Economic support intervention improves tuberculosis treatment outcomes in rural Nigeria.

SETTING: A secondary care hospital in rural Nigeria. OBJECTIVE: To investigate the feasibility of providing financial incentives to tuberculosis (TB) patients under routine conditions, and to determine their impact on TB treatment outcomes in a low-resource setting. DESIGN: A prospective, non-randomised intervention study. RESULTS: A total of 294 TB patients (respectively 173 and 121 in the control and intervention periods of 3 months' duration each) were registered in the study. The patients did not differ in terms of their demographic or clinical characteristics (P not significant). The treatment success rate was 104/121 (86.0%) during the intervention, and 123/173 (71.1%) during the control period (P = 0.003). The proportion of patients who were lost to follow-up significantly decreased during the intervention period (20.2% vs. 5.0%, P <0.001). There were no differences in deaths (P = 0.8) or treatment failure rates (P = 0.5) in the intervention and control periods. There was also no difference in the rate of sputum smear conversion after the intensive phase of treatment (88.1% vs. 91.5%, P = 0.5). Independent determinants of treatment success were female sex (adjusted odds ratio [aOR] 1.9), human immunodeficiency virus negativity (aOR 2.5) and receiving financial incentives (aOR 2.3). CONCLUSIONS: Financial incentives proved to be effective in improving treatment success and reducing loss to follow-up among poor TB patients in Nigeria.

Six- vs. eight-month anti-tuberculosis regimen for pulmonary tuberculosis under programme conditions.

SETTING: One urban tertiary care and one rural secondary care hospital in Nigeria. OBJECTIVE: To compare the epidemiological characteristics and treatment outcomes of tuberculosis (TB) patients treated with an 8-month or 6-month anti-tuberculosis regimen in a low-resource setting. DESIGN: Retrospective cohort study. RESULTS: A total of 928 newly diagnosed smear-positive TB patients were treated with either daily ethambutol (EMB), isoniazid (INH), rifampicin (RMP) and pyrazinamide (PZA) for 2 months followed by EMB and INH for 6 months (2RHZE/6EH), or the same intensive phase as the first regimen followed by 4 months of daily RMP and INH (2RHZE/4RH). The proportion of successful outcomes was 381/490 (77.8%) with 2RHZE/6EH and 373/438 (85.2%) with 2RHZE/4RH (P = 0.004). Defaulting was significantly more frequent in patients who received 2RHZE/6EH (14.3% vs. 5.5%; P < 0.001). Treatment failure was not significantly higher in patients who received 2RHZE/6EH (2.9% vs. 1.6%; P = 0.15). After adjusting for confounders, older age (adjusted odds ratio [aOR] 1.7), 2RHZE/6EH treatment (aOR 1.6) and male sex (aOR 1.5) independently predicted unsuccessful outcomes in human immunodeficiency virus negative TB patients. CONCLUSIONS: Newly diagnosed TB patients on 2RHZE/4RH have a higher treatment success rate than those treated with 2RHZE/6EH under programme conditions in a low-resource, high-burden setting. Current World Health Organization recommendations should be maintained.

Investigating gender disparities in the profile and treatment outcomes of tuberculosis in Ebonyi state, Nigeria.

SUMMARY Globally, twice as many men as women are being diagnosed with tuberculosis (TB) annually. Little is known about gender differentials in TB in Africa. A retrospective cohort analysis of routine data was conducted on adult TB patients treated between 2011 and 2012 in two large healthcare facilities in Nigeria. Gender differences in their demographic characteristics and treatment outcomes were analysed accordingly. Of 1668 TB patients enrolled, the male:female ratio was 1.4:1. The mean ages of males and females were 40.2 ± 14.7 and 36.1 ± 14.6 years, respectively (t test 6.62, P < 0.001). Male gender was associated with a higher failure to smear convert after 2 months (21.8% vs. 17.5%, P = 0.06) and 5 months (4.3% vs. 1.5%, P = 0.02) of treatment for smear-positive TB patients. Moreover, men were more likely than women to fail treatment (2.2% vs. 0.7%, P = 0.01). No significant differences exist in the treatment success rates between women and men (78.2% vs. 74.5%, P = 0.08). Adjusted analyses showed significant association between being an urban male and a HIV-infected female with unsuccessful outcome adjusted by socio-demographic and clinical factors. We found that gender disparities exist in TB profile and treatment outcomes in Nigeria and gender-specific strategies are needed to optimize TB management.

