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Age-specific relationship between HIV and TB treatment outcomes in the West Region of Cameroon: a cross-sectional study

BMC Infectious Diseases volume 25, Article number: 475 (2025) Cite this article

Abstract

Background

Co-infection with Mycobacterium tuberculosis (M. tuberculosis) and Human Immunodeficiency Virus (HIV) poses significant global public health challenges, with varying impacts across age cohorts. Evaluating tuberculosis (TB) treatment outcomes, especially among HIV patients across different age groups, is crucial for effective TB management. This study assessed the age-specific relationship between HIV status and TB treatment outcomes among TB patients in Cameroon.

Methods

This cross-sectional study included 2,455 TB patients receiving treatments in the West Region of Cameroon between January 2015 and December 2019. Data were extracted from National Tuberculosis Program Registers. The association of TB treatment outcomes with HIV and age was assessed using multivariate logistic regression.

Results

TB-HIV co-infection was significantly associated with lower TB treatment success. For HIV patients on antiretroviral therapy (ART), the odds ratio (OR) was 0.463 (95% confidence interval [CI]: 0.367–0.583, Bonferroni-adjusted P < 0.001). For HIV patients not on ART, the OR was 0.077 (95% CI: 0.030–0.200, Bonferroni-adjusted P < 0.001). A significant trend (P < 0.001) further indicated a consistent association between TB-HIV co-infection and treatment status. Older age was significantly associated with slightly lower treatment success (OR: 0.976; 95% CI: 0.969–0.983, Bonferroni-adjusted P < 0.001). TB-HIV co-infection remained significantly associated with lower TB treatment success after age categorization (OR; 95% CI, Bonferroni-adjusted P = 0.498; 0.394–0.631, < 0.001 for HIV patients on ART and 0.081; 0.032–0.210, < 0.001 for those without ART). The interaction between age and HIV was significant (P < 0.001). Age stratification revealed a significantly lower treatment success among HIV patients aged 25 and above, especially those not taking ART: OR (95% CI, Bonferroni-adjusted P) = 0.101 (0.032–0.312, < 0.001) and 0.038 (0.004–0.322, 0.025) for 25–44 and ≥ 45 years, respectively.

Conclusion

In this study, HIV status and older age were jointly associated with lower TB treatment success. Notably, treatment success was lower among HIV-positive patients aged 25 and above, especially those not on ART. Effective patient management, routine follow-up, and integration of TB and HIV services could improve TB treatment outcomes, particularly among adult HIV patients not taking ART.

Trial registration

Not applicable. This study is observational.

Peer Review reports

Background

Twin epidemics of TB and HIV present major global health challenges in the 21st century [1]. People with TB-HIV co-infection usually face compounded challenges, as this dual infection predisposes them to opportunistic infections and accelerates disease progression [2, 3]. Mortality rates are three times higher in TB-HIV-co-infected individuals compared to HIV-negative TB patients [4]. Approximately one-third of HIV patients in the world are affected by TB [5]. In 2014, the estimated incidence and mortality rates for TB were 1,000,000 and 140,000, respectively, with around 40% of these deaths attributed to TB-HIV co-infection [6]. Approximately 920,000 HIV-positive persons developed TB in 2017 [7]. Cameroon had a TB incidence of 164 per 100,000 in 2021 [8]. In 2022, 2.6% of Cameroonians between 15 and 49 years old had HIV [8]. Various TB comorbidities and opportunistic diseases contribute to higher mortality rates among Cameroonians [9].

TB and HIV have a bidirectional relationship, creating a dual public health burden, especially in resource-limited countries [10]. For instance, HIV is a key risk factor for TB: HIV-positive individuals are 20 to 21 times more prone to active TB than their HIV-negative counterparts [11]. Moreover, HIV is immunosuppressive and can promote the reactivation of latent TB [12]. TB, on the other hand, is the most frequent life-threatening opportunistic infection and the leading cause of death among HIV patients [11, 13]. To prevent immune reconstitution inflammatory syndrome (IRIS), HIV patients on anti-TB treatment typically wait eight weeks before starting antiretroviral therapy (ART). This delay can accelerate viral replication, resulting in higher viral loads and consequently complicating the management of both diseases [14]. Starting ART before or during TB therapy has been shown to reduce the risk of death during TB treatment by approximately 60% in clinical settings [13]. Age is a significant risk factor for TB and other respiratory diseases [15], with older individuals being particularly more vulnerable to new infections and the reactivation of latent TB [15]. The proportion of older adults with incident TB increased from 59% in 2000 to 69% in 2020 [16].

