Increasing access to the MDR-TB surveillance programme through a collaborative model in western Kenya.

OBJECTIVE: Kenya, like many resource-constrained countries, has a single mycobacterial laboratory, centrally located in Nairobi, with capacity for drug-susceptibility testing (DST) - the gold standard in diagnosing drug-resistant tuberculosis. We describe and evaluate a novel operational design that attempts to overcome diagnostic delivery barriers. METHODS: Review of the public DST programme identified several barriers limiting access: lack of programme awareness amongst physicians, limited supplies, unreliable transport and no specimen tracking methods. Staff visited 19 clinic sites in western Kenya and trained healthcare providers in regard to the novel diagnostics model. Provincial laboratory registries were reviewed to assess utilization of DST services prior to and after programme modification. RESULTS: Onsite training consisted of the inclusion criteria for re-treatment patients - the high-priority group for DST. Additionally, infrastructural support established a stable supply chain. An existing transport system was adapted to deliver sputum specimens. Task shifting created an accession and tracking system of specimens. During the 24 months post-implementation, the number of re-treatment specimens from the catchment area increased from 9.1 to 23.5 specimens per month. In comparing annual data pre- and post-implementation, the proportion of re-treatment cases receiving DST increased from 24.7% (n = 403) to 32.5% (n = 574) (P < 0.001), and the number of multidrug-resistant (MDR) TB cases increased from 5 to 10 cases. CONCLUSION: The delivery model significantly increased the proportion of re-treatment cases receiving DST. Barriers to accessing the national MDR-TB surveillance programme can be overcome through an operational model based on pragmatic use of existing services from multiple partners.

Misclassification of first-line antiretroviral treatment failure based on immunological monitoring of HIV infection in resource-limited settings.

BACKGROUND: The monitoring of patients with human immunodeficiency virus (HIV) infection who are treated with antiretroviral medications in resource-limited settings is typically performed by use of clinical and immunological criteria. The early identification of first-line antiretroviral treatment failure is critical to prevent morbidity, mortality, and drug resistance. Misclassification of failure may result in premature switching to second-line therapy. METHODS: Adult patients in western Kenya had their viral loads (VLs) determined if they had adhered to first-line therapy for >6 months and were suspected of experiencing immunological failure (ie, their CD4 cell count decreased by 25% in 6 months). Misclassification of treatment failure was defined as a 25% decrease in CD4 cell count with a VL of <400 copies/mL. Logistic and tree regressions examined relationships between VL and 4 variables: CD4 T cell count (hereafter CD4 cell count), percentage of T cells expressing CD4 (hereafter CD4 cell percentage), percentage decrease in the CD4 T cell count (hereafter CD4 cell count percent decrease), and percentage decrease in the percentage of T cells expressing CD4 (hereafter CD4% percent decrease). RESULTS: There were 149 patients who were treated for 23 months; they were identified as having a 25% decrease in CD4 cell count (from 375 to 216 cells/microL) and a CD4% percent decrease (from 19% to 15%); of these 149 patients, 86 (58%) were misclassified as having experienced treatment failure. Of 42 patients who had a 50% decrease in CD4 cell count, 18 (43%) were misclassified. In multivariate logistic regression, misclassification odds were associated with a higher CD4 cell count, a shorter duration of therapy, and a smaller CD4% percent decrease. By combining these variables, we may be able to improve our ability to predict treatment failure. CONCLUSIONS: Immunological monitoring as a sole indicator of virological failure would lead to a premature switch to valuable second-line regimens for 58% of patients who experience a 25% decrease in CD4 cell count and for 43% patients who experience a 50% decrease in CD4 cell count, and therefore this type of monitoring should be reevaluated. Selective virological monitoring and the addition of indicators like trends CD4% percent decrease and duration of therapy may systematically improve the identification of treatment failure. VL testing is now mandatory for patients suspected of experiencing first-line treatment failure within the Academic Model Providing Access to Healthcare (AMPATH) in western Kenya, and should be considered in all resource-limited settings.

