783 research outputs found
What is the true tuberculosis mortality burden? Differences in estimates by the World Health Organization and the Global Burden of Disease study
Background: The World Health Organization (WHO) and the Global Burden of Disease
(GBD) study at the Institute for Health Metrics and Evaluation (IHME) periodically provide
global estimates of tuberculosis (TB) mortality. We compared the 2015 WHO and GBD
TB mortality estimates and explored which factors might drive the differences.
Methods: We extracted the number of estimated TB-attributable deaths, disaggregated
by age, HIV status, sex and country from publicly available WHO and GBD datasets for
the year 2015. We ‘standardized’ differences between sources by adjusting each country’s difference in absolute number of deaths by the average number of deaths estimated
by both sources.
Results: For 195 countries with estimates from both institutions, WHO estimated
1 768 482 deaths attributable to TB, whereas GBD estimated 1 322 916 deaths, a difference of 445 566 deaths or 29% of the average of the two estimates. The countries with
the largest absolute differences in deaths were Nigeria (216 621), Bangladesh (49 863)
and Tanzania (38 272). The standardized difference was not associated with HIV prevalence, prevalence of multidrug resistance or global region, but did show correlation with
the case detection rate as estimated by WHO [r ¼ 0.37, 95% confidence interval (CI):
049; 0.24] or, inversely, with case detection rate based on GBD data (r ¼ 0.44, 95% CI:
0.31; 0.54). Countries with a recent national prevalence survey had higher standardized
differences (higher estimates by WHO) than those without (P ¼ 0.006). After exclusion of
countries with recent prevalence surveys, the overall correlation between both estimates
was r ¼ 0.991. Conclusions: A few countries account for the large global discrepancy in TB mortality
estimates. The differences are due to the methodological approaches used by WHO and
GBD. The use and interpretation of prevalence survey data and case detection rates
seem to play a role in the observed differences
Resolution of anaemia in a cohort of HIV-infected patients with a high prevalence and incidence of tuberculosis receiving antiretroviral therapy in South Africa
BACKGROUND: Anaemia is frequently associated with both HIV-infection and HIV-related tuberculosis (TB) in antiretroviral therapy (ART)-naive patients in sub-Saharan Africa and is strongly associated with poor prognosis. However, the effect of ART on the resolution of anaemia in patient cohorts with a high prevalence and incidence of tuberculosis is incompletely defined and the impact of TB episodes on haemoglobin recovery has not previously been reported. We therefore examined these issues using data from a well-characterised cohort of patients initiating ART in South Africa. METHODS: Prospectively collected clinical and haematological data were retrospectively analysed from patients receiving ART in a South African township ART service. TB diagnoses and time-updated haemoglobin concentrations, CD4 counts and HIV viral loads were recorded. Anaemia severity was classified according to WHO criteria. Multivariable logistic regression analysis was used to determine factors independently associated with anaemia after 12months of ART. RESULTS: Of 1,140 patients with baseline haemoglobin levels, 814 were alive in care and had repeat values available after 12months of ART. The majority of patients were female (73%), the median CD4 count was 104 cells/uL and 30.5% had a TB diagnosis in the first year of ART. At baseline, anaemia (any severity) was present in 574 (70.5%) patients and was moderate/severe in 346 (42.5%). After 12months of ART, 218 (26.8%) patients had anaemia of any severity and just 67 (8.2%) patients had moderate/severe anaemia. Independent predictors of anaemia after 12months of ART included greater severity of anaemia at baseline, time-updated erythrocyte microcytosis and receipt of an AZT-containing regimen. In contrast, prevalent and/or incident TB, gender and baseline and time-updated CD4 cell count and viral load measurements were not independent predictors. CONCLUSIONS: Although anaemia was very common among ART-naive patients, the anaemia resolved during the first year of ART in a large majority of patients regardless of TB status without routine use of additional interventions. However, approximately one-quarter of patients remained anaemic after one year of ART and may require additional investigations and/or interventions
The predictive value of current haemoglobin levels for incident tuberculosis and/or mortality during long-term antiretroviral therapy in South Africa: a cohort study
BACKGROUND: Low haemoglobin concentrations may be predictive of incident tuberculosis (TB) and death in HIV-infected patients receiving antiretroviral therapy (ART), but data are limited and inconsistent. We examined these relationships retrospectively in a long-term South African ART cohort with multiple time-updated haemoglobin measurements. METHODS: Prospectively collected clinical data on patients receiving ART for up to 8years in a community-based cohort were analysed. Time-updated haemoglobin concentrations, CD4 counts and HIV viral loads were recorded, and TB diagnoses and deaths from all causes were ascertained. Anaemia severity was classified using World Health Organization criteria. TB incidence and mortality rates were calculated and Poisson regression models were used to identify independent predictors of incident TB and mortality, respectively. RESULTS: During a median follow-up of 5.0years (IQR, 2.5-5.8) of 1,521 patients, 476 cases of incident TB and 192 deaths occurred during 6,459 person-years (PYs) of follow-up. TB incidence rates were strongly associated with time-updated anaemia severity; those without anaemia had a rate of 4.4 (95%CI, 3.8-5.1) cases/100 PYs compared to 10.0 (95%CI, 8.3-12.1), 26.6 (95%CI, 22.5-31.7) and 87.8 (95%CI, 57.0-138.2) cases/100 PYs in those with mild, moderate and severe anaemia, respectively. Similarly, mortality rates in those with no anaemia or mild, moderate and severe time-updated anaemia were 1.1 (95%CI, 0.8-1.5), 3.5 (95%CI, 2.7-4.8), 11.8 (95%CI, 9.5-14.8) and 28.2 (95%CI, 16.5-51.5) cases/100 PYs, respectively. Moderate and severe anaemia (time-updated) during ART were the strongest independent predictors for incident TB (adjusted IRR=3.8 [95%CI, 3.0-4.8] and 8.2 [95%CI, 5.3-12.7], respectively) and for mortality (adjusted IRR=6.0 [95%CI, 3.9-9.2] and adjusted IRR=8.0 [95%CI, 3.9-16.4], respectively). CONCLUSIONS: Increasing severity of anaemia was associated with exceptionally high rates of both incident TB and mortality during long-term ART. Patients receiving ART who have moderate or severe anaemia should be prioritized for TB screening using microbiological assays and may require adjunctive clinical interventions
Drivers and trajectories of resistance to new first-line drug regimens for tuberculosis.