Even though early diagnosis and appropriate treatment could reduce TB-related morbidities, managing TB can be challenging [17]. Factors such as increased adverse drug reactions, poor adherence, and, consequently, decreased drug effectiveness contribute to lower TB treatment success rates [18, 19]. Moreover, pill burden and frequent drug shortages create adherence challenges [20], subsequently resulting in a high default rate, TB recurrence, and death. Implementing well-coordinated therapeutic management programs could ensure optimum treatment outcomes in terms of response and prevention of drug resistance [14].

The World Health Organization (WHO) has established standards for reporting TB treatment outcomes, which are crucial indicators for assessing the performance of National TB programs. TB treatment success rate is a key metric for monitoring and evaluating the effectiveness of the direct observed therapy (DOT) in TB management [5, 21]. Therefore, assessing TB treatment outcomes in patients is substantial. The global TB treatment success rate in 2015 was 83% for TB alone and 78% for HIV-TB co-infection [22]. This success rate varies by country [22]. For instance, in 2015, Cambodia and China reported a success rate of 94%, while Russia, Brazil, and Congo had rates of 71% [22].

The TB treatment success rate in Cameroon was 86% in 2020 [8]. Despite the high success rate among TB patients, the cure rate among those co-infected with HIV remains low, with high mortality rates. Approximately 20% of Cameroons had TB-HIV co-infection in 2021 [8]. To our knowledge, TB treatment outcomes among TB-HIV co-infected people in Cameroon, especially in the West region, have not been thoroughly studied. Moreover, while the elderly population is a significant risk group [23], no studies have evaluated the age-specific TB treatment outcomes among HIV patients in Cameroon. Hence, we assessed the age-specific relationship of TB treatment outcomes with HIV status and other factors among TB patients in the West region of Cameroon.

Methods

Study setting

We retrieved information from standard TB registers containing data from TB patients with known HIV status. These patients received treatment at five health facilities (both public and private) across three districts in the West region of Cameroon. The facilities included, Regional Hospital Bafoussam, District Hospital Foumban, District Hospital Dschang, Hôpital St. Vincent de Paul Dschang, and Centre Medical d’Arrondissement de Lafe Baleng. These institutions serve as referral diagnostic and treatment centers (DTCs) for TB and accommodate many TB patients. Cameroon is a developing country in Sub-Saharan Africa with a population of 27.9 million people as of 2022 [8]. Despite having the smallest surface area, the West region has the highest population density [24]. It is an economic hub with significant commercial activities, attracting merchants from various cities and countries [24].

Study design and participants

This cross-sectional study included TB patients who underwent treatment between 2015 and 2019. All patients were clinically diagnosed and bacteriologically confirmed. According to the National TB Program guideline, all diagnosed patients received counseling, HIV testing, and TB treatment. The data collection and management followed a systematic procedure to ensure accuracy and confidentiality. The research team was granted access to patient registers, and two staff members from the TB program were tasked with entering the data of TB patients undergoing treatment into an Excel sheet. The data were keyed in their natural form, without modification or transformation. To maintain confidentiality, no identifiable information, such as patient names or addresses, was included in the data entry. After the initial entry, the data were handed to the TB focal points at various hospitals for verification, where they cross-checked the entries with the original registers and corrected any discrepancies. To further verify data accuracy, at least two research team members re-entered all the data from the verified Excel file into another sheet, serving as a second layer of verification. The data with no identifiers were stored in a restricted folder, accessible only to authorized research team members. The final dataset was then transferred to the Regional Technical Group for Tuberculosis coordinator in the West Region for further verification and archiving. We initially analyzed data on HIV status, sex, TB test date, TB treatment start date, and TB treatment outcomes — including death, cure, complete treatment, failed treatment, and loss to follow-up (LTFU) — from 3110 TB patients. However, due to incomplete data, 655 individuals were not eligible for further analyses. Of these, 604 had missing TB test or treatment start dates; 42 were transferred, 4 were duplicates (resulting in 2 deletions), and 7 had inconsistent or missing values for TB treatment outcomes. The final analyses included 2455 TB patients with complete information. The Regional Delegation of Public Health, Training Office, West Region, Cameroon authorized this study (112/L/MINSANTE/QG/DRSPO/CBF), and the Institutional Review Board (IRB) of the Regional Hospital, Bafoussam gave ethical clearance for the study, with the number 384/L/MINSANTE/SG/DRSPO/HRB/D.

