Abstract
Background
There is a significant intersection between Tuberculosis (TB) and HIV, which has contributed greatly to the disease burden, especially in Nigeria. Among approximately 1.9 million people living with HIV (PLHIV), an estimated 46,000 also had TB in 2019 alone. HIV-associated TB incidence has continuously increased nationally. It is important to understand how PLHIV with TB undergo treatment because this is essential for improving outcomes. This study assessed the uptake of TB treatment and evaluated outcomes among PLHIV receiving antiretroviral therapy at a tertiary healthcare facility in South-South Nigeria.
Methods
The study was a hospital-based retrospective cohort study, that reviewed the records of 213 PLHIV treated for TB between January 2015 and December 2019. Patient records were examined and data extracted using a structured pro forma. Analysis was done with IBM SPSS version 26 using descriptive statistics (frequencies and Percentages) and inferential statistics (chi-square test) with statistical significance set at p < 0.05.
Results
All participants were enrolled in the National Tuberculosis, Leprosy and Buruli Ulcer Control Programme (NTBLCP). Of these, 182 individuals (85.5%) successfully completed the full 24-week course of anti-tuberculosis therapy. Treatment outcomes were classified separately, with 99 (46.5%) patients cured and 74 (34.7%) completing treatment without bacteriological confirmation, 28 (13.1%) discontinued treatment prematurely, and 12 (5.6%) were referred to other healthcare facilities for continued care.
Conclusion
TB treatment outcomes among PLHIV were suboptimal, with notable levels of default and transfer-out. Outcomes were significantly associated with socio-demographic factors and treatment duration. Strengthening adherence, support mechanisms and improving access to affordable diagnostic monitoring services may enhance TB treatment outcomes among PLHIV.
Keywords: tuberculosis treatment, TB-HIV co-infection, antiretroviral therapy, people living with HIV, TB treatment outcomes, tertiary health facility
Plain Language Summary
Tuberculosis (TB) is one of the leading causes of illness and death among people living with HIV, especially in sub-Saharan Africa. Although effective treatments are available for both HIV and TB, managing both conditions at the same time can be challenging. It is important to understand whether people living with HIV who develop TB are starting treatment promptly and how well they respond to it. This study looked at HIV-positive patients receiving antiretroviral therapy (ART) at a tertiary health facility in South-South Nigeria. We examined how many patients diagnosed with TB started TB treatment, how quickly treatment was started, and what their treatment outcomes were. We also explored factors that may have influenced whether patients completed treatment successfully. Our findings provide insight into how TB and HIV services are working together in a real-world healthcare setting. The results highlight areas where care is performing well and where improvements may be needed. For example, delays in starting treatment or challenges in completing treatment can increase the risk of poor health outcomes and ongoing transmission of TB. By identifying gaps in treatment uptake and outcomes, this study can help healthcare providers, hospital managers, and policymakers strengthen TB-HIV collaborative services. Improving early diagnosis, prompt treatment, and patient support systems may lead to better health outcomes for people living with HIV and reduce the burden of TB in high-risk communities. This research supports efforts to improve integrated care for TB and HIV in resource-limited settings.
Introduction
Tuberculosis continues to pose a significant global health threat, with its impact varying considerably from region to region. The majority of TB cases are found within the World Health Organization (WHO) regions of Southeast Asia (34%), Africa (25%), and the Western Pacific (27%), collectively representing the largest share of global incidence.1,2 While TB affects people across all age groups and genders, adult men are disproportionately affected, accounting for approximately 54–55% of all incident TB cases globally. 3 In 2024, individuals living with HIV comprised an estimated 5.8% of new TB diagnoses (approximately 620,000 cases), and mortality from TB within this group remained high, particularly throughout Africa and parts of Asia, where HIV-associated TB accounts for a substantial share of the regional TB burden.1,2
Nigeria remains one of the countries, most severely impacted by tuberculosis worldwide. The 2024 Global Tuberculosis Report indicates that Nigeria was responsible for roughly 4.6% of the world’s TB cases in 2023, with an estimated incidence rate of 206 cases per 100,000 people. 1 Beyond the high incidence of drug-sensitive TB, Nigeria also reports the highest rate of drug-resistant TB on the continent. 4 These issues are further complicated by ongoing gaps in case detection and treatment coverage, despite notable improvements in the national TB programme’s performance. 1
Although TB case reporting declined during the initial waves of the COVID-19 pandemic, subsequent years have shown a rebound in notifications across the WHO African Region. 5 Nigeria was a major contributor to this increase, which reflects both enhanced detection and continued disease spread.2,4 On a positive note, recent national data reveal that treatment success rates have improved, at times surpassing the regional average.2,4
In 1993, Nigeria adopted the directly observed treatment short-course (DOTS) as its main strategy to fight TB. 6 The DOTS approach is built on several foundational elements: firm political commitment, accurate and prompt diagnosis, standardized treatment regimens with a focus on patient support, a reliable drug supply, and strong monitoring mechanisms. 7 Integrating TB and HIV services within this framework has become especially critical in regions with high HIV prevalence. In Delta State, recent surveillance data indicate a decline in HIV prevalence, suggesting progress in control efforts that may also influence TB trends.8,9
HIV infection remains one of the most important drivers of TB incidence in Nigeria. Immune suppression associated with HIV significantly increases the risk of progression from latent to active TB, particularly in high TB-burden settings.1,7 Evidence shows that the risk of active TB rises soon after HIV infection and increases over time in the absence of antiretroviral therapy or isoniazid preventive therapy.10-12 People living with HIV are substantially more likely to develop TB disease than those without HIV infection, and TB continues to account for a significant proportion of HIV-related mortality worldwide.1,13
Studies from Nigeria and other settings have documented suboptimal TB treatment outcomes among PLHIV. In Ebonyi State, for example, unsuccessful outcomes such as defaulted treatment, death, and transferred out were commonly reported among HIV-infected TB patients. 14 Treatment interruption, particularly during or after the intensive phase, has been highlighted as a major contributor to poor outcomes. 15 Age has also been shown to influence adherence, although findings vary across settings. While some studies report higher default rates among older patients, 15 others have found younger age and rural residence to be associated with treatment interruption. 16
Additional factors affecting TB treatment uptake and outcomes among PLHIV include access to DOTS facilities, nutritional status, concurrent antiretroviral therapy, alcohol use, smoking, and socio-economic conditions.1,17,18 Both alcohol use and smoking have been linked to increased TB risk and poorer treatment outcomes, contributing substantially to the global TB burden. 1
A related hospital-based study from Southeast Nigeria also reported considerable variation in tuberculosis treatment outcomes over time. In that study, although overall treatment success declined over time, cure rates showed little variation; however, ‘defaulted treatment’, ’transferred out’, and ‘death’ continued to contribute substantially to unfavorable outcomes. 19 Age and HIV status were identified as key determinants of treatment success, with younger patients more likely to achieve favourable outcomes than older individuals. Those living without HIV had better outcomes compared to patients with HIV infection at treatment initiation. 19
Considering these persistent obstacles, it is vital to assess how people living with HIV on antiretroviral therapy access and respond to TB treatment, especially within tertiary hospitals that function as referral hubs. These analyses yield critical information to bolster integrated TB–HIV efforts, decrease avoidable illness and death, and support progress toward both national and international TB elimination benchmarks.
