anti-retroviral drugs are provided to patients with MDR-TB [13], although some investigators [14] found a more protective effect with XDR-TB. The treatment regimen for MDR-TB is generally determined by considering drug susceptibility profiles of the infecting M. tuberculosis isolate, and includes the use of second-line anti-TB drugs [3]. The selected regimen can either be standardised or individualised, depending on the country’s treatment policy and resources [16–18]. The strategy of providing MDR-TB patient management in specialised institutions, often accompanied with individualised treatment regimens, has been used extensively and with success in developed countries with low TB/HIV prevalence [19, 20]. Regions with high TB burden and limited resources often opt for the World Health Organization (WHO) recommended standardised treatment strategy [21, 22]. In South Africa, the management of MDR-TB involves the referral of patients to specialised, provincial centres where the WHO standardised programme is followed. However, issues regarding citizenship, loss of income, inconvenience and associated stigma probably play an important role in whether patients undergo treatment at referral hospitals.
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Additionally, problems with follow-up and patient tracing in the province have been found to be a substantial barrier in the fight to control drug-resistant TB in the province [23]. There have been studies on decentralised and community-based treatment [24–26] that were developed due to high TB load, limited medical personnel and facilities, and the great distances to the hospitals. In these cases, the decentralised treatment regime was found to be more effective than that of the conventional methods of referral hospitals. Whether a similar approach would work in Gauteng remains to be seen. Gauteng is the most populous and industrialised province in South Africa, with the cities of Johannesburg and Pretoria being the largest centres. It is estimated that over 12 million people live in this 16,548-km2, highly urbanised province, which experiences a constant influx of job seekers from other provinces and countries in Africa [1]. There is one MDR-TB hospital in the province and patients identified at other medical centres are referred there. The standardised WHO treatment protocol was initiated at this hospital in 2004, and, at this time, consisted of a 4-month intensive phase with kanamycin, pyrazinamide, ofloxacin, ethionamide and either terizidone or ethambutol, followed by a 18–24-month continuous phase of ofloxacin, ethionamide and either terizidone or ethambutol [16, 21]. An HIV clinic providing ART was opened in 2005, and the integration of HIV and TB treatment was initiated. Molecular epidemiological investigations have primarily been undertaken in the Western and Eastern Cape, and there has, until recently, been a paucity of molecular data on MDR-TB genotypes in Gauteng. A study published in 2012 suggested that EAI1-SOM was the largest MDR-TB grouping in Gauteng, but the small sample size limits this interpretation [27]. Our group has recently published the genotypes of over 400 MDR-TB isolates from the Johannesburg municipality, showing that Beijing, LAM4 and Haarlem form the biggest groups [28]. Similar results for Gauteng were reported in a publication on the population structure of both MDR- and XDR-TB in South Africa [29]. The current study aimed to investigate the outcomes of MDR-TB patients who had been treated at the provincial MDRTB referral hospital for C2 years, and to identify possible risk factors associated with poor treatment outcomes. We also used molecular typing to characterise the MDR-TB genotypes from patients at the hospital and investigated possible associations between genotypes and treatment outcomes.
Methods Study population A total of 351 patients with culture-confirmed MDR-TB, who started treatment at the referral hospital between 2004
MDR-TB outcome Gauteng South Africa
and 2007, were included in this study. This represented all patients in this time period. Ethics approval for the retrospective review of patient cases was granted by the University of the Witwatersrand Human Research (Medical) Ethics Committee. Permission to access patient information from the referral hospital was obtained from the Gauteng Provincial Department of Health. Decontaminated sputum specimens were cultured in a Mycobacteria Growth Indicator Tube (MGIT) and drug susceptibility testing (DST) was performed upon request. Resistance against all first-line drugs, excluding pyrazinamide, were assessed using the BACTEC MGIT 960 system (Becton Dickinson Biosciences, Sparks, MD, USA). Final concentrations were isoniazid (INH) at 0.1 lg/ml, rifampicin (RMP) at 1.0 lg/ml, ethambutol (EMB) at 5.0 lg/ml and streptomycin (STR) at 1.0 lg/ ml. Aliquots of positive M. tuberculosis cultures were obtained from the National Health Laboratory Service (NHLS) laboratory, and heat-killed to generate DNA extracts for spoligotyping. Standard definitions for cure, treatment completion, treatment failure, death, default and transfer out were used [30]. Successful treatment was defined as cure and/or completion of treatment [31]. The duration of planned treatment for all patients was C2 years. Molecular characterisation of MDR-TB isolates All 351 MDR-TB isolates from the study population were typed using spoligotyping, with the first MDR isolate used per patient. Spoligotyping was performed according to the manufacturer’s instructions using membranes and equipment provided (Isogen, Bioscience BV, Utrecht, the Netherlands). Polymerase chain reaction (PCR) amplification was performed using an iCycler thermal cycler (Bio-Rad, Hercules, CA, USA). The individual spoligotyping patterns were compared to those of the international database SITVIT2 (Institut Pasteur de Guadeloupe, http://www.pasteur-guadeloupe. fr:8081/SITVITDemo).
Results Of the 351 patients whose isolates were collected for analysis at the beginning of the study, 16 (4.6 %) patients had no recorded final treatment outcome and 11 (3.1 %) patients were transferred out to other regions for continued treatment. Almost all of the patients were South African citizens; eight were from other countries in sub-Saharan Africa. The study group consisted predominantly of residents in areas of Gauteng outside of Central Johannesburg, as it was found that only 10 % of patients diagnosed with MDR-TB from the Johannesburg municipality were admitted to the hospital during the study period. Seventyone percent of patients had isolates that were resistant to all four first-line drugs tested (isoniazid, rifampicin, ethambutol and streptomycin) (Table 1). Clinical outcome was available for 324 (92 %) of the patients, and their baseline characteristics are shown in Table 1. Among these patients, 93 (28.7 %) defaulted, 65 (20 %) died and there were 8 patients (2.5 %) where treatment failed. Successful outcomes were observed for
Table 1 Baseline characteristics of multidrug-resistant tuberculosis (MDR-TB) patients starting treatment between 2004 and 2007 Characteristic
Number (%)
Total
324
Sex Female
154 (47.5)
Male
170 (52.5)
Age (years) B15
9 (2.8)
16–35
167 (51.5)
C36
145 (44.8)
Missing
3 (0.9)
HIV status HIV-positive HIV-negative
203 (62.7) 72 (22.2)
Missing
49 (15.1)
Prior history of TB
Statistical analysis Associations between baseline characteristics and treatment outcomes were examined using likelihood ratio tests from univariable and multivariable logistic regression models. The characteristics examined included: age, gender, year of MDR-TB diagnosis, drug susceptibility profiles, prior history of TB, HIV status and spoligotypedefined clades. Variables with P \ 0.1 on univariable analysis were then incorporated into a multivariable logistic regression model to estimate the predictors of successful treatment outcome.