Definitions of TB treatment outcomes

We classified TB outcomes as successful (favorable) and unsuccessful (poor or unfavorable), following the WHO [25] and National TB guidelines [26]. Patients had a successful treatment outcome if they completed their treatment or were cured. On the other hand, patients had an unsuccessful treatment outcome if they died, were lost to follow-up, or experienced treatment failure. The definition of TB outcomes followed the revised WHO guidelines [25] as follows:

Cure

A pulmonary TB patient with bacteriologically confirmed TB at the start of treatment who completed treatment with evidence of bacteriological response and no evidence of treatment failure was considered cured.

Complete treatment

A patient who completed treatment and the outcome did not meet the definition of a cure or treatment failure was considered to have completed treatment.

Failed treatment

A patient whose treatment regimen needed to be terminated or permanently changed to a new regimen or treatment strategy was considered to have a failed treatment.

Death

Death of a confirmed patient before or during treatment.

Loss to follow-up

A patient who did not start treatment or whose treatment was interrupted for at least two consecutive months was considered lost to follow-up.

Definitions of HIV status and other variables

HIV-positive TB patient or HIV-TB co-infected patient

Any clinically diagnosed or bacteriologically confirmed TB patient who tested positive for HIV at the time of TB diagnosis or was enrolled in HIV care, such as pre-ART or ART registration [27].

HIV-negative TB patient

Any clinically diagnosed or bacteriologically confirmed TB patient who tested negative for HIV at the time of TB diagnosis. The WHO guidelines recommend reclassification if an HIV-negative TB patient subsequently tests positive for HIV [27].

Age was self-reported or provided by the caregiver and categorized into four groups (< 15, 15–24, 25–44, and ≥ 45 years) using the WHO guide on monitoring and evaluating collaborative TB/HIV activities [28] and related publications [29, 30]. Sex was self-reported or visually determined by the TB treatment nurse. The turnaround time (TAT) was defined as the interval (in days) between the TB test and treatment start dates.

Statistical analyses

Data were managed and analyzed with Python (version 3.11.5), using the pandas (version 2.0.3), statsmodels (version 0.14.0), and scipy (1.11.1) libraries. Data loading, cleaning, transformation, and manipulation were done using pandas. Differences in categorical variables (HIV status, age group, sex, and treatment year) between successful and unsuccessful treatment outcomes were determined by Chi-square using the scipy’s chi2_contingency() function. Differences in the mean (± standard deviations) ages and TAT of patients with unsuccessful TB treatment outcomes were determined by t-test using the scipy’s ttest_ind() function. The relationship of TB treatment outcome (dependent variable) with various predictors (independent variables), including HIV status (negative, positive and taking ART, positive and not on ART), age groups (< 15, 15–24, 25–44, and ≥ 45years), sex (men and women), TAT, and treatment year (2015, 2016, 2017, 2018, and 2019) was assessed with multivariate logistic regression using the statsmodels’ Logit() function. Key assumptions were evaluated before performing logistic regression. For instance, multicollinearity was assessed using the Variance Inflation Factor (VIF). All values were < 2, indicating no significant collinearity concerns. The model’s goodness of fit was assessed with the Hosmer-Lemeshow method. The p-value (0.981) was non-significant, indicating a good fit between observed and predicted values. The linearity of continuous variables (age and TAT) was tested using the Box-Tidwell method, with a non-significant p-value (> 0.05) indicating linearity. For age, the p-value for the relationship between age and the log-transformed odds of the outcome was 0.014, indicating non-linearity. For TAT, the p-value for the relationship between TAT and the log-transformed odds of the outcome was 0.261, signifying linearity. As such, TAT was retained as a continuous variable, while age was categorized to address the linearity assumption. The reference groups for the categorical variables included HIV-negative individuals, < 15 years, female sex, and the year 2015. The interaction between HIV status and age groups was also assessed using logistic regression. The interaction (HIV*age group) was included in the model while adjusting for other variables (TAT, treatment year, and sex) to explore how the combination of HIV status and different age cohorts influenced TB treatment outcome (dependent variable). Multiple comparisons were corrected using the Bonferroni method. The odds ratios (ORs), 95% confidence intervals (CIs), and p-values were reported for all the regression analyses. A p-value < 0.05 was considered statistically significant for all the analyses.