Despite existing studies on tuberculosis treatment outcomes in Nigeria, there is limited context-specific evidence on treatment uptake and outcomes among people living with HIV receiving antiretroviral therapy in tertiary care settings in South-South Nigeria. In particular, the role of diagnostic access and broader health system factors in shaping treatment continuity and outcomes in this population remains underexplored. This gap limits the ability of policymakers and program managers to design targeted interventions that address context-specific barriers to optimal TB-HIV care. This study, therefore, provides facility-based evidence to help inform policy and program improvements in similar resource-constrained settings. Although the data were collected between 2015 and 2019, the organization of TB/HIV service delivery within the national program has remained largely consistent, particularly in tertiary settings, supporting the continued relevance of these findings.
This study aimed to assess the uptake of tuberculosis treatment and evaluate treatment outcomes among people living with HIV receiving antiretroviral therapy at a tertiary health facility in South-South Nigeria.
Methods
Study Area
This research was conducted at an Endemic Disease Clinic within a tertiary healthcare facility in South-South Nigeria. The clinic, which is part of the Department of Public Health, delivers combined tuberculosis and HIV care. Outpatient services are available on weekdays, accommodating a continuous stream of individuals with TB and HIV-related illnesses. As a tertiary referral hospital, the facility offers specialist services to residents within the state and neighbouring states in the region.
Study Design
A retrospective cohort study design was used to assess TB treatment uptake and outcomes using routinely documented patient records. Information was extracted from records covering both the intensive and continuation phases of TB treatment, including laboratory and radiological investigations used to monitor treatment progress. The study period was selected to allow adequate follow-up for treatment outcomes within the available dataset.
Study Population
The study included 213 out of 2002 adults living with HIV diagnosed with TB between January 2015 and December 2019. Diagnosis was based on standard clinical and laboratory criteria, including chest radiography, sputum GeneXpert testing, and acid-fast bacilli smear microscopy. All participants were on antiretroviral therapy. Information on timing of ART initiation and viral load measurements was not consistently available in the records and therefore was not analyzed. Patients with previous TB treatment, severe comorbidities, incomplete diagnostic records, or missing treatment outcome data were excluded to ensure comparability of outcomes (Figure 1).
Figure 1.
Study flow diagram- TB-HIV co-infected patients on ART (2015–2019)
All patients were managed under the National Tuberculosis, Leprosy and Buruli Ulcer Control Programme, which provides standardized guidelines for TB diagnosis, treatment, and follow-up across Nigeria. 20
Sampling Strategy
Due to the retrospective nature of the study, no formal sample size calculation was performed. All eligible TB-HIV co-infected patients managed between January 2015 and December 2019 who met the inclusion criteria and had complete records were included in the analysis. A total of 213 patients who met the inclusion criteria were selected. Inclusion criteria were: (i) confirmed diagnosis of tuberculosis, (ii) HIV-positive status, (iii) receipt of anti-TB treatment within the study period, and (iv) availability of complete treatment records.
Data Collection
The DOTS clinic register was used to select eligible clients for the study over a five-year period (January 2015 to December 2019). An average of 10-15 patients visited the clinic weekly, with 5-6 treated for TB and HIV co-infection. Retrospective data collection was performed by reviewing the case files of patients who met the study criteria, employing a standardized proforma. The extracted data were categorized into three sections. The first section gathered information on patients’ socio-demographic details and the length of anti-tuberculosis therapy. The second section included findings from key laboratory and radiological investigations, such as sputum acid-fast bacilli microscopy (AAFB ×2), GeneXpert assay, and chest X-rays- as documented in the patients’ records. These tests were typically conducted at essential treatment milestones, namely at the start of therapy, at the conclusion of the intensive phase, and during the continuation phase.
The third section addressed both treatment uptake and patient outcomes. Uptake was considered as registration in the National Tuberculosis, Leprosy and Buruli Ulcer Control Programme (NTBLCP) and documented adherence to anti-TB medication protocols. Outcomes were categorized according to national standards: cured, treatment completed, defaulted, transferred out, treatment failure, or death.