Yes
182 (56.2)
No
97 (29.9)
Missing
45 (13.9)
Resistance to TB drugs INH ? RIF only
30 (9.3)
INH ? RIF ? STR
30 (9.3)
INH ? RIF ? EMB
26 (8)
INH ? RIF ? STR ? EMB
232 (71.6)
INH ? RIF, no additional DST
6 (1.9)
HIV human immunodeficiency virus, TB tuberculosis, INH isoniazid, RIF rifampicin, EMB ethambutol, STR streptomycin, DST drug susceptibility testing
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158 (48.8 %) patients (Fig. 1). The majority of MDR-TB patients (56 %) had a history of previous TB, while 30 % had no prior history and 14 % were missing data on prior TB history (Table 1). The proportion of cases with successful treatment increased from 2004 to 2007, with a commensurate decrease in the proportion of default and poor outcome (Fig. 1). Univariable analysis revealed that an earlier year of starting treatment, female sex and the Haarlem family were associated with death rather than a successful treatment outcome (Table 2). Although there was a trend towards poorer outcomes amongst those who were resistant to both ethambutol and streptomycin, this was not significant (Table 2). There was no evidence of association between death as an outcome and either HIV or previous TB among those for whom data were available. In the multivariable analysis, the year of MDR-TB diagnosis and strain family remained significantly associated with treatment outcome, while sex showed only weak evidence of an association (Table 2). When spoligotyping results were compared to the updated international spoligotyping database (SITVIT2), all 351 isolates matched existing shared spoligotype international types (STIs), resulting in 41 different shared types belonging to clades Beijing, LAM, H, EAI, CAS, S, T, X and an unknown clade (ST 46) (Table 3). Spoligotyping grouped 339 isolates into 29 clusters, resulting in a high clustering rate of 88.3 % (339 - 29/351). The largest families were similarly sized with Beijing, making up an average of 16.8 %, LAM4 15.4 % and H3 14.5 % (Table 3). There was a downward trend in H3 representation over time, from 20 to 7 % in 2007 (Fig. 2), LAM4 from 19 to 7 %), although the Beijing family was relatively
Fig. 1 Treatment outcomes for multidrug-resistant tuberculosis (MDR-TB) patients starting treatment between 2004 and 2007
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constant over time. The variation in HIV positivity, H3 clade and successful outcome is shown in Fig. 2.
Discussion Many of the studies on MDR-TB treatment outcomes are from countries with a low HIV prevalence, and these report successful treatment rates of 51–77 % [9, 20, 22, 32]. Rates of successful treatment outcome reported recently in South Africa vary from 41 to 49 % [11, 12, 15], but these are all pre-ART. A study of community-based, post-ART treatment in Lesotho showed a successful treatment rate of 62 % in 132 patients [13]. Although the 48.8 % overall successful treatment rate determined in our study is similar to the pre-ART studies, the outcome of patients enrolled in 2007 approaches 70 %, which is similar to that of the Lesotho group and approaches that of the Stop TB Global Partnership plan’s aim of 75 % by 2015. In South Africa, the hospital-based MDR-TB treatment system means that patients are separated from their families and work for long periods, and this can result in treatment interruption or termination (default) as patients attempt to leave the hospitals. Dissatisfaction with treatment and substance abuse also play a role in default [33]. The overall default rate observed in the current study was high (28.7 %), consistent with other studies in South Africa [11, 15], but it decreased over the years 2004–2007 (from 36.3 to 20.5 %). The reduced default rate towards the end of the study corresponds to a period when the country was implementing health care reform measures in response to the description of XDR-TB in KZN in 2006 [34]. At around the same time, staffing at the hospital was expanded
MDR-TB outcome Gauteng South Africa Table 2 Odds ratios (ORs) for death versus successful treatment amongst MDR-TB patients Variables
Death n
Univariable analysis %
OR
Multivariable analysis
95 % CI
P-value
OR
\0.001
1
95 % CI
P-value
Start year \0.001
2004
19/37
51.4
1
2005
23/53
43.4
0.73
0.31–1.69
1.10
0.44–2.79
2006
15/68
22.1
0.27
0.11–0.64
0.30
0.11–0.76
2007
8/65
12.3
0.13
0.05–0.35
0.16
0.06–0.49
41/108 24/115
38.0 20.9
1 0.43
0.24–0.78
1 0.62
0.30–1.29
LAM
13/56
23.2
1
T
12/41
29.3
1.37
0.55–3.42
1.72
0.61–4.85
Gender Female Male
0.005
0.200
Strain family 0.002
1
0.015
Beijing
10/38
26.3
1.18
0.46–3.06
1.31
0.45–3.76
H
21/37
56.8
4.34
1.77–10.67
5.11
1.81–14.40
Other
9/51
17.7
0.71
0.27–1.83
0.98
0.34–2.81
0–15
1/7
14.3
0.30
0.03–2.55
0.18
0.02–1.80
16–35
40/111
36.0
1
C36
23/102
22.6
0.52
Missing
1/3
33.3
Age (years) 0.062 0.28–0.95
1 0.59
0.138 0.28–1.24
MDR additional resistance embRstrR
52/159
32.7
1
embRstrS embSstrR
4/18 4/21
22.2 19.1
0.59 0.48
0.18–1.87 0.16–1.51
0.302
embSstrS
4/21
19.1
0.48
0.16–1.51
Missing
1/4
25.0
No
11/53
20.8
1
Yes
45/150
30.0
1.64
Missing
9/20
45.0
No
15/69
21.7
1
Yes
39/130
30.0
1.54
Missing
11/24
45.8
HIV status 0.187 0.77–3.46
Previous TB 0.207 0.78–3.06
P-values from likelihood ratio tests CI confidence interval, HIV human immunodeficiency virus, TB tuberculosis, embR ethambutol resistant, strR streptomycin resistant, embS ethambutol susceptible, strR streptomycin resistant, LAM Latin American Mediterranean, H Haarlem, T ill-defined T family
and enhanced senior expert input introduced, which we believe to be an important factor in contributing towards the decrease in the default rate. Although individualised treatment may be an ideal scenario in countries with lower TB prevalence and sufficient resources, a standardised regimen provided an opportunity for the assessment of factors contributing to patient outcome in our setting. The importance of improving programmatic factors such as standardised protocols, communication between personnel and patients,
and increased patient supervision have been shown to enhance treatment completion rates in other studies [35]. Our study showed a significant improvement in the management of MDR-TB cases at the referral hospital over the study period. It is believed that the improvement over time is as a result of several factors. The WHO treatment protocol was initiated in South Africa in 2004, when the first samples were collected, and ART started in 2005, and it is also during this period that the hospital started to exclusively treat drug-resistant TB. It would have taken some
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123 000000000003771 000000007760771 677776777760601 703377400001771 703777740003771 776177607760771 776377777760771 777737777760771 777777607760771 777777770000000 777777774020771 777777777413731 777777777720771 777777777760700 777777777760771 777777606060771 777777607760731 777777774020731 776337777760771 777737777760731 700076777760771 700777747413771 777776777760601 777737777760601 777777777760601 777757777760771 777677777760771 776177407760771 777761007760771 777740007760771 757777777413731 777777604060731 777777606060731 773777777760771 777777407560731 776377607760771 707777777760771 601777606060771 776377737760771 677777777760601 753777777413731
Octal Code
59 (16.81) 3 (0.85) 6 (1.71) 3 (0.85) 1 (0.28) 12 (3.42) 19 (5.41) 7 (1.99) 7 (1.99) 5 (1.42) 2 (0.57) 15 (4.27) 51 (14.53) 1 (0.28) 26 (7.41) 1 (0.28) 54 (15.38) 2 (0.57) 3 (0.85) 2 (0.57) 16 (4.56) 2 (0.57) 2 (0.57) 1 (0.28) 1 (0.28) 1 (0.28) 1 (0.28) 2 (0.57) 4 (1.14) 1 (0.28) 2 (0.57) 3 (0.85) 4 (1.14) 7 (1.99) 1 (0.28) 3 (0.85) 1 (0.28) 1 (0.28) 1 (0.28) 15 (4.27) 3 (0.85)
