Can BMI change be used to identify TB patients at high risk of mortality? Analysis of smear-negative and extrapulmonary TB patients with HIV in Myanmar and Zimbabwe 1
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2
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Lenka Benova, Katherine Fielding, Jane Greig, Bern-Thomas Nyang'wa, Esther Carrillo Casas, Marcio Silveira da Fonseca, Philipp du Cros
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1 London School of Hygiene and Tropical Medicine, London, UK 2 Médecins Sans Frontières, London, UK 3 Médecins Sans Frontières, Amsterdam, The Netherlands
Introduction
Results
In 2010, 8.8 million incident cases of tuberculosis (TB) occurred, 1.45 million people died from the disease and 24% of those who died were co-infected with HIV. TB in HIV-positive patients is more likely to be diagnosed as smear-negative or extrapulmonary than in HIV-negative patients. WHO guidelines on interim indicators of treatment success in TB patients focus on smear-positive patients. No prognostic indicators are currently systematically applied among smear-negative and extrapulmonary TB patients to identify those at increased risk of unfavourable TB treatment outcomes.
63% of adult HIV-positive TB patients were diagnosed with smear-negative or extrapulmonary TB in MSF TB projects in six countries (2006-2008)
Methods Retrospective cohort study using patient data from three MSF TB treatment sites.
Study data project locations Shan
Smear negative
Inclusion criteria
Extrapulmonary Outcome Nicholas S, Balkan S, Pujades Rodrίguez M (2009) Outcomes of tuberculosis treatment in HIV-infected adults: multicentric analysis in 8 African HIV/ AIDS programs. MSF Intersectional SPOT report. 5th IAS Conference on HIV Pathogenesis, Treatment and Prevention. Cape Town, South Africa.
Exposure
Objective We aim to establish how change in standard body mass index (BMI) category after the first month of TB treatment in new adult smear-negative and extrapulmonary patients co-infected with HIV is associated with mortality during TB treatment.
Background
BMI changes during early TB treatment can be useful indicators of TB treatment outcomes in cohorts of mixed HIV status. The association of BMI change has not been assessed among smear-negative and extrapulmonary HIV-positive patients.
Indicator (WHO and UNAIDS, 2009) TB incidence per 100,000 HIV prevalence in 18-49 year-olds New TB cases smear-negative or extrapulmonary
Zimbabwe 742
Myanmar 404
14.3%
0.6%
51%
66%
HIV-positive new adult patients between February 2003 and July 2010 Receiving treatment for smear-negative or extrapulmonary TB Followed at least until day 15 of TB treatment All-cause mortality during TB treatment Change in BMI category between start and one month of TB treatment (Weight measurement within ±15 days of each date considered) 2 Standard categories of BMI: Severely underweight <16 kg/m 2 Underweight 16.00-18.49 kg/m 2 Normal 18.5-24.99 kg/m 2 Overweight and obese ≥25 kg/m Cox proportional hazards regression
Ethical approval
London School of Hygiene and Tropical Medicine Met MSF Ethics Review Board criteria for retrospective study of routinely collected programmatic data
Sample Description
299
80
3.44
Stable or higher BMI category
791
70
1 (ref)
Subsample with CD4 count at TB treatment start n=557
34% from Shan, 29% from Yangon and 37% from Gweru
60% of patients were underweight or severely underweight at the start of TB treatment
246 unfavourable outcomes, among which 150 deaths, were recorded Overall mortality rate 28.9 per 100 person-years (95% CI 24.6-33.9)
2.77-5.91 <0.001
n
# of deaths
HR
168
50
4.24
Stable or higher BMI category
389
31
1 (ref)
4.05 1 (ref)
Crude 95% CI P
Adjusted** HR 95% CI P
2.71-6.64 <0.001
5.25
3.09-8.91 <0.001
1 (ref)
p-value of likelihood ratio test. CI-confidence interval. HR-hazard ratio. TB-tuberculosis. ART-antiretroviral therapy. BMI-body mass index. **Adjusted for sex, age group, project, ART as time dependent variable, BMI category and CD4 category at TB treatment start.
Sensitivity analysis In a sample of 1330 patients surviving to day 30 of TB treatment, the direction and magnitude of association between BMI category change and TB treatment mortality was similar to the main model presented (adjusted HR 4.80, 95% CI 3.27-7.05, p<0.001).
Discussion
Strong association exists between binary BMI category change during early TB treatment and TB treatment mortality among HIV-positive TB smear-negative and extrapulmonary patients.
This inexpensive measure, collected and recorded during routine clinical visits, could be used for interim monitoring of patients.
Patients identified as being at increased risk of mortality could benefit from more intensive monitoring, nutritional supplementation and prioritization for further investigations.
Further research is needed to evaluate whether the use of this interim marker can improve patient and programme outcomes.
1,090 TB patients in final sample 605 smear-negative (56%) 485 extrapulmonary (44%)
2.50-4.75 <0.001
Remained severely underweight or lost a BMI category
HR
Remained severely underweight or lost a BMI category
Myanmar
Statistical analysis
Successful TB treatment should result in weight gain among underweight individuals by restoring muscle and fat mass.
n
# of deaths
Adjusted* HR 95% CI P
Adjustment for CD4 count measured at the start of TB treatment showed an even stronger magnitude of association between BMI category change and TB treatment mortality.
Yangon
Zimbabwe
Main sample n=1,090
Crude 95% CI P
p-value of likelihood ratio test. CI-confidence interval. HR-hazard ratio. TB-tuberculosis. ART-antiretroviral therapy. BMI-body mass index. *Adjusted for sex, age group, project, ART as time dependent variable and BMI category at TB treatment start.
Gweru Smear positive
Mortality rate among patients who remained severely underweight or moved to a lower BMI category during first month of TB treatment was four times higher compared to those who remained in the same BMI category or gained a BMI category in adjusted analysis.
Acknowledgments We thank our patients and field teams; Sarah Venis for editorial and Laura Feetham for graphic design assistance.
Contact info: Lenka.Benova@lshtm.ac.uk, Katherine.Fielding@lshtm.ac.uk, Jane.Greig@london.msf.org, Bern.Nyangwa@london.msf.org, Esther.Casas@amsterdam.msf.org, Marcio.Silveira.Da.Fonseca@amsterdam.msf.org, Philipp.DuCros@london.msf.org