The effect of the Xpert MTB/RIF test on the time to MDR-TB treatment initiation in a rural setting: a cohort study in South Africa’s Eastern Cape Province

Isoniazid and Rifampicin (RIF) are still the cornerstones of Tuberculosis (TB) chemotherapy. Resistance to both these drugs defines multi-drug resistant TB (MDR-TB) [1]. While culture and in-vitro sensitivity testing is still the reference standard for MDR-TB diagnosis, newer molecular diagnostic methods significantly reduce the time to diagnosis. The World Health Organization endorsed the Line Probe Assay (LPA) in 2008 [2] followed by the Xpert MTB/RIF (Xpert) in 2010 [1]. Xpert is a cartridge based nucleic acid amplification test that can identify both Mycobacterium tuberculosis (MTB) and resistance to RIF within 2 h of specimen processing. While Xpert identifies RIF monoresistance, it is a proxy for MDR-TB [3, 4] and patients are treated as such [5]. In South Africa, diagnosis of MDR-TB was based on culture and phenotypic DST until 2008 when the Department of Health adopted LPA for smear positive sputum and culture isolates. Xpert testing started in October 2011 [6] and replaced smear microscopy as the initial test for both TB and MDR-TB diagnosis [7].

In 2014, 5.9% of all TB notifications in South Africa were MDR-TB [1]. However, only 62% of the estimated 18, 734 MDR-TB cases in 2014 were enrolled on treatment and the treatment success rate for the 2012 cohort was 52% [1]. The high loss to follow-up may be due to a high early mortality especially among HIV positive patients [8]. While the use of Xpert had not been shown to reduce mortality [9] or morbidity [10] from drug-sensitive TB, early treatment initiation in MDR-TB is associated with a reduced time to culture conversion [11, 12] and it is anticipated that early treatment will reduce transmission.

The length of time for which the patient is infectious has been implicated as a major factor in the spread of the disease [7] while treatment renders patients rapidly non-infectious [13]. This underscores the need for early diagnosis and treatment.

The time-to-treatment initiation of MDR-TB (TTTI) is defined as the period between sputum collection for drug sensitivity testing and initiation of MDR-TB treatment. The target TTTI is five days in South Africa [14]. Studies have reported significant delays in TTTI depending on the diagnostic modality. With the use of culture and phenotypic drug sensitivity testing (culture/phenotypic DST), delays of 6 to 12 weeks have been reported [15, 16]. TTTI’s for LPA are between 18 and 62 days [11, 12, 17]. The shortest TTTI’s of 8 to 17 days [18‐20] are associated with Xpert, Xpert has a sensitivity of 95% and a specificity of 98% for diagnosing RIF resistance in adults [21].

The impact of Xpert on TTTI to date has been evaluated in urban settings [18‐20]. The authors could not find any study evaluating the effectiveness of Xpert on TTTI in a rural setting in a developing country. The aim of this study is to describe the TTTI and the effect of the Xpert test on the TTTI among patients with MDR-TB in the King Sabata Dalindyebo (KSD) Sub-District of the Eastern Cape.

For the years 2009–2014, 342 records were found and assessed for eligibility and exceeded the sample size calculated.

This study demonstrates the effectiveness (implementation under real world conditions) of Xpert in a rural setting. The results of this study show that the median TTTI was significantly reduced with use of Xpert compared to LPA and culture/phenotypic DST. The median TTTI of 18 days is similar to that of 16 days and 17 days in two studies [18, 20] while a shorter TTTI of 8 days was reported by Cox et al. [19], all conducted in urban and peri-urban settings.

The reduction in TTTI was due to a reduction in the time to diagnosis, which was significantly shorter with Xpert compared to LPA and culture/phenotypic DST. This is similar to the study by Naidoo et al. [18] where the time to diagnosis was reduced from 24 days with LPA to 1 day with Xpert; and that of Van Kampen [20] where the time to diagnosis was reduced from 75 days with culture/phenotypic DST to 1 day with Xpert. However, Naidoo et al. [18] attributed 20% of the reduction in TTTI to improved program management. Cox et al., [19] while not quantifying the contribution, also attributed their greatly improved TTTI of 8 days to both implementation of a decentralized community-based programme for drug-resistant TB, and the reduced time to diagnosis from use of Xpert.

The time from diagnosis to treatment in this study did not differ significantly between the three diagnostic modalities. Similar to this study, Hanrahan [11] and Jacobson [17] did not find a reduction in median time from diagnosis to treatment comparing LPA to culture/phenotypic DST. However, Naidoo et al. [18] reported a reduced median time from diagnosis to treatment from 14 days with LPA to 10 days with Xpert which was attributed to better programme management.