0.9 1.09 15.38 0.95 0.1 1.18 2.59 2.31 0.27 3.11 0.17 3.8 1.86 0.45 0.54 0.26 15.08 0.48 4.11 0.99 3.92 4.76 0.2 12.5 0.98 4.76 4.76 2.25 12.5 3.57 3.92 5.45 3.36 24.14 2.08 21.43 10 14.29 33.33 65.22 27.27
% in this study as compared to database Beijing LAM3 X2 CAS1-Kili CAS1-Delhi LAM3 S T3 LAM9 Unk H1 EAI1-SOM H3 T1 T1 LAM11-ZWE LAM4 H1 S T X3 EAI6-BGD1 X2 T3 T1 T1 T1 LAM3 LAM9 LAM9 EAI1-SOM LAM4 LAM11-ZWE T1 LAM6 LAM9 T1 LAM11-ZWE S T1 EAI1-SOM
b
Clade
Clustered Clustered Clustered Clustered Unique Clustered Clustered Clustered Clustered Clustered Clustered Clustered Clustered Unique Clustered Unique Clustered Clustered Clustered Clustered Clustered Clustered Clustered Unique Unique Unique Unique Clustered Clustered Unique Clustered Clustered Clustered Clustered Unique Clustered Unique Unique Unique Clustered Clustered
Clustered vs. unique c patterns
Clade designations according to the SITVIT2 database using revised SpolDB4 rules; Unk: Unknown pattern within any of the major clades described in SITVIT2
SIT designations in the SITVIT2 database
Spoligotype Description
Number (%) in this study
Clustered strains correspond to a similar spoligotype pattern shared by two or more strains ‘‘within this study’’, as opposed to unique strains harbouring a spoligotype pattern that does not match with another strain from this study
c
b
a
1 4 18 21 26 33 34 37 42 46 47 48 50 51 53 59 60 62 71 73 92 129 137 158 244 393 498 719 766 803 806 811 815 926 1355 1536 1597 1607 1915 2531 2997
SIT
a
Table 3 Description of 41 shared types containing 351 isolates; all patterns matched a pre-existing shared type in the SITVIT2 database
E. Marais et al.
MDR-TB outcome Gauteng South Africa
Fig. 2 Human immunodeficiency virus (HIV) status, clade and treatment outcome over the study period
time for the medical personnel to successfully integrate two potentially toxic regimens for the 2-year treatment period and deal with an increased case load, resulting in a possible lag in successful outcomes. The patients admitted in 2006 showed the first improvement in success rates. This is also the year that infection control measures, data capture, admission and discharge guidelines, as well as security measures, were scaled up at the hospital subsequent to the KZN XDR-TB outbreak in 2006. An additional reason for the improvement in treatment outcome noted could be the declining proportion of Haarlem (H3) strains identified. The H3 strains, of which 98 % were found to be additionally resistant to ethambutol and streptomycin, were found to be significantly associated with a worse outcome. Despite the fact that ARTs were only provided 1 year into the study, there was no association between HIV status and poor treatment outcomes. This is likely due to the effectiveness of integrating second-line anti-TB treatment with ART [13, 36, 37] and which has also been reported for XDR-TB patients [38]. A history of previous TB infection and treatment is often associated with the development of acquired MDR-TB in areas with a high prevalence of TB [11, 32]. This is usually attributed to the failure of TB control efforts due to poor case management, interruptions of drug supply and the use of inadequate drug regimens or treatment defaults. The higher number of re-treatment TB cases observed in our study is in keeping with the above-mentioned studies and suggests that previous exposure to anti-TB drugs may result in acquired drug-resistant TB. However, statistical analysis showed no association between treatment outcomes and previous TB. The lack of association between outcomes of new versus re-treatment MDR-TB cases is
believed to be due to the ongoing transmission of the strains, as supported by the genotypic data. An association between the strain family and treatment outcome was observed in the study (P = 0.015). All the strain families, with the exception of the Haarlem (H) family, seemed to have similar rates of successful treatment outcome, whereas the H family was associated with death. Data on the associations between strain family and outcomes need to be interpreted with caution in regions with high MDR-TB prevalence. Further studies investigating the strain types and resistance patterns of serial isolates of M. tuberculosis strains during MDR-TB treatment would provide more information on the associations of strain families and treatment outcomes. Genotyping data confirmed the diversity of strains circulating in our region. Unlike the Western and Eastern Cape [32], the Beijing family does not make up the vast majority of the strains in Gauteng, with clades such as LAM4, H3 and others playing more important roles. This may reflect the founder effect and migration pattern differences between these provinces, and, hence, the transmission of strains. Our results are in keeping with those from a recently published study on the strain population of Johannesburg [28]. Of concern was the discrepancy between the number of patients that were diagnosed with MDR-TB and the number that were admitted to the referral hospital. Less than 10 % of persons identified as having MDR-TB originating from the Johannesburg municipality had hospital records at the hospital. This suggests that some of the patients may have died before they could have been admitted, that they were treated elsewhere or that they were not treated at all. Loss of patients due to death is supported by a recent study done in the same setting in 2008, where 21 % of drugresistant patients died between diagnosis and referral [23]. This would have had obvious consequences in terms of medical care and the transmission of drug-resistant strains to the community. At the time of the study, admission to MDR-TB referral hospitals was voluntary, and this policy only changed in 2007 following concerns about XDR-TB. That admission rates have improved since this study was undertaken can be seen from WHO estimates that 70 % of MDR-TB cases in South Africa in 2011 were enrolled in treatment [2]. Also, a recently published study using data from the same Gauteng referral hospital [39] showed a 63 % treatment uptake of MDR-TB patients, which is an improvement from the low rate observed in our study. One of the main limitations of a retrospective review of patient records for a laboratory-based case recruitment is the reliance on the accurate capture of data by staff members at admission and the patient information from hospital files. Data on ART drugs, doses and duration of treatment were not always complete. The data collection