Bias
To minimize selection bias, all eligible patient records within the study period that met the inclusion criteria were included in the analysis. Data extraction was conducted using a standardized pro forma to improve consistency and reduce information bias.
Study Variables
The primary outcome variable was TB treatment outcome, categorized according to NTBLCP/WHO definitions as cured, treatment completed, defaulted, transferred out, treatment failure, or death. For regression analysis, outcomes were further grouped into successful treatment outcomes (cured and treatment completed) and unsuccessful treatment outcomes (defaulted and transferred out).
Predictor variables included age, sex, marital status, educational status, place of residence, and duration on anti-TB treatment. Diagnostic criteria for TB were based on chest radiography, sputum GeneXpert testing, and acid-fast bacilli smear microscopy as documented in patient records.
Outcome Definitions
Treatment outcomes were classified according to standard national and World Health Organization guidelines.1,2 A patient was considered cured if they had bacteriological confirmation of tuberculosis at diagnosis and were smear- or culture-negative in the last month of treatment and on at least one previous occasion.1,3 Treatment completed referred to patients who completed treatment but without bacteriological confirmation at the end of therapy.1,2 Default (lost to follow-up) was defined as interruption of treatment for two consecutive months or more.1,2 Transferred out referred to patients who were transferred to another health facility and whose treatment outcomes were not known at the reporting facility.1,9 Treatment failure was defined as persistent or recurrent bacteriological positivity at five months or later during treatment.1,3 Death referred to patients who died from any cause during the course of treatment.1,2
Data Analysis
Before extracting data, patient files were checked for completeness. Records with incomplete key outcome variables were excluded during data cleaning; consequently, there were no missing data in the final analysis. The team then compiled and coded the necessary information, which was entered into IBM SPSS Statistics version 26 for further analysis. Descriptive statistics were generated: categorical data (for example, marital status and education level) were reported as counts and percentages, and continuous variables were summarized using means and standard deviations. To explore relationships between TB treatment outcomes and variables such as socio-demographic factors or length of therapy, Chi-square tests, and multivariable logistic regression were applied. For logistic regression analysis, marital status was regrouped into single, married/cohabiting, and previously married categories, while educational status was categorized as secondary or less and tertiary education to improve model stability. Odds ratios (ORs) with 95% confidence intervals (CIs) were reported, and statistical significance was set at p < 0.05. For statistical analysis, transfer-out cases were grouped with unsuccessful outcomes because their final treatment status could not be ascertained at the reporting facility.”
This study was reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for cohort studies [see Supplementary File]. 21
Ethical Approval
Ethical approval for the study was obtained from the Institutional Ethics and Research Committee (Approval No: FMC/ASB/A81 VOL XII/125). Due to the retrospective nature of the study and the use of anonymized routinely collected clinical records, the requirement for informed consent was waived by the Ethics Committee. The confidentiality of all patient data was strictly upheld, and information was accessed exclusively for the purposes of this research.
Results
A total of 213 out of 2002 patients met the inclusion criteria and were included in the final analysis. Figure 1 presents a flow diagram of patient disposition throughout the study period.
A significant proportion of patients, 72 (33.8%) and 71 (33.3%), fell within the age groups of 31 – 40 years and 41– 50 years, respectively, with a mean age of 44.7 ± 17.3 years (Table 1). There was a preponderance of males (139, 65.3%), and most participants (204, 95.8%) identified as Christians. Regarding education, 155 (72.8%) patients completed secondary school, and the majority, 166 (77.9%), lived in urban areas. Additionally, more than three–fifths (139, 65.3%) of the participants were married.
Table 1.
Sociodemographic Characteristics of Participants
| Variables | Frequency (n=213) | (%) |
|---|---|---|
| Age groups (years) | ||
| < 20 | 7 | 3.3 |
| 21 – 30 | 27 | 12.7 |
| 31 – 40 | 72 | 33.8 |
| 41 – 50 | 71 | 33.3 |
| 51 – 60 | 31 | 14.6 |
| 61 – 70 | 2 | 0.9 |
| > 70 | 3 | 1.4 |
| Sex | ||
| Male | 139 | 65.3 |
| Female | 74 | 34.7 |
| Marital status of respondents | ||
| Single | 44 | 20.7 |
| Married | 139 | 65.3 |
| Cohabiting | 5 | 2.3 |
| Separated/divorced | 3 | 1.4 |
| Widow/widower | 22 | 10.3 |
| Religion of respondents | ||
| Christianity | 204 | 95.8 |
| Islam | 7 | 3.3 |
| African Traditional Religion | 2 | 0.9 |
| Level of Education | ||
| Primary | 17 | 8 |
| Secondary | 155 | 72.8 |
| Tertiary | 41 | 19.2 |
| Residence | ||
| Urban | 166 | 77.9 |
| Rural | 47 | 22.1 |
Figure 2 shows that all study participants were enrolled in the NTBLCP, with 182 (85.4%) completing anti-tuberculosis medications within 24 weeks of treatment initiation. Among the 28 participants who defaulted treatment, 20 (71.4%) were male and 16 (57.1%) resided in rural areas. “Furthermore, two–thirds, 142 (66.7%) of the study participants had GeneXpert results indicating Mycobacterium tuberculosis (MTB) detection without rifampicin resistance, while slightly less than one–fourth, 51 (23.9%) participants had positive AFBX2 test results, while 130 (61.0%) tested negative.
Figure 2.