BACKGROUND: New first-line drug regimens for treatment of tuberculosis (TB) are in clinical trials: emergence of resistance is a key concern. Because population-level data on resistance cannot be collected in advance, epidemiological models are important tools for understanding the drivers and dynamics of resistance before novel drug regimens are launched. METHODS: We developed a transmission model of TB after launch of a new drug regimen, defining drug-resistant TB (DR-TB) as resistance to the new regimen. The model is characterized by (1) the probability of acquiring resistance during treatment, (2) the transmission fitness of DR-TB relative to drug-susceptible TB (DS-TB), and (3) the probability of treatment success for DR-TB versus DS-TB. We evaluate the effect of each factor on future DR-TB prevalence, defined as the proportion of incident TB that is drug-resistant. RESULTS: Probability of acquired resistance was the strongest predictor of the DR-TB proportion in the first 5 years after the launch of a new drug regimen. Over a longer term, however, the DR-TB proportion was driven by the resistant population's transmission fitness and treatment success rates. Regardless of uncertainty in acquisition probability and transmission fitness, high levels (>10%) of drug resistance were unlikely to emerge within 50 years if, among all cases of TB that were detected, 85% of those with DR-TB could be appropriately diagnosed as such and then successfully treated. CONCLUSIONS: Short-term surveillance cannot predict long-term drug resistance trends after launch of novel first-line TB regimens. Ensuring high treatment success of drug-resistant TB through early diagnosis and appropriate second-line therapy can mitigate many epidemiological uncertainties and may substantially slow the emergence of drug-resistant TB
Delays and loss to follow-up before treatment of drug-resistant tuberculosis following implementation of Xpert MTB/RIF in South Africa: A retrospective cohort study.
BACKGROUND: South Africa has a large burden of rifampicin-resistant tuberculosis (RR-TB), with 18,734 patients diagnosed in 2014. The number of diagnosed patients has increased substantially with the introduction of the Xpert MTB/RIF test, used for tuberculosis (TB) diagnosis for all patients with presumptive TB. Routine aggregate data suggest a large treatment gap (pre-treatment loss to follow-up) between the numbers of patients with laboratory-confirmed RR-TB and those reported to have started second-line treatment. We aimed to assess the impact of Xpert MTB/RIF implementation on the delay to treatment initiation and loss to follow-up before second-line treatment for RR-TB across South Africa. METHODS AND FINDINGS: A nationwide retrospective cohort study was conducted to assess second-line treatment initiation and treatment delay among laboratory-diagnosed RR-TB patients. Cohorts, including approximately 300 sequentially diagnosed RR-TB patients per South African province, were drawn from the years 2011 and 2013, i.e., before and after Xpert implementation. Patients with prior laboratory RR-TB diagnoses within 6 mo and currently treated patients were excluded. Treatment initiation was determined through data linkage with national and local treatment registers, medical record review, interviews with health care staff, and direct contact with patients or household members. Additional laboratory data were used to track cases. National estimates of the percentage of patients who initiated treatment and time to treatment were weighted to account for the sampling design. There were 2,508 and 2,528 eligible patients in the 2011 and 2013 cohorts, respectively; 92% were newly diagnosed with RR-TB (no prior RR-TB diagnoses). Nationally, among the 2,340 and 2,311 new RR-TB patients in the 2011 and 2013 cohorts, 55% (95% CI 53%-57%) and 63% (95% CI 61%-65%), respectively, started treatment within 6 mo of laboratory receipt of their diagnostic specimen (p < 0.001). However, in 2013, there was no difference in the percentage of patients who initiated treatment at 6 mo between the 1,368 new RR-TB patients diagnosed by Xpert (62%, 95% CI 59%-65%) and the 943 diagnosed by other methods (64%, 95% CI 61%-67%) (p = 0.39). The median time to treatment decreased from 44 d (interquartile range [IQR] 20-69) in 2011 to 22 d (IQR 2-43) in 2013 (p < 0.001). In 2013, across the nine provinces, there were substantial variations in both treatment initiation (range 51%-73% by 6 mo) and median time to treatment (range 15-36 d, n = 1,450), and only 53% of the 1,448 new RR-TB patients who received treatment were recorded in the national RR-TB register. This retrospective study is limited by the lack of information to assess reasons for non-initiation of treatment, particularly pre-treatment mortality data. Other limitations include the use of names and dates of birth to locate patient-level data, potentially resulting in missed treatment initiation among some patients. CONCLUSIONS: In 2013, there was a large treatment gap for RR-TB in South Africa that varied significantly across provinces. Xpert implementation, while reducing treatment delay, had not contributed substantially to reducing the treatment gap in 2013. However, given improved case detection with Xpert, a larger proportion of RR-TB patients overall have received treatment, with reduced delays. Nonetheless, strategies to further improve linkage to treatment for all diagnosed RR-TB patients are urgently required
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