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sheet used was designed to capture information on risk factors known from the MDR-TB literature. Some of these variables had to be excluded from analysis because of incomplete data capture and, therefore, other potential factors that affect the treatment outcomes could not be evaluated. Improved methods for recording patient data as well as complete clinical information would allow for further insight into factors associated with treatment outcomes for MDR-TB patients. This knowledge would also aid in developing appropriate interventions in order to improve treatment outcomes. Another limitation of this study is that drug susceptibility testing for second-line anti-TB drugs was not mandatory and, therefore, not performed in the NHLS TB laboratory at the time of sample collection. Many of the isolates were not viable after storage, which eliminated the possibility of retrospective testing. Some of the patients may have had XDR-TB, which likely would have contributed to poor outcomes. Policies regarding testing for second-line drug resistance have been modified subsequent to the discovery of XDR-TB in all the provinces, and further investigations that include a more comprehensive drug susceptibility profile of MDR-TB isolates should provide a better understanding of the contribution of XDRTB to patient outcomes. In summary, this study highlights the value of concurrent treatment of HIV in MDR-TB patients in a high dual prevalence setting, and may support an association between the MDR-TB genotype and patient outcome. The study identified a modest successful treatment rate of 48.8 %, although significant improvements were noted over the study period that were attributed to programmatic initiatives at the hospital. The diverse and transmissible MDRTB strain population described, as well as the gap between diagnosis and admission to the MDR-TB centre, is postulated to contribute to the current prevalence of MDR-TB in the region. Attention to early TB and drug-resistant TB diagnosis and treatment, adequate follow-up of referrals and continued co-treatment of HIV would likely result in further improvements in treatment outcomes. Acknowledgements The authors would like to thank the staff of the Tuberculosis Referral Laboratory, National Health Laboratory Service, Johannesburg, the Pasteur Institute in Guadeloupe, University of Stellenbosch (Tygerberg) and University of the Witwatersrand (CMID) for their assistance. We thank Dr. A. Dziewiecki, Sizwe Hospital, for the important discussions. This work was supported by the South African Tuberculosis AIDS Training (SATBAT) programme (National Institutes of Health/Fogarty International Center 1U2RTW007370/3), the Third World Organization for Women in Science (TWOWS), University of the Witwatersrand Health Sciences, European Regional Development Fund, European Commission (ERDF/FEDER, A34-05) and the Regional Council of Guadeloupe (Biodiversity project, CR08/ 031380), Medical Research Council of South Africa and the DST/ NRF Centre of Excellence for Biomedical TB Research. Dr. Zozio
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was awarded a Ph.D. fellowship by the European Social Funds through the Regional Council of Guadeloupe. James Lewis was funded by the Consortium to Respond Effectively to the AIDS/TB Epidemic (CREATE), United States, who received funding from the Bill and Melinda Gates Foundation. Conflict of interest
There are no conflicts of interest.
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MDR-TB outcome Gauteng South Africa 11. Brust JC, Gandhi NR, Carrara H, Osburn G, Padayatchi N. High treatment failure and default rates for patients with multidrugresistant tuberculosis in KwaZulu-Natal, South Africa, 2000–2003. Int J Tuberc Lung Dis. 2010;14:413–9. 12. Farley JE, Ram M, Pan W, Waldman S, Cassell GH, Chaisson RE, Weyer K, Lancaster J, Van der Walt M. Outcomes of multi-drug resistant tuberculosis (MDR-TB) among a cohort of South African patients with high HIV prevalence. PLoS One. 2011;6:e20436. 13. Satti H, McLaughlin MM, Hedt-Gauthier B, Atwood SS, Omotayo DB, Ntlamelle L, Seung KJ. Outcomes of multidrug-resistant tuberculosis treatment with early initiation of antiretroviral therapy for HIV co-infected patients in Lesotho. PLoS One. 2012;7:e46943. 14. Gandhi NR, Andrews JR, Brust JC, Montreuil R, Weissman D, Heo M, Moll AP, Friedland GH, Shah NS. Risk factors for mortality among MDR- and XDR-TB patients in a high HIV prevalence setting. Int J Tuberc Lung Dis. 2012;16:90–7. 15. Shean KP, Willcox PA, Siwendu SN, Laserson KF, Gross L, Kammerer S, Wells CD, Holtz TH. Treatment outcome and follow-up of multidrug-resistant tuberculosis patients, West Coast/Winelands, South Africa, 1992–2002. Int J Tuberc Lung Dis. 2008;12:1182–9. 16. World Health Organization (WHO) Guidelines for the programmatic management of drug-resistant tuberculosis—emergency update 2008. WHO/HTM/TB/2008.402. 2008. http://whqlibdoc. who.int/publications/2008/9789241547581_eng.pdf. 17. Van Deun A, Salim MA, Das AP, Bastian I, Portaels F. Results of a standardised regimen for multidrug-resistant tuberculosis in Bangladesh. Int J Tuberc Lung Dis. 2004;8:560–7. 18. Shin SS, Furin JJ, Alca´ntara F, Bayona J, Sa´nchez E, Mitnick CD. Long-term follow-up for multidrug-resistant tuberculosis. Emerg Infect Dis. 2006;12:687–8. 19. Ferrara G, Richeldi L, Bugiani M, Cirillo D, Besozzi G, Nutini S, Casali L, Fiorentini F, Codecasa LR, Migliori GB. Management of multidrug-resistant tuberculosis in Italy. Int J Tuberc Lung Dis. 2005;9:507–13. 20. Mitnick CD, Franke MF, Rich ML, Alcantara Viru FA, Appleton SC, Atwood SS, Bayona JN, Bonilla CA, Chalco K, Fraser HS, Furin JJ, Guerra D, Hurtado RM, Joseph K, Llaro K, Mestanza L, Mukherjee JS, Mun˜oz M, Palacios E, Sanchez E, Seung KJ, Shin SS, Sloutsky A, Tolman AW, Becerra MC. Aggressive regimens for multidrug-resistant tuberculosis decrease all-cause mortality. PLoS One. 2013;8:e58664. 21. Weyer K. DOTs-Plus for standardised management of multidrugresistant tuberculosis in South Africa. Policy guidelines.. Medical Research Council, Pretoria. 2004. http://www.sahealthinfo.org/tb/ mdrtbguidelines.pdf. 22. Rodriguez M, Monedero I, Caminero JA, Encarnacio´n M, Dominguez Y, Acosta I, Mun˜oz E, Camilo E, Martinez-Selmo S, de los Santos S, del Granado M, Casals M, Cayla J, Marcelino B. Successful management of multidrug-resistant tuberculosis under programme conditions in the Dominican Republic. Int J Tuberc Lung Dis. 2013;17:520–5. 23. Nkosi D, Janssen S, Padanilam X, Louw R, Menezes CN, Grobusch MP. Factors influencing specialist care referral of multidrug- and extensively drug-resistant tuberculosis patients in Gauteng/South Africa: a descriptive questionnaire-based study. BMC Health Serv Res. 2013;13:268. 24. Padayatchi N, Friedland G. Decentralised management of drugresistant tuberculosis (MDR- and XDR-TB) in South Africa: an alternative model of care. Int J Tuberc Lung Dis. 2008;12:978–80. 25. Heller T, Lessells RJ, Wallrauch CG, Ba¨rnighausen T, Cooke GS, Mhlongo L, Master I, Newell ML. Community-based treatment for multidrug-resistant tuberculosis in rural KwaZulu-Natal, South Africa. Int J Tuberc Lung Dis. 2010;14:420–6. 26. Brust JC, Shah NS, Scott M, Chaiyachati K, Lygizos M, van der Merwe TL, Bamber S, Radebe Z, Loveday M, Moll AP, Margot
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CLINICAL AND EPIDEMIOLOGICAL STUDY
Treatment outcomes of multidrug-resistant tuberculosis patients in Gauteng, South Africa E. Marais • C. K. Mlambo • J. J. Lewis • N. Rastogi • T. Zozio • M. P. Grobusch • A. Duse • T. Victor • R. W. Warren
Received: 8 September 2013 / Accepted: 10 December 2013 Ó Springer-Verlag Berlin Heidelberg 2013
Abstract Purpose Multidrug-resistant tuberculosis (MDR-TB) is associated with lengthy treatment, expensive and potentially toxic regimens, and high rates of treatment failure and death. This study describes the outcomes of 351 MDRTB patients who started treatment between 2004 and 2007 at the provincial MDR-TB referral hospital in Johannesburg, South Africa, and investigates risk factors associated with death. Methods The study involved the assessment of factors associated with treatment outcomes using a retrospective
E. Marais (&) C. K. Mlambo M. P. Grobusch A. Duse Department of Clinical Microbiology and Infectious Diseases, School of Pathology, University of the Witwatersrand and National Health Laboratory Service, Johannesburg, South Africa e-mail: [email protected] J. J. Lewis MRC Tropical Epidemiology Group, London School of Hygiene and Tropical Medicine, London, UK