Results

Table 1 shows the general characteristics of the 2,455 TB patients, categorized into successful and unsuccessful TB treatment outcomes. Overall, 2,068 (84.24%) achieved successful treatment, while 387 (15.76%) had unsuccessful treatment. Significant differences were observed between the treatment groups regarding HIV status, age, TAT, and treatment year (P < 0.05). Among patients with successful treatment, 1494 (72.24%) were HIV-negative, and 574 (27.76%) were HIV-positive, with 567 of the HIV patients receiving ART and 7 not receiving it. In the unsuccessful treatment group, 205 (52.97%) individuals were HIV-negative, and 182 (47.03%) were HIV-positive, with 169 on ART and 13 not on ART. The mean ages among individuals with successful and unsuccessful treatment outcomes were 37.55 ± 15.71 and 43.62 ± 16.85 years, respectively. Supplementary Table 1 shows the general characteristics of TB patients according to treatment outcomes (died, failed treatment, lost to follow-up, cured, and completed treatment). Patients who died were significantly different from those who did not die based on HIV status, age, and TAT (P < 0.05). Those in the failed and non-failed treatment groups significantly differed according to treatment year (P < 0.001). The TB patients were not significantly different in terms of loss to follow-up. Those who completed treatment were significantly different from those who did not complete treatment in terms of HIV status, age, sex, and treatment year (P < 0.05). Finally, those who were cured were significantly different from those who were not cured in terms of HIV status, age, sex, TAT, and treatment year (P < 0.05). Supplementary Table 2 illustrates the distribution of participants by age group based on HIV and ART status.

Table 1 The basic characteristics of the study participants grouped into successful and unsuccessful TB treatment
Full size table

Table 2 shows the association of HIV status and age (treated as a continuous variable) with TB treatment success. TB treatment success was significantly lower among HIV-positive compared to HIV-negative TB patients, with outcomes being consistently lower among those not receiving ART. The OR was 0.463 (95% CI: 0.367–0.583, P < 0.001) for patients receiving ART and 0.077 (95% CI: 0.030–0.200, P < 0.001) for those not receiving ART. The association remained significant after multiple comparison corrections (Bonferroni-adjusted P < 0.001). The declining trend in TB treatment success from HIV patients on ART and not on ART was significant (P-trend < 0.001). Older age was significantly associated with a lower likelihood of treatment success (OR = 0.976, 95% CI = 0.969–0.983, unadjusted P < 0.001, Bonferroni-adjusted P < 0.001). Higher TAT was significantly associated with lower treatment success, but the results became insignificant after multiple comparison corrections (OR = 0.978, 95% CI = 0.960–0.997, unadjusted P = 0.022, Bonferroni-adjusted P = 0.220). TB treatment success was significantly higher in 2019 compared to 2015 (OR, 95% CI, unadjusted P, and Bonferroni-adjusted P = 1.738, 1.213–2.490, 0.003, and 0.030, respectively).