Tuberculosis treatment outcome and its determinants in a tertiary care setting in south-eastern Nigeria.

AIMS AND OBJECTIVES: To evaluate tuberculosis treatment outcomes in a Nigerian tertiary-care setting and to identify factors associated with unsuccessful treatment outcome. PATIENTS AND METHODS: Retrospective audit of tuberculosis patients registered for treatment from January 2006 to December 2010 at Federal Medical Centre Abakaliki, Nigeria. Six treatment outcome criteria were assessed based on guidelines set by the World Health Organisation (WHO). Analysis was conducted using SPSS. Multivariable logistic regression analysis were used to identify independent predictors for unsuccessful treatment outcome and statistical significance was taken as P <0.05. RESULTS: A total of 671 patients (55% male, 45% female) with a mean age of 36.4 years were registered for treatment; 147 (22%) were smear-positive, 270 (40%) smear-negative and 254 (38%) had extra-pulmonary tuberculosis. Also, 189 (28.2%) of them were HIV positive and; 341 (51%) lived in a rural area. Overall, 387 patients (57.7%) had a successful treatment outcome and 284 (42.3%) had an unsuccessful treatment outcome. Of the patients with unsuccessful treatment outcome, 192 (67.6%) had defaulted, 55 (19.4%) had died, 3 (1%) had treatment failure and 34 (12%) were transferred-out. Nil significant change in trend of treatment success over the study period [P = 0.75 for trend]. In multivariable analysis, unsuccessful treatment was associated with older age (aOR = 2.3), rural residence (aOR = 2.1), smear negative PTB (aOR=1.6), being on retreatment (aOR 3.8), and HIV seropositivity (aOR=1.7). CONCLUSION: Treatment success rate was poor; targeted measures should be considered to improve treatment success among identified high-risk groups.

The economic burden of tuberculosis care for patients and households in Africa: a systematic review.

OBJECTIVES: To summarise the state of knowledge on the economic impact and consequences of tuberculosis (TB) diagnosis and treatment for patients/households in Africa, and to highlight any weaknesses in the work conducted to date. METHODS: We systematically searched for published articles in English between 1990 and June 2010 in eight databases and the World Health Organization (WHO) website. Broad search terms were used ('tuberculosis' OR 'tuberculosis/HIV' AND 'costs' AND 'Africa'). Only studies that reported any costs of TB care for patients/households were retained. All costs were converted to 2009 USD in accordance with WHO cost analysis guidelines. RESULTS: Overall, 11 articles from eight countries met the inclusion criteria. Only one study met all the quality criteria for a cost-of-illness study; most of the studies focused on urban populations, reported incomplete (pre-diagnostic/average) costs, and did not report coping costs. Mean patient pre-diagnostic costs varied between US$36 and US$196, corresponding to respectively 10.4% and 35% of their annual income. Average patient treatment costs ranged between US$3 and US$662, corresponding to 0.2-30% of their annual income. Pre-diagnostic household costs accounted for 13% and 18.8% of patients' annual household income, while total household treatment costs ranged between US$26 and US$662, accounting for 2.9-9.3% of annual household income; 18-61% of patients received financial assistance from outside their household to cope with the cost of TB care. CONCLUSION: The average patient's/household's pre-diagnostic costs for TB care were catastrophic. More properly designed studies are needed among different populations throughout Africa.