Infectious diseases represent a public health challenge especially in resource-limited countries. Tuberculosis (TB) is caused in humans by a bacterial pathogen belonging to genus
Since the achievement of full coverage of TB in Cameroon in 2002, the National Control Programme of TB has continuously improved its fight through policy and many key strategies including the implementation of surveillance system, a faster management through 248 diagnostic and treatment centers (DTCs) distributed over the territory. Also, there was an increase in full adherence to treatment as well as the proportion of cured patients through the adoption of directly observed treatment strategy (DOTS) based on rifampicin used as first-line treatment [
We present in this study an overview of treatment outcomes of TB in Cameroon for the period 2014–2016 using a more robust analysis method based on meta-analysis approach. In addition, we evaluate the influence of loss to follow-up and death rates and the cotrimoxazole (CTX) and antiretroviral therapy (ART) coverage in treatment outcomes of the TB therapy by performing subgroup analysis. It is hoped that this overview will improve the understanding of the dynamics of TB treatment in Cameroon and inform policy.
Data of interest was obtained from the electronic database of the Regional Health Delegation in the Littoral Region upon obtaining all ethical clearance from the Institutional Review Board of the Faculty of Health Sciences of the University of Buea and administrative authorizations from regional delegation of public health for the Littoral Region. They were collected from 15 diagnostic and treatment centers (DTCs) of the Littoral Region, namely, CSI Delangue + Prison (CSIDelP), Dibamba Medical Center (DiMedC), Ekol-Mbeng CSI (EMCSI), Loum District Hospital (LDH), Mbanga District Hospital (MDH), St Jean de Malthe Hospital (StJDMH), CEBEC Ndoungue Hospital (CNH), Nkondjock District Hospital (NDH), Nkongsamba Protestant Hospital (NPH), Pouma Catholic Hospital (PCH), Epec Sakbayeme Hospital (ESH), Yabassi District Hospital (YDH), Melong District Hospital (MeDH), Alucam Medical and Social Center (AMSC), and Edea Regional Hospital (ERH).
Data collected consisted of the following: total number of TB-infected people treated, the number of people who successfully responded to treatment, the number of therapeutic failure (TF), the type of patients (HIV-uninfected and HIV-infected), and the number of HIV-positive people under cotrimoxazole (CTX) and antiretroviral therapy (ARV). These data were presented with respect to the above-mentioned DTCs. It is worth noticing that multidrug-resistant TB (MDR-TB) patients are not managed in these DTCs; thus, this category of patients was not included in the present study.
The treatment success rates (TSR) were the parameter investigated in the study. Treatment success rate corresponds to percentage of TB patients (new and relapse cases) registered under DOTS in a given year that successfully completed treatment, with or without bacteriological evidence of success (“cured” and “treatment completed,” respectively) [
These parameters were computed using two approaches, namely, intention-to-treat (ITT) analysis and per protocol (PP) analysis. In the ITT analysis, the denominator is the total number of patients initially enrolled in a given year while in the PP analysis, the denominator is the total number of patients in whom the efficacy of treatment can be evaluated at the end of follow-up (i.e., success or failure). Thus, deaths, lost to follow-up, defaulted, and transferred out remain included in the ITT analysis while they are excluded from the calculation in PP analysis [
The manually extracted data was keyed into Excel and exported to the OpenMeta Analyst and SPSS version 25 software for meta-analysis and inferential statistics. Data was presented as charts or tables where appropriate. Spearman correlation and chi-squared tests were used to study both quantitative and qualitative variables, respectively. The significance was set at
This was obtained from the Institutional Review Board of the Faculty of Health Sciences of the University of Buea in Cameroon.
The distribution of population with regard to gender and age is presented in Figure
Distribution of patients with tuberculosis according to gender from 2014 to 2016.
Distribution of patients with tuberculosis according to age from 2014 to 2016 in the Littoral Region of Cameroon.
A total of 581, 501, and 441 TB-infected and HIV-uninfected individuals were registered in the National Control Programme in the Littoral Region in the years 2014, 2015, and 2016, respectively. Four DTCs, namely, CSIDelP, StJDMH, NPH, and LDH, managed more than half of registered patients irrespective of the year.
The prevalence of HIV infection among TB-positive patients has decreased over three years, from 38.50% in 2014 to 34.60% in 2016, even though none statistically significant difference was found (
Cotrimoxazole and antiretroviral drugs coverage among HIV-infected patients according to the DTC and year (2014-2016) in the Littoral Region of Cameroon.