Table 2 Multivariate logistic regression showing the association of HIV and age with TB treatment success
Full size table

Table 3 shows the association of HIV and age groups with TB treatment success. HIV remained significantly associated with lower treatment success regardless of ART status, with the likelihood of success being much lower for patients not receiving ART. The ORs (95% CIs, Bonferroni-adjusted P) were 0.498 (0.394–0.631, < 0.001) for HIV patients on ART and 0.081 (0.032–0.210, < 0.001) for HIV patients not taking ART. The trend test remained significant (P < 0.001). Higher TAT remained significantly associated with lower treatment success, with the association becoming insignificant after multiple comparison corrections (OR = 0.977, 95% CI = 0.959–0.996, unadjusted P = 0.016, Bonferroni-adjusted P = 0.192). TB treatment success remained significantly higher in 2019, even after multiple comparison corrections, with the OR being 1.704 (95% CI: 1.190–2.440, unadjusted P = 0.004, Bonferroni-adjusted P = 0.048). Compared to < 15 years, the age groups 15–24, 25–44, and ≥ 45 years had no significant association with treatment success. However, the interaction between HIV and age group was significant (P < 0.001).

Table 3 Multivariate logistic regression showing the association of HIV and age groups with TB treatment success
Full size table

Table 4 details the association between HIV and TB treatment success across different age groups. Compared to HIV-negative TB patients, HIV patients in the age groups 25–44 and ≥ 45 years had lower treatment success, with those not taking ART having even lower odds of success (P-trend < 0.05). For those on ART, the ORs (95% CIs, unadjusted P, Bonferroni-adjusted P) were 0.365 (0.261–0.509, < 0.001, < 0.001) and 0.730 (0.503–1.058, 0.097, 0.869), for 25–44 and ≥ 45 years years, respectively. For those not on ART, the ORs (95% CIs, unadjusted P, Bonferroni-adjusted P) were 0.101 (0.032–0.312, < 0.001, 0.001) and 0.038 (0.004–0.322, 0.003, 0.025) for 25–44 and ≥ 45 years, respectively. Longer TAT was significantly associated with lower treatment success among patients aged 15–24 (OR = 0.953, 95% CI = 0.914–0.994, and an adjusted P = 0.025). The significant relationship ceased after multiple comparison corrections (Bonferroni-adjusted P = 0.198). Treatment success in 2019 was significantly higher among those aged 25–44 years, even though the significance disappeared after correction for multiple comparisons: OR, 95% CI, unadjusted P, and Bonferroni-adjusted P = 1.942, 1.135–3.322, 0.015, and 0.138, respectively.

Table 4 The association between HIV and TB treatment success stratified by age groups
Full size table

Discussion

In our study, 84.07% of TB patients achieved successful TB treatment, aligning with the 84.4% previously reported in Cameroon [29] and 84% reported in Zambia [30]. HIV status and older age were associated with lower TB treatment success. Of note, the success rate was significantly lower among HIV-positive TB patients compared to their HIV-negative counterparts, corroborating earlier findings [30,31,32,33]. While HIV was associated with poorer TB treatment outcomes regardless of ART status, the treatment success was consistently higher among those receiving ART compared to those not on ART. The consistent pattern of poorer TB treatment outcomes among HIV-positive patients, particularly those not on ART, underscores the critical role of ART in improving treatment success. These findings highlight the need to prioritize timely ART initiation and adherence support as part of integrated TB and HIV care strategies. Our findings are in line with those previously reported [31,32,33], where HIV patients on ART had more successful TB treatment outcomes than those who were not on ART.

The co-infection of TB and HIV represents a significant burden of infectious diseases in resource-limited countries [28]. These two pathogens exacerbate one another in co-infected individuals, leading to accelerated deterioration of immunological functions, poor treatment outcomes, and increased mortality [28]. Poor treatment outcomes may stem from delayed diagnosis, inadequate training on patient follow-up, and non-adherence to clinical guidelines. Implementing systematic TB screening at both facility and community levels could facilitate earlier diagnosis since some individuals delay seeking TB screening. Moreover, some hospitals’ TB focal points lack formal training on effective patient follow-up, favoring poorer treatment outcomes. Furthermore, some clinicians do not strictly follow clinical algorithms and mainly depend on bacteriological confirmation of TB before initiating treatments.

Previous studies reported a positive relationship between age and unsuccessful TB treatment [34,35,36]. In our study, age (as a continuous variable) was significantly associated with poor TB treatment outcomes. However, when age was stratified into groups due to non-linearity, it showed no significant association with TB treatment outcome in the groups. Nonetheless, the interaction between HIV status and age group was significant, revealing a significantly lower rate among TB-HIV co-infected individuals aged 25 years and above. Our findings indicate that TB, HIV, and their co-infection pose therapeutic challenges, particularly among older adults not taking ART. Given that age is a non-modifiable disease risk factor, sensitizing vulnerable age groups to prevent TB-HIV co-infection could help mitigate its adverse effects.

