Mortality in adults with multidrug-resistant tuberculosis and HIV by antiretroviral therapy and tuberculosis drug use: an individual patient data meta-analysis

Bisson, Gregory P.; Bastos, Mayara Lisboa; Campbell, Jonathon R.; Bang, Didi; Brust, James C.M.; Isaakidis, Petros; Lange, Christoph; Menzies, Dick; Migliori, Giovanni Battista; Pape, Jean William; Palmero, Domingo; Baghaei, Parvaneh; Tabarsi, Payam; Viiklepp, Piret; Vilbrun, Stalz Charles; Walsh, Jonathan; Marks, Suzanne M.

doi:10.1016/s0140-6736(20)31316-7

Cited by 51 publications

(46 citation statements)

References 25 publications

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“…Different predictors contribute to this unacceptable high level of mortality. Even though there are previously conducted systematic reviews regarding the poor treatment outcome of DR-TB and its predictors, most of the studies are geographically restricted or restricted to a certain study group [14][15][16]. For example, our team performed a systematic review and meta-analysis to assess the poor treatment outcome and its predictors among DR-TB patients in Ethiopia.…”

Section: Resultsmentioning

confidence: 99%

Predictors of mortality in patients with drug-resistant tuberculosis: A systematic review and meta-analysis

Alemu

Bitew

Worku³

et al. 2021

PLoS ONE

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Background Even though the lives of millions have been saved in the past decades, the mortality rate in patients with drug-resistant tuberculosis is still high. Different factors are associated with this mortality. However, there is no comprehensive global report addressing these risk factors. This study aimed to determine the predictors of mortality using data generated at the global level. Methods We systematically searched five electronic major databases (PubMed/Medline, CINAHL, EMBASE, Scopus, Web of Science), and other sources (Google Scholar, Google). We used the Joanna Briggs Institute Critical Appraisal tools to assess the quality of included articles. Heterogeneity assessment was conducted using the forest plot and I2 heterogeneity test. Data were analyzed using STATA Version 15. The pooled hazard ratio, risk ratio, and odd’s ratio were estimated along with their 95% CIs. Result After reviewing 640 articles, 49 studies met the inclusion criteria and were included in the final analysis. The predictors of mortality were; being male (HR = 1.25,95%CI;1.08,1.41,I2;30.5%), older age (HR = 2.13, 95%CI;1.64,2.62,I2;59.0%,RR = 1.40,95%CI; 1.26, 1.53, I2; 48.4%) including a 1 year increase in age (HR = 1.01, 95%CI;1.00,1.03,I2;73.0%), undernutrition (HR = 1.62,95%CI;1.28,1.97,I2;87.2%, RR = 3.13, 95% CI; 2.17,4.09, I2;0.0%), presence of any type of co-morbidity (HR = 1.92,95%CI;1.50–2.33,I2;61.4%, RR = 1.61, 95%CI;1.29, 1.93,I2;0.0%), having diabetes (HR = 1.74, 95%CI; 1.24,2.24, I2;37.3%, RR = 1.60, 95%CI;1.13,2.07, I2;0.0%), HIV co-infection (HR = 2.15, 95%CI;1.69,2.61, I2; 48.2%, RR = 1.49, 95%CI;1.27,1.72, I2;19.5%), TB history (HR = 1.30,95%CI;1.06,1.54, I2;64.6%), previous second-line anti-TB treatment (HR = 2.52, 95% CI;2.15,2.88, I2;0.0%), being smear positive at the baseline (HR = 1.45, 95%CI;1.14,1.76, I2;49.2%, RR = 1.58,95%CI;1.46,1.69, I2;48.7%), having XDR-TB (HR = 2.01, 95%CI;1.50,2.52, I2;60.8%, RR = 2.44, 95%CI;2.16,2.73,I2;46.1%), and any type of clinical complication (HR = 2.98, 95%CI; 2.32, 3.64, I2; 69.9%). There are differences and overlaps of predictors of mortality across different drug-resistance categories. The common predictors of mortality among different drug-resistance categories include; older age, presence of any type of co-morbidity, and undernutrition. Conclusion Different patient-related demographic (male sex, older age), and clinical factors (undernutrition, HIV co-infection, co-morbidity, diabetes, clinical complications, TB history, previous second-line anti-TB treatment, smear-positive TB, and XDR-TB) were the predictors of mortality in patients with drug-resistant tuberculosis. The findings would be an important input to the global community to take important measures.