review of patient records, drug-susceptibility data and spoligotyping of isolates. Results Treatment success (completion/cure) was recorded in 158 (48.8 %) patients, while 65 (20 %) died, 93 (28.7 %) defaulted, 8 (2.5 %) failed treatment, 11(3.1 %) were transferred out to other health facilities and 16 (4.6 %) had no recorded final outcome. The proportion of successful treatment increased significantly over time. Univariable and multivariable analysis (P = 0.05) identified the year of MDR-TB diagnosis and spoligotypedefined families as factors associated with treatment outcome. No associations were found between treatment outcome and human immunodeficiency virus (HIV) status, previous TB and additional MDR resistance to streptomycin or ethambutol. Molecular typing of the strains revealed a diverse group of spoligotypes, with Beijing, LAM4 and H3 making up the largest groups. Conclusions This is the first published study to investigate treatment outcomes at this facility and to find a link between genotype and treatment outcome, suggesting that genotype determination could potentially serve as a prognostic factor.
N. Rastogi T. Zozio WHO Supranational TB Reference Laboratory, TB Mycobacteria Unit, Institut Pasteur de la Guadeloupe, Abymes, France
Keywords Multidrug-resistant tuberculosis Treatment outcome South Africa
M. P. Grobusch Department of Infectious Diseases, Center of Tropical Medicine and Travel Medicine, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
Introduction
T. Victor R. W. Warren Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Faculty of Health Sciences, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, US/MRC Centre for Molecular and Cellular Biology, Stellenbosch University, Tygerberg, South Africa
South Africa is faced with the dual epidemics of human immunodeficiency virus (HIV) (a prevalence of 10.6 % in 2011 [1] and tuberculosis (TB) (768 cases per 100,000 population in 2011 [2]), as well as resource and medical care limitations, making it a potential incubator for drugresistant Mycobacterium tuberculosis. This is evidenced by the country having a high burden of multidrug-resistant
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tuberculosis (MDR-TB) and numerous cases of extensively drug-resistant TB (XDR-TB) [2]. MDR-TB is characterised by difficulties in treatment as compared to drug-susceptible TB, since MDR-TB strains are resistant to the two most efficient anti-tuberculosis drugs, rifampicin and isoniazid [3]. MDR-TB treatment is frequently associated with high rates of treatment failure, which is more marked in countries with less developed TB programmes [4, 5]. It is also much more costly to treat an MDR-TB patient than a drugsusceptible patient, putting further pressure on health care systems in resource-constrained countries [6]. Knowledge of risk factors associated with poor outcomes for MDR-TB treatment is crucial for developing effective solutions. Several studies have been performed in developed countries to evaluate the treatment outcomes of MDR-TB patients and also to identify predictors of poor outcomes [7, 8]. Risk factors in developed and developing countries often include prior treatment with anti-TB drugs, resistance to TB drugs, HIV infection, age, male sex, hypertension, extra-pulmonary TB and the use of less effective drugs [9, 10]. There are less data on the outcomes of MDR-TB patients and factors associated with poor outcomes in high TB/HIV prevalence regions such as sub-Saharan Africa. Studies from the province of KwaZulu-Natal (KZN) highlight the magnitude of TB drug resistance as well as the negative effects of HIV infection, prior history of TB, year of diagnosis, male sex and low weight on poor treatment outcomes [11, 12]. However, these studies were performed before the roll-out of anti-retroviral treatment (ART). More recent work shows that HIV infection is not the primary factor influencing treatment outcome when anti-retroviral drugs are provided to patients with MDR-TB [13], although some investigators [14] found a more protective effect with XDR-TB. The treatment regimen for MDR-TB is generally determined by considering drug susceptibility profiles of the infecting M. tuberculosis isolate, and includes the use of second-line anti-TB drugs [3]. The selected regimen can either be standardised or individualised, depending on the country’s treatment policy and resources [16–18]. The strategy of providing MDR-TB patient management in specialised institutions, often accompanied with individualised treatment regimens, has been used extensively and with success in developed countries with low TB/HIV prevalence [19, 20]. Regions with high TB burden and limited resources often opt for the World Health Organization (WHO) recommended standardised treatment strategy [21, 22]. In South Africa, the management of MDR-TB involves the referral of patients to specialised, provincial centres where the WHO standardised programme is followed. However, issues regarding citizenship, loss of income, inconvenience and associated stigma probably play an important role in whether patients undergo treatment at referral hospitals.
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Additionally, problems with follow-up and patient tracing in the province have been found to be a substantial barrier in the fight to control drug-resistant TB in the province [23]. There have been studies on decentralised and community-based treatment [24–26] that were developed due to high TB load, limited medical personnel and facilities, and the great distances to the hospitals. In these cases, the decentralised treatment regime was found to be more effective than that of the conventional methods of referral hospitals. Whether a similar approach would work in Gauteng remains to be seen. Gauteng is the most populous and industrialised province in South Africa, with the cities of Johannesburg and Pretoria being the largest centres. It is estimated that over 12 million people live in this 16,548-km2, highly urbanised province, which experiences a constant influx of job seekers from other provinces and countries in Africa [1]. There is one MDR-TB hospital in the province and patients identified at other medical centres are referred there. The standardised WHO treatment protocol was initiated at this hospital in 2004, and, at this time, consisted of a 4-month intensive phase with kanamycin, pyrazinamide, ofloxacin, ethionamide and either terizidone or ethambutol, followed by a 18–24-month continuous phase of ofloxacin, ethionamide and either terizidone or ethambutol [16, 21]. An HIV clinic providing ART was opened in 2005, and the integration of HIV and TB treatment was initiated. Molecular epidemiological investigations have primarily been undertaken in the Western and Eastern Cape, and there has, until recently, been a paucity of molecular data on MDR-TB genotypes in Gauteng. A study published in 2012 suggested that EAI1-SOM was the largest MDR-TB grouping in Gauteng, but the small sample size limits this interpretation [27]. Our group has recently published the genotypes of over 400 MDR-TB isolates from the Johannesburg municipality, showing that Beijing, LAM4 and Haarlem form the biggest groups [28]. Similar results for Gauteng were reported in a publication on the population structure of both MDR- and XDR-TB in South Africa [29]. The current study aimed to investigate the outcomes of MDR-TB patients who had been treated at the provincial MDRTB referral hospital for C2 years, and to identify possible risk factors associated with poor treatment outcomes. We also used molecular typing to characterise the MDR-TB genotypes from patients at the hospital and investigated possible associations between genotypes and treatment outcomes.