Cotrimoxazole coverage | Antiretroviral therapy coverage | |||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Year 2014 | Year 2015 | Year 2016 | Year 2014 | Year 2015 | Year 2016 | |||||||||||||
DTCs | % | % | % | % | % | % | ||||||||||||
CSIDelP | 58 | 58 | 100.0 | 62 | 61 | 98.39 | 51 | 50 | 98.04 | 58 | 49 | 84.48 | 62 | 54 | 87.10 | 51 | 47 | 92.16 |
DiMedC | 7 | 3 | 42.86 | 0 | 0 | NA | 6 | 4 | 66.67 | 7 | 0 | 0.00 | 0 | 0 | NA | 6 | 5 | 83.33 |
EMCSI | 4 | 4 | 100.0 | 0 | 0 | NA | 2 | 2 | 100.0 | 4 | 3 | 75.0 | 0 | 0 | NA | 2 | 2 | 100.0 |
LDH | 19 | 19 | 100.0 | 15 | 15 | 100.0 | 12 | 11 | 91.67 | 19 | 0 | 0.00 | 15 | 4 | 26.67 | 12 | 9 | 75.00 |
MDH | 6 | 5 | 83.33 | 7 | 5 | 71.43 | 7 | 6 | 85.71 | 6 | 0 | 0.00 | 7 | 0 | 0.00 | 7 | 5 | 71.43 |
StJDMH | 62 | 62 | 100.0 | 62 | 62 | 100.0 | 45 | 45 | 100.0 | 62 | 59 | 95.16 | 62 | 62 | 100.0 | 45 | 42 | 93.33 |
CNH | 9 | 4 | 44.44 | 8 | 2 | 25.0 | 7 | 2 | 28.57 | 9 | 0 | 0.00 | 8 | 1 | 12.50 | 7 | 1 | 14.29 |
NDH | 0 | 0 | NA | 0 | 0 | NA | 0 | 0 | NA | 0 | 0 | NA | 0 | 0 | NA | 0 | 0 | NA |
NPH | 63 | 39 | 61.90 | 77 | 70 | 90.91 | 48 | 47 | 97.92 | 63 | 30 | 47.62 | 77 | 62 | 80.52 | 48 | 45 | 93.75 |
PCH | 7 | 5 | 71.43 | 13 | 13 | 100.0 | 13 | 13 | 100.0 | 7 | 5 | 71.43 | 13 | 13 | 100.0 | 13 | 13 | 100.0 |
ESH | 7 | 7 | 100.0 | 6 | 5 | 83.33 | 6 | 6 | 100.0 | 7 | 3 | 42.86 | 6 | 3 | 50.0 | 6 | 6 | 100.0 |
YDH | 4 | 2 | 50.0 | 6 | 6 | 100.0 | 4 | 4 | 100.0 | 4 | 1 | 25.0 | 6 | 5 | 83.33 | 4 | 4 | 100.0 |
MeDH | 2 | 2 | 100.0 | 3 | 3 | 100.0 | 4 | 1 | 25.0 | 2 | 2 | 100.0 | 3 | 2 | 66.67 | 4 | 2 | 50.0 |
AMSC | 2 | 0 | 0.00 | 0 | 0 | NA | 0 | 0 | NA | 2 | 0 | 0.00 | 0 | 0 | NA | 0 | NA | |
ERH | 58 | 40 | 68.97 | 52 | 42 | 80.77 | 35 | 35 | 100.0 | 58 | 33 | 56.90 | 52 | 34 | 65.38 | 35 | 35 | 100.0 |
Total | 308 | 243 | 78.90 | 311 | 284 | 91.32 | 240 | 226 | 94.17 | 308 | 185 | 60.06 | 311 | 240 | 77.17 | 240 | 216 | 90.00 |
The proportion of HIV-uninfected TB patients successfully cured from TB has slightly decreased between 2014 and 2016 (Figure
Evolution of proportion of treatment success, treatment failure, deaths, loss to follow-up, and transfer in HIV-uninfected patients with regard to trimester (Trim) and year (2014-2016) in the Littoral Region of Cameroon.
Forest plots of pooled values of anti-TB treatment success rate in HIV-uninfected patients with regard to year and DTCs using ITT analysis (a) and PP analysis (b) from 2014 to 2016 in the Littoral Region of Cameroon. TB: tuberculosis;
In 2014, the proportion of treatment success gradually decreased and then increased as from 2015 to 2016 (Figure
Evolution of proportion of treatment success, treatment failure, deaths, loss to follow-up, and transfer in HIV-infected patients with regard to trimester (Trim) and year (2014-2016) in the Littoral Region of Cameroon.
Forest plots of pooled values of anti-TB treatment success rate in HIV-positive patients with regard to year and DTCs using ITT analysis (a) and PP analysis (b) from 2014 to 2016 in the Littoral Region of Cameroon. : individual values of anti-TB therapy success rate in each DTCs; : global value of anti-TB therapy success rate in each year; : global value of anti-TB therapy success rate for the three years; TB: tuberculosis;
The treatment success rates were strongly and negatively correlated with the rates of patients lost to follow-up regardless to the year. The correlation coefficient values were statistically significant:
The treatment success rates were strongly and negatively correlated with the rates of deaths regardless to the year with the exception of 2015 (Figure
Correlation between the percentage of ITT-based treatment success in HIV-negative patients and the percentage of patients lost to follow-up in 2014 (a), 2015 (b), and 2016 (c) in the Littoral Region of Cameroon.
Correlation between the percentage of ITT-based treatment success in HIV-positive patients and the percentage of deaths in 2014 (a), 2015 (b) and 2016 (c) in the Littoral Region of Cameroon.