Participants enrolled in the NTBLCP and duration on anti-tuberculosis drugs
Chest radiography was performed at different stages of treatment monitoring. Baseline chest X-rays were conducted at diagnosis/initiation of anti-TB therapy, followed by repeat imaging at the end of the intensive phase and continuation phase where documented. Some participants therefore appeared in more than one radiographic assessment category because the investigations were conducted sequentially during treatment follow-up. The baseline chest X-ray in most participants (162, 76.1%) showed abnormalities. In contrast, the follow–up chest X-ray showed abnormalities in about one–fifth (55, 25.8%) of the participants, while about half 108 (50.7%) did not undergo the second chest X-ray as requested. By the end of the continuation phase, 61 (28.6%) participants had normal chest X-ray findings, while an equal proportion, 61 (28.6%), did not undergo the recommended follow-up chest X-ray at this stage (Table 2).
Table 2.
Investigation Results of the Participants
| Results | Frequency (n=213) | (%) |
|---|---|---|
| AFBX2 results of participants | ||
| Negative | 130 | 61.0 |
| Positive | 51 | 23.9 |
| Not done | 32 | 15.0 |
| GeneXpert results of participants | ||
| MTB detected; non – rifampicin resistant | 142 | 66.7 |
| MTB not detected | 45 | 21.1 |
| Not done | 26 | 12.2 |
| Baseline X – ray results of participants | ||
| Normal chest X – ray | 34 | 15.9 |
| Abnormal chest X – ray | 162 | 76.1 |
| Not done | 17 | 8.0 |
| Chest X – ray at the end of the Intensive phase | ||
| Normal chest X – ray | 31 | 14.6 |
| Abnormal chest X – ray | 55 | 25.8 |
| Improved | 19 | 8.9 |
| Not done | 108 | 50.7 |
| Chest X – ray at the end of the Continuation phase | ||
| Normal chest X – ray | 61 | 28.6 |
| Abnormal chest X – ray | 44 | 20.7 |
| Improved | 47 | 22.1 |
| Not done | 61 | 28.6 |
Figure 3 shows the treatment outcomes: 99 (46.5%) participants were cured, and approximately a third, 74 (34.7%), completed their anti-TB regimen. Slightly over one–tenth, 28 (13.2%) defaulted, while twelve (5.6%) were transferred to other health facilities. Completion of the 24-week treatment course reflects adherence to the recommended treatment duration, whereas treatment outcomes (cured, treatment completed, default, and transfer-out) were classified according to standard program definitions based on clinical and bacteriological criteria.
Figure 3.
Treatment outcomes of participants
Table 3 tests the association between sociodemographic variables and duration on anti-TB drugs and treatment outcomes of participants. The participants’ age group, marital status, educational background, place of residence, and duration of anti-tuberculosis treatment were all statistically significant factors in treatment outcomes.
Table 3.
Association Between Socio–Demographic Variables, Duration on Anti – TB Drugs, and Treatment Outcomes of Participants
| Variables | Successful outcome (cured + completed) n (%) | Unsuccessful outcome (default + transferred out) n (%) | χ2 | p-value |
|---|---|---|---|---|
| Age group (years) | ||||
| ≤30 | 32 (94.1) | 2 (5.9) | 47.578 | 0.001* |
| 31–50 | 118 (82.5) | 25 (17.5) | ||
| >50 | 23 (63.9) | 13 (36.1) | ||
| Sex | ||||
| Male | 109 (78.4) | 30 (21.6) | 5.573 | 0.130 |
| Female | 64 (86.5) | 10 (13.5) | ||
| Marital status | ||||
| Married | 116 (83.5) | 23 (16.5) | 87.809 | 0.001* |
| Not married (single, cohabiting, widowed, separated, divorced) | 57 (77.0) | 17 (23.0) | ||
| Educational status | ||||
| Primary | 10 (58.8) | 7 (41.2) | 37.379 | 0.001* |
| Secondary | 126 (81.3) | 29 (18.7) | ||
| Tertiary | 37 (90.2) | 4 (9.8) | ||
| Residence | ||||
| Urban | 148 (89.2) | 18 (10.8) | 29.704 | 0.001* |
| Rural | 25 (53.2) | 22 (46.8) | ||
| Duration on anti-TB drugs | ||||
| <24 weeks | 0 (0.0) | 25 (100.0) | 105.441 | 0.001* |
| ≥24 weeks | 173 (92.0) | 15 (8.0) | ||
Participants aged 31–50 years recorded the highest proportion of successful treatment outcomes, with 118 (82.5%) achieving cure or treatment completion, while participants aged above 50 years had a relatively higher proportion of unsuccessful outcomes, 13 (36.1%). Among male participants, 109 (78.4%) had successful treatment outcomes, compared with 64 (86.5%) of female participants. Married participants had a higher proportion of successful treatment outcomes, 116 (83.5%), compared with unmarried participants, 57 (77.0%). A preponderance, 37 (90.2%), of participants with tertiary education achieved successful treatment outcomes, compared with 126 (81.3%) of those with secondary education and 10 (58.8%) of those with primary education. Urban residents demonstrated better treatment outcomes, with 148 (89.2%) achieving successful outcomes compared with 25 (53.2%) of rural residents (Table 4).
Table 4.
Multivariable Logistic Regression Analysis of Factors Associated With Unsuccessful TB Treatment Outcomes Among PLHIV
| Variable | Category | AOR (Exp(B)) | 95% CI | p-value |
|---|---|---|---|---|
| Age | Continuous | 0.518 | 0.233 – 1.151 | 0.106 |
| Sex | Male vs Female | 1.139 | 0.567 – 2.289 | 0.714 |
| Residence | Urban vs Rural | 0.606 | 0.300 – 1.225 | 0.163 |
| Duration of anti-TB drugs | Continuous | 1.019 | 0.993 – 1.045 | 0.154 |
| Educational status | Secondary or less vs Tertiary | 0.538 | 0.243 – 1.194 | 0.128 |
| Marital status | Overall (3 categories) | 2.439 | 1.283 – 4.637 | 0.007* |
Notes. Outcome variable: Unsuccessful TB treatment (default + transferred out), Reference category for marital status: Previously married (widowed/divorced/separated), AOR = Adjusted Odds Ratio; CI = Confidence Interval.