We observed higher treatment success rates among patients treated in 2019 compared to previous years. This finding may be attributed to several key factors, including advanced diagnostic technology, improved policies, community-based contact tracing, and enhanced healthcare access and delivery. For instance, before 2012, microscopy was the primary tool for early TB detection in Cameroon, but its low sensitivity, particularly for smear-negative cases, limited its effectiveness. In 2012, the National Tuberculosis Control Program introduced Xpert Mycobacterium Tuberculosis/Rifampicin (Xpert MTB/RIF), which detects M. tuberculosis complex and rifampicin resistance simultaneously and rapidly. This advanced method has been increasingly adopted nationwide, leading to improved case detection and, consequently, enhancing treatment outcomes [37].

In our current analysis, TAT had a significant inverse relationship with treatment success, even though the significance disappeared after multiple comparison corrections. Previous reports have shown improved TB treatment success with lower TAT [38]. Specifically, the shorter the time from testing to initiation of treatment, the more favorable the treatment outcome. Delays in treatment commencement, which can lead to unsuccessful outcomes, may be due to shortages in anti-TB medications or long distances to health facilities. Moreover, the poor financial status of some patients may have hindered timely access to their TB lab results. Additionally, some healthcare personnel may not have been thoroughly familiar with the National TB program guidelines on initiating anti-TB treatment, resulting in inadequate counseling on the importance of timely treatment commencement. The workload on healthcare personnel could also be a reason behind treatment delays [39]. Based on clinical evaluation, clinicians usually prescribe other antibiotics and wait at least 2 weeks before initiating anti-TB treatment, which can increase the risk of drug-resistant TB [40]. Delays in starting anti-TB medications have been shown to increase the rate of TB transmission and mortality [41]. Higher TAT has been associated with higher mortality among TB patients commencing treatment [42]. Therefore, reducing the time from the onset of TB symptoms to diagnosis and treatment initiation is crucial for improving treatment outcomes.

Our study found no significant differences in TB treatment outcomes between men and women, aligning with some previous research [43]. Nonetheless, other studies reported higher proportions of TB and unsuccessful TB outcomes in men [36, 44, 45], potentially due to riskier behavior such as smoking [46]. A study in Burundi found that women, often responsible for patient care in families, were more compliant with TB treatment than men [47].

Study strengths and limitations

A key strength of this study is the involvement of participants from several health facilities across different districts. One major limitation is the significant differences observed between the treatment groups regarding HIV status, age, TAT, and treatment year. These disparities may confound the results and impact the comparability of the two groups. Addressing these variances in future research will be essential to ensure a more accurate comparison of the treatment effects. Another limitation of our study is that we did not have information on the type of ART used by HIV patients. Moreover, since our data were secondary, we could not account for the missing information or assess essential lifestyle factors such as smoking and alcohol intake and socioeconomic status (SES) that could have impacted the outcome. Additionally, the lack of public access to our data could restrict other researchers’ ability to validate and replicate our results. Another limitation of this study is that while the < 15 age group was chosen based on WHO guidelines and previous research, further stratification into 0–4 and 5–14 years was not feasible due to sample size constraints. Given the biological and epidemiological differences between younger children (0–4 years) and older children (5–14 years), future studies should consider further disaggregating this age group to explore potential variations in TB treatment outcomes.

Conclusion

In this study, HIV status and older age were jointly associated with poorer TB treatment outcomes. Notably, treatment success was significantly lower among HIV-positive patients aged 25 and above, particularly those not on ART. Treatment success rates were notably higher among patients treated in 2019. Our findings suggest that HIV-positive patients, especially older individuals not receiving ART, may face greater challenges in achieving successful TB treatment. To improve TB treatment outcomes, effective patient management, routine follow-up, and the integration of TB and HIV services, including ensuring timely ART initiation, could be crucial, particularly for older HIV patients not taking ART. These insights may assist the National TB program in developing or revising preventive and management strategies. The government and related health authorities could implement TB sensitization campaigns in communities and all healthcare facilities. While SES, lifestyle, and other sociodemographic factors could influence treatment outcomes, this study did not examine them due to their unavailability in the TB registers. Future efforts to restructure TB program registers and improve data collection and monitoring practices will be essential in exploring additional factors that may affect TB treatment outcomes.