Methods Study population A total of 351 patients with culture-confirmed MDR-TB, who started treatment at the referral hospital between 2004
MDR-TB outcome Gauteng South Africa
and 2007, were included in this study. This represented all patients in this time period. Ethics approval for the retrospective review of patient cases was granted by the University of the Witwatersrand Human Research (Medical) Ethics Committee. Permission to access patient information from the referral hospital was obtained from the Gauteng Provincial Department of Health. Decontaminated sputum specimens were cultured in a Mycobacteria Growth Indicator Tube (MGIT) and drug susceptibility testing (DST) was performed upon request. Resistance against all first-line drugs, excluding pyrazinamide, were assessed using the BACTEC MGIT 960 system (Becton Dickinson Biosciences, Sparks, MD, USA). Final concentrations were isoniazid (INH) at 0.1 lg/ml, rifampicin (RMP) at 1.0 lg/ml, ethambutol (EMB) at 5.0 lg/ml and streptomycin (STR) at 1.0 lg/ ml. Aliquots of positive M. tuberculosis cultures were obtained from the National Health Laboratory Service (NHLS) laboratory, and heat-killed to generate DNA extracts for spoligotyping. Standard definitions for cure, treatment completion, treatment failure, death, default and transfer out were used [30]. Successful treatment was defined as cure and/or completion of treatment [31]. The duration of planned treatment for all patients was C2 years. Molecular characterisation of MDR-TB isolates All 351 MDR-TB isolates from the study population were typed using spoligotyping, with the first MDR isolate used per patient. Spoligotyping was performed according to the manufacturer’s instructions using membranes and equipment provided (Isogen, Bioscience BV, Utrecht, the Netherlands). Polymerase chain reaction (PCR) amplification was performed using an iCycler thermal cycler (Bio-Rad, Hercules, CA, USA). The individual spoligotyping patterns were compared to those of the international database SITVIT2 (Institut Pasteur de Guadeloupe, http://www.pasteur-guadeloupe. fr:8081/SITVITDemo).
Results Of the 351 patients whose isolates were collected for analysis at the beginning of the study, 16 (4.6 %) patients had no recorded final treatment outcome and 11 (3.1 %) patients were transferred out to other regions for continued treatment. Almost all of the patients were South African citizens; eight were from other countries in sub-Saharan Africa. The study group consisted predominantly of residents in areas of Gauteng outside of Central Johannesburg, as it was found that only 10 % of patients diagnosed with MDR-TB from the Johannesburg municipality were admitted to the hospital during the study period. Seventyone percent of patients had isolates that were resistant to all four first-line drugs tested (isoniazid, rifampicin, ethambutol and streptomycin) (Table 1). Clinical outcome was available for 324 (92 %) of the patients, and their baseline characteristics are shown in Table 1. Among these patients, 93 (28.7 %) defaulted, 65 (20 %) died and there were 8 patients (2.5 %) where treatment failed. Successful outcomes were observed for
Table 1 Baseline characteristics of multidrug-resistant tuberculosis (MDR-TB) patients starting treatment between 2004 and 2007 Characteristic
Number (%)
Total
324
Sex Female
154 (47.5)
Male
170 (52.5)
Age (years) B15
9 (2.8)
16–35
167 (51.5)
C36
145 (44.8)
Missing
3 (0.9)
HIV status HIV-positive HIV-negative
203 (62.7) 72 (22.2)
Missing
49 (15.1)
Prior history of TB
Statistical analysis Associations between baseline characteristics and treatment outcomes were examined using likelihood ratio tests from univariable and multivariable logistic regression models. The characteristics examined included: age, gender, year of MDR-TB diagnosis, drug susceptibility profiles, prior history of TB, HIV status and spoligotypedefined clades. Variables with P \ 0.1 on univariable analysis were then incorporated into a multivariable logistic regression model to estimate the predictors of successful treatment outcome.
Yes
182 (56.2)
No
97 (29.9)
Missing
45 (13.9)
Resistance to TB drugs INH ? RIF only
30 (9.3)
INH ? RIF ? STR
30 (9.3)
INH ? RIF ? EMB
26 (8)
INH ? RIF ? STR ? EMB
232 (71.6)
INH ? RIF, no additional DST
6 (1.9)
HIV human immunodeficiency virus, TB tuberculosis, INH isoniazid, RIF rifampicin, EMB ethambutol, STR streptomycin, DST drug susceptibility testing
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158 (48.8 %) patients (Fig. 1). The majority of MDR-TB patients (56 %) had a history of previous TB, while 30 % had no prior history and 14 % were missing data on prior TB history (Table 1). The proportion of cases with successful treatment increased from 2004 to 2007, with a commensurate decrease in the proportion of default and poor outcome (Fig. 1). Univariable analysis revealed that an earlier year of starting treatment, female sex and the Haarlem family were associated with death rather than a successful treatment outcome (Table 2). Although there was a trend towards poorer outcomes amongst those who were resistant to both ethambutol and streptomycin, this was not significant (Table 2). There was no evidence of association between death as an outcome and either HIV or previous TB among those for whom data were available. In the multivariable analysis, the year of MDR-TB diagnosis and strain family remained significantly associated with treatment outcome, while sex showed only weak evidence of an association (Table 2). When spoligotyping results were compared to the updated international spoligotyping database (SITVIT2), all 351 isolates matched existing shared spoligotype international types (STIs), resulting in 41 different shared types belonging to clades Beijing, LAM, H, EAI, CAS, S, T, X and an unknown clade (ST 46) (Table 3). Spoligotyping grouped 339 isolates into 29 clusters, resulting in a high clustering rate of 88.3 % (339 - 29/351). The largest families were similarly sized with Beijing, making up an average of 16.8 %, LAM4 15.4 % and H3 14.5 % (Table 3). There was a downward trend in H3 representation over time, from 20 to 7 % in 2007 (Fig. 2), LAM4 from 19 to 7 %), although the Beijing family was relatively
Fig. 1 Treatment outcomes for multidrug-resistant tuberculosis (MDR-TB) patients starting treatment between 2004 and 2007
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constant over time. The variation in HIV positivity, H3 clade and successful outcome is shown in Fig. 2.