*Statistically significant at p < 0.05.
Participants who remained on anti-TB treatment for at least 24 weeks had better treatment outcomes, with 173 (92.0%) achieving successful outcomes, whereas all participants who received treatment for less than 24 weeks had unsuccessful outcomes. There was a statistically significant association between age group and treatment outcomes (χ2 = 47.578, p = 0.001), with better outcomes observed among participants in the 31–50-year age range. Marital status was also significantly associated with treatment outcomes (χ2 = 87.809, p = 0.001), with higher default rates observed among widowed participants. Similarly, educational status showed a significant relationship with treatment outcomes (χ2 = 37.379, p = 0.001), as participants with secondary and tertiary education demonstrated better outcomes compared to those with lower levels of education.
Place of residence was significantly associated with treatment outcomes (χ2 = 29.704, p = 0.001), with participants residing in urban areas more likely to achieve favourable outcomes than their rural counterparts. Duration on anti-tuberculosis treatment also showed a strong association with treatment outcomes (χ2 = 105.441, p = 0.001), with patients who completed at least 24 weeks of treatment more likely to be cured or complete therapy. However, no statistically significant association was observed between sex and treatment outcomes (χ2 = 5.573, p = 0.130). No deaths were recorded in the available patient records.
A multivariable logistic regression analysis was conducted to identify independent predictors of unsuccessful treatment outcomes (default and transfer-out). Variables entered into the model included age, sex, residence, educational status, marital status, and duration on anti-TB treatment.
The overall model was statistically significant (χ2 = 12.799, p = 0.046), explaining 7.8% of the variance in treatment outcomes (Nagelkerke R2 = 0.078). Marital status was the only variable independently associated with treatment outcome (AOR = 2.439, 95% CI: 1.283–4.637; p = 0.007). Sex, duration on anti-TB treatment, residence, educational status, and age were not significantly associated with treatment outcomes after adjustment for potential confounders (p > 0.05).
Discussion
This study evaluated treatment outcomes among patients with tuberculosis (TB) and HIV co-infection managed at a tertiary health facility. Although most patients were initiated on and remained on treatment for an adequate duration, overall treatment success (85.5%; defined as the sum of cured and treatment completed) remained below the World Health Organization target of 90%, for TB treatment success. 22 By comparison, a recent study from Rivers State University Teaching Hospital reported treatment success of only 50.4% among TB only and TB-HIV co-infected patients, with significantly higher mortality (9.6% vs. 1.5%, p = 0.001) and loss to follow-up (49.5% vs. 38.6%, p = 0.005) compared to TB-only patients. 23 Our results also align with observations from Ghana, where TB treatment success among co-infected patients increased from 43% to 78% following TB/HIV service integration, though mortality remained high at 18-25% in HIV-associated cases. 24 This highlights the ongoing challenge of attaining successful TB treatment results among people living with HIV, even in well-organized care settings.
The less-than-ideal treatment success rate seen here does not appear to be due to inadequate healthcare access, since nearly all participants completed the intensive phase of their regimen. Instead, it may be attributed to the intricacies of managing TB-HIV co-infection and the sustained effort required by patients. Those affected must take several medications at the same time, often over many months, which can lead to side effects, fatigue from prolonged treatment, and difficulties adhering to therapy. Research from Uganda identified pill burden, knowledge gaps, and drug stock-outs as major barriers to TB preventive therapy completion among people living with HIV, with treatment completion rates reaching 98% when shorter regimens and adherence counselling were provided. 25 The characteristics of the study group mirror the established TB epidemiology in Nigeria, showing more cases among middle-aged adults and men, consistent with other local studies. 26 A study from Bauchi State, Nigeria, reported the highest TB prevalence (57.6%) among individuals aged 31-40 years, with males (54.5%) having a slightly higher prevalence than females (45.5%). 27 The higher occurrence of TB in men is thought to arise from factors such as occupational risks, delays in seeking medical care, and certain biological vulnerabilities. 28 Moreover, alcohol consumption, which is widely accepted and frequent in the South-South region, could also negatively impact immunity and treatment adherence, particularly in male patients, though this aspect was not directly evaluated in our research.
The level of education impacted how well patients completed treatment. The majority had attained secondary education or higher, and those who stayed in the program for the full duration were more likely to finish treatment. Education is often linked to increased disease awareness, stronger adherence, and more active involvement with healthcare services. 29 Although we did not directly measure health literacy, our findings imply that having at least some formal education may help patients stick to lengthy TB treatment regimens. Variations in educational background and available health system resources could also account for differences in treatment outcomes seen across various states in Nigeria. 30
Place of Residence and Access to Care
Where patients lived played a significant role in their treatment results, with urban dwellers achieving better outcomes overall. In our study, urban residents achieved 89.4% treatment success compared to 76.2% among rural residents, an absolute difference of 13.2 percentage points. Benefits of living in urban areas include easier access to healthcare facilities, more readily available diagnostic tests, and regular interactions with medical professionals. Other studies in Nigeria have shown comparable patterns, including a study from northern Nigeria, which reported a 14.1 percentage point difference favoring urban patients. 29 In contrast, those in rural or semi-urban locations often face worse results due to limited infrastructure and fewer trained healthcare workers 30
Unlike previous studies that reported worse outcomes for TB-HIV patients managed at tertiary hospitals, often due to delayed care and advanced illness, our findings indicated relatively more favourable results.27,30 A likely reason is that many participants were already receiving HIV care at the centre before developing TB, which may have led to earlier identification of TB, prompt treatment, and ongoing monitoring. This points to the advantage of having integrated TB and HIV services under one roof.