Data availability

The data that support the findings of this study are available from TB registers in the hospitals involved but restrictions apply to the availability of these data, which were used under authorization for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of the Regional Delegation of Public Health, West Region, Cameroon.

Abbreviations

ART:

Antiretroviral therapy

CI:

Confidence interval

DOT:

Directly observed therapy

HIV/AIDS:

Human immunodeficiency virus/acquired immune deficiency syndrome

IRIS:

Immune reconstitution inflammatory syndrome

NTP:

National tuberculosis program

SD:

Standard deviation

OR:

Odds ratio

ref.:

Reference

TAT:

Turnaround time

TB:

Tuberculosis

TB/HIV:

Tuberculosis/human immunodeficiency virus

WHO:

World health organization

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Acknowledgements

We extend our sincere gratitude to all the tuberculosis focal persons at the health facilities in the West Region, Cameroon for their assistance with data collection.

Funding

This work was supported by the National Science and Technology Council (NSTC), Taiwan (grant numbers: 111-2221-E-005-073-MY3, 111-2423-H-006-002-MY3, 112-2634-F-005-002, and 113-2321-B-006-014) and National Chung Hsing University-Changhua Christian Hospital (grant number: NCHU-CCH 11307).

Author information

Author notes

  1. Solange Mudih Ngala and Disline Manli Tantoh contributed equally to this work and share the first authorship.

Authors and Affiliations

  1. GTR-TB Délégation Régionale de la Santé Publique de l’Ouest, Bafoussam, Cameroon

    Solange Mudih Ngala, Gamo Djouomo Francis & Adeline Fitame

  2. Doctoral Program in Medical Biotechnology, National Chung Hsing University, Taichung City, Taiwan

    Disline Manli Tantoh & Yen-Wei Chu

  3. Department of Public Health, Institute of Public Health, Chung Shan Medical University, Taichung City, Taiwan

    Oswald Ndi Nfor

  4. Graduate Institute of Genomics and Bioinformatics, National Chung Hsing University, Taichung City, Taiwan

    Yen-Wei Chu

  5. Institute of Molecular Biology, National Chung Hsing University, Taichung City, Taiwan

    Yen-Wei Chu

  6. Smart Sustainable New Agriculture Research Center (SMARTer), Taichung City, Taiwan

    Yen-Wei Chu

Authors
  1. Solange Mudih Ngala
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  2. Disline Manli Tantoh
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  4. Gamo Djouomo Francis
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Contributions

SMN, DMT, and Y-WC conceived the study. SMN, DMT, ONN, and Y-WC designed the study. SMN, DMT, ONN, GDF, AF, and Y-WC performed literature searches. SMN, GDF, and AF acquired data. DMT and Y-WC performed data analysis. SMN, DMT, ONN, GDF, AF, and Y-WC interpreted the data. SMN and DMT wrote the manuscript. SMN, DMT, ONN, GDF, AF, and Y-WC critically revised the manuscript for important intellectual contents. Y-WC supervised the study. All the authors approved the final version of the manuscript.

Corresponding authors

Correspondence to Disline Manli Tantoh or Yen-Wei Chu.

Ethics declarations

Ethics approval and consent to participate

This study was approved by the IRB review committee of Regional Hospital, Bafoussam, with the number 384/L/MINSANTE/SG/DRSPO/HRB/D. The board waived the written informed consent because of the study’s retrospective nature and encrypted data.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

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Ngala, S.M., Tantoh, D.M., Nfor, O.N. et al. Age-specific relationship between HIV and TB treatment outcomes in the West Region of Cameroon: a cross-sectional study. BMC Infect Dis 25, 475 (2025). https://doi.org/10.1186/s12879-025-10860-3

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BMC Infectious Diseases

ISSN: 1471-2334

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