Discussion Many of the studies on MDR-TB treatment outcomes are from countries with a low HIV prevalence, and these report successful treatment rates of 51–77 % [9, 20, 22, 32]. Rates of successful treatment outcome reported recently in South Africa vary from 41 to 49 % [11, 12, 15], but these are all pre-ART. A study of community-based, post-ART treatment in Lesotho showed a successful treatment rate of 62 % in 132 patients [13]. Although the 48.8 % overall successful treatment rate determined in our study is similar to the pre-ART studies, the outcome of patients enrolled in 2007 approaches 70 %, which is similar to that of the Lesotho group and approaches that of the Stop TB Global Partnership plan’s aim of 75 % by 2015. In South Africa, the hospital-based MDR-TB treatment system means that patients are separated from their families and work for long periods, and this can result in treatment interruption or termination (default) as patients attempt to leave the hospitals. Dissatisfaction with treatment and substance abuse also play a role in default [33]. The overall default rate observed in the current study was high (28.7 %), consistent with other studies in South Africa [11, 15], but it decreased over the years 2004–2007 (from 36.3 to 20.5 %). The reduced default rate towards the end of the study corresponds to a period when the country was implementing health care reform measures in response to the description of XDR-TB in KZN in 2006 [34]. At around the same time, staffing at the hospital was expanded
MDR-TB outcome Gauteng South Africa Table 2 Odds ratios (ORs) for death versus successful treatment amongst MDR-TB patients Variables
Death n
Univariable analysis %
OR
Multivariable analysis
95 % CI
P-value
OR
\0.001
1
95 % CI
P-value
Start year \0.001
2004
19/37
51.4
1
2005
23/53
43.4
0.73
0.31–1.69
1.10
0.44–2.79
2006
15/68
22.1
0.27
0.11–0.64
0.30
0.11–0.76
2007
8/65
12.3
0.13
0.05–0.35
0.16
0.06–0.49
41/108 24/115
38.0 20.9
1 0.43
0.24–0.78
1 0.62
0.30–1.29
LAM
13/56
23.2
1
T
12/41
29.3
1.37
0.55–3.42
1.72
0.61–4.85
Gender Female Male
0.005
0.200
Strain family 0.002
1
0.015
Beijing
10/38
26.3
1.18
0.46–3.06
1.31
0.45–3.76
H
21/37
56.8
4.34
1.77–10.67
5.11
1.81–14.40
Other
9/51
17.7
0.71
0.27–1.83
0.98
0.34–2.81
0–15
1/7
14.3
0.30
0.03–2.55
0.18
0.02–1.80
16–35
40/111
36.0
1
C36
23/102
22.6
0.52
Missing
1/3
33.3
Age (years) 0.062 0.28–0.95
1 0.59
0.138 0.28–1.24
MDR additional resistance embRstrR
52/159
32.7
1
embRstrS embSstrR
4/18 4/21
22.2 19.1
0.59 0.48
0.18–1.87 0.16–1.51
0.302
embSstrS
4/21
19.1
0.48
0.16–1.51
Missing
1/4
25.0
No
11/53
20.8
1
Yes
45/150
30.0
1.64
Missing
9/20
45.0
No
15/69
21.7
1
Yes
39/130
30.0
1.54
Missing
11/24
45.8
HIV status 0.187 0.77–3.46
Previous TB 0.207 0.78–3.06
P-values from likelihood ratio tests CI confidence interval, HIV human immunodeficiency virus, TB tuberculosis, embR ethambutol resistant, strR streptomycin resistant, embS ethambutol susceptible, strR streptomycin resistant, LAM Latin American Mediterranean, H Haarlem, T ill-defined T family
and enhanced senior expert input introduced, which we believe to be an important factor in contributing towards the decrease in the default rate. Although individualised treatment may be an ideal scenario in countries with lower TB prevalence and sufficient resources, a standardised regimen provided an opportunity for the assessment of factors contributing to patient outcome in our setting. The importance of improving programmatic factors such as standardised protocols, communication between personnel and patients,
and increased patient supervision have been shown to enhance treatment completion rates in other studies [35]. Our study showed a significant improvement in the management of MDR-TB cases at the referral hospital over the study period. It is believed that the improvement over time is as a result of several factors. The WHO treatment protocol was initiated in South Africa in 2004, when the first samples were collected, and ART started in 2005, and it is also during this period that the hospital started to exclusively treat drug-resistant TB. It would have taken some
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123 000000000003771 000000007760771 677776777760601 703377400001771 703777740003771 776177607760771 776377777760771 777737777760771 777777607760771 777777770000000 777777774020771 777777777413731 777777777720771 777777777760700 777777777760771 777777606060771 777777607760731 777777774020731 776337777760771 777737777760731 700076777760771 700777747413771 777776777760601 777737777760601 777777777760601 777757777760771 777677777760771 776177407760771 777761007760771 777740007760771 757777777413731 777777604060731 777777606060731 773777777760771 777777407560731 776377607760771 707777777760771 601777606060771 776377737760771 677777777760601 753777777413731
Octal Code
59 (16.81) 3 (0.85) 6 (1.71) 3 (0.85) 1 (0.28) 12 (3.42) 19 (5.41) 7 (1.99) 7 (1.99) 5 (1.42) 2 (0.57) 15 (4.27) 51 (14.53) 1 (0.28) 26 (7.41) 1 (0.28) 54 (15.38) 2 (0.57) 3 (0.85) 2 (0.57) 16 (4.56) 2 (0.57) 2 (0.57) 1 (0.28) 1 (0.28) 1 (0.28) 1 (0.28) 2 (0.57) 4 (1.14) 1 (0.28) 2 (0.57) 3 (0.85) 4 (1.14) 7 (1.99) 1 (0.28) 3 (0.85) 1 (0.28) 1 (0.28) 1 (0.28) 15 (4.27) 3 (0.85)
0.9 1.09 15.38 0.95 0.1 1.18 2.59 2.31 0.27 3.11 0.17 3.8 1.86 0.45 0.54 0.26 15.08 0.48 4.11 0.99 3.92 4.76 0.2 12.5 0.98 4.76 4.76 2.25 12.5 3.57 3.92 5.45 3.36 24.14 2.08 21.43 10 14.29 33.33 65.22 27.27
% in this study as compared to database Beijing LAM3 X2 CAS1-Kili CAS1-Delhi LAM3 S T3 LAM9 Unk H1 EAI1-SOM H3 T1 T1 LAM11-ZWE LAM4 H1 S T X3 EAI6-BGD1 X2 T3 T1 T1 T1 LAM3 LAM9 LAM9 EAI1-SOM LAM4 LAM11-ZWE T1 LAM6 LAM9 T1 LAM11-ZWE S T1 EAI1-SOM
b
Clade
Clustered Clustered Clustered Clustered Unique Clustered Clustered Clustered Clustered Clustered Clustered Clustered Clustered Unique Clustered Unique Clustered Clustered Clustered Clustered Clustered Clustered Clustered Unique Unique Unique Unique Clustered Clustered Unique Clustered Clustered Clustered Clustered Unique Clustered Unique Unique Unique Clustered Clustered
Clustered vs. unique c patterns
Clade designations according to the SITVIT2 database using revised SpolDB4 rules; Unk: Unknown pattern within any of the major clades described in SITVIT2
SIT designations in the SITVIT2 database
Spoligotype Description
Number (%) in this study
Clustered strains correspond to a similar spoligotype pattern shared by two or more strains ‘‘within this study’’, as opposed to unique strains harbouring a spoligotype pattern that does not match with another strain from this study
c
b
a
1 4 18 21 26 33 34 37 42 46 47 48 50 51 53 59 60 62 71 73 92 129 137 158 244 393 498 719 766 803 806 811 815 926 1355 1536 1597 1607 1915 2531 2997
SIT
a
Table 3 Description of 41 shared types containing 351 isolates; all patterns matched a pre-existing shared type in the SITVIT2 database