Financial Constraints and Diagnostic Follow-Up
While laboratory tests for diagnosing TB were available free of charge, patients had to cover the cost of chest X-rays themselves. Although the majority of participants received initial imaging, far fewer returned for additional X-rays as treatment went on. The decline in follow-up chest radiography uptake suggests gaps in continuity of diagnostic monitoring during treatment, which is important for assessing treatment response and informing clinical decisions. However, this study did not directly examine the reasons for non-uptake, and these findings should be interpreted with caution.
There is a well-documented link between TB and economic hardship, as the expenses related to diagnosis, travel, and time away from work can be a major burden for patients and their families. 1 The decline in repeat imaging seen in our cohort highlights how paying out-of-pocket can disrupt comprehensive care, even if primary treatment is subsidized. Our results underscore the need for expanded financial support to cover essential diagnostic and monitoring services for TB patients, especially those with HIV.
Unsuccessful Treatment Outcomes
A proportion of participants experienced treatment interruption, while some were transferred to other facilities for continuation of care. Because treatment outcomes for transferred-out patients could not be verified within the study centre, their final outcomes could not be ascertained. Dropping out of care is typically caused by a combination of factors, such as side effects from medication, the challenge of taking many pills, financial problems, competing life demands, and cultural attitudes toward illness. Research involving people on both antiretroviral and TB drugs consistently identifies these reasons as major barriers to adherence.31,32
Those who transferred out of the program probably did so due to job or family moves, or to receive treatment nearer to home. This emphasizes the need for stronger referral networks and seamless care across different health centers. Scaling up TB and HIV services at the community level and enhancing coordination between facilities could help reduce interruptions in therapy and boost the success of treatment programs overall. Although marital status emerged as an independent predictor of treatment outcome, the relatively low explanatory power of the model suggests that additional clinical, behavioral, and health-system factors not captured in this study may also influence treatment outcomes among PLHIV with TB.
Notably, no deaths were recorded in this cohort. While this may reflect early diagnosis, ongoing HIV care, and integrated service delivery at the study site, it is also possible that deaths occurring outside the facility were not captured in the records.
Policy and Programmatic Implications
The findings from this study have several implications for strengthening TB/HIV programs. First, the association between treatment duration and outcomes shows the importance of sustained adherence support throughout the treatment period. Interventions such as patient follow-up systems, adherence counselling, and community-based support mechanisms may help reduce treatment interruption.
Second, the observed gaps in diagnostic follow-up highlight the need to strengthen routine monitoring within TB programs. Ensuring consistent access to recommended investigations and improving patient tracking systems could enhance treatment evaluation and clinical decision-making.
Third, disparities observed between urban and rural participants suggest a need to expand access to integrated TB/HIV services beyond tertiary centres. Decentralizing care and improving referral linkages may support continuity of care, particularly for mobile populations.
Study Limitations
A key limitation of this research was its retrospective design and reliance on standard clinical records, making it difficult to verify the accuracy and completeness of the data. Unavailable or inconsistent information could not be cross-checked, raising the possibility of bias. The use of retrospective data from 2015–2019 may limit direct applicability to current practice; however, core programmatic structures have remained relatively stable. Additionally, no deaths were recorded in this cohort of 213 TB-HIV patients, which is unusual. Mortality outcomes may have been underreported, because deaths occurring after transfer or outside the facility may not have been documented, the absence of recorded mortality should be interpreted cautiously. The study did not employ a priori sample size estimation because all eligible patient records within the study period were included. Consequently, the sample size may have limited statistical power for some subgroup analyses and multivariable modelling. Transfer-out cases may have subsequently completed treatment elsewhere; therefore, their classification as unsuccessful outcomes may have resulted in outcome misclassification. Nevertheless, these findings offer a valuable perspective on TB-HIV outcomes in real-world practice and highlight opportunities for improving similar health programs.
Conclusion
Multiple elements shape how people living with HIV engage with and respond to TB treatment, such as age, marital status, level of education, length of therapy, and where they live. This work also points to major obstacles to successful treatment, namely, difficulties with adherence, barriers to accessing diagnostic tests, and challenges related to geographic location. To address these issues, this study recommends expanding standardized TB and HIV care to community health centers nationwide, implementing incentive programs to reduce treatment default rates, and providing free or highly subsidized diagnostic tests beyond AFBX2 and GeneXpert for this patient population. These measures will help strengthen adherence to treatment and improve overall TB treatment outcomes for PLHIV.
Supplemental Material
Supplemntal material for Tuberculosis Treatment Uptake and Outcomes Among HIV-Positive Patients on Antiretroviral Therapy at a Tertiary Health Facility in South-South, Nigeria by Adesuwa Queen Aigbokhaode, Ayodapo Oluwadare Jegede, Nosa Lancy Orhue, Omo Ekeneam, Oluwaseun Opeyemi Adesoye, Noruwa Patience Ekhator, Silvia Isioma Ezemenahi, Emmanuel Okechukwu Ezunu, Raymond Aghimien, Uchenna Enwereuzo, and Ibukun Jacob Akinkunmi in Journal of the International Association of Providers of AIDS Care (JIAPAC).
Acknowledgements
The authors sincerely acknowledge the Management and staff of the Federal Medical Centre, Asaba, particularly the Centre for Communicable Diseases Control and Research, the Department of Obstetrics and Gynaecology, the Department of Paediatrics, and the Health Information Management Department, for facilitating access to relevant records and providing logistical support. We also acknowledge the patients whose anonymised records contributed to this research.