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Section: Resultsmentioning

confidence: 99%

Predictors of mortality in patients with drug-resistant tuberculosis: A systematic review and meta-analysis

Alemu

Bitew

Worku³

et al. 2021

PLoS ONE

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“…[ 49 ]. Evidence supports the feasibility, safety, and effectiveness of integration of ART and TB services, [ 50 ], while failing to integrate TB and HIV services has been shown to increase mortality and poor treatment outcomes [ 51 , 52 ]. Greater overall integration is important for reducing TB mortality, be that integration between HIV, TB, and noncommunicable disease programmes [ 53 ] or integration across levels of service.…”

Section: Discussionmentioning

confidence: 99%

Health system determinants of tuberculosis mortality in South Africa: a causal loop model

Osman

Karat

Khan³

et al. 2021

BMC Health Serv Res

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Background Tuberculosis (TB) is a major public health concern in South Africa and TB-related mortality remains unacceptably high. Numerous clinical studies have examined the direct causes of TB-related mortality, but its wider, systemic drivers are less well understood. Applying systems thinking, we aimed to identify factors underlying TB mortality in South Africa and describe their relationships. At a meeting organised by the ‘Optimising TB Treatment Outcomes’ task team of the National TB Think Tank, we drew on the wide expertise of attendees to identify factors underlying TB mortality in South Africa. We generated a causal loop diagram to illustrate how these factors relate to each other. Results Meeting attendees identified nine key variables: three ‘drivers’ (adequacy & availability of tools, implementation of guidelines, and the burden of bureaucracy); three ‘links’ (integration of health services, integration of data systems, and utilisation of prevention strategies); and three ‘outcomes’ (accessibility of services, patient empowerment, and socio-economic status). Through the development and refinement of the causal loop diagram, additional explanatory and linking variables were added and three important reinforcing loops identified. Loop 1, ‘Leadership and management for outcomes’ illustrated that poor leadership led to increased bureaucracy and reduced the accessibility of TB services, which increased TB-related mortality and reinforced poor leadership through patient empowerment. Loop 2, ‘Prevention and structural determinants’ describes the complex reinforcing loop between socio-economic status, patient empowerment, the poor uptake of TB and HIV prevention strategies and increasing TB mortality. Loop 3, ‘System capacity’ describes how fragmented leadership and limited resources compromise the workforce and the performance and accessibility of TB services, and how this negatively affects the demand for higher levels of stewardship. Conclusions Strengthening leadership, reducing bureaucracy, improving integration across all levels of the system, increasing health care worker support, and using windows of opportunity to target points of leverage within the South African health system are needed to both strengthen the system and reduce TB mortality. Further refinement of this model may allow for the identification of additional areas of intervention.

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“…odds of dying was associated with not using ART at the time of MDR/RR-TB treatment initiation 14 : In our study, the number of patients who started ART after starting MDR/RR-TB treatment was too small to identify a correlation. Since 2016, all HIVcoinfected patients have been started on ART irrespective of the CD4 count.…”

Section: Discussionmentioning

confidence: 61%

Predictors of Rifampicin-Resistant Tuberculosis Mortality among HIV-Coinfected Patients in Rwanda

Habimana

Ngabonziza

Migambi

et al. 2021

The American Journal of Tropical Medicine and Hygiene

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Tuberculosis (TB), including multidrug-resistant (MDR; i.e., resistant to at least rifampicin and isoniazid)/rifampicin-resistant (MDR/RR) TB, is the most important opportunistic infection among people living with HIV (PLHIV). In 2005, Rwanda launched the programmatic management of MDR/RR-TB. The shorter MDR/RR-TB treatment regimen (STR) has been implemented since 2014. We analyzed predictors of MDR/RR-TB mortality, including the effect of using the STR overall and among PLHIV. This retrospective study included data from patients diagnosed with RR-TB in Rwanda between July 2005 and December 2018. Multivariable logistic regression was used to assess predictors of mortality. Of 898 registered MDR/RR-TB patients, 861 (95.9%) were included in this analysis, of whom 360 (41.8%) were HIV coinfected. Overall, 86 (10%) patients died during MDR/RR-TB treatment. Mortality was higher among HIV-coinfected compared with HIV-negative TB patients (13.3% versus 7.6%). Among HIV-coinfected patients, patients aged ≥ 55 years (adjusted odds ratio = 5.89) and those with CD4 count ≤ 100 cells/mm3 (adjusted odds ratio = 3.77) had a higher likelihood of dying. Using either the standardized longer MDR/RR-TB treatment regimen or the STR was not correlated with mortality overall or among PLHIV. The STR was as effective as the long MDR/RR-TB regimen. In conclusion, older age and advanced HIV disease were strong predictors of MDR/RR-TB mortality. Therefore, special care for elderly and HIV-coinfected patients with ≤ 100 CD4 cells/mL might further reduce MDR/RR-TB mortality.

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Mortality in adults with multidrug-resistant tuberculosis and HIV by antiretroviral therapy and tuberculosis drug use: an individual patient data meta-analysis

Cited by 51 publications

References 25 publications

Predictors of mortality in patients with drug-resistant tuberculosis: A systematic review and meta-analysis

Predictors of mortality in patients with drug-resistant tuberculosis: A systematic review and meta-analysis

Health system determinants of tuberculosis mortality in South Africa: a causal loop model

Predictors of Rifampicin-Resistant Tuberculosis Mortality among HIV-Coinfected Patients in Rwanda

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