E. Marais et al.
MDR-TB outcome Gauteng South Africa
Fig. 2 Human immunodeficiency virus (HIV) status, clade and treatment outcome over the study period
time for the medical personnel to successfully integrate two potentially toxic regimens for the 2-year treatment period and deal with an increased case load, resulting in a possible lag in successful outcomes. The patients admitted in 2006 showed the first improvement in success rates. This is also the year that infection control measures, data capture, admission and discharge guidelines, as well as security measures, were scaled up at the hospital subsequent to the KZN XDR-TB outbreak in 2006. An additional reason for the improvement in treatment outcome noted could be the declining proportion of Haarlem (H3) strains identified. The H3 strains, of which 98 % were found to be additionally resistant to ethambutol and streptomycin, were found to be significantly associated with a worse outcome. Despite the fact that ARTs were only provided 1 year into the study, there was no association between HIV status and poor treatment outcomes. This is likely due to the effectiveness of integrating second-line anti-TB treatment with ART [13, 36, 37] and which has also been reported for XDR-TB patients [38]. A history of previous TB infection and treatment is often associated with the development of acquired MDR-TB in areas with a high prevalence of TB [11, 32]. This is usually attributed to the failure of TB control efforts due to poor case management, interruptions of drug supply and the use of inadequate drug regimens or treatment defaults. The higher number of re-treatment TB cases observed in our study is in keeping with the above-mentioned studies and suggests that previous exposure to anti-TB drugs may result in acquired drug-resistant TB. However, statistical analysis showed no association between treatment outcomes and previous TB. The lack of association between outcomes of new versus re-treatment MDR-TB cases is
believed to be due to the ongoing transmission of the strains, as supported by the genotypic data. An association between the strain family and treatment outcome was observed in the study (P = 0.015). All the strain families, with the exception of the Haarlem (H) family, seemed to have similar rates of successful treatment outcome, whereas the H family was associated with death. Data on the associations between strain family and outcomes need to be interpreted with caution in regions with high MDR-TB prevalence. Further studies investigating the strain types and resistance patterns of serial isolates of M. tuberculosis strains during MDR-TB treatment would provide more information on the associations of strain families and treatment outcomes. Genotyping data confirmed the diversity of strains circulating in our region. Unlike the Western and Eastern Cape [32], the Beijing family does not make up the vast majority of the strains in Gauteng, with clades such as LAM4, H3 and others playing more important roles. This may reflect the founder effect and migration pattern differences between these provinces, and, hence, the transmission of strains. Our results are in keeping with those from a recently published study on the strain population of Johannesburg [28]. Of concern was the discrepancy between the number of patients that were diagnosed with MDR-TB and the number that were admitted to the referral hospital. Less than 10 % of persons identified as having MDR-TB originating from the Johannesburg municipality had hospital records at the hospital. This suggests that some of the patients may have died before they could have been admitted, that they were treated elsewhere or that they were not treated at all. Loss of patients due to death is supported by a recent study done in the same setting in 2008, where 21 % of drugresistant patients died between diagnosis and referral [23]. This would have had obvious consequences in terms of medical care and the transmission of drug-resistant strains to the community. At the time of the study, admission to MDR-TB referral hospitals was voluntary, and this policy only changed in 2007 following concerns about XDR-TB. That admission rates have improved since this study was undertaken can be seen from WHO estimates that 70 % of MDR-TB cases in South Africa in 2011 were enrolled in treatment [2]. Also, a recently published study using data from the same Gauteng referral hospital [39] showed a 63 % treatment uptake of MDR-TB patients, which is an improvement from the low rate observed in our study. One of the main limitations of a retrospective review of patient records for a laboratory-based case recruitment is the reliance on the accurate capture of data by staff members at admission and the patient information from hospital files. Data on ART drugs, doses and duration of treatment were not always complete. The data collection
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sheet used was designed to capture information on risk factors known from the MDR-TB literature. Some of these variables had to be excluded from analysis because of incomplete data capture and, therefore, other potential factors that affect the treatment outcomes could not be evaluated. Improved methods for recording patient data as well as complete clinical information would allow for further insight into factors associated with treatment outcomes for MDR-TB patients. This knowledge would also aid in developing appropriate interventions in order to improve treatment outcomes. Another limitation of this study is that drug susceptibility testing for second-line anti-TB drugs was not mandatory and, therefore, not performed in the NHLS TB laboratory at the time of sample collection. Many of the isolates were not viable after storage, which eliminated the possibility of retrospective testing. Some of the patients may have had XDR-TB, which likely would have contributed to poor outcomes. Policies regarding testing for second-line drug resistance have been modified subsequent to the discovery of XDR-TB in all the provinces, and further investigations that include a more comprehensive drug susceptibility profile of MDR-TB isolates should provide a better understanding of the contribution of XDRTB to patient outcomes. In summary, this study highlights the value of concurrent treatment of HIV in MDR-TB patients in a high dual prevalence setting, and may support an association between the MDR-TB genotype and patient outcome. The study identified a modest successful treatment rate of 48.8 %, although significant improvements were noted over the study period that were attributed to programmatic initiatives at the hospital. The diverse and transmissible MDRTB strain population described, as well as the gap between diagnosis and admission to the MDR-TB centre, is postulated to contribute to the current prevalence of MDR-TB in the region. Attention to early TB and drug-resistant TB diagnosis and treatment, adequate follow-up of referrals and continued co-treatment of HIV would likely result in further improvements in treatment outcomes. Acknowledgements The authors would like to thank the staff of the Tuberculosis Referral Laboratory, National Health Laboratory Service, Johannesburg, the Pasteur Institute in Guadeloupe, University of Stellenbosch (Tygerberg) and University of the Witwatersrand (CMID) for their assistance. We thank Dr. A. Dziewiecki, Sizwe Hospital, for the important discussions. This work was supported by the South African Tuberculosis AIDS Training (SATBAT) programme (National Institutes of Health/Fogarty International Center 1U2RTW007370/3), the Third World Organization for Women in Science (TWOWS), University of the Witwatersrand Health Sciences, European Regional Development Fund, European Commission (ERDF/FEDER, A34-05) and the Regional Council of Guadeloupe (Biodiversity project, CR08/ 031380), Medical Research Council of South Africa and the DST/ NRF Centre of Excellence for Biomedical TB Research. Dr. Zozio
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was awarded a Ph.D. fellowship by the European Social Funds through the Regional Council of Guadeloupe. James Lewis was funded by the Consortium to Respond Effectively to the AIDS/TB Epidemic (CREATE), United States, who received funding from the Bill and Melinda Gates Foundation. Conflict of interest
There are no conflicts of interest.
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