Author Contributions: A.Q.A. conceptualized the study, contributed to methodology development, led the formal analysis and data collection, and participated in statistical analysis, data interpretation, and literature review. A.O.O. contributed to methodology development, statistical analysis, and data interpretation. E.O., E.O.E., R.A., U.E., A.I.J., and other co-authors contributed to formal analysis and interpretation of findings. A.O.J. was involved in drafting the manuscript and contributed substantially to manuscript review and editing. A.Q.A., N.L.O., E.O., A.O.O., N.P.E., S.I.E., and E.O.E. contributed to manuscript review and critical revisions. A.Q.A. provided overall supervision and final approval of the version to be published. All authors approved the final manuscript and agree to be accountable for the integrity and accuracy of the work.
Funding: The authors received no financial support for the research, authorship, and/or publication of this article.
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Disclaimer: We certify that this work is original and has not been published previously. The views and opinions expressed are those of the authors and are the product of professional research. We take full responsibility for the accuracy of this work and the integrity of its content.
Supplemental Material: Supplemental material for this article is available online.
ORCID iD
Ayodapo Oluwadare Jegede https://orcid.org/0000-0002-9061-3622
Ethical Considerations
Ethical approval for this study was obtained from the Ethics and Research Committee of the Federal Medical Centre, Asaba (Approval No: FMC/ASB/A81 VOL XII/125). Permission to access patient records was granted by the Health Information Management Department. As this was a retrospective review of routinely collected clinical data, the ethics committee waived individual patient consent. All data were de-identified prior to analysis to ensure confidentiality, and no personally identifiable information was included in this study.
Data Availability Statement
The datasets generated and/or analysed during the current study are not publicly available due to institutional data protection policies but are available from the corresponding author upon reasonable request and with permission from the Federal Medical Centre, Asaba.*
References
- 1.World Health Organization . Global tuberculosis report 2024. Geneva. World Health Organization; 2024. https://iris.who.int/handle/10665/379339, Accessed 23 Dec 2025. [Google Scholar]
- 2.World Health Organization Regional Office for Africa . Tuberculosis (TB). Brazzaville: WHO AFRO. [Internet] [cited 2026 Mar 3]. Available from. https://www.afro.who.int/health-topics/tuberculosis-tb [Google Scholar]
- 3.World Health Organization . WHO Director-General's opening remarks at the media briefing – 1 November 2024. 2025. https://www.who.int/news-room/speeches/item/who-director-general-s-opening-remarks-at-the-media-briefing---1-november-2024, Accessed 1 Mar 2026.
- 4.Federal Ministry of Health and Social Welfare . Only 37% drug resistance tuberculosis cases treated in 2024 - FG. Lagos: Tribune Online; 2025. [cited 2026 May 3]. Available from. https://tribuneonlineng.com/only-37-drug-resistance-tuberculosis-cases-treated-in-2024-fg/ [Google Scholar]
- 5.World Health Organization . Global tuberculosis report 2020. Geneva: World Health Organization; 2020. https://www.who.int/publications/i/item/9789240013131 [Google Scholar]
- 6.Federal Ministry of Health, Department of Public Health . The National Strategic Plan for Tuberculosis Control: Towards Universal Access to Prevention. Diagnosis and Treatment (2015–2020) Abuja: National Tuberculosis and Leprosy Control Programme. 2014. https://indexmedicus.afro.who.int/iah/fulltext/National_Strategic_Plan_for_Tuberculosis_Control____2015_2020.pdf [Google Scholar]
- 7.World Health Organization . Treatment of tuberculosis: guidelines for national programmes. Geneva. World Health Organization; 2010. https://www.who.int/publications/i/item/9789241547833 [Google Scholar]
- 8.National Agency for the Control of AIDS . Nigeria HIV/AIDS indicator and impact survey (NAIIS). 2018. Technical Report. https://naca.gov.ng/naiis-press-release/
- 9.Aigbokhaode AQ, Orhue NI, Ojimba AO, Ekhator NP. Sociodemographic characteristics of HIV/AIDS patients attending HIV clinics in a tertiary health facility in South-South Nigeria: a 10-year retrospective study. J Dent Med Sci. 2024;23:37-42. doi: 10.9790/0853-2302073742. [DOI] [Google Scholar]
- 10.Sonnenberg P, Glynn JR, Fielding K, Murray J, Godfrey-Faussett P, Shearer S. How soon after infection with HIV does the risk of tuberculosis start to increase? A retrospective cohort study in South African gold miners. J Infect Dis. 2005;191(2):150-158. [DOI] [PubMed] [Google Scholar]
- 11.Horsburgh CRJ. Priorities for the treatment of latent tuberculosis infection in the United States. N Engl J Med. 2004;350(20):2060-2067. [DOI] [PubMed] [Google Scholar]
- 12.Assebe LF, Reda HL, Wubeneh AD, Lerebo WT, Lambert SM. The effect of isoniazid preventive therapy on incidence of tuberculosis among HIV-infected clients under pre-ART care in Jimma, Ethiopia: a retrospective cohort study. BMC Public Health. 2015;15:346. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Cain KP, McCarthy KD, Heilig CM, et al. An algorithm for tuberculosis screening and diagnosis in people with HIV. N Engl J Med. 2010;362(8):707-716. [DOI] [PubMed] [Google Scholar]