A positive and statistically significant correlation was found between the cotrimoxazole coverage rate and the treatment success in 2015 and 2016 (Table
Correlation between the anti-TB therapy success and rate coverage of CTX and ARV in HIV-positive patients from 2014 to 2016 in the Littoral Region of Cameroon.
Nature of the correlation | 95% CI | |||
---|---|---|---|---|
Treatment success and CTX coverage rates | ||||
Year 2014 | 14 | -0.044 | -0.562 to 0.498 | 0.883 |
Year 2015 | 11 | 0.779 | 0.337 to 0.940 | 0.003 |
Year 2016 | 13 | 0.758 | 0.355 to 0.923 | 0.001 |
Treatment success and ARV coverage rates | ||||
Year 2014 | 14 | -0.254 | -0.692 to 0.319 | 0.388 |
Year 2015 | 11 | 0.240 | -0.421 to 0.734 | 0.489 |
Year 2016 | 13 | 0.806 | 0.458 to 0.940 | 0.0004 |
TB: tuberculosis; CTX: cotrimoxazole; ARV: antiretroviral; HIV: human immunodeficiency virus;
Tuberculosis still remains one of the main causes for concern in Cameroon. We used a meta-analysis to compute the efficacy of anti-TB therapy over three years. The pooled values of percentage of cured patients, both HIV-uninfected and HIV-infected, have gradually decreased over time. This is partially attributable to the high rate of patients lost to follow-up as showed in this study. The findings are consistent with previous findings that outlined that nonadherence to treatment was the main cause of lost to follow-up [
Besides, the pooled values of cure rates were below the threshold of 85% defined by the WHO [
We used two approaches to compute the data and the pooled prevalence of treatment success, namely, ITT and PP analyses. Heterogeneity was higher in ITT analysis as compared to PP analysis, and this can be due to the fact that these two methods rely on different bases for calculating treatment success as above-mentioned. In PP analysis, denominator used to compute TSR corresponds to the number of people in whom the efficacy of therapy can be evaluated at the end of follow-up while the total number of initially enrolled patients constitutes the denominator in ITT analysis. ITT is considered as a standard for analysis of clinical trials due to the fact that its results reflect better clinical practice characterized by a high between-study heterogeneity. Thus, it is not surprising to have a high heterogeneity in TS between different DTCs using ITT analysis. Besides, ITT analysis allows for maintenance of comparability between groups, sample size, and eliminates bias [
The treatment rates were significantly lower in TB/HIV-coinfected people using the ITT analysis, and this is consistent with previous hospital-based study conducted in Yaoundé [
We found that not all HIV-infected individuals were under cotrimoxazole and under ARV therapy despite an increase in the coverage rate from 2014 to 2016. This was shown by a strong positive correlation between the rates of coverage with CTX and ARV therapy and anti-TB therapy success, thereby outlining the higher CTX or ARV therapy rates, the higher anti-TB therapy success rates. Also, the complication of HIV disease due to the absence of ARV therapy could also have been involved in some of these deaths. Cotrimoxazole (CTX) and ARV therapies are both necessary to reduce the risk of deaths in HIV/TB-coinfected people. Cotrimoxazole is an antibiotic used to prevent the occurrence of opportunistic diseases while the ARV therapy is used to slow down the course of the disease and stabilize the immune system of HIV patients [
The findings of this study should be interpreted in light of its limitations. First, the study analysed date from 15 DTCs of the Littoral Region, and this does not reflect the picture at the national level. Second, we found strong correlation between TSR with both CTX and ART therapy coverages in HIV-positive TB patients. However, we did not explore other factors, such as treatment adherence and intrinsic susceptibility of
In conclusion, this study outlined a slight decrease in the anti-TB treatment success rates from 2014 to 2016. These rates were lower than the WHO threshold in both TB infected alone and TB/HIV coinfected and were mainly attributable to lost to follow-up and nonobservance to CTX/ARV, respectively. Finally, this study also points out a need for strengthening the policies for cotrimoxazole and ARV therapy in TB/HIV coinfected. An improvement in the reduction of percentage of lost to follow-up and CTX and ARV therapy coverage could greatly increase the chances to efficiently control TB in Cameroon. There is need to develop, implement, or reinforce strategies aimed at limiting the magnitude of loss to follow-up and increasing the coverage rates with cotrimoxazole and antiretroviral therapy. These strategies should be focused mainly on change in behavior of TB patients.
The data used to support the findings of this study are available from the corresponding author upon request.
The authors declare having no competing interest.
This is part of a PhD thesis by DFKM under the supervision of DSN in the Department of Public Health and Hygiene, Faculty of Health Sciences at the University of Buea, DA Faculty of Medicine and Pharmaceutical Sciences at the University of Douala, and JCNA Department of Medical Laboratory Sciences, Faculty of Health Sciences at the University of Buea in Cameroon. We acknowledge all stakeholders including the District Medical Officers, the Tuberculosis Reference Laboratory at the Regional Delegation for Public Health in the Littoral Region for authorization to collect data, and the Chief of Health Centers, Community leaders, and colleagues for their contributions in the realization of this study during data collection.