Age and sex and HIV status had no influence on TTTI, similar to the study by Naidoo et al. [18]. For time from diagnosis to treatment, age and sex and HIV status also had no influence. However, while age had no influence on time to diagnosis, males were significantly more likely to be diagnosed after 12 days compared to females. In South Africa, women utilize health care services more than men [24] and may present earlier in the course of illness. Patients with HIV were significantly likely to be diagnosed faster compared to HIV negative patients when using univariate analysis. However, multinomial regression did not show any significant association between the HIV status and time to diagnosis. As HIV positive patients typically have paucibacillary TB [28], it is expected that it would actually take longer for them to be diagnosed. The univariate analysis may have been affected by confounding factors.

In this study, the median TTTI for LPA was also significantly better compared to culture/phenotypic DST. This result was expected as LPA technology has been shown to improve TTTI mainly due to a reduction in time to diagnosis [11, 12, 17, 19]. In this study the median TTTI of 29 days for LPA was similar to that of 28 days in Khayelitsha [19]. However, the time to diagnosis of 12 days was shorter than in the comparative studies above. It is likely that this was because the majority of LPA tests were done directly on smear positive sputums and not on culture isolates. While Hanrahan et al. [11] found an overall time to diagnosis of 26 days, the time to diagnosis was only 13 days when LPA was done directly on smear positive sputums. Other studies did not report separately on the results of LPA done directly on sputum compared to culture isolates [17, 18]. However, in this study, there were few patients diagnosed with LPA. This may have been due to the limited capacity for LPA testing in the Eastern Cape Province. Furthermore, the number of LPA results was too small for a meaningful statistical analysis.

The studies from South Africa [11, 17‐19], Georgia [12] and Indonesia [20] consistently show a reduction in time to diagnosis and TTTI when changing from older to newer technologies. However, neither this study nor the two published South African studies on the effectiveness of Xpert [18, 19] met the target for TTTI of five working days [14]. The challenge therefore is to reduce the time from diagnosis to treatment, which can be due to either programmatic or patient-related issues, or both.

Programmatic factors that impacted on the time from diagnosis to treatment initiation in this study included the following related to a centralized care model: all patients had to be admitted to designated hospitals approximately 200 km outside of the sub-district for initiation of treatment where they stayed until confirmed culture negative; and logistical challenges contributed to delays e.g. availability of hospital beds and transportation.

Strengthening of health systems with innovative programs of care can improve outcomes including survival, a high treatment rate (86% of those diagnosed), reduced treatment delay, and improved case detection of MDR-TB in South Africa [29, 30]. A systematic review and meta-analysis concluded that community based MDR-TB treatment programs globally were non-inferior to centralized programs [31]. The South African Department of Health is implementing a decentralised model of care [32].

The HIV prevalence (61%) in patients with MDR-TB in this study is broadly similar to studies in South Africa namely, Cape Town, 74% [19]; Cape Town, 59% [18]; Northern Cape Province, 67% [11]; and KwaZulu Natal, 71% [33]. People with HIV are at increased risk of MDR-TB. with an odds ratio of 1.24 compared to HIV negative people [34].

All patients diagnosed with HIV and MDR-TB were on antiretroviral therapy (ART). As all patients were hospitalised for initiation of MDR-TB treatment, it was easy to ensure compliance with national guidelines which state that patients with MDR-TB must be fast-tracked on ART [5, 35]. The fact that 100% of HIV positive patients were on ART means a working policy i.e. ART guidelines are well implemented. ART is associated with improved survival in patients with HIV and MDR-TB [36, 37].

In this study, there were significantly more males than females with MDR-TB and HIV with a male to female ratio of 1.4, similar to two South African studies where the ratios were 1.2 [38] and 1.3 [18]. There were also more male than female HIV negative patients with MDR-TB, with a ratio of 1.2. Farley [38] also found a higher male to female ratio of 1.7 in HIV negative patients. The male to female ratio was 1.3 among all patients diagnosed with TB in South Africa in 2014 [1]. The reasons for the male preponderance are not well characterised but may reflect biological differences in male and female susceptibility to TB infection and disease [39].

A limitation of retrospective observational studies is missing data. There are challenges with the EDRWeb system including poor-quality data entry and the lack of a unique patient identifier to track patient data [40]. In this study, missing data were managed by omitting patients from analysis (case deletion) as opposed to data imputation which is typically used with very large computerised databases [41].

Exclusion of patients with missing data from analysis may have biased results. However, there was no reason to suspect that patients with missing data differed in any respect than those who were included. The time to diagnosis and TTTI did not account for the time from collection of sputum to registration at the laboratory. If specimens arrive late in the day at the laboratory, they would be analysed the next day. Thus, the time to diagnosis and TTTI in this study may have been underestimated by approximately one day.

The strength of this study is that it analysed real world clinical practice in a deprived rural sub-district in South Africa and depicted high statistical power and reliability due to the adequate sample. It is likely that the results of this study are applicable in similar rural settings in South Africa.

This study shows that Xpert reduces time to treatment initiation in a rural setting with a median TTTI of 18 days. This is similar to TTTI’s in urban settings in South Africa. However, to achieve the national target of 5 days, it is necessary to reduce the time from diagnosis to treatment by addressing health system and patient-related challenges contributing to delayed treatment initiation.