- 14.Oshi DC, Oshi SN, Alobu I, Ukwaja KN. Profile, outcomes, and determinants of unsuccessful tuberculosis treatment outcomes among HIV-infected tuberculosis patients in a Nigerian state. Tuberc Res Treat. 2014;2014:202983. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Ukwaja KN. Tuberculosis treatment default among TB-HIV co-infected patients in Nigeria. Ann Trop Med Public Health. 2013;6(3):382-383. [Google Scholar]
- 16.Maruza M, Albuquerque MF, Coimbra I, et al. Risk factors for default from tuberculosis treatment in HIV-infected individuals in the state of Pernambuco, Brazil: a prospective cohort study. BMC Infect Dis. 2011;11:351. doi: 10.1186/1471-2334-11-351. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Dim CC. Declining uptake of HIV testing among tuberculosis patients in Enugu State of Nigeria: the need for a reappraisal of strategy. Niger J Clin Pract. 2012;15(2):206-209. [DOI] [PubMed] [Google Scholar]
- 18.Okonko IO, Anyanwu A, Osadebe AU, Odu NN. HIV and tuberculosis co-infection in a highly HIV-infected population of Rivers State, Nigeria. J Immunoassay Immunochem. 2018;39(6):636-646. [DOI] [PubMed] [Google Scholar]
- 19.Umeokonkwo CD, Okedo-Alex IN, Azuogu BN, Utulu R, Adeke AS, Disu YO. Trend and determinants of tuberculosis treatment outcome in a tertiary hospital in Southeast Nigeria. J Infect Public Health. 2020;13(7):1029-1033. [DOI] [PubMed] [Google Scholar]
- 20.National Tuberculosis, Leprosy and Buruli Ulcer Control Programme (NTBLCP) . Data centre. Abuja. Federal Ministry of Health; 2023. Available from. https://ntblcp.org.ng/data-centre/, Accessed 20 Jan 2026. [Google Scholar]
- 21.von Elm E, Altman DG, Egger M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol. 2008;61(4):344-349. doi: 10.1016/j.jclinepi.2007.11.008. [DOI] [PubMed] [Google Scholar]
- 22.World Health Organization . WHO Implementing the End TB Strategy: the essentials. In: Implementing the End TB Strategy: the essentials. Geneva; 2022. World Health Organization [Internet] [cited 2026 Mar 3]. Available from. [Google Scholar]
- 23.Alali A, Abere SO, Oyan B, Chijioke J, Igosein A. Treatment outcomes of Tuberculosis single infection and Tuberculosis/HIV co-infection in Rivers State University Teaching Hospital, Nigeria. J Med Womens Assoc Nig. 2025;10(2). doi: 10.71526/jmwan.v10i2.74. [DOI] [Google Scholar]
- 24.Ansa GA, Walley JD, Siddiqi K, Wei X. Assessing the impact of TB/HIV services integration on TB treatment outcomes and their relevance in TB/HIV monitoring in Ghana. Infect Dis Poverty. 2012;1(1):13. doi: 10.1186/2049-9957-1-13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Mande R, Thekkur P, Mudoola D, et al. Tuberculosis Preventive Treatment in People Living with HIV in Uganda: Facilitators and Barriers for Initiation and Completion. Trop Med Infect Dis. 2025;10(11):303. doi: 10.3390/tropicalmed10110303. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.shi DC, Oshi SN, Alobu I, Ukwaja KN. Profile, Outcomes, and Determinants of Unsuccessful Tuberculosis Treatment Outcomes among HIV-Infected Tuberculosis Patients in a Nigerian State. Tuberc Res Treat. 2014;2014:202983. doi: 10.1155/2014/202983. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Shehu MA, Amoo FK, Ibrahim MM, et al. Prevalence and risk factors associated with tuberculosis among patients attending General Hospital Toro, Bauchi State, Nigeria. DUJOPAS. 2025;11(2c):42-50. doi: 10.4314/dujopas.v11i2c.5. [DOI] [Google Scholar]
- 28.Miller PB, Zalwango S, Galiwango R, et al. Association between tuberculosis in men and social network structure in Kampala, Uganda. BMC Infect Dis. 2021;21(1):1023. doi: 10.1186/s12879-021-06475-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Idoko CA, Adeyemi O. Compliance of patients to DOTS tuberculosis treatment strategy in a South-East Nigeria Teaching Hospital. Afr Health Sci. 2022;22(3):599-606. doi: 10.4314/ahs.v22i3.64. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Adebayo AM, Adeniyi BO, Oluwasanu M, et al. Tuberculosis treatment outcomes and associated factors in two states in Nigeria. Trop Med Int Health. 2020;25(10):1261-1270. doi: 10.1111/tmi.13467. [DOI] [PubMed] [Google Scholar]
- 31.Gebremariam MK, Bjune GA, Frich JC. Barriers and facilitators of adherence to TB treatment in patients on concomitant TB and HIV treatment: a qualitative study. BMC Public Health. 2010;10:651. doi: 10.1186/1471-2458-10-651. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Izudi J, Tamwesigire IK, Bajunirwe F. Treatment success and mortality among adults with tuberculosis in rural eastern Uganda: a retrospective cohort study. BMC public health. 2020;20(1):501. doi: 10.1186/s12889-020-08646-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplemntal material for Tuberculosis Treatment Uptake and Outcomes Among HIV-Positive Patients on Antiretroviral Therapy at a Tertiary Health Facility in South-South, Nigeria by Adesuwa Queen Aigbokhaode, Ayodapo Oluwadare Jegede, Nosa Lancy Orhue, Omo Ekeneam, Oluwaseun Opeyemi Adesoye, Noruwa Patience Ekhator, Silvia Isioma Ezemenahi, Emmanuel Okechukwu Ezunu, Raymond Aghimien, Uchenna Enwereuzo, and Ibukun Jacob Akinkunmi in Journal of the International Association of Providers of AIDS Care (JIAPAC).
Data Availability Statement
The datasets generated and/or analysed during the current study are not publicly available due to institutional data protection policies but are available from the corresponding author upon reasonable request and with permission from the Federal Medical Centre, Asaba.*