Use of Lot Quality Assurance Sampling to Ascertain Levels of Drug Resistant Tuberculosis in Western Kenya.

OBJECTIVE: To classify the prevalence of multi-drug resistant tuberculosis (MDR-TB) in two different geographic settings in western Kenya using the Lot Quality Assurance Sampling (LQAS) methodology. DESIGN: The prevalence of drug resistance was classified among treatment-naïve smear positive TB patients in two settings, one rural and one urban. These regions were classified as having high or low prevalence of MDR-TB according to a static, two-way LQAS sampling plan selected to classify high resistance regions at greater than 5% resistance and low resistance regions at less than 1% resistance. RESULTS: This study classified both the urban and rural settings as having low levels of TB drug resistance. Out of the 105 patients screened in each setting, two patients were diagnosed with MDR-TB in the urban setting and one patient was diagnosed with MDR-TB in the rural setting. An additional 27 patients were diagnosed with a variety of mono- and poly- resistant strains. CONCLUSION: Further drug resistance surveillance using LQAS may help identify the levels and geographical distribution of drug resistance in Kenya and may have applications in other countries in the African Region facing similar resource constraints.

HIV diversity and drug resistance from plasma and non-plasma analytes in a large treatment programme in western Kenya.

INTRODUCTION: Antiretroviral resistance leads to treatment failure and resistance transmission. Resistance data in western Kenya are limited. Collection of non-plasma analytes may provide additional resistance information. METHODS: We assessed HIV diversity using the REGA tool, transmitted resistance by the WHO mutation list and acquired resistance upon first-line failure by the IAS-USA mutation list, at the Academic Model Providing Access to Healthcare (AMPATH), a major treatment programme in western Kenya. Plasma and four non-plasma analytes, dried blood-spots (DBS), dried plasma-spots (DPS), ViveST(TM)-plasma (STP) and ViveST-blood (STB), were compared to identify diversity and evaluate sequence concordance. RESULTS: Among 122 patients, 62 were treatment-naïve and 60 treatment-experienced; 61% were female, median age 35 years, median CD4 182 cells/µL, median viral-load 4.6 log10 copies/mL. One hundred and ninety-six sequences were available for 107/122 (88%) patients, 58/62 (94%) treatment-naïve and 49/60 (82%) treated; 100/122 (82%) plasma, 37/78 (47%) attempted DBS, 16/45 (36%) attempted DPS, 14/44 (32%) attempted STP from fresh plasma and 23/34 (68%) from frozen plasma, and 5/42 (12%) attempted STB. Plasma and DBS genotyping success increased at higher VL and shorter shipment-to-genotyping time. Main subtypes were A (62%), D (15%) and C (6%). Transmitted resistance was found in 1.8% of plasma sequences, and 7% combining analytes. Plasma resistance mutations were identified in 91% of treated patients, 76% NRTI, 91% NNRTI; 76% dual-class; 60% with intermediate-high predicted resistance to future treatment options; with novel mutation co-occurrence patterns. Nearly 88% of plasma mutations were identified in DBS, 89% in DPS and 94% in STP. Of 23 discordant mutations, 92% in plasma and 60% in non-plasma analytes were mixtures. Mean whole-sequence discordance from frozen plasma reference was 1.1% for plasma-DBS, 1.2% plasma-DPS, 2.0% plasma-STP and 2.3% plasma-STB. Of 23 plasma-STP discordances, one mutation was identified in plasma and 22 in STP (p<0.05). Discordance was inversely significantly related to VL for DBS. CONCLUSIONS: In a large treatment programme in western Kenya, we report high HIV-1 subtype diversity; low plasma transmitted resistance, increasing when multiple analytes were combined; and high-acquired resistance with unique mutation patterns. Resistance surveillance may be augmented by using non-plasma analytes for lower-cost genotyping in resource-limited settings.